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Abstract Due to the resistance of carbapenem-resistant Klebsiella pneumoniae (CRKP) to most antibiotics, CRKP treatment is challenging, which results a high mortality rate. CRKP infection poses a significant challenge for infection management and treatment, especially among neonates and premature infants. Therefore, it is important to understand the clinical characteristics of CRKP bloodstream infection (BSI) in premature infants and identify the related risk factors for death. This study aims to explore and analyze the clinical characteristics and risk factors affecting mortality of BSI caused by CRKP in premature infants. A retrospective study was conducted in a Children’s Hospital in Henan to analyze clinical data of premature infants with CRKP BSI admitted from January 2015 to December 2022. Univariate and multivariate logistic regression models were utilized to investigate risk factors affecting mortality. Receiver operating characteristic curves were employed to evaluate the predictive value of different indicators on mortality, and differences in area under the curve (AUC) were compared using Stata 17 SE. A total of 96 premature infants with CRKP BSI were enrolled, including 70 patients in the survival group and 26 in the death group. At the onset of infection, 69 (71.9%) patients exhibited persistent tachycardia (heart rate > 180 beats/min), 61 (63.5%) had fever, and 59 (61.4%) experienced apnea episodes. Concurrent meningitis (OR 9.588, 95% CI 1.401–57.613, P = 0.021), concurrent necrotizing enterocolitis (NEC) (OR 7.881, 95% CI 1.672–73.842, P = 0.032), and the maximum vasoactive-inotropic score (VIS) value within 48 h of onset (OR 1.467, 95% CI 1.021–1.782, P = 0.001) were identified as independent risk factors for mortality. The univariate analysis showed that ceftazidime-avibactam (CAZ/AVI) treatment and appropriate early antimicrobial treatment were significantly associated with survival (P

Background and goal: The reverse shock index multiplied by the Glasgow Coma Scale score(rSIG)predicts trauma patient mortality, according to previous studies. It is unclear if rSIGCan predict massive transfusion (MT) in trauma patients. This study examines whether rSIG predicts MT in trauma patients. The study also tests whether rSIG can predict trauma patient's coagulopathy, in-hospital mortality, and 24-hour death, rSIG's prognostic value for MT in trauma patients is compared to TASH and ABC scores. Methods: This single -- center prospective observational study at B.L.D. E (DU), SHRI B.M. Patil medical college hospital and research center's emergency medicine department. In trauma patients, rSIG's prognostic value for MTP was compared to older scoring systems as TASH and ABC scores. Results: MT was given to 20 of 195 patients. MT, in-hospital mortality, 24-hour mortality, and coagulopathy are better predicted by rSIG than SI, SIA, and qSOFA. The in-hospital mortality AUROC for rSIG was 0.812, indicating its dependability. Prior study shows that rSIG can predict trauma patient's death and coagulopathy. All three tests are discriminatory, but evaluation assessment blood consumption is most accurate, followed by TASH score and rSIGusing ROC values. MT rSIG predicted better than SL, SLA, and qSOFA (AUROC=0.842). rSIG predicted coagulopathy, in-hospital, and 24-hour mortality better than SI, SIA and qSOFA. RSIG combines hemodynamic instability (reverse SI) and consciousness (GCS) for a more complete trauma patient evaluation. Detecting coagulopathy early with rSIG permits rewarming, acidosis correction, balanced transfusion and massive transfusion regimens. Conclusion: The study shows that rSIG can identify trauma patients at high risk for major transfusion, coagulopathy, and death. Assessment Blood consumption evaluation is most accurate, followed by TASH Score and rSIG, for managing severe trauma situations swiftly and effectively which could improve patient outcomes. [ABSTRACT FROM AUTHOR]

Abstract Accurate prediction of oocyte maturation is a critical determinant of success in in vitro fertilization-embryo transfer (IVF-ET) procedures. This review provides a comprehensive analysis of the various predictive approaches employed to assess oocyte maturity, including single indicators, combined indicators, and predictive models. Factors such as ovarian reserve, patient characteristics, and controlled ovarian hyperstimulation (COH) strategies can significantly influence oocyte maturation rates. Single indicators, including hormone levels, ultrasound parameters, and clinical parameters, have been extensively studied. However, their predictive power may be limited when used in isolation. Combined indicators, integrating multiple parameters, have demonstrated improved predictive performance compared to single indicators. Additionally, predictive models and algorithms, such as machine learning and deep learning models, have emerged as promising tools for assessing oocyte maturity. These models leverage advanced statistical and computational methods to analyze complex datasets and identify patterns that can predict oocyte maturation rates with potentially higher accuracy. Despite these advancements, several gaps and limitations persist, including limited generalizability, lack of standardization, insufficient external validation, and the need to incorporate patient-specific factors and emerging technologies. The review highlights potential areas for further research, such as multicenter collaborative studies, integration of advanced omics technologies, development of personalized prediction models, and investigation of trigger time optimization strategies. Recommendations for clinical practice include utilizing a combination of indicators, adopting validated predictive models, tailoring approaches based on individual patient characteristics, continuous monitoring and adjustment, and fostering multidisciplinary collaboration. Accurate prediction of oocyte maturation holds profound implications for improving the success rates of IVF-ET and enhancing the chances of achieving a healthy pregnancy. Continued research, innovative approaches, and the implementation of evidence-based practices are essential to optimize assisted reproductive outcomes.

Hua-Jing Yuan,1 Hua-Chen Jiao,2 Xiu-Juan Liu,2 Hao Hao,2 Yang Liu,2 Yi-Tao Xue,2 Yan Li2 1Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, 250014, People’s Republic of China; 2Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, 250014, People’s Republic of ChinaCorrespondence: Yi-Tao Xue; Yan Li, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Shanshi East Road, Lixia District, Jinan City, Shandong Province, People’s Republic of China, Tel +86-531-82602943 ; +86-531-68611662, Email xytsdzydfy@126.com; liyan88130@163.comPurpose: The association between serum uric acid (SUA) and atrial fibrillation (AF) has been widely focused on and studied in recent years. However, the exact association between SUA and AF is unclear, and the effect of gender on the association between SUA levels and AF has been controversial. This study aimed to investigate the association between SUA levels and non-valvular AF (NVAF) and the potential effect of gender on it.Patients and Methods: A total of 866 NVAF patients (463 males, age 69.44 ± 8.07 years) and 646 sex-matched control patients in sinus rhythm, with no history of arrhythmia were included in this study. t-test, ANOVA, and chi-square test were used for baseline data analysis. The receiver operating characteristic curve, logistic regression and Pearson correlation analysis were used for correlation analysis.Results: Compared to controls, NVAF patients exhibited higher SUA (P< 0.001). After adjusting for confounders of NVAF, SUA remained significantly associated with NVAF, regardless of gender (OR= 1.31, 95% CI 1.18– 1.43, P< 0.001). SUA demonstrated higher predictability and sensitivity in predicting the occurrence of female NVAF compared to male (area under the curve was 0.68 (95% CI 0.64– 0.72, P< 0.001), sensitivity 87.3%), with the optimal cut-off point identified as 5.72 mg/dL. Furthermore, SUA levels correlated with APOA1, Scr and NT-proBNP in NVAF patients. SUA levels varied significantly among NVAF subtypes.Conclusion: High SUA levels were independently associated with NVAF, regardless of gender. SUA exhibited higher predictability and sensitivity in predicting the occurrence of NVAF in females compared to males. High SUA levels may affect other NVAF-related factors and participate in the pathophysiological process of NVAF.Keywords: serum uric acid, non-valvular atrial fibrillation, gender difference, retrospective study, predictive indicators

Accurate prediction of oocyte maturation is a critical determinant of success in in vitro fertilization-embryo transfer (IVF-ET) procedures. This review provides a comprehensive analysis of the various predictive approaches employed to assess oocyte maturity, including single indicators, combined indicators, and predictive models. Factors such as ovarian reserve, patient characteristics, and controlled ovarian hyperstimulation (COH) strategies can significantly influence oocyte maturation rates. Single indicators, including hormone levels, ultrasound parameters, and clinical parameters, have been extensively studied. However, their predictive power may be limited when used in isolation. Combined indicators, integrating multiple parameters, have demonstrated improved predictive performance compared to single indicators. Additionally, predictive models and algorithms, such as machine learning and deep learning models, have emerged as promising tools for assessing oocyte maturity. These models leverage advanced statistical and computational methods to analyze complex datasets and identify patterns that can predict oocyte maturation rates with potentially higher accuracy. Despite these advancements, several gaps and limitations persist, including limited generalizability, lack of standardization, insufficient external validation, and the need to incorporate patient-specific factors and emerging technologies. The review highlights potential areas for further research, such as multicenter collaborative studies, integration of advanced omics technologies, development of personalized prediction models, and investigation of trigger time optimization strategies. Recommendations for clinical practice include utilizing a combination of indicators, adopting validated predictive models, tailoring approaches based on individual patient characteristics, continuous monitoring and adjustment, and fostering multidisciplinary collaboration. Accurate prediction of oocyte maturation holds profound implications for improving the success rates of IVF-ET and enhancing the chances of achieving a healthy pregnancy. Continued research, innovative approaches, and the implementation of evidence-based practices are essential to optimize assisted reproductive outcomes. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to assess the clinical importance of various biomarkers, including NLR, CEA, CA199, CA125, CA153, and HE4, through dynamic testing to evaluate the effectiveness of neoadjuvant chemotherapy (NACT) for individuals facing advanced ovarian cancer. This provides valuable information for tailoring treatment plans to individual patients, thereby leading to a more personalized and effective management of individuals facing ovarian cancer. Methods: The levels of NLR, CA125, CA199, CEA, CA153, and HE4 were detected before chemotherapy and after 3 courses of chemotherapy. Patients were categorized into ineffective and effective groups according to the effectiveness of NACT. To evaluate the factors influencing NACT’s effectiveness in individuals facing advanced ovarian cancer, receiver operating characteristic (ROC) curves, predictive modeling, and multifactorial regression analysis were employed. Results: In the effective group, the patients’ age, maximum tumor diameter, and CEA and HE4 levels of the patients were significantly higher compared to those in the ineffective group (P <.05). Additionally, the difference in HE4 levels before and after treatment between the effective and ineffective groups was statistically significant (P<.05). Multifactorial analysis showed that age and maximum tumor diameter were independent risk factors impacting the effectiveness of NACT in individuals facing advanced ovarian cancer (P<.05). The ROC curve for predicting the effectiveness of NACT in individuals facing advanced ovarian cancer showed a sensitivity of 93.3% for NLR and a specificity of 92.3% for CA199. HE4 emerged as the most reliable predictor, demonstrating a specificity of 84.6% and a sensitivity of 75.3%. The area under the curve of the combined CA125 and HE4 assays for predicting the ineffectiveness of NACT in individuals facing advanced ovarian cancer was 0.825, showcasing a specificity of 74.2% and a sensitivity of 84.6%. Conclusion: The predictive capacity for the effectiveness of NACT in individuals facing advanced ovarian cancer is notably high when considering the sensitivity of NLR and the specificity of CA199. Additionally, the combination of CA125 and HE4 assays can obtain a better predictive effect, which can accurately select patients suitable for NACT, determine the appropriate timing of the interval debulking surgery (IDS) surgery, and achieve a satisfactory tumor reduction effect. [ABSTRACT FROM AUTHOR]

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Chimeric antigen receptor T‐cell (CAR‐T) therapy has demonstrated remarkable efficacy in treating relapsed/refractory acute B‐cell lymphoblastic leukaemia (R/R B‐ALL). However, a subset of patients does not benefit from CAR‐T therapy. Our study aims to identify predictive indicators and establish a model to evaluate the feasibility of CAR‐T therapy. Fifty‐five R/R B‐ALL patients and 22 healthy donors were enrolled. Peripheral blood lymphocyte subsets were analysed using flow cytometry. Sensitivity, specificity, accuracy, positive and negative predictive values and receiver operating characteristic (ROC) areas under the curve (AUC) were determined to evaluate the predictive values of the indicators. We identified B lymphocyte, regulatory T cell (Treg) and peripheral blood minimal residual leukaemia cells (B‐MRD) as indicators for predicting the success of CAR‐T cell preparation with AUC 0.936, 0.857 and 0.914. Furthermore, a model based on CD3+ T count, CD4+ T/CD8+ T ratio, Treg and extramedullary diseases (EMD) was used to predict the response to CAR‐T therapy with AUC of 0.938. Notably, a model based on CD4+ T/CD8+ T ratio, B, Treg and EMD were used in predicting the success of CAR‐T therapy with AUC 0.966 [0.908–1.000], with specificity (92.59%) and sensitivity (91.67%). In the validated group, the predictive model predicted the success of CAR‐T therapy with specificity (90.91%) and sensitivity (100%). We have identified several predictive indicators for CAR‐T cell therapy success and a model has demonstrated robust predictive capacity for the success of CAR‐T therapy. These results show great potential for guiding informed clinical decisions in the field of CAR‐T cell therapy. [ABSTRACT FROM AUTHOR]

Background: One of the main risk factors for the occurrence of oral cancer is oral precancerous lesions (OPLs). Early management and preventive efforts depend on knowing the transformation rate and detecting predictive signs of malignancy. Methods: For 6 months, a group of 200 individuals with clinically diagnosed OPLs was followed up on in this longitudinal research. To examine biomarker expression levels and describe the lesions, examinations using immunohistochemistry, histopathology, and clinical methods were carried out. Findings: Over the course of 2 years, 200 patients with OPLs were monitored in this study. Most lesions had mild dysplasia, according to histopathological examination. The expression of many biomarkers that were correlated with the dysplasia grade were p53 (60.0%), Ki-67 (40.0%), CDKN2A (30.0%), and epidermal growth factor receptor (EGFR) (25.0%). Conclusion: In summary, this study emphasizes how crucial it is to provide patients with OPLs with individualized care plans and routine surveillance. Certain biomarkers, such EGFR, Ki-67, and p53, can be useful prognostic markers for identifying malignant transformation. To confirm these results and create tailored therapies for high-risk patients, more study is necessary.

Xiaojing Li,1 Liwei Bai,2 Ziru Niu,3 Qiang Lu3 1Department of Obstetrics, First Hospital of Qinhuangdao, Qinhuangdao, Hebei, 066000, People’s Republic of China; 2Department of Obstetrics, Qinhuangdao Hospital for Maternal and Child Health, Qinhuangdao, Hebei, 066000, People’s Republic of China; 3Department of Endocrinology, First Hospital of Qinhuangdao, Qinhuangdao, Hebei, 066000, People’s Republic of ChinaCorrespondence: Qiang Lu, Department of Endocrinology, First Hospital of Qinhuangdao, Qinhuangdao, Hebei, 066000, People’s Republic of China, Tel +86-13933909066, Email 13933909066@126.comPurpose: The objective of this study was to explore whether neck circumference can serve as an early predictor of the risk of Gestational Diabetes (GDM).Patients and Methods: A total of 318 singleton pregnant women who underwent routine prenatal examinations at Qinhuangdao Maternal and Child Health Hospital from September 2017 to September 2020 were selected and categorized into the GDM group and the normal glucose tolerance group (NGT) based on the results of the oral glucose tolerance test (OGTT) conducted during the second trimester. The general information and laboratory test results were compared and analyzed. Inter-group comparison was conducted using the t-test, and multivariate logistic regression analysis was employed to analyze the independent risk factors of GDM. The predictive threshold of various indicators for GDM occurrence during pregnancy was determined using the subject’s work curve.Results: The GDM group exhibited significantly higher levels of pre-pregnancy weight, pre-pregnancy BMI, neck circumference, waist circumference, hip circumference, triglycerides (TG), uric acid (UA), TG/HDL-C ratio, and waist-hip ratio compared to the NGT group. Additionally, HDL cholesterol (HDL-C) levels were significantly lower in the GDM group, and blood glucose levels at each point of the OGTT were markedly higher compared to the NGT group (P< 0.05). Multivariate logistic regression analysis revealed that neck circumference (OR=1.239, P< 0.001) and early pregnancy TG (OR=1.842, P< 0.001) were independent risk factors for GDM. The receiver operating characteristic analysis demonstrated that the optimal critical value of neck circumference for predicting GDM was 32.6 cm, with a sensitivity of 50% and specificity of 74.3%.Conclusion: The neck circumference during early pregnancy was found to be related to GDM, and the predictive cutoff point of 32.6 cm for neck circumference could be employed as a simple index to predict GDM in early pregnancy.Keywords: neck circumference, gestational diabetes, obesity, predictive indicators

China’s economy is in a state of rapid development in today’s digital era, and big data technology has become a key force in promoting industrial upgrading and economic operation. The article first constructs 14 economic operation indexes in 7 aspects to establish the regional economic index system according to each type of regional economy. After researching BP neural networks, a TMBA-BP neural network prediction model based on adaptive t-distribution has been proposed. The prediction model is used to predict the economic development of Liaoning City, and the results show that the TMBABP prediction model is accurate. Finally, the Gini coefficient is combined with the TMBA-BP model to explore the causes of regional economic differentiation in China. In terms of the contribution rate of regional differences, the inter-regional contribution rate is higher than the intra-regional contribution rate. It indicates that in the big data environment, the main reasons for the obvious regional economic differentiation in China are inter-regional differences, followed by intra-regional differences.

Hypocalcaemia being one of the most common complications after total thyroidectomy may not be avoidable in all cases. This study evaluated the effectiveness of intact Parathyroid hormone (iPTH) measured at 1-h after total thyroidectomy in predicting postoperative hypocalcaemia in early postoperative period in South Indian population. Patients who underwent total thyroidectomy in our institute from 2016 to 2018 were included. Preoperative calcium and iPTH levels were measured. Patients' iPTH level was measured 1 h after surgery and serum calcium level was measured at 24 h after surgery. Patients were also monitored clinically for any symptoms and signs of hypocalcaemia. A total of 57 patients were studied. The malignant causes accounted for 75.4% with papillary carcinoma thyroid being the most common cause. 65.7% of patients who underwent total thyroidectomy and 100% of patients who underwent total thyroidectomy with neck dissection developed hypocalcaemia. 70% of patients with low iPTH developed hypocalcaemia and none of the patients who had normal iPTH developed hypocalcaemia. This relation was statistically significant with p value of 0.018 (< 0.05). The positive predictive value is 70% and negative predictive value is 100%. Though our study supports the hypothesis that iPTH is effective in predicting hypocalcaemia after total thyroidectomy in the early postoperative period, a larger sample study is needed to further support this. It can be used to consider patients for early discharge or to prophylactically start oral calcium and Vitamin D supplementation based on iPTH levels at 1 h after surgery. [ABSTRACT FROM AUTHOR]

Purpose: The recurrence of atrial fibrillation (AF) after cryoablation still needs to be prioritized, including discriminating predictive indicators.Methods: Eighty-seven patients aged 43-83 years who underwent cryo-balloon ablation were divided into paroxysmal atrial fibrillation (PAF) and non-paroxysmal atrial fibrillation (non-PAF) groups. Baseline data, intraoperative index, and miRNA21, IL-18, NLRP3, and visfatin levels in peripheral venous blood and left atrial blood were assessed. Follow-up was performed for 6 months to observe the recurrence of AF. A Cox risk ratio model was used to analyze indicators for predicting AF recurrence.Results: The non-PAF and PAF group recurrence rates of AF were statistically different (p < 0.05) at 9/22 (40.9%) and 11/65 (16.9%), respectively. Biomarker levels in the left atrial blood were higher in the non-PAF group than in the PAF group (p < 0.05). The effects of non-PAF and levels of miRNA21 and IL-18 in left atrial serum on the recurrence of AF after cryoablation statistically differed (p < 0.05).Conclusion: The levels of miRNA21 and IL-18 were higher in left atrial blood than in peripheral blood, which may be related to the severity of AF and recurrence of AF after cryoablation. [ABSTRACT FROM AUTHOR]

Background: One of the main risk factors for the occurrence of oral cancer is oral precancerous lesions (OPLs). Early management and preventive efforts depend on knowing the transformation rate and detecting predictive signs of malignancy., Methods: For 6 months, a group of 200 individuals with clinically diagnosed OPLs was followed up on in this longitudinal research. To examine biomarker expression levels and describe the lesions, examinations using immunohistochemistry, histopathology, and clinical methods were carried out., Findings: Over the course of 2 years, 200 patients with OPLs were monitored in this study. Most lesions had mild dysplasia, according to histopathological examination. The expression of many biomarkers that were correlated with the dysplasia grade were p53 (60.0%), Ki-67 (40.0%), CDKN2A (30.0%), and epidermal growth factor receptor (EGFR) (25.0%)., Conclusion: In summary, this study emphasizes how crucial it is to provide patients with OPLs with individualized care plans and routine surveillance. Certain biomarkers, such EGFR, Ki-67, and p53, can be useful prognostic markers for identifying malignant transformation. To confirm these results and create tailored therapies for high-risk patients, more study is necessary., Competing Interests: There are no conflicts of interest., (Copyright: © 2024 Journal of Pharmacy and Bioallied Sciences.)

Mathematical models aimed at predicting Intimate Partner Violence levels are being developed nowadays. However, most of them do not prescribe how to use them systematically by either care centers or experts. This article proposes a detailed questionnaire to identify probable domestic violence scenarios through a mathematical model whose key factor is the loss of control by the perpetrator. Based on the the results collected, a table of indicators and graphs have been generated which could be used by care centers and experts to help in their process at making decisions. [ABSTRACT FROM AUTHOR]

Objectives: Portal venous gas (PVG) was an important clinical sign in stage II or III necrotizing enterocolitis (NEC) in preterm neonates. Not a proper predictive indicator was found to predict the diseases (NEC with the presence of PVG) up to now. There is a need to put forward predictive indicators and compare the predictive effects among them.Methods: We conducted a retrospective study of preterm neonates with NEC-PVG (n = 61) or NEC-non PVG (n = 62) from 2014 to 2021. Predictive indicators were put forward and determined by receiver operating characteristic curve analysis. An analysis of the surgical interventions and their outcomes was performed.Results: The incidence rate of NEC among preterm neonates was 4.99%; surgical and conservative interventions accounted for 20.47 and 75.07%, and the mortality rate was 0.03%. The composition ratio of shock in the NEC-PVG group increased 13.2% (P = 0.029). C-reactive protein, fibrinogen degradation product, and blood glucose had better predictive effects in the predictive indicators (P < 0.05). Intestinal necrosis and subependymal hemorrhage in the outcomes of surgical interventions had a strong relationship with the presence of PVG in NEC II/III (P < 0.05).Conclusion: Early and reasonable use of antibiotics, improvement of coagulation function, rectification of acidosis, and decreased blood glucose could cut down the occurrence of the disease (NEC with the presence of PVG). Except for subependymal hemorrhage and intestinal necrosis, NEC with the presence of PVG did not increase the occurrence of other outcomes after surgery.

Objective: This study aimed to assess the clinical importance of various biomarkers, including NLR, CEA, CA199, CA125, CA153, and HE4, through dynamic testing to evaluate the effectiveness of neoadjuvant chemotherapy (NACT) for individuals facing advanced ovarian cancer. This provides valuable information for tailoring treatment plans to individual patients, thereby leading to a more personalized and effective management of individuals facing ovarian cancer., Methods: The levels of NLR, CA125, CA199, CEA, CA153, and HE4 were detected before chemotherapy and after 3 courses of chemotherapy. Patients were categorized into ineffective and effective groups according to the effectiveness of NACT. To evaluate the factors influencing NACT's effectiveness in individuals facing advanced ovarian cancer, receiver operating characteristic (ROC) curves, predictive modeling, and multifactorial regression analysis were employed., Results: In the effective group, the patients' age, maximum tumor diameter, and CEA and HE4 levels of the patients were significantly higher compared to those in the ineffective group ( P <.05). Additionally, the difference in HE4 levels before and after treatment between the effective and ineffective groups was statistically significant ( P <.05). Multifactorial analysis showed that age and maximum tumor diameter were independent risk factors impacting the effectiveness of NACT in individuals facing advanced ovarian cancer ( P <.05). The ROC curve for predicting the effectiveness of NACT in individuals facing advanced ovarian cancer showed a sensitivity of 93.3% for NLR and a specificity of 92.3% for CA199. HE4 emerged as the most reliable predictor, demonstrating a specificity of 84.6% and a sensitivity of 75.3%. The area under the curve of the combined CA125 and HE4 assays for predicting the ineffectiveness of NACT in individuals facing advanced ovarian cancer was 0.825, showcasing a specificity of 74.2% and a sensitivity of 84.6%., Conclusion: The predictive capacity for the effectiveness of NACT in individuals facing advanced ovarian cancer is notably high when considering the sensitivity of NLR and the specificity of CA199. Additionally, the combination of CA125 and HE4 assays can obtain a better predictive effect, which can accurately select patients suitable for NACT, determine the appropriate timing of the interval debulking surgery (IDS) surgery, and achieve a satisfactory tumor reduction effect., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Huang, Du, Chen, Luo, Wang, Li, Li and Yu.)

Technology emergence has become a hot topic in R&D policy and management communities. Various methods of measuring technology emergence have been developed. However, there is little literature discussing how to evaluate the results identified by different methods. This research sharpens a promising Technology Emergence Indicator (TEI) set by assessing alternative formulations on three distinct datasets: Dye-Sensitized Solar Cells, Non-Linear Programming, and Nano-Enabled Drug Delivery. Our TEIs derive from a conceptual foundation including three attributes of emergence: persistence, community, and growth that we systematically address through a 3-dimensional evaluation framework. Comparing TEI behavior through sensitivity analyses shows good robustness for the measures. The TEI serve to distinguish emerging R&D topics in the field under study. They can further be used to identify highly active players publishing on those topics. Importantly, results show that identified emerging terms and topics persist to a strong degree; thus, they serve to predict highly active R&D foci within the technical domain under study. [ABSTRACT FROM AUTHOR]

Objective Predictive scores were developed in adults to identify patients at risk for traumatic hemorrhage but have not been studied in children. Our objective was to identify clinical predictors of massive transfusion (≥40 ml/kg red blood cells or ≥80 ml/kg total blood product at 24 h) in injured children. Methods We conducted a retrospective case–control study of children <18 years old who presented from 2005 to 2014 for trauma care. Cases were children who received massive transfusion. Two control groups were identified: (1) ‘random’ and (2) matched for age and injury severity score (matched). Variables included vital signs, injury mechanism, active bleeding, and laboratory values. Multivariate logistic regression models to predict massive transfusion were developed using only clinical findings (‘pre-arrival’ model) and then also including laboratory values (emergency department model). Results Of 11,995 injured children, 44 received massive transfusion. We selected 132 random and 127 matched controls. Using random controls, the pre-arrival model included heart rate, Glasgow Coma Scale, temperature, and penetrating injury mechanism (AUC = 0.965). With matched controls, the pre-arrival model included Glasgow Coma Scale, penetrating injury, and active bleeding resulted (AUC = 0.812). The ED model using random controls included Glasgow Coma Scale, hemoglobin, and penetrating injury (AUC = 0.987). The emergency department model using matched controls included hemoglobin, temperature, prolonged partial thromboplastin time, and active bleeding on arrival (AUC = 0.734). Conclusions We identified predictive models for children who receive massive transfusion that rely on only clinical findings pre-arrival to the emergency department and then incorporate laboratory tests for those in the emergency department. [ABSTRACT FROM AUTHOR]

Soil properties are thought to affect annual plant productivity in rangelands, and thus soil variables that are consistently correlated with plant biomass may be general indicators of rangeland health. Here we measured several soil properties (e.g. aggregate stability, organic carbon, total nitrogen) and tested each as a would-be predictor of local variation in peak aboveground grassland biomass. Individual properties explained a slight (≤10%) amount of variation in plant biomass. Plant biomass was mainly (negatively) associated with two soil properties, subsurface soil carbonate concentration and the stability of soil macroaggregates near the soil surface. Less important predictive variables included: elevation, plant community composition, surface soil organic carbon, and soil carbon:nitrogen. Plot-to-plot variation in plant biomass is seemingly difficult to predict based on soil properties, including popular indicators of soil and rangeland health and even root biomass. While protection of soil is critical to overall rangeland ecosystem function, our findings suggest that the relationship between soil properties and plant biomass in natural grasslands is complex. Thus, there may not be one or even several soil properties that consistently predict appreciable variation in peak grassland biomass, especially variation within an ecosystem independent of precipitation. [ABSTRACT FROM AUTHOR]

Introduction: Clinical manifestations of influenza range from relatively mild and self-limiting respiratory infections to severe clinical manifestations with significant morbidity and mortality. The awareness of predictive indicators for the lethal outcome of influenza is of particular significance in making timely and exact decision for adequate treatment. The aim of this study was to identify the factors in patients with a severe form of influenza, resulting in lethal outcome. Materials and methods: The investigation was a prospective group comparison conducted at the University Clinic for Infectious Diseases in Skopje, R. Macedonia in the period from January 01, 2012 to January 01, 2015. The study included adult patients with a severe form of influenza who were further categorized into a group of either survived patients or a group of deceased patients. Demographic, clinical and biochemical data were noted in all patients included in the study on admission. The variables of the univariate analysis that showed a significant difference in terms of the outcome were used for creating multivariate logistic and regression analysis of the outcome as dependent factors. The independent predictors for lethal outcome in severe cases of influenza were identified by using logistic regression. Results: The study included 87 patients with a severe form of clinical and laboratory confirmed influenza. The patients were divided in two groups: survived (n = 75) and deceased (n = 75). The overall mortality was 13.79%. Multivariate analysis conducted on admission to hospital identified cardiovascular comorbid diseases (p = 0.014), urea values higher than 8.3 U/L (p = 0.045) and SAPS score (p = 0.048) as independent predictors of the outcome in patients with severe form of influenza. Influenza patients with cardiovascular diseases had 2.024 times greater risk of death from influenza in comparison to the patients having influenza without history of such a disease (OR = 2.024 95% CI 1.842-17.337). Patients with serum urea values higher than 8.3 U/L had 1.89 times higher chance of death compared to patients with normal values (OR = 1.89 95% CI 1.091-11.432). The increase of the SAPS score in one point increased the chance of death in patients with influenza by 1.2% (OR = 1.12 95% CI 1.01-2.976). The ROC analysis indicated that cardiovascular diseases, increased urea values and SAPS score in combination act as a good prognostic model for the fatal outcome. The global authenticity of this predictive model to foresee lethal outcome amounts to 80%, sensitivity being 82%, and specificity 70%. Conclusion: Cardiovascular diseases, increased values of urea over 8.3 mmol/l and SAPS score are independent predictive indicators for lethal outcome in severe influenza. Early identification of the outcome predictors in patients with severe influenza will allow implementation of adequate medical treatment and will contribute to decreasing of mortality in patients with severe form of influenza. [ABSTRACT FROM AUTHOR]

This paper is an abstract of the dissertation Profitability of a library using social media and highlights research carried out in order to demonstrate the profitability of libraries that make use of social media both to offer products and services to the users in line with their expectations and needs and to deliver different types of ROI. A set of social media indicators to measure the evolution and results has also been established. [ABSTRACT FROM AUTHOR]

Real-time hybrid simulation (RTHS) is gaining acceptance as an efficient and cost-effective method for realistic structural evaluation. Advances in real-time computing and control methods have enabled research in the development of this novel methodology to progress rapidly. However, to explore effectiveness and accuracy, and thus build broader confidence in the use of this method as an alternative to shake table testing, there is a need to better understand and address the key features that determine the success of an RTHS. Here we discuss the design and analysis of a SDOF RTHS case study conducted in Purdue University’s Intelligent Infrastructure Systems Lab (IISL). We examine the key factors that determine the success, through configuration of the test using predictive indicators, design of an appropriately effective actuator controller, and a thorough comparison with shake table testing. The reference structure chosen for this case study is a single story, moment resisting frame structure. This particular specimen is of lab scale and well-known component properties, making it a suitable choice for such an investigation. However, noise, control–structure interaction and damping introduce numerous challenges typically faced in establishing an effective RTHS configuration. We investigate two key issues that lead to the design of a successful RTHS, specifically the partitioning between numerical and physical substructure for stability and performance, and the actuator motion control algorithm. Predictive indicators are demonstrated to be particularly helpful for properly configuring an RTHS experiment to meet a researcher’s specified objectives. Furthermore a direct comparison is conducted to examine the ability of RTHS to replicate a shake table test. The results demonstrate that with proper partitioning and actuator control design, successful RTHS can be implemented despite unfavorable transfer system properties. [ABSTRACT FROM AUTHOR]

• Established correlations of thematic identifiers within a sample of home studies. • Identification of indicators could help to reduce subjective decision making. • Potential to reduce the amount of time and resources used to complete home studies. • Potential methods to ensure applicants are being assessed and treated similarly. A mixed method correlational exploratory pilot was conducted in Washington State to determine items within the home study assessment that could be used as indicators to identify baseline requirements of the assessment and suggest anticipated depth (expansion or reduction) within the required topic(s). The purpose of the home study is to assess the caregiver(s)' ability to provide a safe home, the quality of care needed by children and an environment that is nurturing, respectful and supportive. The goal of this study is to identify predicative indicators that will assist in the development of a home study that will increase consistency within home studies and decrease timeliness of completion. The use of predictive indicators may have the potential to reduce subjective decision making as well as identify inconsistencies when determining the recommendation of approval or denial of a home study. Additionally, with a carefully designed home study system inclusive of predictive analytics, it is possible to reduce the amount of time an assessor uses to approve or deny a home study, saving agency time and resources. Finally, by using focused technical assistance with those applicants who need more or specific support, the use of predictive indicators may increase the success of timely placement and permanency goals. This mixed method study included a case review of 207 home studies where 19 primary and secondary themes emerged as significant. It lays the ground work for methods used to identify predictive elements within the assessment process. Preliminary results are provided along with further recommendations. [ABSTRACT FROM AUTHOR]

Objectives: Portal venous gas (PVG) was an important clinical sign in stage II or III necrotizing enterocolitis (NEC) in preterm neonates. Not a proper predictive indicator was found to predict the diseases (NEC with the presence of PVG) up to now. There is a need to put forward predictive indicators and compare the predictive effects among them. Methods: We conducted a retrospective study of preterm neonates with NEC-PVG ( n = 61) or NEC-non PVG ( n = 62) from 2014 to 2021. Predictive indicators were put forward and determined by receiver operating characteristic curve analysis. An analysis of the surgical interventions and their outcomes was performed. Results: The incidence rate of NEC among preterm neonates was 4.99%; surgical and conservative interventions accounted for 20.47 and 75.07%, and the mortality rate was 0.03%. The composition ratio of shock in the NEC-PVG group increased 13.2% ( P = 0.029). C-reactive protein, fibrinogen degradation product, and blood glucose had better predictive effects in the predictive indicators ( P < 0.05). Intestinal necrosis and subependymal hemorrhage in the outcomes of surgical interventions had a strong relationship with the presence of PVG in NEC II/III ( P < 0.05). Conclusion: Early and reasonable use of antibiotics, improvement of coagulation function, rectification of acidosis, and decreased blood glucose could cut down the occurrence of the disease (NEC with the presence of PVG). Except for subependymal hemorrhage and intestinal necrosis, NEC with the presence of PVG did not increase the occurrence of other outcomes after surgery., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Lin, Zeng, Fang, Lin and Yang.)

Objective: To query the literature for predictive factors for performance on arthroscopic and laparoscopic surgical simulators in novice surgical trainees. These predictive factors may prove a valuable tool in identifying certain innate potential to becoming a future skilled surgeon that could benefit both surgical residency candidates and program directors alike, while also improving patient care., Design: Systematic Review., Results: The initial searches yielded 249 articles. After screening titles/abstracts and implementing inclusion and exclusion criteria, 36 studies were included in the final systematic review., Conclusions: Current literature suggests that video game experience/frequency, psychomotor and visuospatial aptitude, and perceptual ability are among the most promising predictive indicators of baseline simulator performance. Study limitations include utilization of different standards for characterizing predictive factors. Future studies should aim to utilize standard guidelines for accurate quantification of innate predictive factors. Future research should also focus on utilizing standardized simulator platforms and aptitude tests to allow for more accurate cross-study comparisons and meta-analyses with larger sample sizes., (Copyright © 2020 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.)