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Purpose: Evaluation of the prognostic significance of four different scoring systems in a real-world cohort of patients with metastatic urothelial carcinoma (mUC) or renal cell carcinoma (mRCC) undergoing immunotherapy (IO). Methods: For 120 patients with mUC (n = 67) and mRCC (n = 53) who received IO between July 2016 and December 2020 at the tertiary Urological University Medical Centre Mannheim, the following scores were recorded at pre-treatment baseline: modified Glasgow prognostic score (mGPS), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), neutrophil-to-eosinophil ratio (NER). Overall survival (time between the beginning of IO until the patients' death or last contact) was determined for every patient. Results: Kaplan-Meier analyses revealed that high baseline mGPS, SII (> 979) and NLR (> 3) were associated with poor overall survival (OS) (p < 0.05). Cox proportional hazards regression analyses showed that baseline mGPS and NLR had a significant independent prognostic influence on OS (p < 0.05), of which mGPS had a greater significance (p < 0.001, mGPS Score 2 vs. Score 0: HR 4.1, 95% CI 1.9–8.8). Although a high baseline NER (63.9) was associated with poor OS, it did not reach statistical significance. Baseline NER was also not identified as a significant score in the regression analyses. Conclusion: mGPS, SII and NLR are scoring systems that are easy to record in routine clinical practice. As they provide good prediction of OS in patients with mUC and mRCC under IO, they may allow identification of patients at high-risk and monitor them more cautiously in addition to imaging. [ABSTRACT FROM AUTHOR]

Purpose: Atherosclerosis and cancer may progress through common pathological factors. This study was performed to investigate the association between the abdominal aortic calcification (AAC) volume and outcomes following surgical treatment for pancreatic cancer. Methods: The subjects of this retrospective study were 194 patients who underwent pancreatic cancer surgery between 2007 and 2020. The AAC volume was assessed through routine preoperative computed tomography. Univariate and multivariate analyses were performed to evaluate the impact of the AAC volume on oncological outcomes. Results: A higher AAC volume (≥ 312 mm3) was identified in 66 (34%) patients, who were significantly older and had a higher prevalence of diabetes and sarcopenia. Univariate analysis revealed several risk factors for overall survival (OS), including male sex, an AAC volume ≥ 312 mm3, elevated carbohydrate antigen 19–9, prolonged operation time, increased intraoperative bleeding, lymph node metastasis, poor differentiation, and absence of adjuvant chemotherapy. Multivariate analysis identified an AAC volume ≥ 312 mm3, prolonged operation time, lymph node metastasis, poor differentiation, and absence of adjuvant chemotherapy as independent OS risk factors. The OS rate was significantly lower in the high AAC group than in the low AAC group. Conclusion: The AAC volume may serve as a preoperative prognostic indicator for patients with pancreatic cancer. [ABSTRACT FROM AUTHOR]

The prognosis for patients with hepatocellular carcinoma (HCC) depends on tumor stage and remnant liver function. However, it often includes tumor morphology, which is usually assessed with imaging studies or pathologic analysis, leading to limited predictive performance. Therefore, the aim of this study was to develop a simple and low-cost prognostic score for HCC based on serum biomarkers in routine clinical practice. A total of 3,100 patients were recruited. The least absolute shrinkage and selector operation (LASSO) algorithm was used to select the significant factors for overall survival. The prognostic score was devised based on multivariate Cox regression of the training cohort. Model performance was assessed by discrimination and calibration. Albumin (ALB), alkaline phosphatase (ALP), and alpha-fetoprotein (AFP) were selected by the LASSO algorithm. The three variables were incorporated into multivariate Cox regression to create the risk score (APP score = 0.390* ln (ALP) + 0.063* ln(AFP) - 0.033*ALB). The C-index, K-index, and time-dependent AUC of the score displayed significantly better predictive performance than 5 other models and 5 other staging systems. The model was able to stratify patients into three different risk groups. In conclusion, the APP score was developed to estimate survival probability and was used to stratify three strata with significantly different outcomes, outperforming other models in training and validation cohorts as well as different subgroups. This simple and low-cost model could help guide individualized follow-up. [ABSTRACT FROM AUTHOR]

Background: Transarterial chemoembolization (TACE) is recommended as a palliative treatment for patients of the B stage of the Barcelona Clinic Liver Cancer (BCLC) classification. Aims: To identify clinical, biological, and radiological predictors of survival in patients undergoing TACE and develop a pre-therapeutic prognostic score. Methods: 191 adult cirrhotic patients treated for HCC with TACE at the University Hospital (UH) of Clermont-Ferrand (France) from 2007–2017 were retrospectively included. We investigated the impact of baseline liver function, patient characteristics, and tumor burden on overall survival and developed a prognostic score. Results: Patients had a median age of 66 years and 126 patients were Child A. The AFP-DIAM score distinguishes two groups with a significant difference in survival time (median OS 28.3 months in patients with a score = 0 versus 17.7 months in patients with a score > 0). AFP-DIAM was validated on an external cohort, is well calibrated, and has the best discrimination capacity (C-index) as compared to NIACE, HAP, STATE, and SIX TO TWELVE. AFP-DIAM and SIX TO TWELVE are the more easy-to-use scores. When AFP-DIAM and the SIX TO TWELVE scores were tested in the same statistical model, results confirmed a better AFP-DIAM performance. Conclusions: The AFP-DIAM is an easy-to-use score which allows to distinguish two groups with different prognosis before the first TACE session. Its use could provide further support to BCLC system to guide the therapeutic strategy of patients with HCC. An easy-to-use score allows to distinguish two groups with a different median survival. Patient with a high score could receive immunotherapy as first-line treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: In patients with hepatocellular carcinoma (HCC), predicting survival after treatment is crucial for informed decision-making. This retrospective study investigated how muscle health (myosteatosis) and liver function (the albumin–bilirubin grade) influence survival outcomes in patients undergoing transarterial chemoembolization (TACE), resulting in the development of the Myo-ALBI prognostic score. The Myo-ALBI score was found to be a more accurate tool for predicting survival compared to existing methods. This study highlights the potential of the Myo-ALBI score to help clinicians personalize treatments and improve patient outcomes. Objective: This study aimed to investigate the prognostic value of preoperative myosteatosis and the albumin–bilirubin (ALBI) grade in patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE) and develop a robust prognostic score based on these factors. Methods: Patients with HCC who underwent TACE between January 2009 and December 2020 were included. Multivariate Cox regression analysis identified prognostic factors. CT-based body composition parameters were acquired from baseline abdominal CT images at the level of the third lumbar vertebra. A prognostic score (Myo-ALBI) was developed based on the presence of preoperative myosteatosis and the ALBI grade, and its prognostic value was evaluated. Results: Of 446 patients, 63% were male, and the mean age was 62.4 years. Preoperative myosteatosis was present in 41.5% of patients. The BCLC stages were mostly B (67.9%). Multivariate analysis shows that preoperative myosteatosis, ALBI grade 2, and ALBI grade 3 were independent prognostic factors. The Myo-ALBI grade was incorporated into a prognostic model, including alpha-fetoprotein and up-to-seven criteria, to generate a nomogram. The C-index of the nomogram based on the Myo-ALBI grade (0.743) was significantly higher than the non-Myo-ALBI nomogram (0.677), the up-to-seven criteria (0.653), the ALBI grade (0.616), and the Child–Pugh class (0.573) (all p < 0.05). The t-ROC curve for the nomogram was consistently superior to the other models throughout the observation period in all patients and the BCLC-B subgroup. Conclusions: The combination of preoperative CT-derived myosteatosis and ALBI grade enhances prognostication for patients with unresectable HCC undergoing TACE. The Myo-ALBI nomogram constructed in this study could support individualized prognosis prediction, assisting in treatment decision-making for HCC patients. [ABSTRACT FROM AUTHOR]

Background: Propensity scores (PS) are typically evaluated using balance metrics that focus on covariate balance, often without considering their predictive power for the outcome. This approach may not always result in optimal bias reduction in the treatment effect estimate. To address this issue, evaluating covariate balance through prognostic scores, which account for the relationship between covariates and the outcome, has been proposed. Similarly, using a typical model averaging approach for PS estimation that minimizes prediction error for treatment status and covariate imbalance does not necessarily optimize PS-based confounding adjustment. As an alternative approach, using the averaged PS model that minimizes inter-group differences in the prognostic score may further reduce bias in the treatment effect estimate. Moreover, since the prognostic score is also an estimated quantity, model averaging in the prognostic scores can help identify a better prognostic score model. Utilizing the model-averaged prognostic scores as the balance metric for constructing the averaged PS model can contribute to further decreasing bias in treatment effect estimates. This paper demonstrates the effectiveness of the PS model averaging approach based on prognostic score balance and proposes a method that uses the model-averaged prognostic score as a balance metric, evaluating its performance through simulations and empirical analysis. Methods: We conduct a series of simulations alongside an analysis of empirical observational data to compare the performances of weighted treatment effect estimates using the proposed and existing approaches. In our examination, we separately provid four candidate estimates for the PS and prognostic score models using traditional regression and machine learning methods. The model averaging of PS based on these candidate estimators is performed to either maximize the prediction accuracy of the treatment or to minimize intergroup differences in covariate distributions or prognostic scores. We also utilize not only the prognostic scores from each candidate model but also an averaged score that best predicted the outcome, for the balance assessment. Results: The simulation and empirical data analysis reveal that our proposed model-averaging approaches for PS estimation consistently yield lower bias and less variability in treatment effect estimates across various scenarios compared to existing methods. Specifically, using the optimally averaged prognostic scores as a balance metric significantly improves the robustness of the weighted treatment effect estimates. Discussion: The prognostic score-based model averaging approach for estimating PS can outperform existing model averaging methods. In particular, the estimator using the model averaging prognostic score as a balance metric can produce more robust estimates. Since our results are obtained under relatively simple conditions, applying them to real data analysis requires adjustments to obtain accurate estimates according to the complexity and dimensionality of the data. Conclusions: Using the prognostic score as the balance metric for the PS model averaging enhances the performance of the treatment effect estimator, which can be recommended for a wide variety of situations. When applying the proposed method to real-world data, it is important to use it in conjunction with techniques that mitigate issues arising from the complexity and high dimensionality of the data. [ABSTRACT FROM AUTHOR]

Background: Identifying high-risk COVID-19 patients is critical for emergency department decision-making. Our study's primary objective was to identify new independent predictors of mortality and their predictive utility in combination with traditional pneumonia risk assessment scores and new risk scores for COVID-19 developed during the pandemic. Methods: A retrospective study was performed in two Italian University Hospitals. A multivariable logistic model was used to locate independent parameters associated with mortality. Results: Age, PaO2/FiO2, and SpO2/FiO2 ratios were found to be independent parameters associated with mortality. This study found that the Pneumonia Severity Index (PSI) was superior to many of the risk scores developed during the pandemic, for example, the International Severe Acute Respiratory Infection Consortium Coronavirus Clinical Characterisation Consortium (ISARIC 4C) (AUC 0.845 vs. 0.687, p < 0.001), and to many of the risk scores already in use, for example, the National Early Warning Score 2 (NEWS2) (AUC 0.845 vs. 0.589, p < 0.001). Furthermore, our study found that the Pneumonia Severity Index had a similar performance to other risk scores, such as CRB-65 (AUC 0.845 vs. 0.823, p = 0.294). Combining the PaO2/FiO2 or SpO2/FiO2 ratios with the risk scores analyzed improved the prognostic accuracy. Conclusions: Adding the SpO2/FiO2 ratio to the traditional, validated, and already internationally known pre-pandemic prognostic scores seems to be a valid and rapid alternative to the need for developing new prognostic scores. Future research should focus on integrating these markers into existing pneumonia scores to improve their prognostic accuracy. [ABSTRACT FROM AUTHOR]

Recent years have seen an increasing interest in incorporating external control data for designing and evaluating randomized clinical trials (RCT). This may decrease costs and shorten inclusion times by reducing sample sizes. For small populations, with limited recruitment, this can be especially important. Bayesian dynamic borrowing (BDB) has been a popular choice as it claims to protect against potential prior data conflict. Digital twins (DT) has recently been proposed as another method to utilize historical data. DT, also known as PROCOVA™, is based on constructing a prognostic score from historical control data, typically using machine learning. This score is included in a pre‐specified ANCOVA as the primary analysis of the RCT. The promise of this idea is power increase while guaranteeing strong type 1 error control. In this paper, we apply analytic derivations and simulations to analyze and discuss examples of these two approaches. We conclude that BDB and DT, although similar in scope, have fundamental differences which need be considered in the specific application. The inflation of the type 1 error is a serious issue for BDB, while more evidence is needed of a tangible value of DT for real RCTs. [ABSTRACT FROM AUTHOR]

Early prognostic assessment of patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is important for guiding clinical management and reducing mortality. The aim of this study was to dynamically monitor the clinical characteristics of HBV-ACLF patients, thereby allowing the construction of a novel prognostic scoring model to predict the outcome of HBV-ACLF patients. Clinical data was prospectively collected for 518 patients with HBV-ACLF and randomly divided into training and validation sets. We constructed day-1, day-2, and day-(1 + 3) prognostic score models based on dynamic time points. The prognostic risk score constructed for day-3 was found to have the best predictive ability. The factors included in this scoring system, referred to as DSM-ACLF-D3, were age, hepatic encephalopathy, alkaline phosphatase, total bilirubin, triglycerides, very low-density lipoprotein, blood glucose, neutrophil count, fibrin, and INR. ROC analysis revealed the area under the curve predicted by DSM-ACLF-D3 for 28-day and 90-day mortality (0.901 and 0.889, respectively) was significantly better than those of five other scoring systems: COSSH-ACLF IIs (0.882 and 0.836), COSSH-ACLFs (0.863 and 0.832), CLIF-C ACLF (0.838 and 0.766), MELD (0.782 and 0.762) and MELD-Na (0.756 and 0.731). Dynamic monitoring of the changes in clinical factors can therefore significantly improve the accuracy of scoring models. Evaluation of the probability density function and risk stratification by DSM-ACLF-D3 also resulted in the best predictive values for mortality. The novel DSM-ACLF-D3 prognostic scoring model based on dynamic data can improve early warning, prediction and clinical management of HBV-ACLF patients. [ABSTRACT FROM AUTHOR]

Objective Pediatric adrenocortical carcinoma (pACC) is rare, and prognostic stratification remains challenging. We aimed to confirm the prognostic value of the previously published pediatric scoring system (pS-GRAS) in an international multicenter cohort. Design Analysis of pS-GRAS items of pACC from 6 countries in collaboration of ENSAT-PACT, GPOH-MET, and IC-PACT. Methods We received patient data of the pS-GRAS items including survival information from 9 centers. PS-GRAS score was calculated as a sum of tumor stage (1 = 0; 2-3 = 1; 4 = 2 points), grade (Ki67 index: 0%-9% = 0; 10%-19% = 1; ≥20% = 2 points), resection status (R0 = 0; RX/R1/R2 = 1 point), age (<4 years = 0; ≥4 years = 1 point), and hormone production (androgen production = 0; glucocorticoid-/mixed-/no-hormone production = 1 point) generating 8 scores and 4 groups (1: 0-2, 2: 3-4, 3: 5, 4: 6-7). Primary endpoint was overall survival (OS). Results We included 268 patients with median age of 4 years. The analysis of the pS-GRAS score showed a significantly favorable prognosis in patients with a lower scoring compared to higher scoring groups (5-year OS: Group 1 98%; group 2 87% [hazard ratio {HR} of death 3.6, 95% CI of HR 1.6-8.2]; group 3 43% [HR of death 2.8, 95% CI 1.9-4.4]; group 4: OS 18% [HR of death 2.1, 95% CI 1.7-2.7]). In the multivariable analysis, age (HR of death 3.5, 95% CI 1.8-7.0), resection status (HR of death 5.5, 95% CI 2.7-11.1), tumor stage (HR of death 1.9, 95% CI of HR 1.2-3.0), and Ki67 index (HR of death 1.7, 95% CI 1.2-2.4) remained strong independent outcome predictors. Especially infants < 4 years showed more often low-risk constellations with a better OS for all tumor stages. Conclusion In an international multicenter study, we confirmed that the pS-GRAS score is strongly associated with overall survival among patients with pACC. Age, resection status, stage, and Ki67 index are important parameters for risk stratification. [ABSTRACT FROM AUTHOR]

Background: Type C hepatitis B-related acute-on-chronic liver failure (HBV-ACLF), which is based on decompensated cirrhosis, has different laboratory tests, precipitating events, organ failure and clinical outcomes. The predictors of prognosis for type C HBV-ACLF patients are different from those for other subgroups. This study aimed to construct a novel, short-term prognostic score that applied serological indicators of hepatic regeneration and noninvasive assessment of liver fibrosis to predict outcomes in patients with type C HBV-ACLF. Method: Patients with type C HBV-ACLF were observed for 90 days. Demographic information, clinical examination, and laboratory test results of the enrolled patients were collected. Univariate and multivariate logistic regression were performed to identify independent prognostic factors and develop a novel prognostic scoring system. A receiver operating characteristic (ROC) curve was used to analyse the performance of the model. Results: A total of 224 patients with type C HBV-ACLF were finally included. The overall survival rate within 90 days was 47.77%. Age, total bilirubin (TBil), international normalized ratio (INR), alpha-fetoprotein (AFP), white blood cell (WBC), serum sodium (Na), and aspartate aminotransferase/platelet ratio index (APRI) were found to be independent prognostic factors. According to the results of the logistic regression analysis, a new prognostic model (named the A3Twin score) was established. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) was 0.851 [95% CI (0.801-0.901)], the sensitivity was 78.8%, and the specificity was 71.8%, which were significantly higher than those of the MELD, IMELD, MELD-Na, TACIA and COSSH‐ACLF II scores (all P < 0.001). Patients with lower A3Twin scores (<-9.07) survived longer. Conclusions: A new prognostic scoring system for patients with type C HBV-ACLF based on seven routine indices was established in our study and can accurately predict short-term mortality and might be used to guide clinical management. [ABSTRACT FROM AUTHOR]

Observational studies are frequently used to estimate the effect of an exposure or treatment on an outcome. To obtain an unbiased estimate of the treatment effect, it is crucial to measure the exposure accurately. A common type of exposure misclassification is recall bias, which occurs in retrospective cohort studies when study subjects may inaccurately recall their past exposure. Particularly challenging is differential recall bias in the context of self-reported binary exposures, where the bias may be directional rather than random and its extent varies according to the outcomes experienced. This paper makes several contributions: (1) it establishes bounds for the average treatment effect even when a validation study is not available; (2) it proposes multiple estimation methods across various strategies predicated on different assumptions; and (3) it suggests a sensitivity analysis technique to assess the robustness of the causal conclusion, incorporating insights from prior research. The effectiveness of these methods is demonstrated through simulation studies that explore various model misspecification scenarios. These approaches are then applied to investigate the effect of childhood physical abuse on mental health in adulthood. [ABSTRACT FROM AUTHOR]

Osteosarcoma stratification relies on clinical parameters and histological response. We developed a new personalized stratification using less invasive circulating tumor DNA (ctDNA) quantification. Plasma from patients homogeneously treated in the prospective protocol OS2006, at diagnosis, before surgery and end of treatment, were sequenced using low-passage whole-genome sequencing (lpWGS) for copy number alteration detection. We developed a prediction tool including ctDNA quantification and known clinical parameters to estimate patients' individual risk of event. ctDNA quantification at diagnosis (diagCPA) was evaluated for 183 patients of the protocol OS2006. diagCPA as a continuous variable was a major prognostic factor, independent of other clinical parameters, including metastatic status [diagCPA hazard ratio (HR) = 3.5, P = 0.002 and 3.51, P = 0.012, for progression-free survival (PFS) and overall survival (OS)]. At the time of surgery and until the end of treatment, diagCPA was also a major prognostic factor independent of histological response (diagCPA HR = 9.2, P < 0.001 and 11.6, P < 0.001, for PFS and OS). Therefore, the addition of diagCPA to metastatic status at diagnosis or poor histological response after surgery improved the prognostic stratification of patients with osteosarcoma. We developed the prediction tool PRONOS to generate individual risk estimations, showing great performance ctDNA quantification at the time of surgery and the end of treatment still required improvement to overcome the low sensitivity of lpWGS and to enable the follow-up of disease progression. The addition of ctDNA quantification to known risk factors improves the estimation of prognosis calculated by our prediction tool PRONOS. To confirm its value, an external validation in the Sarcoma 13 trial is underway. • ctDNA detection is a non-invasive procedure. • The use of lpWGS is cost-effective. • This procedure represents a considerable step in reducing therapeutic burden and trauma for patients with cancer. • PRONOS is a tool that estimates relapse risk using ctDNA at diagnosis and known clinical risk factor in osteosarcoma. [ABSTRACT FROM AUTHOR]

The purpose of this study is to illustrate how matching approaches based on different balancing scores lead to variations in the treatment effect estimators. We introduced a case study evaluating the effect of anti-thrombotic agents on the severe progression of patients with intracerebral hemorrhage. We extracted subpopulations based on propensity and prognostic scores and then estimated the relative risk between the treatment groups. Furthermore, to illustrate the situation where the treatment effect estimates varied depending on employed balancing scores, we conducted a simulation experiment. In the case study, the matching using different balancing scores extracted subpopulations with different characteristics. Then, the estimated relative risk (95% confidence interval) was 1.27 (0.98–1.94) among the propensity score matched cohort, whereas it was 0.91 (0.76–1.08) among the prognostic score matched cohort. In the simulation experiments, the results indicated that the matching schemes based on different balancing scores created distinct matched cohorts, leading to varying estimates under treatment effect heterogeneity. Moreover, the variability of the estimated effect becomes substantial when there are covariates strongly related to the dependent variable of the nuisance functions. The difference in the selected subpopulation via matching based on different balancing scores is a thoughtful factor that can result in different estimates when there is effect heterogeneity. In practice, we recommend assessing the characteristics of the matched subpopulation and employing the balancing score that can estimate the treatment effect among the target population of interest in each study. Plain Language Summary: This study aimed to understand why different methods of matching patients in a study can lead to different estimates of how well a treatment works. We used a real example of a study where the treatment's effectiveness varied for different patients and compared how different methods of matching patients affected the results. We also did a series of experiments to see how the different methods affected estimates of treatment effect when the effectiveness varied among patients. Our study found that the different matching methods extracted the different patients. The difference in the matched patients led to very different results, especially when the treatment's effectiveness was not the same for all patients. Therefore, it is important to check the characteristics of patients after matching and consider whether the treatment's effectiveness is not the same for all patients. [ABSTRACT FROM AUTHOR]

• Prevalence of mayor adverse cardiovascular events (MACE) was 7.8 % following one year of COVID-19 hospitalization. • Age, history of cardiovascular disease, hypertension, increased troponin serum levels at admission and acute renal failure during hospitalization were identified as predictors of MACE and combined in a clinical score. • HOPE-2 clinical score classified patients into three risk categories and the observed MACE rates were 1.9 %, 9.4 % and 26.3 % for low- intermediate and high-risk patients, respectively. Long-term consequences of COVID-19 are still partly known. To derive a clinical score for risk prediction of long-term major cardiac adverse events (MACE) and all cause death in COVID-19 hospitalized patients. 2573 consecutive patients were enrolled in a multicenter, international registry (HOPE-2) from January 2020 to April 2021 and identified as the derivation cohort. Five hundred and twenty-six patients from the Cardio-Covid-Italy registry were considered as external validation cohort. A long-term prognostic risk score for MACE and all cause death was derived from a multivariable regression model. Out of 2573 patients enrolled in the HOPE-2 registry, 1481 (58 %) were male, with mean age of 60±16 years. At long-term follow-up, the overall rate of patients affected by MACE and/or all cause death was 7.8 %. After multivariable regression analysis, independent predictors of MACE and all cause death were identified. The HOPE-2 prognostic score was therefore calculated by giving: 1–4 points for age class (<65 years, 65–74, 75–84, ≥85), 3 points for history of cardiovascular disease, 1 point for hypertension, 3 points for increased troponin serum levels at admission and 2 points for acute renal failure during hospitalization. Score accuracy at ROC curve analysis was 0.79 (0.74 at external validation). Stratification into 3 risk groups (<3, 3–6, >6 points) classified patients into low, intermediate and high risk. The observed MACE and all-cause death rates were 1.9 %, 9.4 % and 26.3 % for low- intermediate and high-risk patients, respectively (Log-rank test p < 0.01). The HOPE-2 prognostic score may be useful for long-term risk stratification in patients with previous COVID-19 hospitalization. High-risk patients may require a strict follow-up. [Display omitted] [ABSTRACT FROM AUTHOR]

The article highlights the limitations of using ejection fraction (EF) as a standalone metric for cardiac health, advocating for the inclusion of an associated companion (EFC) metric to provide a more comprehensive assessment. Topics include the analysis of cardiac patients, particularly those with acute myocardial infarction, the distribution of EFC for patients with mid-range EF values, and the importance of combining EF and EFC to accurately locate individual patient profiles.

Simple Summary: Despite the promising evidence of the Royal Marsden Hospital (RMH) score as a readily available prognostic biomarker in patients with cancer, the wide scale implementation in clinical practice as well as the true benefit in clinical decision-making is lacking. Therefore, we systematically reviewed the available evidence on the association between the RMH score and prognosis in patients with cancer. This comprehensive meta-analysis, encompassing over a hundred thousand patients, revealed a negative association between a higher RMH score and survival in cancer patients. The available evidence demonstrates that the RMH score is not only a selective biomarker for patients enrolled in clinical trials, but also a useful prognostic biomarker in a real-world setting. Future research should aim to validate and refine this score, ensuring its optimal application in clinical practice and decision-making. Background: Cancer remains a leading cause of death globally, necessitating the identification of prognostic biomarkers to guide treatment decisions. The Royal Marsden Hospital (RMH) score, based on readily available blood tests and clinical features, has emerged as a prognostic tool, although its performance across variable clinical scenarios is not thoroughly delineated. Therefore, we aimed to systematically assess the association between RMH score and survival in cancer patients. Methods: We conducted a systematic literature search across Pubmed, Scopus, and Web of Science databases for studies published up to 15 February 2024. We performed a meta-analysis with the generic inverse variance method with a random-effects model and reported hazard ratios (HR) with 95% confidence intervals (CI). Results: Nineteen studies encompassing 127,230 patients were included. A higher RMH score was significantly associated with worse overall survival (OS) (HR: 2.09, 95% CI: 1.87–2.33, p < 0.001) and progression-free survival (PFS) (HR: 1.80, 95% CI: 1.48–2.18, p < 0.001). This association was consistent across various subgroups, including study population (clinical trial vs. real-world cohort), geographic region, and tumor type. Conclusion: This meta-analysis, including over a hundred thousand patients, demonstrates a negative association between a higher RMH score and survival in cancer patients. The RMH score holds promise as a readily available prognostic tool across diverse cancer types and clinical settings. Future research should focus on validating and refining this score to aid clinical decision-making. [ABSTRACT FROM AUTHOR]

Despite neutrophil involvement in inflammation and tissue repair, little is understood about their inflammatory status in acute coronary syndrome (ACS) patients with poor outcomes. Hence, we investigated the potential correlation between neutrophil inflammatory markers and the prognosis of ACS patients with/without diabetes and explored whether neutrophils demonstrate a unique inflammatory phenotype in patients experiencing an adverse in-hospital outcome. The study enrolled 229 ACS patients with or without diabetes. Poor evolution was defined as either death, left ventricular ejection fraction (LVEF) <40%, Killip Class 3/4, ventricular arrhythmias, or mechanical complications. Univariate and multivariate analyses were employed to identify clinical and paraclinical factors associated with in-hospital outcomes. Neutrophils isolated from fresh blood were investigated using qPCR, Western blot, enzymatic assay, and immunofluorescence. Poor evolution post-myocardial infarction (MI) was associated with increased number, activity, and inflammatory status of neutrophils, as indicated by significant increase of Erythrocyte Sedimentation Rate (ESR), C-reactive protein (CRP), fibrinogen, interleukin-1β (IL-1β), and, interleukin-6 (IL-6). Among the patients with complicated evolution, neutrophil activity had an important prognosis value for diabetics. Neutrophils from patients with unfavorable evolution revealed a pro-inflammatory phenotype with increased expression of CCL3, IL-1β, interleukin-18 (IL-18), S100A9, intracellular cell adhesion molecule-1 (ICAM-1), matrix metalloprotease (MMP-9), of molecules essential in reactive oxygen species (ROS) production p22phox and Nox2, and increased capacity to form neutrophil extracellular traps. Inflammation is associated with adverse short-term prognosis in acute ACS, and inflammatory biomarkers exhibit greater specificity in predicting short-term outcomes in diabetics. Moreover, neutrophils from patients with unfavorable evolution exhibit distinct inflammatory patterns, suggesting that alterations in the innate immune response in this subgroup may exert detrimental effects on disease progression. [ABSTRACT FROM AUTHOR]

Predicting survival is essential to tailoring treatment for patients diagnosed with brain metastases. We have evaluated the performance of widely used, validated prognostic scoring systems (Graded Prognostic Assessment and diagnosis-specific Graded Prognostic Assessment) in over 1000 'real-world' patients treated with stereotactic radiosurgery to the brain, selected according to National Health Service commissioning criteria. Survival outcomes from our dataset were consistent with those predicted by the prognostic systems, but with certain cancer subtypes showing a significantly better survival than predicted. Although performance status remains the simplest tool for prediction, total brain tumour volume emerges as an independent prognostic factor, and a new, improved, prognostic scoring system incorporating this has been developed. • Real-world data for patients with brain metastases are consistent with the predictions made by the prognostic tool, DS-GPA. • Intracranial tumour volume is a novel independent risk factor for survival. • Incorporating tumour volume with existing prognostic factors improves a valuable pan-cancer prognostic tool. • Performance status remains a simple and robust predictor of survival. [ABSTRACT FROM AUTHOR]

Prognostic estimates for older mRCC patients might be key for clinical decision-making. The outcome of realworld older mRCC patients treated with any line cabozantinib study was analyzed according to the baseline Meet-URO score. Meet-URO score is a valid prognostic tool in older mRCC patients treated with cabozantinib for informing the patient and clinical decisions. Background: The addition of neutrophil to lymphocyte ratio (NLR) and bone metastases to the IMDC classification provided by the Meet-URO score, resulted in higher prognostic accuracy in metastatic renal cell carcinoma (mRCC) patients receiving ≥2nd line nivolumab or cabozantinib in 2 retrospective analyses and 1st line nivolumab-ipilimumab in an expanded access programme. Prognostic estimates for older mRCC patients might be key for clinical decisionmaking. Methods: The outcome of real-world older (≥70 years) mRCC patients treated with any line cabozantinib within the multicenter observational prospective ZEBRA (Meet-URO 9) study was analyzed according to the baseline Meet-URO score. The primary endpoint was overall survival (OS). The discriminative ability by Harrell's c-index and calibration were assessed to compare the Meet-URO and IMDC scores. Results: A total of 104 mRCC patients received cabozantinib as 1st (38%), 2nd (20%), or ≥3rd (41%) line. With a median follow-up of 11.2 months, the median OS (mOS) was of 18.4 months. According to the IMDC score, favorable (15%), intermediate (65%) and poor-risk (19%) patients had a mOS not reached, of 15.6 and 5.7 months respectively (p = .011). According to the Meet-URO score groups, mOS was not reached in both group 1 (10%) and group 2 (25%), while in group 3 (33%), group 4 (25%) and group 5 (8%) mOS was of 13.6, 12.5, and 3.7 months, respectively (p < .001). The discriminative ability of the Meet-URO score was maintained by merging groups 1 to 2 vs. 3 to 4 vs. 5 (p < .001). The Meet-URO score (with either the original 5-group stratification or the modified 3-group one) showed higher accuracy than the IMDC score (c-index of 0.686 and 0.676 vs. 0.622). Conclusion: This analysis confirmed the prognostic accuracy of the Meet-URO score in older mRCC patients treated with cabozantinib and its role as a convenient tool for informing the patient and clinical decisions. [ABSTRACT FROM AUTHOR]

Background: No widely used prognostic tool exists to demonstrate the benefit of oxaliplatin plus 5-fluorouracil/leucovorin (FOLFOX4) in patients with advanced hepatocellular carcinoma (HCC). We aimed to establish a prognostic score and demonstrate the real-world efficacy of FOLFOX4 chemotherapy in Thai patients. Methods: Between August 2017 and December 2021, we identified 58 FOLFOX4-treated patients with HCC. Overall survival (OS), progression-free survival (PFS), and objective response rate (ORR) were assessed. The prognostic score was constructed by stepwise Cox proportional hazards regression analysis to select variables for the best model with the lowest Akaike information criterion from all potential variables. Results: Forty-four patients (76%) received FOLFOX4 as first-line therapy. The ORR in the entire cohort was 8.6%, and the disease control rate was 29.3%. The PFS and OS were 3.7 and 4.8 months, respectively. Four clinically relevant variables were included in the new prognostic score to predict 6-month OS: L, the presence of lung metastasis; A, alcoholic cirrhosis; B, elevated total bilirubin level; and S, sorafenib-naïve status. Using the LABS score, patients were classified into low-, intermediate-, and high-risk groups, demonstrating OS values of 9.3, 4.2, and 2.1 months, respectively (p < 0.0001). The C-index and area under the receiver-operating characteristic curve of the score were 0.71 and 0.73, respectively. Conclusions: The proposed LABS score could discriminate patients who would derive benefit from FOLFOX4 chemotherapy. FOLFOX4 chemotherapy is an option for patients who cannot receive immunotherapy and targeted therapy, particularly those with a low-risk score. However, further validation of this model via larger cohorts is warranted. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to determine whether the RNA, 5‐methylcytosine (m5C), is involved in the progression of head and neck squamous cell carcinoma (HNSCC). Materials and methods: We used least absolute shrinkage and selection operator to establish a prognostic score (PS) model based on the m5C regulator expression. Immune scores were calculated using the estimation of stromal and immune cells in malignant tumor tissues using expression data. The biological functions of the m5C regulator, NOP2/Sun RNA methyltransferase 3 (NSUN3), were thoroughly investigated in vitro and in vivo. Results: The PS model acted as efficient prognostic factors in HNSCC. The expression of NSUN3, with the maximum weight, was found to be upregulated and indicated a poor prognosis. Meanwhile, NSUN3 knockdown inhibited the tumor proliferation and growth both in vitro and in vivo. High PS status was negatively correlated with CD8+ T, γδ+ T, and M1 macrophage percentages. NSUN3 knockdown increased the infiltration of M1 macrophages but decreased the percentage of M2 macrophages. Conclusions: The PS index is a novel and promising biomarker for predicting the prognosis and immune infiltration microenvironment in HNSCC. Moreover, NSUN3 plays a key role in this process and may serve as a potential therapeutic target for HNSCC. [ABSTRACT FROM AUTHOR]

Different prognostic scores have been applied to identify patients with non-small cell lung cancer who have a higher probability of poor outcomes. In this study, we evaluated whether the Naples Prognostic Score, a novel index that considers both inflammatory and nutritional values, was associated with long-term survival. This study presents a retrospective propensity score matching analysis of patients who underwent curative surgery for non-small cell lung cancer from January 2016 to December 2021. The score considered the following four pre-operative parameters: the neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, serum albumin, and total cholesterol. The Kaplan–Meier method and Cox regression analysis were performed to evaluate the relationship between the score and disease-free survival, overall survival, and cancer-related survival. A total of 260 patients were selected for the study, though this was reduced to 154 after propensity score matching. Post-propensity Kaplan–Meier analysis showed a significant correlation between the Naples Prognostic Score, overall survival (p = 0.018), and cancer-related survival (p = 0.007). Multivariate Cox regression analysis further validated the score as an independent prognostic indicator for both types of survival (p = 0.007 and p = 0.010, respectively). The Naples Prognostic Score proved to be an easily achievable prognostic factor of long-term survival in patients with non-small cell lung cancer after surgical treatment. [ABSTRACT FROM AUTHOR]

Background: Patients with malignant pleural effusion (MPE) typically have poor prognoses, and predicting survival is challenging. The present study aimed to identify prognostic factors of overall survival (OS) in non‐small cell lung cancer (NSCLC) patients with MPE in the time of immunotherapy and targeted therapy. Methods: Data of 344 consecutive NSCLC patients with MPE on clinical, radiological, and molecular characteristics and treatment options were collected. The risk factors in the training cohort were assessed using univariate and multivariate proportional hazards analyses. A clinical prognostic score was established and validated. Results: According to the results of the multivariable survival analysis, the Eastern Cooperative Oncology Group (ECOG) performance score (PS), antiangiogenic therapy, immunotherapy, and lactic dehydrogenase (LDH) in pleural fluid (CAIL) prognostic score was developed (n = 275) and subsequently validated (n = 69). Patients who underwent risk stratification into low‐, moderate‐, and high‐risk groups had median OS of 46.1, 23.1, and 9.6 months, respectively (P < 0.0001). The area under the curve (AUC) analysis showed the CAIL score to be superior at predicting survival compared with the LENT score at 6 (0.84 vs. 0.77, P < 0.01), 12 (0.87 vs. 0.82, P < 0.01), and 36 months (0.80 vs. 0.77, P < 0.01). Conclusions: For NSCLC patients with MPE, the validated CAIL prognostic score integrates clinical characteristics and therapeutic modalities to predict survival. [ABSTRACT FROM AUTHOR]

Background: More than three years after the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic outbreak, hospitals worldwide are still affected by coronavirus disease 19 (COVID-19). The availability of a clinical score that can predict the risk of death from the disease at the time of diagnosis and that can be used even if population characteristics change and the virus mutates can be a useful tool for emergency physicians to make clinical decisions. During the first COVID-19 waves, we developed the ANCOC (age, blood urea nitrogen, C-reactive protein, oxygen saturation, comorbidities) score, a clinical score based on five main parameters (age, blood urea nitrogen, C-reactive protein, oxygen saturation, comorbidities) that accurately predicts the risk of death in patients infected with SARS-CoV-2. A score of less than −1 was associated with 0% mortality risk, whereas a score of 6 was associated with 100% risk of death, with an overall accuracy of 0.920. The aim of our study is to internally validate the ANCOC score and evaluate whether it can predict 60-day mortality risk independent of vaccination status and viral variant. Methods: We retrospectively enrolled 843 patients admitted to the emergency department (ED) of our hospital with a diagnosis of COVID-19. A total of 515 patients were admitted from July 2021 to September 2021, when the Delta variant was prevalent, and 328 in January 2022, when the Omicron 1 variant was predominant. All patients included in the study had a diagnosis of COVID-19 confirmed by polymerase chain reaction (PCR) on an oropharyngeal swab. Demographic data, comorbidities, vaccination data, and various laboratory, radiographic, and blood gas parameters were collected from all patients to determine differences between the two waves. ANCOC scores were then calculated for each patient, ranging from −6 to 6. Results: Patients infected with the Omicron variant were significantly older and had a greater number of comorbidities, of which hypertension and chronic obstructive pulmonary disease (COPD) were the most common. Immunization was less common in Delta patients than in Omicron patients (34% and 56%, respectively). To assess the accuracy of mortality prediction, we constructed a receiver operating characteristic (ROC) curve and found that the area under the ROC curve was greater than 0.8 for both variants. These results suggest that the ANCOC score is able to predict 60-day mortality regardless of viral variant and whether the patient is vaccinated or not. Conclusion: In a population with increasingly high vaccination rates, several parameters may be considered prognostic for the risk of fatal outcomes. This study suggests that the ANCOC score can be very useful for the clinician in an emergency setting to quickly understand the patient's evolution and provide proper attention and the most appropriate treatments. [ABSTRACT FROM AUTHOR]

Simple Summary: Liver metastasis is a significant factor contributing to mortality associated with colorectal cancer. Establishing the biological mechanisms of metastasis is crucial for refining diagnostics and identifying therapeutic windows for interventions. Currently, little is known of the processes that govern the development of liver metastases, the role of the tumor microenvironment, the role of epigenetics, and potential treatment-induced shaping effects. Machine learning-based bioinformatics has provided an important methodical option to decipher fine-granular details of the transcriptomic landscape of tumor heterogeneity and the underlying molecular mechanisms. Our molecular portrayal method has potential implications for treatment decisions, which may require personalized diagnostics. The molecular mechanisms of the liver metastasis of colorectal cancer (CRLM) remain poorly understood. Here, we applied machine learning and bioinformatics trajectory inference to analyze a gene expression dataset of CRLM. We studied the co-regulation patterns at the gene level, the potential paths of tumor development, their functional context, and their prognostic relevance. Our analysis confirmed the subtyping of five liver metastasis subtypes (LMS). We provide gene-marker signatures for each LMS, and a comprehensive functional characterization that considers both the hallmarks of cancer and the tumor microenvironment. The ordering of CRLMs along a pseudotime-tree revealed a continuous shift in expression programs, suggesting a developmental relationship between the subtypes. Notably, trajectory inference and personalized analysis discovered a range of epigenetic states that shape and guide metastasis progression. By constructing prognostic maps that divided the expression landscape into regions associated with favorable and unfavorable prognoses, we derived a prognostic expression score. This was associated with critical processes such as epithelial–mesenchymal transition, treatment resistance, and immune evasion. These factors were associated with responses to neoadjuvant treatment and the formation of an immuno-suppressive, mesenchymal state. Our machine learning-based molecular profiling provides an in-depth characterization of CRLM heterogeneity with possible implications for treatment and personalized diagnostics. [ABSTRACT FROM AUTHOR]

Purpose: To investigate a prognostic score for stage II–III colorectal cancer (CRC) based on post-CEA and pT4 levels. Methods: Two cohorts of stage II–III CRC patients who underwent curative surgery between 2011 and 2017 were included. The prognostic score (T-CEA score) was calculated as follows: T-CEA-0, post-CEA ≤ 5 ng/mL and pT1–3; T-CEA-1, post-CEA > 5 ng/mL or pT4; T-CEA-2, post-CEA > 5 ng/mL and pT4. Results: The T-CEA scores of the 587 patients were as follows: T-CEA-0 (n = 436; 74%), T-CEA-1 (n = 129; 22%), and T-CEA-2 (n = 10; 2%). The 5-year recurrence-free survival (RFS) rates of the T-CEA-0, 1, and 2 groups were 80.3%, 54.8%, and 0%, respectively (P < 0.01), and the 5-year overall survival (OS) rates were 90.9%, 74.2%, and 0%, respectively (T-CEA-0 vs T-CEA-1: P < 0.01, T-CEA-1 vs T-CEA-2: P = 0.04). Multivariate analysis revealed that an elevated T-CEA score of 1 or 2 was a significant risk factor for poor RFS (HR: 2.89, P < 0.01) and OS (HR: 2.85, P < 0.01). Conclusion: The T-CEA score is a reliable and convenient prognostic score for stage II–III CRC. [ABSTRACT FROM AUTHOR]

Brain metastases (BM) from lung cancer are among the most common intracranial tumors. Several studies have published scales to estimate the survival of patients with BM. Routine access to molecular diagnostics and modern oncologic treatments, including targeted therapy and immunotherapy, is limited in low- and middle-income countries (LMICs); therefore, incorporating them into recent prognostic scales may diminish the reliability of the scales in LMICs. This retrospective study aimed to determine the survival of 55 patients who were surgically treated for BM from lung cancer at a Brazilian public tertiary teaching hospital between 2012 and 2022. We determined clinical factors associated with survival, and compared observed survival rates with the estimated survival on prognostic scales. The mean overall survival (OS) was 9.3 months (range:0.2–76.5). At univariate analysis, female sex and improved postoperative Karnofsky performance status (KPS) score were associated with longer survival. The median survival did not differ between groups when classified using the Graded Prognostic Assessment (GPA)-2008, Lung-molecular GPA-2017, and Lung-GPA-2021 scales. According to the Diagnosis-Specific (DS)-GPA-2012 scale, there was a significant difference between the groups. In the multivariate Cox regression survival analysis, a higher DS-GPA-2012 and improved postoperative KPS score remained significantly associated with longer survival. In conclusion, this cohort showed a mean OS of < 1 year. Improved KPS score after surgery was associated with increased survival. This cohort DS-GPA scale demonstrated the highest concordance with observed survival, indicating its potential as a valuable tool for patient stratification in surgical treatment decision-making in LMICs. [ABSTRACT FROM AUTHOR]

Study Design.: Retrospective case series. Objective.: To investigate the accuracy of seven scoring systems for the prediction of survival in lung cancer patients with spinal metastases (SPM). Summary of Background Data.: Although survival scoring systems have been developed for surgical decision-making, the reliability and validity of these models are unclear for specific cancer types. As the prevalence of patients with lung cancer increases, it is imperative to determine the accuracy of these models for lung cancer patients with SPM. Materials and Methods.: This is a retrospective study of a cohort of lung cancer patients with SPM who underwent spine surgery between 2019 and 2021 at two centers. The optimal area under the curve (AUC) was calculated to evaluate the accuracy of seven candidate scoring systems at 3, 6, and 12 months. Calibration and decision curve analysis was used for further validation. Results.: A total of 166 patients (mean age: 58.98±10.94; 105 males and 61 females) with SPM were included. The median postoperative survival was 12.87±0.93 months. The modified Bauer score, revised Tokuhashi score, Linden score, Tomita score, the Skeletal Oncology Research Group nomogram, and the New England Spinal Metastasis Score in prediction survival at 3, 6, and 12 months showed a slightly weaker AUC (range 0.464–0.659). The AUC of the Katagiri-New score in predicting 1-year survival for lung cancer patients was the highest (0.708; range 0.619–0.798). The decision curve analysis showed that the Katagiri-New score led to a greater net benefit than the strategies of changing management for all patients or none of the patients. Conclusions.: This study suggests that the most commonly used models have limitations in predicting survival in patients undergoing spinal surgery for metastatic lung cancer and underestimate survival. In this sample of lung cancer patients, the Katagiri-New Scoring system score had the best performance in predicting 1-year survival. Level of Evidence.: 4. [ABSTRACT FROM AUTHOR]

Introduction: Surgical-site infections (SSI) account for a large proportion of morbidity, with an incidence of 500,000 cases per year from 27 million surgeries. Some researchers have found that the factors contributing to surgical wound infections include the number of bacterial contaminants, the virulence of the bacteria, the micro-environment around the surgical wound, and the immune system of the host. Aim: The aim of the study is to calculate the risk factors for surgical-site infections in a neonatal and pediatric intensive care unit and to apply them in a risk index for neonates and pediatrics in critical care units. Method: A retrospective cohort study was conducted at Tarakan General Hospital from January 2018 to July 2019 to investigate risk factors for SSIs. The various factors were then analyzed with the chi-square test, whereas the multivariate binary logistic regression model was used to examine independent risk factors for SSIs. Results: A total of 179 patients met the inclusion criteria. There were 66 patients in the NICU and 113 in the PICU. The bivariate analysis showed that SSI was associated with the type of ward, the operating room temperature, perioperative septicemia, the length of stay, and the use of chlorhexidine bathing (p < 0.05). The multivariate analysis identified three independent parameters correlating with the occurance of SSI: operating room temperature (odds ratio [OR] 12,510; 95% confidence interval [CI] 4,198 –37,279; p < 0.001); perioperative septicemia (OR 6,424; 95% CI 2,221–18,581; p=0.001); and chlorhexidine bathing (OR 35,751; 95% CI 8,627–148,164; p < 0.001). Conclusion: From these three independent paramaters, we recommend a prognostic scoring index for SSIs in postoperative NICU and PICU patients that requires further diagnostic, validity and realibility testing to improve patient outcomes. [ABSTRACT FROM AUTHOR]

Introduction: There are few scores for mortality prediction in acute respiratory distress syndrome (ARDS) incorporating comprehensive ventilatory, acute physiological, organ dysfunction, oxygenation, and nutritional parameters. This study aims to determine the risk factors of ARDS mortality from the above-mentioned parameters at 48 h of invasive mechanical ventilation (IMV), which are feasible across most intensive care unit settings. Methods: Prospective, observational, single-center study with 150 patients with ARDS defined by Berlin definition, receiving IMV with lung protective strategy. Results: Our study had a mortality of 41.3% (62/150). We developed a 9-point novel prediction score, the driving pressure oxygenation and nutritional evaluation (DRONE) score comprising of driving pressure (DP), oxygenation accessed by the ratio of partial pressure of arterial oxygen to the fraction of inspired oxygen (PaO2/FiO2) ratio and nutritional evaluation using the modified nutrition risk in the critically ill (mNUTRIC) score. Each component of the DRONE score with the cutoff value to predict mortality was assigned a particular score (the lowest DP within 48 h in a patient being always ≥15 cmH2O a score of 2, the highest achievable PaO2/FiO2 <208 was assigned a score of 4 and the mNUTRIC score ≥4 was assigned a score of (3). We obtained the DRONE score ≥4, area under the curve 0.860 to predict mortality. Cox regression for the DRONE score >4 was highly associated with mortality (P < 0.001, hazard ratio 5.43, 95% confidence interval [2.94–10.047]). Internal validation was done by bootstrap analysis. The clinical utility of the DRONE score ≥4 was assessed by Kaplan–Meier curve which showed significance. Conclusions: The DRONE score ≥4 could be a reliable predictor of mortality at 48 h in ARDS patients receiving IMV. [ABSTRACT FROM AUTHOR]

Background: Despite high effectiveness of therapeutic plasma exchange as the first‐line therapy, thrombotic thrombocytopenic purpura (TTP) remains a life‐threatening condition and may require utilization of adjunct modalities in certain patients. Mortality In TTP Score (MITS) is a prognostic risk stratified scoring tool designed to predict mortality in hospitalized patients with TTP. There has not been an external validation of MITS to date. Study Design and Methods: We performed an external validation of MITS in patients hospitalized with TTP using the National Inpatient Sample database from 2016 to 2019. We identified 4589 patients who met the selection criteria. Univariate and multivariable logistic regression models were run based on the MITS parameters of arterial thrombosis, intracranial haemorrhage, age, renal failure, ischemic stroke, platelet transfusion, and myocardial infarction to evaluate prognostic performance and discriminatory power of this tool. Results: All‐cause mortality was reported more frequently in female subjects (57.8%), Caucasian race (58.9%), and ages 60 years, and above (52.3%). In a multivariable analysis, the variables included in the MITS criteria remained significant predictors of mortality. Moreover, MITS correlated with mortality risk. Our model's area under the receiving operator character curve was 71%, compared to 78.6% in the derivation cohort study. Discussion: In this external validation cohort, performance of MITS was similar to the derivation cohort, validating it as a valuable clinical tool that may guide management of TTP patients. [ABSTRACT FROM AUTHOR]

Simple Summary: The preoperative risk estimation of non-enhancing suspected "low-grade" glioma (NEG) is key in determining the optimal timing of diagnosis and treatment to delay malignant progression and avoid undertreatment. The updated 2021 WHO classification brought new facets to glioma grading. Therefore, we sought to identify preoperative risk factors of malignancy in NEG by considering molecular criteria, including IDH mutation and CDKN2A/B deletion status. A total of 72 NEG patients were analyzed, and a high prevalence of malignant gliomas was detected considering both the traditional WHO grading (WHO grade 3 + 4) and the integrated molecular classification (IDHwt glioblastoma WHO grade 4 and IDHmut astrocytoma WHO grade 4). Easily determinable preoperative factors (age, T2/FLAIR mismatch sign, and SVZ involvement) were identified by uni- and multivariate analyses and incorporated into a score. The score estimates the probability of an NEG harboring a malignant glioma. Finally, the score was validated in a cohort of 40 NEG patients and proved to be a better prediction model than the Pignatti score or the T2/FLAIR mismatch sign. The preoperative grading of non-enhancing glioma (NEG) remains challenging. Herein, we analyzed clinical and magnetic resonance imaging (MRI) features to predict malignancy in NEG according to the 2021 WHO classification and developed a clinical score, facilitating risk estimation. A discovery cohort (2012–2017, n = 72) was analyzed for MRI and clinical features (T2/FLAIR mismatch sign, subventricular zone (SVZ) involvement, tumor volume, growth rate, age, Pignatti score, and symptoms). Despite a "low-grade" appearance on MRI, 81% of patients were classified as WHO grade 3 or 4. Malignancy was then stratified by: (1) WHO grade (WHO grade 2 vs. WHO grade 3 + 4) and (2) molecular criteria (IDHmut WHO grade 2 + 3 vs. IDHwt glioblastoma + IDHmut astrocytoma WHO grade 4). Age, Pignatti score, SVZ involvement, and T2/FLAIR mismatch sign predicted malignancy only when considering molecular criteria, including IDH mutation and CDKN2A/B deletion status. A multivariate regression confirmed age and T2/FLAIR mismatch sign as independent predictors (p = 0.0009; p = 0.011). A "risk estimation in non-enhancing glioma" (RENEG) score was derived and tested in a validation cohort (2018–2019, n = 40), yielding a higher predictive value than the Pignatti score or the T2/FLAIR mismatch sign (AUC of receiver operating characteristics = 0.89). The prevalence of malignant glioma was high in this series of NEGs, supporting an upfront diagnosis and treatment approach. A clinical score with robust test performance was developed that identifies patients at risk for malignancy. [ABSTRACT FROM AUTHOR]

Background: Morbidity/mortality and oncologic outcomes can be worsened in geriatric rectal cancer patients due to comorbidities and frailty. The aim of this study was to compare surgical and oncological results of geriatric rectal cancer patients using inflammation-based prognostic scores. Methods: The prospectively maintained database of 991 rectal cancer patients treated at our center between 2007 and 2020 were analyzed. All conventional clinicopathologic features, and oncologic outcomes are compared between patients ≥ 65 years old (geriatric patients: Group I) and < 65 years old (non-geriatric patients: Group II). The modified Glasgow Prognostic Score (mGPS) and the C-reactive protein-albumin ratio (CAR), were determined. The prognostic value of mGPS and CAR as well as the well-known clinico-pathologic factors to predict surgical morbidity, mortality, local and/or distant recurrence, and overall survival was assessed. Results: There were 567 (57.2%) patients who were ≥ 65 years old (Group I; 349 males, median age 74 [range 65–9]) years) and 424 (42.8%) who were < 65 years old (Group II; 252 males, median age 58 [range 20–64] years). The high-grade [Clavien–Dindo III–IV] complications rates of Group I and Group II patients sere 20% (n = 113), and 9% (n = 37), respectively. High-grade complications were related to mGPS (p < 0.001) and CAR (p < 0.001) values. The high-grade complication rate was found to be higher in Group I than in Group II, and this was statistically significant (p < 0.001). High preoperative mGPS and CAR values were significantly associated with postoperative mortality (p < 0.001). In Cox multivariate analysis, mGPS (p = 0.003) and CAR (p = 0.001) were significantly in correlation with lowered overall survival. The mGPS and CAR were found to be independent prognostic factors for overall survival. Conclusions: The mGPS and CAR can predict severe postoperative complications and early mortality. mGPS, and CAR have a powerful prognostic value and the potential clinical usefulness to predict decreased overall survival in both geriatric and non-geriatric rectal cancer patients. [ABSTRACT FROM AUTHOR]

Among the myeloproliferative diseases, myelofibrosis is a widely heterogeneous entity characterized by a highly variable prognosis. In this context, several prognostic models have been proposed to categorize these patients appropriately. Identifying who deserves more invasive treatments, such as bone marrow transplantation, is a critical clinical need. Age, complete blood count (above all, hemoglobin value), constitutional symptoms, driver mutations, and blast cells have always represented the milestones of the leading models still used worldwide (IPSS, DIPSS, MYSEC-PM). Recently, the advent of new diagnostic techniques (among all, next-generation sequencing) and the extensive use of JAK inhibitor drugs have allowed the development and validation of new models (MIPSS-70 and version 2.0, GIPSS, RR6), which are continuously updated. Finally, the new frontier of artificial intelligence promises to build models capable of drawing an overall survival perspective for each patient. This review aims to collect and summarize the existing standard prognostic models in myelofibrosis and examine the setting where each of these finds its best application. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is one of the greatest challenges facing global medical research. The availability of a clinical score that can predict mortality risk at the time of diagnosis could be a valuable tool in the hands of emergency physicians to make clinical decisions. Our study is designed to evaluate clinical and laboratory endpoints associated with mortality and to determine a prognostic score based on clinical and laboratory variables. We retrospectively enrolled 367 patients diagnosed with coronavirus disease 19 (COVID-19) in our emergency department (ED). We evaluated their mortality 60 days after diagnosis. Symptoms, demographic data, concomitant diseases, and various laboratory parameters were obtained from all patients. Variables related to death were assessed using multiple logistic regression analysis. From these, we created a score called ANCOC (Age, blood urea Nitrogen, C-reactive protein, Oxygen saturation, Comorbidities). The area under the receiver operating characteristic (ROC) curve was calculated for the ANCOC and for the 4C score. The 4C score has been described and validated in previous works and can predict mortality in COVID-19 patients. We compared the 2 scores and analysed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for 60-day mortality for the ANCOC score. The ANCOC and 4C scores accurately predicted death from COVID-19. There were no differences in accuracy between the scores. An ANCOC score <-1 identified patients who will recover with a PPV and sensitivity of 100%, whereas a score >3 identified patients at high risk of death. The ANCOC score has very high diagnostic accuracy in predicting the risk of death in patients with COVID-19 diagnosed at ED. The ANCOC score has similar accuracy to the 4C score but is easier to calculate. If validated by external cohorts, this score could be an additional tool in the hands of ED physicians to identify COVID-19 patients at high risk of death. [ABSTRACT FROM AUTHOR]

An important step for any causal inference study design is understanding the distribution of the subjects in terms of measured baseline covariates. However, not all baseline variation is equally important. We propose a set of visualizations that reduce the space of measured covariates into two components of baseline variation important to the design of an observational causal inference study: a propensity score summarizing baseline variation associated with treatment assignment and a prognostic score summarizing baseline variation associated with the untreated potential outcome. These assignment-control plots and variations thereof visualize study design tradeoffs and illustrate core methodological concepts in causal inference. As a practical demonstration, we apply assignment-control plots to a hypothetical study of cardiothoracic surgery. To demonstrate how these plots can be used to illustrate nuanced concepts, we use them to visualize unmeasured confounding and to consider the relationship between propensity scores and instrumental variables. While the family of visualization tools for studies of causality is relatively sparse, simple visual tools can be an asset to education, application, and methods development. [ABSTRACT FROM AUTHOR]

Colloid cysts, although benign, may occasionally cause obstructive hydrocephalus and sudden death. Reliable prognostic factors for symptomatic progression have been sought, with heterogenous results. We conducted a retrospective review of all cases of colloid cysts of the third ventricle managed at our center between 2009 and 2019. Clinical and neuroimaging characteristics were analyzed using logistic regression in relation to symptomatic status and hydrocephalus. The cutoff values for outcome prediction were calculated using the receiver operating characteristic curve analysis. There were 82 patients with colloid cysts, of whom 60 were asymptomatic and 22 symptomatic. None of the asymptomatic patients experienced acute neurologic decline or hydrocephalus during follow-up, whereas half (n = 11) of the symptomatic patients presented with hydrocephalus, 8 of whom had acute hydrocephalus. We found 3 putative candidate risk factors for symptomatic colloid cysts: T1-weighted magnetic resonance imaging hyperintense/mixed signal appearance (P = 0.004), location in risk zone I (P = 0.007), and a volume >236.49 mm3 (P = 0.007). Cyst diameter and volume/foramen of Monro diameter ratios had a decreasing trend over time among asymptomatic patients, providing new insights into the natural history of the disease. Only a few asymptomatic colloid cysts showed progression requiring surgery, with no acute deterioration or fatal events, whereas the rest remained stable over time, thus supporting a more conservative approach for this group of patients. Higher risk for developing symptomatic colloid cyst was defined by a risk score that included T1-weighted magnetic resonance imaging appearance, risk zone, and colloid cyst volume, aiding the detection of patients at risk of clinical deterioration. [ABSTRACT FROM AUTHOR]

Background: Early recognition and treatment of patients with acute pancreatitis (AP) is important to improve prognosis and increase survival. Many scoring systems have been developed to assess the prognosis and disease severity in AP. The aim of this study was to compare the effectiveness of the Charlson Comorbidity Index (CCI), Bedside Index for Severity in AP (BISAP), and Acute Physiology and Chronic Health Evaluation (APACHE II) scores in predicting 30-day mortality and the development of severe AP (SAP) in patients with mild AP (MAP). Materials and Methods: This single-center, retrospective, and observational study was conducted with adult patients classified as MAP within 48 hours of arrival at the emergency department. Areas under the receiver operating characteristic curve (AUC) were calculated for each score to evaluate the effectiveness of the scores in predicting the development of SAP and 30-day mortality. Results: A total of 1419 patients with MAP were included in the study between January 01, 2018 and April 01, 2022. In MAP patients, SAP development rate was 14.4%, and the 30-day mortality rate was 1.8%. The accuracy of CCI (AUC=0.797±0.015) in predicting the development of SAP was significantly higher than BISAP (AUC =0.736±0.019, p<0.001) and APACHE II (AUC =0.755±0.017, p=0.028) scores. The accuracy of CCI (AUC 0.797±0.040) in predicting 30-day mortality was similar to the BISAP score (AUC 0.790±0.041, p=0.844) and APACHE II score (AUC=0.762±0.042, p=0.417). There was no significant difference between the accuracy of BISAP and APACHE II scores in predicting the development of SAP (p= 0.196) and 30-day mortality (p=0.462). Conclusion: The CCI is a scoring system as effective as BİSAP and APACHE 2 scores in predicting the development of SAP and 30-day mortality in patients with MAP in our study population. [ABSTRACT FROM AUTHOR]

Simple Summary: Radioembolization (RE) for intrahepatic cholangiocarcinoma (ICC) is a viable treatment option. As the overall survival (OS) is subject to considerable variance, proper patient selection is of the utmost importance. The current study elucidated overall survival (time from treatment to the patient's death) in 39 patients after RE in ICC. Out of all the investigated parameters, we identified three pre-therapeutic parameters which were able to predict both OS and patient prognosis by means of a score. More specifically, stratification of the patient cohort by pre-therapeutic GGT, clinical performance status (ECOG) and albumin resulted in significant differences regarding OS (0 risk factors, 15.3 months; 1 risk factor, 7.6 months; ≥2 risk factors, 1.8 months, respectively). Consequently, implementation of this proposed prognostic score may facilitate pre-therapeutic identification of patients who could benefit from RE in ICC. Radioembolization (RE) is a viable therapy option in patients with intrahepatic cholangiocarcinoma (ICC). This study delineates a prognostic score regarding overall survival (OS) after RE using routine pre-therapeutic parameters. A retrospective analysis of 39 patients (median age, 61 [range, 32–82] years; 26 females, 13 males) with ICC and 42 RE procedures was conducted. Cox regression for OS included age, ECOG, hepatic and extrahepatic tumor burden, thrombosis of the portal vein, ascites, laboratory parameters and dose reduction due to hepatopulmonary shunt. Median OS after RE was 8.0 months. Using univariable Cox, ECOG ≥ 1 (hazard ratio [HR], 3.8), AST/ALT quotient (HR, 1.86), high GGT (HR, 1.002), high CA19-9 (HR, 1.00) and dose reduction of 40% (HR, 3.8) predicted shorter OS (each p < 0.05). High albumin predicted longer OS (HR, 0.927; p = 0.045). Multivariable Cox confirmed GGT ≥ 750 [U/L] (HR, 7.84; p < 0.001), ECOG > 1 (HR, 3.76; p = 0.021), albumin ≤ 41.1 [g/L] (HR, 3.02; p = 0.006) as a three-point pre-therapeutic prognostic score. More specifically, median OS decreased from 15.3 months (0 risk factors) to 7.6 months (1 factor) or 1.8 months (≥2 factors; p < 0.001). The proposed score may aid in improved pre-therapeutic patient identification with (un-)favorable OS after RE and facilitate the balance between potential life prolongation and overaggressive patient selection. [ABSTRACT FROM AUTHOR]

Objective·To explore clinical and pathological characteristics, prognosis and potential related factors of breast cancer patients with brain metastases. Methods·Seventy-five female breast cancer patients with brain metastases admitted to Renji Hospital, Shanghai Jiao Tong University School of Medicine from January 2007 to December 2021 were selected. The clinical and pathological characteristics of the patients were collected through clinical electronic cases, and the overall survival after brain metastases (OSBM) of the patients was collected during the follow-up period. Receiver operating characteristic curve (ROC curve) was used to evaluate the predictive efficiency of different biochemical factors on OSBM. Kaplan-Meier survival curve was used to analyze the correlation between different clinical and pathological characteristics and patients' OSBM. Cox proportional hazards regression analysis was further performed on statistically significant factors to determine independent influencing factors. Results·The OSBM of 75 patients was 11.0 (5.0, 24.0) months. The results of ROC curve showed that carbohydrate antigen 125 (CA125) had a good prediction effect on OSBM, and its best cut-off value was 22.3 U/mL. The results of Kaplan-Meier survival analysis showed that the patients whose first metastatic site was brain (P=0.046), whose extracranial disease status was progressed (P= 0.042), whose brain metastasis involved one side of tentorium (P=0.013), whose CA125 level<22.3 U/mL (P=0.000), whose treatment methods incladed regional therapy (P=0.034) and whose modified Graded Prognostic Assessment (mGPA) score>1 (P= 0.001), had longer OSBM. Cox proportional hazards regression analysis showed that brain metastasis involving both sides of tentorium or meningeal (P=0.029), and CA125 level≥22.3 U/mL (P=0.005) were the risk factors for OSBM, and mGPA score>1 (P= 0.033) was the protective factor. Conclusion·The position of brain metastases in breast cancer, the level of CA125 and the mGPA score are important factors affecting the prognosis of patients. [ABSTRACT FROM AUTHOR]

Purpose: Achieving complete cytoreduction (CCR) is crucial for a patient's prognosis with advanced epithelial ovarian cancer (EOC). So far, prognostic predictors have failed to predict surgical outcome after neoadjuvant chemotherapy (NACT). In clinical trials, scores were used to predict operability in recurrent ovarian cancer (Harter et al. in N Engl J Med 385(23):2123–2131, 2021) but there is no known prediction score for CCR after NACT. The Peritoneal Cancer Index (PCI) is an established tool to predict surgical outcome in primary setting (Lampe et al. in 25:135–144, 2015). We now examined the predictive power of the PCI to achieve CCR after NACT. Methods: In this single-center study, the data of patients with advanced stage EOC (FIGO > IIIb) treated between 01/2015 and 12/2020 were analyzed retrospectively. Inclusion criteria were a mandatory staging laparoscopy, a PCI score > 25, and NACT. CT scans were analyzed in blinded fashion according to RECIST criteria (Borgani et al. in 237; 93–99, 2019) Reaction of PCI after NACT was compared with the analysis of radiologic imaging and CA-125 levels. Results: Three hundred and sixteen patients were screened, 62 were treated with NACT, and 23 were included in our analysis. 87% of cases presented with an FIGO IIIc stadium. The reduction of PCI itself after NACT showed to be the most powerful predictor for achieving CCR. The reduction of the initial PCI score by minimum of 8.5 points was a better predictor for CCR than reaching a PCI < 25. In contrast to data deriving from patients undergoing primary debulking surgery (PDS), we found a PCI of 17, rather than 25, to be a more valuable cut-off for CCR in neoadjuvant-treated patients. Conclusion: The extend of PCI reduction after NACT is a better predictor for achieving CCR compared with CA125 levels and radiologic imaging. The PCI must be assessed differently in neoadjuvant setting than in a primary situation. CCR was most likely for a post-NACT PCI < 17. [ABSTRACT FROM AUTHOR]

To identify and utilize gene signatures for the prognostic evaluation of postoperative patients with hepatocellular carcinoma (HCC). The gene mRNA expression profiles and corresponding clinicopathological data of postoperative patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) database. Highly differentially expressed genes (DEGs) in tumor tissues compared to adjacent tissues were identified, and their associations with the overall survival (OS) of HCC patients were analyzed. The strongly associated genes were used to develop a prognostic score for the survival stratification of HCC, and the underlying mechanisms were analyzed using bioinformatics. A total of 376 DEGs were identified and four DEGs (ADH4, COL15A1, RET and KCNJ16) were independently associated with OS. A prognostic score derived from the four genes could effectively stratify HCC patients with different OS outcomes, independent of clinical parameters. Patients with high scores exhibited poorer OS than patients with low scores (HR 5.526, 95% CI: 2.451–12.461, p <.001). The four genes were involved in cancer-related biological processes and were independent of each other in bioinformatics analyses. Four genes strongly associated with the prognosis of postoperative patients with HCC were identified, and the derived prognostic score was simple and valuable for overall survival prediction. [ABSTRACT FROM AUTHOR]

Objectives: Coronavirus disease-2019 (COVID-19) disease has overwhelmed the healthcare infrastructure worldwide. The shortage of intensive care unit (ICU) beds leads to longer waiting times and higher mortality for patients. High crowding leads to an increase in mortality, length of hospital stays, and hospital costs for patients. Through an appropriate stratification of patients, rational allocation of the available hospital resources can be accomplished. Various scores for risk stratification of patients have been tried, but for a score to be useful at primary care level, it should be readily available at the bedside and be reproducible. ROX index and CURB-65 are simple bedside scores, requiring minimum equipment, and investigations to calculate. Methods: This retrospective, record-based study included adult patients who presented to the ED from May 1, 2020 to November 30, 2020 with confirmed COVID-19 infection. The patient's clinical and demographic details were obtained from the electronic medical records of the hospital. ROX index and CURB-65 score on ED arrival were calculated and correlated with the need for hospitalization and early (14-day) and late (28-day) mortality. Results: 842 patients were included in the study. The proportion of patients with mild, moderate and severe disease was 46.3%, 14.9%, and 38.8%, respectively. 55% patients required hospitalization. The 14-day mortality was 8.8% and the 28-day mortality was 20.7%. The AUROC of ROX index for predicting hospitalization was 0.924 (p < 0.001), for 14-day mortality was 0.909 (p < 0.001) and for 28-day mortality was 0.933 (p < 0.001). The AUROC of CURB-65 score for predicting hospitalization was 0.845 (p < 0.001), for 14-day mortality was 0.905 (p < 0.001) and for 28-day mortality was 0.902 (p < 0.001). The cut-off of ROX index for predicting hospitalization was ≤18.634 and for 14-day mortality was ≤14.122. Similar cut-off values for the CURB-65 score were ≥1 and ≥2, respectively. Conclusion: ROX index and CURB-65 scores are simple and inexpensive scores that can be efficiently utilised by primary care physicians for appropriate risk stratification of patients with COVID-19 infection. [ABSTRACT FROM AUTHOR]

Simple Summary: Intensive care admission is a common complication of allogeneic hematopoietic stem cell transplantation. Mortality remains very high, and among several prognosis tools, data about power of discrimination showed contradictory results. The aim of our retrospective study was to evaluate the efficacy of a new score, the Prognostic Index for Critically Ill Allogeneic Transplantation (PICAT) Patients, for this specific setting in a cohort of 111 patients. We confirmed the ability of this score to discriminate three groups of patients with different outcomes. Moreover, we evaluated a classic intensive score, the Sequential Organ Failure Assessment (SOFA), and we showed that the SOFA outperformed the PICAT to predict outcomes in our cohort. Background. Allogeneic hematopoietic stem cell transplantation (allo-HCT) recipients requiring intensive care unit (ICU) have high mortality rates. Methods. In the current study, we retrospectively assessed whether the Prognostic Index for Critically Ill Allogeneic Transplantation patients (PICAT) score predicted overall survival in a cohort of 111 consecutive allo-HCT recipients requiring ICU. Results. Survival rates at 30 days and 1 year after ICU admission were 57.7% and 31.5%, respectively, and were significantly associated with PICAT scores (p = 0.036). Specifically, survival at 30-day for low, intermediate, and high PICAT scores was 64.1%, 58.1%, and 31.3%, respectively. At one-year, the figures were 37.5%, 29%, and 12.5%, respectively. In multivariate analyses, high PICAT score (HR = 2.23, p = 0.008) and relapse prior to ICU admission (HR = 2.98, p = 0.0001) predicted higher mortality. We next compared the ability of the PICAT and the Sequential Organ Failure Assessment (SOFA) scores to predict mortality in our patients using c-statistics. C statistics for the PICAT and the SOFA scores were 0.5687 and 0.6777, respectively. Conclusions. This study shows that while the PICAT score is associated with early and late mortality in allo-HCT recipients requiring ICU, it is outperformed by the SOFA score to predict their risk of mortality. [ABSTRACT FROM AUTHOR]

Background: A previous score predicted death ≤ 2 months following radiotherapy for MSCC. For patients with a high probability of early death, best supportive care was recommended. However, some of these patients may benefit from radiotherapy regarding preservation or improvement of motor function. To identify these patients, an additional score was developed.Methods: Pre-treatment factors plus radiotherapy regimen were retrospectively evaluated for successful treatment (improved motor function or remaining ambulatory without aid) and post-treatment ambulatory status in 545 patients who died ≤ 2 months. Factors included age, interval from tumor diagnosis until MSCC, visceral metastases, further bone metastases, primary tumor type, sex, time developing motor deficits, pre-treatment ambulatory status, and number of affected vertebrae. Factors significant on both multivariable analyses were included in the score (worse outcomes 0 points, better outcomes 1 point).Results: On multivariable analyses, myeloma/lymphoma, time developing motor deficits > 14 days, and pre-treatment ambulatory status were significantly associated with both successful treatment and ambulatory status, affection of 1-2 vertebrae with successful treatment only. On univariable analyses, 1 × 8 and 5 × 4 Gy were not inferior to 5 × 5 Gy and longer-course regimens. Considering the three factors significant for both endpoints, three groups were designed (0, 1, 2-3 points) with treatment success rates of 4%, 15% and 39%, respectively (p < 0.0001), and post-treatment ambulatory rates of 4%, 43% and 86%, respectively (p < 0.0001).Conclusion: This score helps identify patients with MSCC who appear to benefit from palliative radiotherapy in terms of improved motor function or remaining ambulatory in spite of being near end of life. [ABSTRACT FROM AUTHOR]

Background: There is a need for a mortality score that can be used to trigger advanced care planning among older patients discharged from acute geriatric units (AGUs).Objective: We developed a prognostic score for 3- and 12-month mortality after discharge from an AGU, based on a comprehensive geriatric assessment, in-hospital events, and the exclusion of patients already receiving palliative care.Methods: Devenir Après la Médecine Aigue Gériatrique (DAMAGE) is a French multicenter, prospective, cohort study. The broad inclusion criteria ensured that the cohort is representative of patients treated in an AGU. The DAMAGE participants underwent a comprehensive geriatric assessment, a daily clinical checkup, and follow-up visits 3 and 12 months after discharge. Multivariable logistic regression models were used to develop a prognostic score for the derivation and validation subsets.Results: A total of 3 509 patients were assessed and 3 112 were included. The patient population was very old and frail or dependant, with a high proportion of deaths at 3 months (n = 455, 14.8%) and at 12 months (n = 1 014, 33%). The score predicted an individual risk of mortality ranging from 1% to 80% at 3 months and between 5% and 93% at 12 months, with an area under the receiving operator characteristic curve in the validation cohort of 0.728 at 3 months and 0.733 at 12 months.Conclusions: Our score predicted a broad range of risks of death after discharge from the AGU. Having this information at the time of hospital discharge might trigger a discussion on advanced care planning and end-of-life care with very old, frail patients. Clinical Trials Registration Number: NCT02949635. [ABSTRACT FROM AUTHOR]

Abbreviated pathogenesis and clinical course of the acute liver failure syndrome. The pathogenesis and clinical course of the syndrome of acute liver failure (ALF) differs depending upon the etiology of the primary liver injury. In turn, the severity of the liver injury and resulting synthetic failure is often the primary determinant of whether a patient is referred for emergency liver transplantation. Injuries by viral etiologies trigger the innate immune system via pathogen-associated molecular patterns (PAMPs), while toxin-induced (and presumably ischemia-induced) injuries do so via damage-associated molecular patterns (DAMPs). The course of the clinical syndrome further depends upon the relative intensity and composition of cytokine release, resulting in an early proinflammatory phenotype (SIRS) and later compensatory anti-inflammatory response phenotype (CARS). The outcomes of overwhelming immune activation are the systemic (extrahepatic) features of ALF (cardiovascular collapse, cerebral edema, acute kidney injury, respiratory failure, sepsis) which ultimately determine the likelihood of death. Acute liver failure (ALF) continues to carry a high risk of mortality or the need for transplantation despite recent improvements in overall outcomes over the past two decades. Optimal management begins with identifying that liver failure is indeed present and its etiology, since outcomes and the need for transplantation vary widely across the different etiologies. Most causes of ALF can be divided into hyperacute (ischemia and acetaminophen) and subacute types (other etiologies), based on time of evolution of signs and symptoms of liver failure; the former evolve in 3 to 4 days and the latter typically in 2 to 4 weeks. Both involve intense release of cytokines and hepatocellular contents into the circulation with multiorgan effects/consequences. Management involves optimizing fluid balance and cardiovascular support, including the use of continuous renal replacement therapy, vasopressors, and pulmonary ventilation. Early evaluation for liver transplantation is advised particularly for acetaminophen toxicity, which evolves so rapidly that delay is likely to lead to death. Vasopressor support, high-grade hepatic encephalopathy, and unfavorable (subacute) etiologies heighten the need for urgent listing for liver transplantation. Prognostic scores such as Kings Criteria, Model for End-Stage Liver Disease, and the Acute Liver Failure Group prognostic index take these features into account and provide reasonable but imperfect predictive accuracy. Future treatments may include liver support devices and/or agents that improve hepatocyte regeneration. [ABSTRACT FROM AUTHOR]

Background: The sequential organ failure assessment (SOFA) score has poor discriminative ability for death in severely or critically ill patients with Coronavirus disease 2019 (COVID-19) requiring intensive care unit (ICU) admission. Our aim was to create a new score powered to predict 28-day mortality. Methods: Retrospective, observational, bicentric cohort study including 425 patients with COVID-19 pneumonia, acute respiratory failure and SOFA score ≥ 2 requiring ICU admission for ≥72 h. Factors with independent predictive value for 28-day mortality were identified after stepwise Cox proportional hazards (PH) regression. Based on the regression coefficients, an equation was computed representing the COVID-SOFA score. Discriminative ability was tested using receiver operating characteristic (ROC) analysis, concordance statistics and precision-recall curves. This score was internally validated. Results: Median (Q1–Q3) age for the whole sample was 64 [55–72], with 290 (68.2%) of patients being male. The 28-day mortality was 54.58%. After stepwise Cox PH regression, age, neutrophil-to-lymphocyte ratio (NLR) and SOFA score remained in the final model. The following equation was computed: COVID-SOFA score = 10 × [0.037 × Age + 0.347 × ln(NLR) + 0.16 × SOFA]. Harrell's C-index for the COVID-SOFA score was higher than the SOFA score alone for 28-day mortality (0.697 [95% CI; 0.662–0.731] versus 0.639 [95% CI: 0.605–0.672]). Subsequently, the prediction error rate was improved up to 16.06%. Area under the ROC (AUROC) was significantly higher for the COVID-SOFA score compared with the SOFA score for 28-day mortality: 0.796 [95% CI: 0.755–0.833] versus 0.699 [95% CI: 0.653–0.742, p < 0.001]. Better predictive value was observed with repeated measurement at 48 h after ICU admission. Conclusions: The COVID-SOFA score is better than the SOFA score alone for 28-day mortality prediction. Improvement in predictive value seen with measurements at 48 h after ICU admission suggests that the COVID-SOFA score can be used in a repetitive manner. External validation is required to support these results. [ABSTRACT FROM AUTHOR]