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Objective: To construct a nomogram model based on clinical risk factors and CT radiohistological features to predict the prognosis of hypertensive intracerebral hemorrhage (HICH). Methods: A total of 148 patients with HICH from April 2022 to July 2024 were retrospectively selected as the research subjects. According to the modified Rankin scale at the time of discharge, they were divided into good group (Rankin scale score 0–2) and bad group (Rankin scale score 3–6). To compare the clinical data and the changes of CT radiographic characteristics in patients with different prognosis. Relevant factors affecting the prognosis were analyzed, and nomogram model was established based on the influencing factors. The fitting degree, prediction efficiency and clinical net benefit of the nomogram model were evaluated by calibration curve, ROC curve and clinical decision curve (DCA). Results: Compared with the good group, the hematoma volume in the poor group was significantly increased, the serum thromboxane 2(TXB2) and lysophosphatidic acid receptor 1(LPAR1) levels were significantly increased, and the energy balance related protein (Adropin) level was significantly decreased. The proportions of irregular shape, promiscuous sign, midline displacement, island sign and uneven density were all significantly increased (p < 0.05). In Logistic multivariate analysis, hematoma volume, Adropin, TXB2, LPAR1 and CT radiological features were all independent factors influencing the poor prognosis of HICH (p < 0.05). A nomogram prediction model was established based on the influencing factors. The calibration curve showed that the C-index was 0.820 (95% CI: 0.799–0.861), the goodness of fit test χ2 = 5.479, and p = 0.391 > 0.05, indicating a high degree of fitting. The ROC curve showed that the AUC was 0.896 (95% CI: 0.817–0.923), indicating that this model had high prediction ability. The DCA curve shows that the net benefit of the nomogram model is higher when the threshold probability is 0.1–0.9. Conclusion: The nomogram prediction model established based on hematoma volume, Adropin, TXB2, LPAR1 and other clinical risk factors as well as CT radiographic characteristics has high accuracy and prediction value in the diagnosis of poor prognosis in patients with HICH. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study is to develop and validate a model for predicting axial spondyloarthritis (axSpA) based on sacroiliac joint (SIJ)‐MRI imaging findings and clinical risk factors. Methods: The study is implemented on the data of 942 patients which contains of 707 patients with axSpA and 235 patients with non‐axSpA. To begin with, the patients were split into training (n = 753) and validation (n = 189) cohorts. Secondly, multiple assessors manually extract the features of active inflammation (bone marrow edema) and structural lesions (erosions, sclerosis, ankylosis, joint space changes, and fat lesions). Meanwhile, we utilize 11 machine learning models and TabNet to develop imaging models, which contain six clinical risk factors for clinical models and combined clinical‐imaging models. Finally, the diagnostic performance of the aforementioned models was evaluated in the validation cohort including accuracy, area under the receiver operating characteristic curve (AUC), sensitivity, specificity, F1‐score, and Matthew's correlation coefficient (MCC). Results: Six features were extracted from the imaging findings. The combined clinical‐imaging models outperform the clinical and imaging models. In contrast, the combined clinical‐imaging model via TabNet (CCMRT) achieved the optimal AUC of 0.93(95% CI: 0.89, 0.97). Furthermore, it is observed that the bilateral joint space changes and right‐sided erosions, HLA‐B27 positivity, and CRP values significantly affected axSpA diagnostic prediction. Conclusion: The prediction model based on clinical risk factors and SIJ‐MRI imaging features can distinguish axSpA and non‐axSpA effectively. In addition, the TabNet demonstrates superior diagnostic efficacy compared with machine learning models. [ABSTRACT FROM AUTHOR]

Background: Granulomatous mastitis (GM) is a chronic inflammatory disorder affecting breast tissue, with a high recurrence Objectives: Regarding this impotence, this paper aims at proposing a retrospective approach to compile an extensive dataset of clinical information as well as to identify potential risk factors associated with GM recurrence. Methods: For this purpose, data on pathologically-confirmed cases of GM were retrospectively collected from the medical archives of the Shahid Beheshti Cancer Research Center, Iran, from March 2020 to February 2023. Then, the descriptive statistics were utilized to analyze demographic information, disease-related variables, patient-related variables, and details regarding treatment modalities. Evaluation of disease recurrence occurred 24 months following the initial GM diagnosis through clinical assessments, ultrasound, or mammography. Among the 100 accessible patients, 33 experienced recurrences within 24 months. Results: According to the obtained results, factors significantly associated with recurrence included body mass index (2831 vs. 26.05), history of breastfeeding and its duration (22.44 months vs. 16.95 months) (90.9% vs. 72.7%), abortion, pain (72.7% vs. 463%), erythema nodosum (51.5% vs. 16.4%), hypertension (18.2% vs. 3%), thyroid disease (333% vs. 14.9%), rheumatologic disease (69.7% vs. 13.4%), dermal involvement (51.5% vs. 10.9%), joint involvement (85.9% vs. 39.4%), and the combined treatment modalities (45.5% vs. 11.9%). Moreover, the predictive model exhibited an overall accuracy of 833%. Conclusions: Finally, it can be concluded that abortion history, breastfeeding and its duration, combined treatment, pain, erythema nodosum, hypertension, thyroid or rheumatologic disease, dermatologie or joint signs, and Body Mass Index (BMI) could be the significant factors related to the recurrence of GM. Thus, special attention to these factors and management of baseline disease may have a predictive effect on the relapse of idiopathic granulomatous mastitis (IGM). [ABSTRACT FROM AUTHOR]

Abstract Bladder lesion commonly occurs in patients with benign prostatic hyperplasia (BPH), and the routine screening of bladder lesion is vital for its timely detection and treatment, in which the risk of bladder lesion progression can be effectively alleviated. However, current clinical methods are inconvenient for routine screening. In this study, we proposed a convenient routine screening method to diagnose bladder lesions based on several clinical risk factors, which can be obtained through non-invasive, easy-to-operate, and low-cost examinations. The contribution of each clinical risk factor was further quantitatively analyzed to understand their impact on diagnostic decision-making. Based on a cohort study of 253 BPH patients with or without bladder lesions, the proposed diagnostic model achieved high accuracy using these clinical risk factors. Bladder compliance, maximum flow rate (Qmax), prostate specific antigen (PSA), and postvoid residual (PVR) were identified as the four most important clinical risk factors. To the best of our knowledge, this is the innovative research to predict bladder lesions based on the risk factors and quantitatively reveal their contributions to diagnostic decision-making. The proposed model has the potential to serve as an effective routine screening tool for bladder lesions in BPH patients, enabling early intervention to prevent lesion progression and improve the quality of life.

Bladder lesion commonly occurs in patients with benign prostatic hyperplasia (BPH), and the routine screening of bladder lesion is vital for its timely detection and treatment, in which the risk of bladder lesion progression can be effectively alleviated. However, current clinical methods are inconvenient for routine screening. In this study, we proposed a convenient routine screening method to diagnose bladder lesions based on several clinical risk factors, which can be obtained through non-invasive, easy-to-operate, and low-cost examinations. The contribution of each clinical risk factor was further quantitatively analyzed to understand their impact on diagnostic decision-making. Based on a cohort study of 253 BPH patients with or without bladder lesions, the proposed diagnostic model achieved high accuracy using these clinical risk factors. Bladder compliance, maximum flow rate (Qmax), prostate specific antigen (PSA), and postvoid residual (PVR) were identified as the four most important clinical risk factors. To the best of our knowledge, this is the innovative research to predict bladder lesions based on the risk factors and quantitatively reveal their contributions to diagnostic decision-making. The proposed model has the potential to serve as an effective routine screening tool for bladder lesions in BPH patients, enabling early intervention to prevent lesion progression and improve the quality of life. [ABSTRACT FROM AUTHOR]

Patients with congenital heart disease (CHD) demonstrate altered structural brain network connectivity. However, there is large variability between reported results and little information is available to identify those patients at highest risk for brain alterations. Thus, we aimed to investigate if network connectivity measures were associated with the individual patient's cumulative load of clinical risk factors and with family‐environmental factors in a cohort of adolescents with CHD. Further, we investigated associations with executive function impairments. In 53 adolescents with CHD who underwent open‐heart surgery during infancy, and 75 healthy controls, diffusion magnetic resonance imaging and neuropsychological assessment was conducted at a mean age of 13.2 ± 1.3 years. Structural connectomes were constructed using constrained spherical deconvolution tractography. Graph theory and network‐based statistics were applied to investigate network connectivity measures. A cumulative clinical risk (CCR) score was built by summing up binary risk factors (neonatal, cardiac, neurologic) based on clinically relevant thresholds. The role of family‐environmental factors (parental education, parental mental health, and family function) was investigated. An age‐adjusted executive function summary score was built from nine neuropsychological tests. While network integration and segregation were preserved in adolescents with CHD, they showed lower edge strength in a dense subnetwork. A higher CCR score was associated with lower network segregation, edge strength, and executive function performance. Edge strength was particularly reduced in a subnetwork including inter‐frontal and fronto‐parietal‐thalamic connections. There was no association with family‐environmental factors. Poorer executive functioning was associated with lower network integration and segregation. We demonstrated evidence for alterations of network connectivity strength in adolescents with CHD — particularly in those patients who face a cumulative exposure to multiple clinical risk factors over time. Quantifying the cumulative load of risk early in life may help to better predict trajectories of brain development in order to identify and support the most vulnerable patients as early as possible. [ABSTRACT FROM AUTHOR]

Background: Chinese patentmedicines are specialty preparations in China that are produced using traditional prescriptions processed by modern pharmaceutical technology. They contain complex ingredients and much attention is paid to their clinical safety. Demonstrating the clinical safety of Chinese patent medicines containing toxic ingredients in modern pharmacological studies has become one of the urgent issues to be solved for the safe use of clinical medicines. Objectives: The aim of this research is to evaluate the safety of Chinese patent medicines containing toxic ingredients by applying the risk-benefit assessment method. Additionally, a database of 'toxic ingredients-toxic Chinese herbal medicines-adverse reactions' will be established to explore the relationship between toxic ingredients and adverse reactions. This will lay the foundation for the rational clinical use of Chinese patent medicines containing toxic ingredients. Methods: 1) Establish a database of 'toxic Chinese herbal medicines-toxic ingredients-toxic Chinese patent medicines' to count the Chinese patent medicines containing toxic ingredients in the 2020 edition of Chinese Pharmacopoeia. 2) Filtered the clinical studies, extracted the drug-related ADEs, and analyzed the characteristics and correlations of these ADEs. 3) Finally, this section summarizes the causes of ADEs related to Chinese patent medicines containing toxic ingredients and extracts the main risk factors to provide a reference for further study. Outcomes: 1) There are four main types of Chinese patent medicines containing toxic ingredients. These include medicines with diester aconitine metabolites, mineral composition, Araceae metabolites, and hydrogen cyanide. 2) Digestive system, skin and its appendages, and allergic reactions were the main types of ADEs related to four types of Chinese patent medicines containing toxic ingredients. 3) There are four primary risk factors associated with the clinical use of Chinese patent medicines containing toxic ingredients: medicine, medication, individual and regulatory factors. [ABSTRACT FROM AUTHOR]

ObjectiveTo construct a nomogram model based on clinical risk factors and CT radiohistological features to predict the prognosis of hypertensive intracerebral hemorrhage (HICH).MethodsA total of 148 patients with HICH from April 2022 to July 2024 were retrospectively selected as the research subjects. According to the modified Rankin scale at the time of discharge, they were divided into good group (Rankin scale score 0–2) and bad group (Rankin scale score 3–6). To compare the clinical data and the changes of CT radiographic characteristics in patients with different prognosis. Relevant factors affecting the prognosis were analyzed, and nomogram model was established based on the influencing factors. The fitting degree, prediction efficiency and clinical net benefit of the nomogram model were evaluated by calibration curve, ROC curve and clinical decision curve (DCA).ResultsCompared with the good group, the hematoma volume in the poor group was significantly increased, the serum thromboxane 2(TXB2) and lysophosphatidic acid receptor 1(LPAR1) levels were significantly increased, and the energy balance related protein (Adropin) level was significantly decreased. The proportions of irregular shape, promiscuous sign, midline displacement, island sign and uneven density were all significantly increased (p 0.05, indicating a high degree of fitting. The ROC curve showed that the AUC was 0.896 (95% CI: 0.817–0.923), indicating that this model had high prediction ability. The DCA curve shows that the net benefit of the nomogram model is higher when the threshold probability is 0.1–0.9.ConclusionThe nomogram prediction model established based on hematoma volume, Adropin, TXB2, LPAR1 and other clinical risk factors as well as CT radiographic characteristics has high accuracy and prediction value in the diagnosis of poor prognosis in patients with HICH.

Diabetic nephropathy, as a severe microvascular complication of diabetes, manifests in four clinical types: classic, albuminuria regression, a rapid decline in kidney function (RDKF), and non-proteinuric or non-albuminuric DKD. Rapidly progressive diabetic nephropathy advances to end-stage renal disease more swiftly than the typical form, posing significant risks. However, a comprehensive understanding of rapidly progressive diabetic nephropathy is currently lacking. This article reviewed latest developments in genetic and clinical risk factors associated with rapidly progressive diabetic nephropathy, aiming to broad perspectives concerning the diagnosis and interventions of this condition.

This retrospective study aimed to assess coronary artery calcium (CAC) progression in serial computed tomography measurements according to risk factor changes. In 448 asymptomatic adults who underwent CAC measurements with more than one-year intervals, CAC progression was assessed according to age, sex, variable traditional risk factors (diabetes mellitus, hypertension, hyperlipidemia, and smoking), and initial CAC score (0, 0.1–100, and >100). Univariate and multivariate logistic regression analyses were assessed for independent predictors of rapid CAC progression (ΔCAC/year > 20). During the 3.5-year follow-up, coronary artery calcifications occurred in 43 (12.8%) of 336 individuals with an initial CAC score of zero. Of 112 individuals with initial CAC presence, 60 (53.6%) had ΔCAC/year > 20. Age, male sex, body mass index, and all risk factors were significantly associated with ΔCAC/year > 20, but recently diagnosed hypertension (odds ratio [OR], 11.3) and initial CAC score (OR, 1.05) were significant independent predictors in multivariate regression analyses. CAC progression was affected by demographic and traditional risk factors; but, adjusting for these factors, recently diagnosed hypertension and initial CAC score were the most influential factors for rapid CAC progression. These findings suggest that individuals with higher initial CAC scores may benefit from more frequent follow-up scans and checks regarding risk factor changes. [ABSTRACT FROM AUTHOR]

Introduction: Distinguishing between malignant pleural effusion (MPE) and benign pleural effusion (BPE) poses a challenge in clinical practice. We aimed to construct and validate a combined model integrating radiomic features and clinical factors using computerized tomography (CT) images to differentiate between MPE and BPE. Methods: A retrospective inclusion of 315 patients with pleural effusion (PE) was conducted in this study (training cohort: n = 220; test cohort: n = 95). Radiomic features were extracted from CT images, and the dimensionality reduction and selection processes were carried out to obtain the optimal radiomic features. Logistic regression (LR), support vector machine (SVM), and random forest were employed to construct radiomic models. LR analyses were utilized to identify independent clinical risk factors to develop a clinical model. The combined model was created by integrating the optimal radiomic features with the independent clinical predictive factors. The discriminative ability of each model was assessed by receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Results: Out of the total 1,834 radiomic features extracted, 15 optimal radiomic features explicitly related to MPE were picked to develop the radiomic model. Among the radiomic models, the SVM model demonstrated the highest predictive performance [area under the curve (AUC), training cohort: 0.876, test cohort: 0.774]. Six clinically independent predictive factors, including age, effusion laterality, procalcitonin, carcinoembryonic antigen, carbohydrate antigen 125 (CA125), and neuron-specific enolase (NSE), were selected for constructing the clinical model. The combined model (AUC: 0.932, 0.870) exhibited superior discriminative performance in the training and test cohorts compared to the clinical model (AUC: 0.850, 0.820) and the radiomic model (AUC: 0.876, 0.774). The calibration curves and DCA further confirmed the practicality of the combined model. Conclusion: This study presented the development and validation of a combined model for distinguishing MPE and BPE. The combined model was a powerful tool for assisting in the clinical diagnosis of PE patients. [ABSTRACT FROM AUTHOR]

Purpose: To explore whether varying degrees of vitreous haemorrhage (VH) and calcification act as risk factors for enucleation in patients with advanced retinoblastoma (RB). Methods: Advanced RB was defined by the international classification of RB (Philadelphia version). Basic information for retinoblastoma patients diagnosed as groups D and E in our hospital between January 2017 and June 2022 was reviewed by logistics regression models. Additionally, a correlation analysis was performed, excluding variables with a VIF (variance inflation factor) >10 from the multivariate analysis. Results: A total of 223 eyes diagnosed with RB were included in assessing VH and calcification; of these, 101 (45.3%) eyes experienced VH, and 182 (76.2%) eyes were found to have calcification within the tumour through computed tomography (CT) or B‐scan ultrasonography. Ninety‐two eyes (41.3%) were enucleated, of which 67 (72.8%) had VH and 68 (73.9%) calcification, both of which were significantly relevant to enucleation (p < 0.001*). Other clinical risk factors, such as corneal edema, anterior chamber haemorrhage, high intraocular pressure during treatment and iris neovascularization, correlated significantly with enucleation (p < 0.001*). Multivariate analysis included IIRC (intraocular international retinoblastoma classification), VH, calcification and high intraocular pressure during treatment as independent risk factors for enucleation. Conclusions: Despite identifying different potential risk factors for RB, there remains significant controversy concerning which patients require enucleation, and the degree of VH varies. Such eyes need to be evaluated carefully, and management with appropriate adjuvant therapy may improve the outcome of these patients. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the diagnostic precision of the 50-gram glucose challenge test (50-g GCT) at various levels for the detection of gestational diabetes mellitus (GDM), and to examine its association with clinical risk indicators. Material and Methods: At Thammasat University Hospital, our retrospective cohort comprised 1,197 pregnant women screened using the 50-g GCT based on risk factors, including a family history of GDM, obesity, and other factors. Out of these, 219 tested positive, with 83 (37.9%) diagnosed with GDM and 136 (62.1%) without GDM. Comprehensive data including baseline characteristics, as well as maternal and neonatal outcomes, were compiled. We assessed the correlations between clinical risk factors and 50-g GCT values to ascertain GDM. The positive predictive value (PPV) and negative predictive value (NPV) for various cut-off levels were determined. Results: The best cutoff for the 50-g GCT for GDM diagnosis was ≥220 mg/dL with 100% PPV without adding clinical risk. The PPVs reached 75% and 100%, respectively, when combined with maternal age ≥35 years at 50-g GCT thresholds of ≥210 mg/dL and ≥220 mg/dL. A history of diabetes in the family combined with a 50-g GCT provided 100% PPV at 200 mg/dL. Conclusion: A 50-g GCT cut-off value of ≥220mg/dL is proposed for a definitive GDM diagnosis in certain circumstances, negating the need for this additional test. When a pregnant woman has a family history of diabetes, the 50-g GCT cut-off of 200 mg/dL could be a promising marker for identifying GDM.

RATIONALE & OBJECTIVE: Few studies have investigated racial disparities in acute kidney injury (AKI), in contrast to the extensive literature on racial differences in the risk of kidney failure. We sought to study potential differences in risk in the setting of chronic kidney disease (CKD). STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: We studied 2,720 self-identified Black or White participants with CKD enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study from July 1, 2013, to December 31, 2017. EXPOSURE: Self-reported race (Black vs White). OUTCOME: Hospitalized AKI (≥50% increase from nadir to peak serum creatinine). ANALYTICAL APPROACH: Cox regression models adjusting for demographics (age and sex), prehospitalization clinical risk factors (diabetes, blood pressure, cardiovascular disease, estimated glomerular filtration rate, proteinuria, receipt of angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers), and socioeconomic status (insurance status and education level). In a subset of participants with genotype data, we adjusted for apolipoprotein L1 gene (APOL1) high-risk status and sickle cell trait. RESULTS: Black participants (n = 1,266) were younger but had a higher burden of prehospitalization clinical risk factors. The incidence rate of first AKI hospitalization among Black participants was 6.3 (95% CI, 5.5-7.2) per 100 person-years versus 5.3 (95% CI, 4.6-6.1) per 100 person-years among White participants. In an unadjusted Cox regression model, Black participants were at a modestly increased risk of incident AKI (HR, 1.22 [95% CI, 1.01-1.48]) compared with White participants. However, this risk was attenuated and no longer significant after adjusting for prehospitalization clinical risk factors (adjusted HR, 1.02 [95% CI, 0.83-1.25]). There were only 11 AKI hospitalizations among individuals with high-risk APOL1 risk status and 14 AKI hospitalizations among individuals with sickle cell trait. LIMITATIONS: Participants were limited to research volunteers and potentially not fully representative of all CKD patients. CONCLUSIONS: In this multicenter prospective cohort of CKD patients, racial disparities in AKI incidence were modest and were explained by differences in prehospitalization clinical risk factors.

Abstract Objective To build and validate an early risk prediction model for gestational diabetes mellitus (GDM) based on first-trimester electronic medical records including maternal demographic and clinical risk factors. Methods To develop and validate a GDM prediction model, two datasets were used in this retrospective study. One included data of 14,015 pregnant women from Máxima Medical Center (MMC) in the Netherlands. The other was from an open-source database nuMoM2b including data of 10,038 nulliparous pregnant women, collected in the USA. Widely used maternal demographic and clinical risk factors were considered for modeling. A GDM prediction model based on elastic net logistic regression was trained from a subset of the MMC data. Internal validation was performed on the remaining MMC data to evaluate the model performance. For external validation, the prediction model was tested on an external test set from the nuMoM2b dataset. Results An area under the receiver-operating-characteristic curve (AUC) of 0.81 was achieved for early prediction of GDM on the MMC test data, comparable to the performance reported in previous studies. While the performance markedly decreased to an AUC of 0.69 when testing the MMC-based model on the external nuMoM2b test data, close to the performance trained and tested on the nuMoM2b dataset only (AUC = 0.70).

Zhiliang Zhang,1,&ast; Zhongxiang Ding,2,&ast; Fenyang Chen,2 Rui Hua,3 Jiaojiao Wu,3 Zhefan Shen,2 Feng Shi,3 Xiufang Xu1 1School of Medical Imaging, Hangzhou Medical College, Hangzhou, People’s Republic of China; 2Department of Radiology, Affiliated Hangzhou First People’s Hospital, Westlake University School of Medicine, Hangzhou, People’s Republic of China; 3Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Feng Shi; Xiufang Xu, Email feng.shi@uii-ai.com; 1996033011@hmc.edu.cnBackground: Cerebral small vessel disease lacks specific clinical manifestations, and extraction of valuable features from multimodal images is expected to improve its diagnostic accuracy. In this study, we used deep learning techniques to segment cerebral small vessel disease imaging markers in multimodal magnetic resonance images and analyze them with clinical risk factors.Methods and results: We recruited 211 lacunar stroke patients and 83 control patients. The patients’ cerebral small vessel disease markers were automatically segmented using a V-shaped bottleneck network, and the number and volume were calculated after manual correction. The segmentation results of the V-shaped bottleneck network for white matter hyperintensity and recent small subcortical infarction were in high agreement with the ground truth (DSC> 0.90). In small lesion segmentation, cerebral microbleed (average recall=0.778; average precision=0.758) and perivascular spaces (average recall=0.953; average precision=0.923) were superior to lacunar infarct (average recall=0.339; average precision=0.432) in recall and precision. Binary logistic regression analysis showed that age, systolic blood pressure, and total cerebral small vessel disease load score were independent risk factors for lacunar stroke (P< 0.05). Ordered logistic regression analysis showed age was positively correlated with cerebral small vessel disease load score and total cholesterol was negatively correlated with cerebral small vessel disease score (P< 0.05).Conclusion: Lacunar stroke patients exhibited higher cerebral small vessel disease imaging markers, and age, systolic blood pressure, and total cerebral small vessel disease score were independent risk factors for lacunar stroke patients. V-shaped bottleneck network segmentation network based on multimodal deep learning can segment and quantify various cerebral small vessel disease lesions to some extent.Keywords: lacunar stroke, cerebral small vessel disease, imaging markers, deep learning, quantification, image segmentation, clinical risk factors

Objective: To build and validate an early risk prediction model for gestational diabetes mellitus (GDM) based on first-trimester electronic medical records including maternal demographic and clinical risk factors. Methods: To develop and validate a GDM prediction model, two datasets were used in this retrospective study. One included data of 14,015 pregnant women from Máxima Medical Center (MMC) in the Netherlands. The other was from an open-source database nuMoM2b including data of 10,038 nulliparous pregnant women, collected in the USA. Widely used maternal demographic and clinical risk factors were considered for modeling. A GDM prediction model based on elastic net logistic regression was trained from a subset of the MMC data. Internal validation was performed on the remaining MMC data to evaluate the model performance. For external validation, the prediction model was tested on an external test set from the nuMoM2b dataset. Results: An area under the receiver-operating-characteristic curve (AUC) of 0.81 was achieved for early prediction of GDM on the MMC test data, comparable to the performance reported in previous studies. While the performance markedly decreased to an AUC of 0.69 when testing the MMC-based model on the external nuMoM2b test data, close to the performance trained and tested on the nuMoM2b dataset only (AUC = 0.70). [ABSTRACT FROM AUTHOR]

Objectives: The addition of CDK4/6 inhibitors to standard hormonotherapy improved progression-free survival(PFS) of hormone-positive, HER-2 negative metastatic breast cancer(mBC). We analyzed clinicopathological risk factors predicting early recurrence in mBC patients treated with a combination of CDK4/6 inhibitor and hormonotherapy. Methods: 229 patients were included, and 95 recurrences were seen. Median ER and PR expressions, ki67 levels, metastatic sites, number of metastasis, and grade were related to recurrence. Patients were classified according to the presence of prognostic factors: group 1 included patients with 0-1 risk factors, group 2 with 2-3 risk factors, and group 3 with ≥4risk factors. Results: Median ER, PR, and ki67 levels were 90, 60, and 25,respectively. Median ER, PR, Kİ67, grade, metastatic site, and the number of metastasis were related to PFS. Advanced CDK4/6 line and response were significant for PFS.Median PFS was 6.5 months for recurrent patients. According to the predictive model, patients who recurred before 6.5 months had a high-risk group (group 2,3). PS, family history, CDK4/6 inhibitor types were found to be related to PFS among the recurrent group. Conclusion: There is a need for a prospective design study to determine the clinicopathological markers identifying early recurrence under CDK4/6 inhibitors so new combination therapies or alternatives can be developed. [ABSTRACT FROM AUTHOR]

Sarcopenic obesity refers to the coexistence of sarcopenia and obesity. This study assessed the prevalence of and risk factors for sarcopenic obesity in community-dwelling older males in Korea. This cross-sectional study analyzed data from 1060 community-dwelling participants. The participants were screened for sarcopenia and obesity. This study examined various risk factors, composed of somatometric, biochemical, and behavioral traits, including age; height; weight; body mass index; waist circumference; skeletal muscle mass index; fasting glucose, triglycerides, and cholesterol levels; systolic and diastolic blood pressure; and smoking and drinking traits. The prevalence of sarcopenic obesity in men had a weighted value of 9.09% (95% CI: 7.20–11.41). The clinical risk factors included short height, as well as high weight, body mass index, waist circumference, skeletal muscle mass index, triglyceride levels, systolic blood pressure, and diastolic blood pressure. Specific prevalence and clinical risk factors for sarcopenic obesity were found among community-dwelling older men. These findings may be beneficial for primary care clinicians and healthcare professionals for identifying individuals with sarcopenic obesity and referring them for early detection and treatment. [ABSTRACT FROM AUTHOR]

(1) Background: The prediction of cervical lesion evolution is a challenge for clinicians. This prospective study aimed to determine and compare the predictive accuracy of cytology, HPV genotyping, and p16/Ki67 dual staining alone or in combination with personal risk factors in the prediction of progression, regression, or persistence of cervical lesions in human papillomavirus (HPV)-infected patients; (2) Methods: This prospective study included HPV-positive patients with or without cervical lesions who underwent follow-up in a private clinic. We calculated the predictive performance of individual tests (cervical cytology, HPV genotyping, CINtecPlus results, and clinical risk factors) or their combination in the prediction of cervical lesion progression, regression, and persistence; (3) Results: The highest predictive performance for the progression of cervical lesions was achieved by a model comprising a Pap smear suggestive of high-grade squamous intraepithelial lesion (HSIL), the presence of 16/18 HPV strains, a positive p16/Ki67 dual staining result along with the presence of at least three clinical risk factors, which had a sensitivity (Se) of 74.42%, a specificity of 97.92%, an area under the receiver operating curve (AUC) of 0.961, and an accuracy of 90.65%. The prediction of cervical lesion regression or persistence was modest when using individual or combined tests; (4) Conclusions: Multiple testing or new biomarkers should be used to improve HPV-positive patient surveillance, especially for cervical lesion regression or persistence prediction. [ABSTRACT FROM AUTHOR]

Lianpeng Wu,1– 3 Dandan Xia,1– 3 Ke Xu1– 3 1Department of Clinical Laboratory Medicine, The Ding Li Clinical College of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of China; 2Department of Clinical Laboratory Medicine, Wenzhou Central Hospital, Wenzhou, 325000, People’s Republic of China; 3Key Laboratory of Diagnosis and Treatment of New and Recurrent Infectious Diseases of Wenzhou, Wenzhou, 325000, People’s Republic of ChinaCorrespondence: Ke Xu, Department of Clinical Laboratory Medicine, Wenzhou Central Hospital, Wenzhou, 325000, People’s Republic of China, Tel +86 135 6629 0303, Email wzxuke72@163.comPurpose: Although highly active antiretroviral therapy (HA-ART) can effectively suppress the disease process in patients with acquired immunodeficiency syndrome (AIDS), opportunistic infections, mainly bloodstream infections (BSI), are still the main cause of death in people living with HIV. There is no effective diagnostic strategy for HIV-infected people with BSI. This study aimed to develop an AI diagnostic model with high sensitivity to improve the early detection of HIV-infected people with BSI.Patients and Methods: This study retrospectively analyzed the 40 clinical factors of 498 HIV-infected people (171 with BSI positive and 327 with BSI negative) who admitted to Wenzhou Central Hospital from September 2014 to July 2021. This study used the hospital information management system to collect the clinical characteristics, laboratory and imaging examination results, and clinical diagnosis of the two groups. The diagnostic results of all patients were in line with the diagnostic criteria of the Chinese Guidelines for the Diagnosis and Treatment of AIDS (2021 Edition), and the BSI diagnosis was in line with the diagnostic criteria of sepsis and bacteremia in Practical Internal Medicine (13th Edition). On this basis, various risk prediction models were established by combining 8 artificial intelligence (AI) algorithms in the training set and validating the diagnosis performance in the testing set. The model with the best diagnostic performance was selected as the final diagnostic model.Results: The clinical characteristics of HIV-infected people with BSI are atypical, and the pathogens in this area are mainly fungi. Ten risk factors were selected: low level of hemoglobin, CD4+T cell and platelets, high level of lactate dehydrogenase and blood urea nitrogen, splenomegaly, without ART treatment, strip shadow, nodular shadow, and shock. The combination of the ten risk factors, age, gender and the “svmRadial” model can identify the HIV-infected people with BSI from the HIV-infected people without BSI with an area under the curve of 0.916 and a sensitivity and specificity of 0.824 and 0.855, respectively.Conclusion: The model showed excellent performance in diagnosing HIV-infected people with BSI. Internal and external validation showed that the diagnosis model had high clinical application value.Keywords: acquired immunodeficiency syndrome, bloodstream infections, clinical risk factors, diagnosis, artificial intelligence model

BackgroundNeonatal hyperbilirubinemia (NHB) is one of the most common diseases in the neonatal period. Without timely diagnosis and treatment, it can lead to long-term complications. In severe cases, it may even result in fatality. The UGT1A1 gene and clinical risk factors play important roles in the development and progression of NHB.MethodsIn this study, we conducted a cohort study and analyzed 3258 newborns from the Jilin Women And Children Health Hospital in northern China, including 372 children with hyperbilirubinemia. We established a predictive model using a logistic regression model based on clinical risk factors and the polymorphism of the G211A locus in the UGT1A1 gene of newborns. Furthermore, the performance of the prediction model was evaluated using the ROC curve.ResultsThe logistic regression model indicates that the following factors are associated with an increased risk of NHB: the time when stool turns yellow [P ≤ 0.001, OR 1.266 (95% CI: 1.125-1.425)]; neonatal cephalohematoma [P ≤ 0.001, OR 33.642 (95% CI: 21.823-51.861)]; hemolytic disease of newborn [P ≤ 0.001, OR 33.849 (95% CI: 18.589-61.636)]; neonatal weight loss [P ≤ 0.001, OR 11.275 (95% CI: 7.842-16.209)]; neonatal premature rupture of membranes (PROM) history [P = 0.021, OR 1.422 (95% CI: 1.056-1.917)]; genetic polymorphism at the UGT1A1 gene G211A locus. Gestational age is a protective factor [P ≤ 0.001, OR 0.766 (95% CI: 0.686-0.855)]. Compared to natural labor, cesarean section is a protective factor [P = 0.011, OR 0.711 (95% CI: 0.546-0.926)], while assisted delivery is a risk factor [P = 0.022, OR 2.207 (95% CI: 1.121-4.346)]. The area under the curve (AUC) of this prediction model is 0.804 (95% CI: 0.777-0.831), indicating good discrimination ability and value for predicting the risk of NHB after birth.ConclusionWe have developed and evaluated a predictive model that combines UGT1A1 gene polymorphism and clinical risk factors for the first time. By using this nomogram and taking into account the results of serum total bilirubin measurement or transcutaneous bilirubin measurement, early prediction of the risk of neonatal hyperbilirubinemia can be achieved.

This paper gives a performance analysis of multiple vote classifiers based on metaclassification methods for estimating the risk of diabetes. The study's dataset includes a number of biological and clinical risk variables that can result in the development of diabetes. In the analysis, classifiers like Random Forest, Logistic Regression, Gradient Boosting, Support Vector Machines, and Artificial Neural Networks were used. In the study, each classifier was trained and evaluated separately, and the outcomes were compared to those attained using meta-classification methods. Some of the meta-classifiers used in the analysis included Majority Voting, Weighted Majority Voting, and Stacking. The effectiveness of each classifier was evaluated using a number of measures, including accuracy, precision, recall, F1-score, and Area under the Curve (AUC). The results show that meta-classification techniques often outperform solo classifiers in terms of prediction precision. Random Forest and Gradient Boosting, two different classifiers, had the highest accuracy, while Logistic Regression performed the worst. The best performing meta-classifier was stacking, which achieved an accuracy of 84.25%. Weighted Majority Voting came in second (83.86%) and Majority Voting came in third (82.95%). [ABSTRACT FROM AUTHOR]

This document presents findings from a study on cardiovascular autonomic neuropathy (CAN) in patients with diabetes. The study aimed to identify risk factors for mortality in individuals with CAN. The results showed that older age at CAN diagnosis, decreased body mass index (BMI), and neurogenic orthostatic hypotension (NOH) were significant risk factors for mortality. Additionally, a genetic variant near the NR5A2 gene was associated with increased risk of CAN in non-Hispanic Caucasians. The study suggests that these findings could inform the development of guidelines for prevention and further research on CAN mortality risk factors. [Extracted from the article]

Ischemic stroke, resulting from insufficient blood supply to the brain, is among the leading causes of death and disability worldwide. A potentially severe complication of the disease itself or its treatment aiming to restore optimal blood flow is hemorrhagic transformation (HT) increasing morbidity and mortality. Detailed summaries can be found in the literature on the pathophysiological background of hemorrhagic transformation, the potential clinical risk factors increasing its chance, and the different biomarkers expected to help in its prediction and clinical outcome. Clinicopathological studies also contribute to the improvement in our knowledge of hemorrhagic transformation. We summarized the clinical risk factors of the hemorrhagic transformation of ischemic strokes in terms of risk reduction and collected the most promising biomarkers in the field. Also, auxiliary treatment options in reperfusion therapies have been reviewed and collected. We highlighted that the optimal timing of revascularization treatment for carefully selected patients and the individualized management of underlying diseases and comorbidities are pivotal. Another important conclusion is that a more intense clinical follow-up including serial cranial CTs for selected patients can be recommended, as clinicopathological investigations have shown HT to be much more common than clinically suspected. [ABSTRACT FROM AUTHOR]

Ischemic stroke (IS) is a multifaceted, complicated illness resulting from a confluence of genetic, environmental and vascular risk factors. Many genes that may contribute to ischemic stroke have been discovered in humans. The genetic contribution appears to be greater in IS patients with hypertension. There is conflicting evidence about a positive correlation between the AGT M235T polymorphism and ischemic stroke. The aim of this study was to examine the possible association of the AGT M235T gene polymorphism with the risk of ischemic stroke. A hospital-based case-control study was carried out in 36 ischemic stroke patient cases and 36 age- and sex-matched healthy controls. Clinical parameters were measured to assess the associated risk factors. DNA was isolated from blood samples, and the AGT M235T genotypes were identified using polymerase chain reaction (PCR) and analyzed by agarose gel electrophoresis. The AGT-TT genotype (OR = 4.64, 95% CL = 1.23–17.4; p = 0.023 and T allele (OR = 2.54, 95% CL = 1.28–5.02; p = 0.003) were significantly more common in patients than in controls, indicating that it may be a major risk factor for the development of ischemic stroke. The results suggest that there may be a significant correlation between the AGT M235T gene polymorphism and the development of ischemic stroke in the studied Ethiopian population.

Abstract Background Esophageal cancer (EC) often occurs in the elderly, and approximately 40% of patients are 70 years or older. To investigate the long‐term survival of EC in elderly patients, to provide a theoretical direction for better management and predicting survival of EC based on the hospital‐based multi‐center study in China. Methods The study was conducted in 18 hospitals including 6 provincial hospitals, 8 municipal hospitals, and 4 county hospitals. We extracted information from medical record homepage, records of admission and discharge, and pathological diagnosis reports from the medical record department of the elderly patients at 70–84 years old to obtain the 3‐year and 5‐year overall survival (OS), and main associated factors, and to analyze the current therapeutic effect of different treatment options for elderly patients. Results The 3‐year and 5‐year OS rate of the 1013 elderly patients was 44.8% and 32.8%, respectively. Their median survival was 28.00 months. The median survival of patients with squamous cell carcinoma was longer than that of other pathological type (squamous vs. other types: 31.00 vs. 20.00 months, p = 0.018). The median survival of patients with surgery only or combined therapy was longer than that of radiotherapy, chemotherapy, and no therapy (surgery only vs. combined therapy vs. radiotherapy vs. chemotherapy vs. no therapy: 56.00 vs. 33.00 vs. 26.00 vs.18.00 vs. 16.00 months, p

Abstract Background Although determining the recurrence of cutaneous squamous cell carcinoma (cSCC) is important, currently suggested systems and single biomarkers have limited power for predicting recurrence. Objective In this study, combinations of clinical factors and biomarkers were adapted into a nomogram to construct a powerful risk prediction model. Methods The study included 145 cSCC patients treated with Mohs micrographic surgery. Clinical factors were reviewed, and immunohistochemistry was performed using tumor tissue samples. A nomogram was constructed by combining meaningful clinical factors and protein markers. Results Among the various factors, four clinical factors (tumor size, organ transplantation history, poor differentiation, and invasion into subcutaneous fat) and two biomarkers (Axin2 and p53) were selected and combined into a nomogram. The concordance index (C-index) of the nomogram for predicting recurrence was 0.809, which was higher than that for the American Joint Committee on Cancer (AJCC) 7th, AJCC 8th, Brigham and Women’s Hospital, and Breuninger staging systems in the patient data set. Conclusion A nomogram model that included both clinical factors and biomarkers was much more powerful than previous systems for predicting cSCC recurrence.

Background: Delirium is an important cause of morbidity and mortality in the general hospitalized population. Few information exists on risk factors in patients with neurological disease. Objective: This study was to analyze risk factors for delirium in patients presenting to a neurological emergency department. Methods: This study was observational prospective cohort study. We included all patients with neurological disease, admitted to the emergency department with a stay of more than 8 h, in the period from January to April 2022. The confusion assessment method-intensive care unit delirium detection instrument and DSM-5 criteria were applied to all patients. We obtained information on epidemiological, clinical, and paraclinical variables at the time of admission. Through a univariate and multivariate logistic regression model, we analyzed risk factors for delirium. Results: Of 3661 patients treated in the emergency department, 189 patients were included, 60.8% male gender, age 48 ± 19 years; 44 (23.2%) met criteria for delirium, 81% were diagnosed on admission; delirium scale score/index 12 (interquartile range [IQR] 10-12), and duration of delirium 5 (IQR 2-11) days. Clinical history for risk of delirium: previous delirium (odds ratio [OR] 3.9, 95% CI 2.4-6.1, p = 0.003), stroke (OR 2.2, 95% CI 1.4-3.9, p = 0.009), neurosurgery (OR 2.1, 95% CI 1.2-3.8, p = 0.024), and use of psychoactive drugs (OR 2.5, CI9 5% 1.3-4.6, p = 0.021). The following variables were independent risk factors for delirium through the multivariate logistic regression model:uncontrolled crisis [OR 5.4 (95% CI 1.2-22.9), p = 0.023], supratentorial structural brain lesion [OR 6.1 (95% CI 1.7-21.2), p = 0.004], and neuroinfection OR 9.6 (95% CI 2.9-31.4), p ≤ 0.001]. Conclusions: The frequency of delirium is 23.2% in patients presenting to the neurological emergency department; uncontrolled epilepsy, neuroinfection, and supratentorial brain lesions are independent risk factors for delirium. [ABSTRACT FROM AUTHOR]

Background: Esophageal cancer (EC) often occurs in the elderly, and approximately 40% of patients are 70 years or older. To investigate the long‐term survival of EC in elderly patients, to provide a theoretical direction for better management and predicting survival of EC based on the hospital‐based multi‐center study in China. Methods: The study was conducted in 18 hospitals including 6 provincial hospitals, 8 municipal hospitals, and 4 county hospitals. We extracted information from medical record homepage, records of admission and discharge, and pathological diagnosis reports from the medical record department of the elderly patients at 70–84 years old to obtain the 3‐year and 5‐year overall survival (OS), and main associated factors, and to analyze the current therapeutic effect of different treatment options for elderly patients. Results: The 3‐year and 5‐year OS rate of the 1013 elderly patients was 44.8% and 32.8%, respectively. Their median survival was 28.00 months. The median survival of patients with squamous cell carcinoma was longer than that of other pathological type (squamous vs. other types: 31.00 vs. 20.00 months, p = 0.018). The median survival of patients with surgery only or combined therapy was longer than that of radiotherapy, chemotherapy, and no therapy (surgery only vs. combined therapy vs. radiotherapy vs. chemotherapy vs. no therapy: 56.00 vs. 33.00 vs. 26.00 vs.18.00 vs. 16.00 months, p < 0.001). The 5‐year OS rate of patients with highly differentiated cancer was higher than that of medium differentiated and poor differentiation/undifferentiated. In multivariate analysis, the older ages, pathological stage, were independent prognostic risk factors for poor EC survival. Treatment method was independent protective factors predictive of a good EC OS. Conclusions: The survival rate of the elderly EC patients was still low in China. Age, therapy method, and pathological stage were mainly associated with the survival rate of EC in elderly patients. [ABSTRACT FROM AUTHOR]

Patient satisfaction is an important indicator of quality in health care and is linked to clinical outcomes, patient retention, and professional satisfaction. Patients admitted to the hospital from the emergency department may not understand their diagnosis, reason for admission or plan of care, which can adversely impact their hospital experience. We aim to identify risk factors that contribute to poor patient-physician communication and to assess the effects of raising awareness of these issues to hospital providers. From November 2020 to April 2021, patients admitted to the surgical floor were surveyed within 24 h of admission. Relevant data were extracted through retrospective chart review. Residents and attendings were debriefed regarding the improving communication. Surveys answered before and after the brief intervention were compared. One hundred thirty one patients who were admitted to the surgical floor were surveyed. Nineteen did not know their diagnoses (14.5%), 29 could not explain their diagnoses (22.1%), and 28 did not know their treatment plans (21.4%). A total of 38 (29.0%) patients answered "no" to at least one question. Trauma patients (P = 0.034), patients with pain score >4 at time of admission (P = 0.038), age >65 y (P = 0.047), and patients with >3 comorbidities were more likely to answer "no" to at least one of the questions. Postintervention, a 10% reduction in number of patients answering "no" was observed. Trauma patients, patients with poor pain control, the elderly, and those with multiple comorbidities are more likely to experience poor patient-physician communication. Raising awareness of the importance of this matter resulted in an improvement in communication. [ABSTRACT FROM AUTHOR]

IntroductionCoital incontinence (CI) is a frequent problem in women with urinary incontinence (UI) with significant impact on female sexuality and quality of life. The underlying mechanism is controversial; it has been known that CI is associated with both stress urinary incontinence (SUI) and detrusor overactivity (DO). However, recently it has been reported that CI is mainly related with SUI and urethral incompetence, but not with DO. Ambulatory urodynamic monitoring (AUM) has been shown to be a sensitive tool for the detection of DO. The aim of this study was to investigate the clinical risk factors for CI and the association of CI with urodynamic diagnoses at single voiding cycle AUM.MethodsRecords of sexually active women with urinary incontinence attending the urogynaecology unit of a university hospital, who completed the PISQ-12 were reviewed retrospectively (n = 1,005). Patients were grouped using the 6th question; patients answering “never” to this question were considered as continent during coitus (n = 591) and patients reporting any urinary leakage at coitus were considered to have CI (n = 414). Demographics, clinical examination findings, incontinence severity measured by the Sandvik Incontinence Severity Index, scores of Turkish validated questionnaires (PFDI-20, IIQ-7, OAB-V8, and PISQ-12) and single voiding cycle AUM findings were compared, and univariate and multivariate logistic regression analyses were performed.ResultsAmong all sexually active women with UI, 41.2% had CI; UI was more severe, symptom bother was higher, related quality of life (p < 0.001) and sexual function were worse (≤0.018) in these women. Younger age (OR 0.967, p < 0.001), history of vaginal delivery (OR 2.127, p = 0.019), smoking (OR 1.490, p = 0.041), postural UI (OR 2.012, p = 0.001), positive cough stress test (OR 2.193, p < 0.001), and positive SEST (OR 1.756, p = 0.01) were found as independent clinical factors associated with CI. Urodynamic SUI (OR 2.168, p = 0.001) and MUI (OR 1.874, p = 0.002) were found as significant and independent urodynamic diagnoses associated with CI, whereas no association was found with DO or UUI.ConclusionBoth clinical and AUM findings supported that CI is a more severe form of UI that it is mainly related with SUI and urethral incompetence, but not with UUI or DO.

Introduction: Several factors affect the survival of End Stage Kidney Disease (ESKD) patients on dialysis. Machine learning (ML) models may help tackle multivariable and complex, often non‐linear predictors of adverse clinical events in ESKD patients. In this study, we used advanced ML method as well as a traditional statistical method to develop and compare the risk factors for mortality prediction model in hemodialysis (HD) patients. Materials and Methods: We included data HD patients who had data across a baseline period of at least 1 year and 1 day in the internationally representative Monitoring Dialysis Outcomes (MONDO) Initiative dataset. Twenty‐three input parameters considered in the model were chosen in an a priori manner. The prediction model used 1 year baseline data to predict death in the following 3 years. The dataset was randomly split into 80% training data and 20% testing data for model development. Two different modeling techniques were used to build the mortality prediction model. Findings: A total of 95,142 patients were included in the analysis sample. The area under the receiver operating curve (AUROC) of the model on the test data with XGBoost ML model was 0.84 on the training data and 0.80 on the test data. AUROC of the logistic regression model was 0.73 on training data and 0.75 on test data. Four out of the top five predictors were common to both modeling strategies. Discussion: In the internationally representative MONDO data for HD patients, we describe the development of a ML model and a traditional statistical model that was suitable for classification of a prevalent HD patient's 3‐year risk of death. While both models had a reasonably high AUROC, the ML model was able to identify levels of hematocrit (HCT) as an important risk factor in mortality. If implemented in clinical practice, such proof‐of‐concept models could be used to provide pre‐emptive care for HD patients. [ABSTRACT FROM AUTHOR]

Ischemic stroke (IS) is a multifaceted, complicated illness resulting from a confluence of genetic, environmental and vascular risk factors. Many genes that may contribute to ischemic stroke have been discovered in humans. The genetic contribution appears to be greater in IS patients with hypertension. There is conflicting evidence about a positive correlation between the AGT M235T polymorphism and ischemic stroke. The aim of this study was to examine the possible association of the AGT M235T gene polymorphism with the risk of ischemic stroke. A hospital-based case-control study was carried out in 36 ischemic stroke patient cases and 36 age- and sex-matched healthy controls. Clinical parameters were measured to assess the associated risk factors. DNA was isolated from blood samples, and the AGT M235T genotypes were identified using polymerase chain reaction (PCR) and analyzed by agarose gel electrophoresis. The AGT-TT genotype (OR = 4.64, 95% CL = 1.23–17.4; p = 0.023 and T allele (OR = 2.54, 95% CL = 1.28–5.02; p = 0.003) were significantly more common in patients than in controls, indicating that it may be a major risk factor for the development of ischemic stroke. The results suggest that there may be a significant correlation between the AGT M235T gene polymorphism and the development of ischemic stroke in the studied Ethiopian population. [ABSTRACT FROM AUTHOR]

Background. The method of recruiting the study subjects is an important element of the study design. It can have a strong influence on the results. Different recruitment schedules can give a different picture of the studied phenomenon. Objectives. The aim of the study was to compare bone health in a group of female patients treated for osteoporosis with a population-based sample. Materials and methods. A cohort of women from GO Study from 1 outpatient osteoporotic clinic (n = 1442, mean age 65.8 ±6.7 years) and population-based female sample of RAC-OST-POL Study (n = 963, mean age 65.8 ±7.5 years) were studied. Mean age did not differ between groups. Mean weight, height and body mass index (BMI) in subjects from GO Study and RAC-OST-POL Study were 69.5 ±13.1 kg, 157.8 ±6.1 cm and 27.9 ±5.1 kg/m2, and 74.2 ±13.7 kg, 156.0 ±6.0 cm and 30.5 ±5.4 kg/m2, respectively, and differed significantly (p < 0.0001 for each variable). Data on clinical risk factors for osteoporosis and fractures were collected. Bone densitometry at hip was performed using a Prodigy or Lunar DPX device (GE Healthcare, Waukesha, USA). Fracture risk was established using FRAX, Garvan and POL-RISK. Results. Mean values of T-score for femoral neck in subjects from GO Study and RAC-OST-POL Study were -1.67 ±0.91 and -1.27 ±0.91 and differed significantly (p < 0.0001). In GO Study and RAC-OST-POL Study, there were 518 (35.9%) and 280 (29.1%) subjects with fractures, respectively. The fracture frequency was significantly higher in the GO Study group (p < 0.001). Among clinical risk factors, only rheumatoid arthritis (p < 0.0001) secondary osteoporosis (p < 0.0001) and falls (p < 0.0001) were more frequent in RAC-OSTPOL Study. Fracture risk established using FRAX, Garvan and POL-RISK calculators was significantly greater in patients enrolled in the GO Study than in subjects from the RAC-OST-POL population-based sample (p < 0.0001 for each variable). Conclusions. Differences noted between female patients treated for osteoporosis and population-based sample, especially in regard to fracture risk, reveal a strong influence of recruitment criteria on study results in the field of bone health and osteoporosis. [ABSTRACT FROM AUTHOR]

Summary: Rationale Appropriate screening can prevent osteoporotic hip fractures (HF). There is little data on clinical risk factors (CRFs) from Africa. Main result: Subjects with HF had similar CRFs to high income countries and poor functional outcomes post HF. Significance: Screening and treatment algorithms to improve outcomes post HF need to be implemented. Purpose: Limited data exist on clinical risk factors (CRFs) for and functional outcomes following hip fractures (HF) in South Africa (SA). Methods: In a prospective observational study conducted in two municipalities in KwaZulu-Natal, a structured questionnaire recorded demographic data, CRFs, self-reported chronic medical conditions and functional status. Parametric and non-parametric tests were used to test for differences and the McNemar test for change over time. Results: The median age of the 287 subjects was 72 years (IQR 64–80 years) with the majority women (67.2%), who were significantly older than men. Two or more comorbidities were present in 76.3%. Hypertension (71.4%) and diabetes (29.6%) were most common. Eleven (3.8%) reported a previous diagnosis of osteoporosis and four (1.4%) prior treatment for osteoporosis. A history of cancer (15.4% v. 1.2%, p < 0.001), previous diagnosis of osteoporosis (17.9% v. 1.6%, p < 0.001) and treatment for osteoporosis (7.7% v. 0.4%, p < 0.001) was significantly more common in private compared to public sector subjects. African subjects had a higher prevalence of HIV infection compared to Indian (12.5% v. 0%, p < 0.001) while Indian subjects were more likely to report two or more comorbidities (p = 0.003) and hypertension (p = 0.005) compared to African subjects. Common CRFs were a previous fracture (32.4%), prior fall (24.7%), weight below 57 kg (23.3%), smoking (19.2%) and alcohol use of more than 3 units per day (17.8%). Less than 5% reported a history of parental HF or glucocorticosteroid use. Functional status was available for 206 subjects. Of the 163 participants who had surgery, 81% were independent prior to the HF, compared to the significantly lower 6.7% and 56.4% at 30 days and 1 year post fracture, respectively. The proportion with some degree of dependency rose significantly from 19% pre-fracture to 43.6%, 1 year post-fracture. Walking up stairs and transfer from bed to chair were the most commonly affected activities. Conclusion: Clinical risk factors for HF are similar to those published internationally and support the use of current risk assessment models in SA. Targeted management and rehabilitation programs are required to improve functional outcomes post-HF. [ABSTRACT FROM AUTHOR]

Background: Aortic root dilation (ARD) has been described in 22q11.2DS, even without congenital heart disease (CHD). However, the clinical implications and longitudinal course are unclear. In this study, we evaluated aortic root (AR) dimensions in 22q112.DS adolescents/adults without major intracardiac CHDs, analyzed the progression over time and investigated correlations with extracardiac comorbidities. Methods: AR dimensions were evaluated in 74 patients, measuring the sinus of Valsalva (VS) and proximal ascending aorta (AA), using Z-score to define mild, moderate and severe degrees. Changes in AR dimensions during longitudinal echocardiographic follow-up were investigated. Phenotypic characteristics have been collected. Results: Twenty-four patients (32.4%) showed ARD in terms of VS Z-score (2.43; IQR 2.08–3.01), eight (33.3%) of a moderate/severe degree. Thirteen (54.2%) had concomitant AAD (Z-score 2.34; IQR 1.60–2.85). The risk of ARD was significantly directly related to skeletal/connective tissue disorders (OR 12.82, 95% CI 1.43–115.31; p = 0.023) and inversely related to BMI (OR 0.86, 95% CI 0.77–0.97; p = 0.011). A significant increase in AR diameter's absolute value (p = 0.001) over time has been detected. Conclusion: Isolated ARD is common in 22q11.2DS. Although some clinical risk factors have been identified, pathogenetic mechanisms and risk of complications are undefined. Regular cardiac evaluations should be part of the 22q11.2DS follow-up, and also in non-CHDs patients, to improve long-term outcome. [ABSTRACT FROM AUTHOR]

aimed to develop and validate a nomogram model with clinical risk factors and radiomic features for differentiating tuberculous spondylitis (TS) from pyogenic spondylitis (PS). Methods: A total of 254 patients with TS (n = 141) or PS (n = 113) were randomly divided into training (n = 180) and validation (n = 74) groups. In addition, 43 patients (TS = 22 and PS = 21) were collected to construct a test cohort. t-test analysis, de-redundancy analysis, and minimum absolute shrinkage and selection operator (lasso) algorithm were utilized on the training set to obtain the optimal radiomics features from computed tomography (CT) for constructing the radiomics model and determine the radiomics score (Rad-score). Eight clinical risk predictors were identified to develop the clinical model. Combined with clinical risk predictors and Rad-scores, a nomogram model was constructed using multivariate logistic regression analysis. Results: A total of 1781 features were extracted, and 12 optimal radiomic features were utilized to construct the radiomic model and determine the Rad-score. The combined clinical radiomics model revealed good discrimination performance in both the training cohort and the validation cohort (AUC =  0.891 and 0.830) and was superior to the clinical (AUC =  0.807 and 0.785) and radiomics (AUC =  0.796 and 0.811) models. The calibration curve and DCA also depicted that the nomogram had better clinical efficacy. The discriminative performance of the model is well validated in the test cohort (AUC=0.877). Conclusion: The clinical radiomic nomogram could serve as a promising predictive tool for differentiating TS from PS, which could be helpful for clinical decision-making. [ABSTRACT FROM AUTHOR]

Background: Although determining the recurrence of cutaneous squamous cell carcinoma (cSCC) is important, currently suggested systems and single biomarkers have limited power for predicting recurrence. Objective: In this study, combinations of clinical factors and biomarkers were adapted into a nomogram to construct a powerful risk prediction model. Methods: The study included 145 cSCC patients treated with Mohs micrographic surgery. Clinical factors were reviewed, and immunohistochemistry was performed using tumor tissue samples. A nomogram was constructed by combining meaningful clinical factors and protein markers. Results: Among the various factors, four clinical factors (tumor size, organ transplantation history, poor differentiation, and invasion into subcutaneous fat) and two biomarkers (Axin2 and p53) were selected and combined into a nomogram. The concordance index (C-index) of the nomogram for predicting recurrence was 0.809, which was higher than that for the American Joint Committee on Cancer (AJCC) 7th, AJCC 8th, Brigham and Women's Hospital, and Breuninger staging systems in the patient data set. Conclusion: A nomogram model that included both clinical factors and biomarkers was much more powerful than previous systems for predicting cSCC recurrence. [ABSTRACT FROM AUTHOR]

Coronavirus disease-2019 (COVID-19)-associated pulmonary aspergillosis (CAPA) is a new disease characterized by secondary Aspergillus mold infection in patients with COVID-19. It primarily affects patients with COVID-19 in critical state with acute respiratory distress syndrome, requiring intensive care and mechanical ventilation. CAPA has a higher mortality rate than COVID-19, posing a serious threat to affected individuals. COVID-19 is a potential risk factor for CAPA and has already claimed a massive death toll worldwide since its outbreak in December 2019. Its second wave is currently progressing towards a peak, while the third wave of this devastating pandemic is expected to follow. Therefore, an early and accurate diagnosis of CAPA is of utmost importance for effective clinical management of this highly fatal disease. However, there are no uniform criteria for diagnosing CAPA in an intensive care setting. Therefore, based on a review of existing information and our own experience, we have proposed new criteria in the form of practice guidelines for diagnosing CAPA, focusing on the points relevant for intensivists and pulmonary and critical care physicians. The main highlights of these guidelines include the role of CAPA-appropriate test specimens, clinical risk factors, computed tomography of the thorax, and non-culture-based indirect and direct mycological evidence for diagnosing CAPA in the intensive care unit. These guidelines classify the diagnosis of CAPA into suspected, possible, and probable categories to facilitate clinical decision-making. We hope that these practice guidelines will adequately address the diagnostic challenges of CAPA, providing an easy-to-use and practical algorithm to clinicians for rapid diagnosis and clinical management of the disease. [ABSTRACT FROM AUTHOR]

• Specific risk factors are associated with exclusion of AIS with a history of OSA. • AIS patients without OSA, with increasing age, coronary artery stenosis, and diabetes were excluded from rtPA. • AIS patients with OSA, dyslipidemia and an improvement in ambulatory status were included for rtPA therapy. The eligibility criteria for thrombolytic therapy may differ between acute ischemic stroke patients (AIS) patients with and without incidence of obstructive sleep apnea (OSA). In this study, we determine the effect of specific comorbidities in the exclusion and inclusion for recombinant tissue plasminogen activator (rtPA) administration in the AIS population with OSA. Retrospective data from a stroke registry were analyzed for baseline clinical and demographic factors in AIS patients with OSA for rtPA therapy from January 2010 to June 2016. The logistic regression model was developed to identify each of the variables predicting inclusion for or exclusion from rtPA. We estimated the odds of the inclusion or exclusion of a particular demographic and clinical risk factor in AIS with and without OSA for rtPA therapy. The validity of the model was tested using a Hosmer-Lemeshow test and the sensitivity of the model was determined using a Receiver Operating Curve (ROC). A total of 170 AIS patients with OSA were identified, of which, 125 did not receive rtPA while 45 received rtPA. Adjusted analysis showed that in the AIS population with OSA, administration of rtPA was associated with a history of dyslipidemia (OR=3.192, 95% CI, 1.148-8.88, p =0.026), direct admission into a Comprehensive Stroke Center (OR=3.248, 95% CI, 1.06-9.95, p =0.039), and ambulatory improvement (OR=3.556, 95% CI, 1.428-8.86, p =0.006). There were no significant factors associated with rtPA exclusion in the AIS population with OSA. The prevalence of OSA in our AIS population was low and no clinical risk factor was associated with the exclusion of patients with AIS and OSA from thrombolytic therapy. Future studies are necessary to explore the effect of OSA in AIS patients to improve eligibility for rtPA therapy for more patients. [ABSTRACT FROM AUTHOR]

Abstract Aims The aim of the present paper was to provide an up‐to‐date view on epidemiology and risk factors of heart failure (HF) development after myocardial infarction. Methods and results Based on literature review, several clinical risk factors and biochemical, genetic, and imaging biomarkers were identified to predict the risk of HF development after myocardial infarction. Conclusions Heart failure is still a frequent complication of myocardial infarction. Timely identification of subjects at risk for HF development using a multimodality approach, and early initiation of guideline‐directed HF therapy in these patients, can decrease the HF burden.

The introduction of the FRAX algorithms has facilitated the assessment of fracture risk on the basis of fracture probability. FRAX integrates the influence of several well-validated risk factors for fracture with or without the use of bone mineral density. Since age-specific rates of fracture and death differ across the world, FRAX models are calibrated with regard to the epidemiology of hip fracture (preferably from national sources) and mortality (usually United Nations sources). Models are currently available for 73 nations or territories covering more than 80% of the world population. FRAX has been incorporated into more than 80 guidelines worldwide, although the nature of this application has been heterogeneous. The limitations of FRAX have been extensively reviewed. Arithmetic procedures have been proposed in order to address some of these limitations, which can be applied to conventional FRAX estimates to accommodate knowledge of dose exposure to glucocorticoids, concurrent data on lumbar spine bone mineral density, information on trabecular bone score, hip axis length, falls history, type 2 diabetes, immigration status and recency of prior fracture. [ABSTRACT FROM AUTHOR]

Background: Breast reconstructive surgery is often a multistage process. The aim was to understand which factors might increase the number of follow-up surgeries and the length of time required to complete the reconstruction process. Methods: A cross-sectional analysis was performed. Clinical data of 110 patients who underwent delayed postmastectomy breast reconstruction with a 5-year examination period were reviewed retrospectively. Impact of clinical risk factors, oncological therapy, and reconstruction approach on the number of surgeries and the length of required time was analyzed. Mann–Whitney U test and Kruskal–Wallis rank sum test were used. Results: In patients undergoing perioperative hormone therapy, an average of 2.9 surgeries and length of 20.2 months were required compared to 2.3 surgeries and 14.0 months in patients without hormone therapy (P = 0.003; P = 0.005). Previous abdominal surgery was associated with an increased number of breast reconstruction stages of 3.1 per patient (P = 0.056) and a longer reconstruction time of 23.0 months (P = 0.050). Patients undergoing nipple reconstruction or implant revision required an increased number of surgeries (P < 0.001; P = 0.012) and a longer reconstruction time (P = 0.002; P < 0.001). Contralateral breast surgery and flap revision were associated only with an increased number of surgeries (P < 0.001; P < 0.001). Conclusion: Perioperative hormone therapy was associated with a significantly higher number of surgeries and duration of time required to complete the reconstruction process. The highest increase in the number of surgeries was in patients with flap revision including anastomosis revision and necrectomy. Level of Evidence IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266. [ABSTRACT FROM AUTHOR]

Abstract Background Caesarean section (CS) rates are increasing and there are wide variations in rates internationally and nationally. There is evidence that women who attend their obstetrician privately have a higher incidence of CS than those who attend publicly. The purpose of this observational study was to further investigate why CS rates may be higher in women who chose to attend their obstetrician privately. Methods This study analysed data collected as part of the clinical records by midwives at the woman’s first antenatal appointment in a large European maternity hospital. All women who delivered between the years 2009 and 2017 were included. Data were analysed both cross-sectionally and longitudinally. Results Overall, 73,266 women had a singleton pregnancy and 1830 had a multiple pregnancy. Of the packages of maternity care, 75.2% chose public, 10.8% chose semiprivate and 14.0% chose private. During the study, 11,991 women attended the hospital for their first and second pregnancies. Overall, women who attended privately were older and had higher proportions of infertility treatment and history of miscarriage (all p

Abstract Background Acute ischemic stroke attack with and without a recent TIA may differ in clinical risk factors, and this may affect treatment outcomes following thrombolytic therapy. We examined whether the odds of exclusion or inclusion for thrombolytic therapy are greater in ischemic stroke with TIA less than 24 h preceding ischemic stroke (recent-TIA) as compared to those without recent TIA or non-TIA > 24 h and less than 1 month (past-TIA). Methods A retrospective hospital-based analysis was conducted on 6315 ischemic stroke patients, of whom 846 had proven brain diffusion-weighted magnetic resonance imaging (DW-MRI) of an antecedent TIA within 24 h prior to ischemic stroke. The logistic regression model was developed to generate odds ratios (OR) to determine clinical factors that may increase the likelihood of exclusion or inclusion for thrombolytic therapy. The validity of the model was tested using a Hosmer-Lemeshow test, while the Receiver Operating Curve (ROC) was used to test the sensitivity of our model. Results In the recent-TIA ischemic stroke population, patients with a history of alcohol abuse (OR = 5.525, 95% CI, 1.003–30.434, p = 0.05), migraine (OR = 4.277, 95% CI, 1.095–16.703, p = 0.037), and increasing NIHSS score (OR = 1.156, 95% CI, 1.058–1.263, p = 0.001) were associated with the increasing odds of receiving rtPA, while older patients (OR = 0.965, 95% CI, 0.934–0.997, P = 0.033) were associated with the increasing odds of not receiving rtPA. Conclusion In recent-TIA ischemic stroke patients, older patients with higher INR values are associated with increasing odds of exclusion from thrombolytic therapy. Our findings demonstrate clinical risks factors that can be targeted to improve the use and eligibility for rtPA in in recent-TIA ischemic stroke patients.