Factors affecting the survival of prediabetic patients: comparison of Cox proportional hazards model and random survival forest method.

BACKGROUND: The worldwide prevalence of type 2 diabetes mellitus in adults is experiencing a rapid increase. This study aimed to identify the factors affecting the survival of prediabetic patients using a comparison of the Cox proportional hazards model (CPH) and the Random survival forest (RSF). METHOD: This prospective cohort study was performed on 746 prediabetics in southwest Iran. The demographic, lifestyle, and clinical data of the participants were recorded. The CPH and RSF models were used to determine the patients' survival. Furthermore, the concordance index (C-index) and time-dependent receiver operating characteristic (ROC) curve were employed to compare the performance of the Cox proportional hazards (CPH) model and the random survival forest (RSF) model. RESULTS: The 5-year cumulative T2DM incidence was 12.73%. Based on the results of the CPH model, NAFLD (HR = 1.74, 95% CI: 1.06, 2.85), FBS (HR = 1.008, 95% CI: 1.005, 1.012) and increased abdominal fat (HR = 1.02, 95% CI: 1.01, 1.04) were directly associated with diabetes occurrence in prediabetic patients. The RSF model suggests that factors including FBS, waist circumference, depression, NAFLD, afternoon sleep, and female gender are the most important variables that predict diabetes. The C-index indicated that the RSF model has a higher percentage of agreement than the CPH model, and in the weighted Brier Score index, the RSF model had less error than the Kaplan-Meier and CPH model. CONCLUSION: Our findings show that the incidence of diabetes was alarmingly high in Iran. The results suggested that several demographic and clinical factors are associated with diabetes occurrence in prediabetic patients. The high-risk population needs special measures for screening and care programs.

Association between changes in high-density lipoprotein cholesterol and risk of cardiovascular disease.

BACKGROUND: The present study was performed to determine the association between changes in the HDL-C concentration and incident CVD. METHODS: Time-dependent Cox regression models were used to evaluate the association between changes in the HDL-C concentration and the risk of incident CVD. Participants were followed up from 2015 to 2021. RESULTS: In total, 24,123 participants with a median follow-up of 4.26 years were analyzed, and the mean age of the cohort was 56.24 years, 57.8 % were female, 24.3 % were current smokers, and 12.8 % had a history of alcohol use. Low, normal, and high HDL-C was defined as <40, 40-80, and >80 mg/dL, respectively. The average time for the two HDL-C measurements was 2.8 years,compared with participants whose HDL-C was maintained at a normal level, the risk of CVD was higher in those whose HDL-C changed to a low level, remained unchanged at a low level(HR, 1.24; 95 % CI, 1.01-1.40,P < 0.001), similarly, the risk of CVD was higher in those whose HDL-C changed from very high level to normal level(HR, 0.81; 95 % CI, 0.67-0.99,P = 0.039). Also compared with participants whose HDL-C was maintained at a normal level, the risk of CVD was lower in those whose HDL-C increased from low to normal and high(HR, 0.80; 95 % CI, 0.66-0.98,P = 0.029). CONCLUSIONS: Participants whose HDL-C changed to a low level and whose low HDL-C level was maintained had a higher risk of CVD, whereas participants whose HDL-C changed from low to high had a lower risk of CVD.

Joint modeling of longitudinal and competing risks for assessing blood oxygen saturation and its association with survival outcomes in COVID-19 patients.

BACKGROUND: The objective of the present study is to evaluate the association between longitudinal and survival outcomes in the presence of competing risk events. To illustrate the application of joint modeling in clinical research, we assessed the blood oxygen saturation (SPO2) and its association with survival outcomes in coronavirus disease (COVID-19). MATERIALS AND METHODS: In this prospective cohort study, we followed 300 COVID-19 patients, who were diagnosed with severe COVID-19 in the Rohani Hospital in Babol, the north of Iran from October 22, 2020 to March 5, 2021, where death was the event of interest, surviving was the competing risk event and SPO2 was the longitudinal outcome. Joint modeling analyses were compared to separate analyses for these data. RESULT: The estimation of the association parameter in the joint modeling verified the association between longitudinal outcome SPO2 with survival outcome of death (Hazard Ratio (HR) = 0.33, P = 0.001) and the competing risk outcome of surviving (HR = 4.18, P < 0.001). Based on the joint modeling, longitudinal outcome (SPO2) decreased in hypertension patients (ß = -0.28, P = 0.581) and increased in those with a high level of SPO2 on admission (ß = 0.75, P = 0.03). Also, in the survival submodel in the joint model, the risk of death survival outcome increased in patients with diabetes comorbidity (HR = 4.38, P = 0.026). CONCLUSION: The association between longitudinal measurements of SPO2 and survival outcomes of COVID-19 confirms that SPO2 is an important indicator in this disease. Thus, the application of this joint model can provide useful clinical evidence in the different areas of medical sciences.

Enhancing pneumonia prognosis in the emergency department: a novel machine learning approach using complete blood count and differential leukocyte count combined with CURB-65 score.

BACKGROUND: Pneumonia poses a major global health challenge, necessitating accurate severity assessment tools. However, conventional scoring systems such as CURB-65 have inherent limitations. Machine learning (ML) offers a promising approach for prediction. We previously introduced the Blood Culture Prediction Index (BCPI) model, leveraging solely on complete blood count (CBC) and differential leukocyte count (DC), demonstrating its effectiveness in predicting bacteremia. Nevertheless, its potential in assessing pneumonia remains unexplored. Therefore, this study aims to compare the effectiveness of BCPI and CURB-65 in assessing pneumonia severity in an emergency department (ED) setting and develop an integrated ML model to enhance efficiency. METHODS: This retrospective study was conducted at a 3400-bed tertiary medical center in Taiwan. Data from 9,352 patients with pneumonia in the ED between 2019 and 2021 were analyzed in this study. We utilized the BCPI model, which was trained on CBC/DC data, and computed CURB-65 scores for each patient to compare their prognosis prediction capabilities. Subsequently, we developed a novel Cox regression model to predict in-hospital mortality, integrating the BCPI model and CURB-65 scores, aiming to assess whether this integration enhances predictive performance. RESULTS: The predictive performance of the BCPI model and CURB-65 score for the 30-day mortality rate in ED patients and the in-hospital mortality rate among admitted patients was comparable across all risk categories. However, the Cox regression model demonstrated an improved area under the ROC curve (AUC) of 0.713 than that of CURB-65 (0.668) for in-hospital mortality (p<0.001). In the lowest risk group (CURB-65=0), the Cox regression model outperformed CURB-65, with a significantly lower mortality rate (2.9% vs. 7.7%, p<0.001). CONCLUSIONS: The BCPI model, constructed using CBC/DC data and ML techniques, performs comparably to the widely utilized CURB-65 in predicting outcomes for patients with pneumonia in the ED. Furthermore, by integrating the CURB-65 score and BCPI model into a Cox regression model, we demonstrated improved prediction capabilities, particularly for low-risk patients. Given its simple parameters and easy training process, the Cox regression model may be a more effective prediction tool for classifying patients with pneumonia in the emergency room.

Evaluating nomogram models for predicting survival outcomes in gastric gastrointestinal stromal tumors with SEER database analysis.

Gastrointestinal stromal tumors (GISTs) predominantly develop in the stomach. While nomogram offer tremendous therapeutic promise, there is yet no ideal nomogram comparison customized specifically for handling categorical data and model selection related gastric GISTs. (1) We selected 5463 patients with gastric GISTs from the SEER Research Plus database spanning from 2000 to 2020; (2) We proposed an advanced missing data imputation algorithm specifically designed for categorical variables; (3) We constructed five Cox nomogram models, each employing distinct methods for the selection and modeling of categorical variables, including Cox (Two-Stage), Lasso-Cox, Ridge-Cox, Elastic Net-Cox, and Cox With Lasso; (4) We conducted a comprehensive comparison of both overall survival (OS) and cancer-specific survival (CSS) tasks at six different time points; (5) To ensure robustness, we performed 50 randomized splits for each task, maintaining a 7:3 ratio between the training and test cohorts with no discernible statistical differences. Among the five models, the Cox (Two-Stage) nomogram contains the fewest features. Notably, at Near-term, Mid-term, and Long-term intervals, the Cox (Two-Stage) model attains the highest Area Under the Curve (AUC), top-1 ratio, and top-3 ratio in both OS and CSS tasks. For the prediction of survival in patients with gastric GISTs, the Cox (Two-Stage) nomogram stands as a simple, stable, and accurate predictive model with substantial promise for clinical application. To enhance the clinical utility and accessibility of our findings, we have deployed the nomogram model online, allowing healthcare professionals and researchers worldwide to access and utilize this predictive tool.

Effect of Novel Inflammatory Biomarkers on Adverse Outcomes in Patients with Interstitial Lung Disease and Pneumonia: A Multicenter Retrospective Cohort Study.

BACKGROUND: Interstitial lung disease frequently coincides with pneumonia in clinical settings, and both conditions are closely associated with immunoinflammation. The Systemic Immune Inflammatory Index (SII) is a recently identified marker, and its connection to the prognosis of individuals suffering from interstitial lung disease and concurrent pneumonia remains unclear. The objective of this study was to scrutinize the correlation between varying SII levels and unfavorable outcomes in patients grappling with interstitial lung disease complicated by pneumonia. METHODS: This study encompassed a retrospective multicenter cohort of 324 patients diagnosed with interstitial lung disease and pneumonia, all receiving glucocorticoid treatment during their hospitalization. We initially conducted ROC analysis to determine the optimal SII threshold. Subsequently, we examined disparities in clinical symptoms, physical signs, clinical test data, and other clinical attributes among patients with differing SII levels. Later, we employed the Kaplan-Meier survival curve method to assess the association between distinct SII levels and the 30-day and 90-day mortality rates in patients dealing with interstitial lung disease complicated by pneumonia. Finally, a Cox regression model was employed to identify factors influencing adverse prognosis in these patients. RESULTS AND DISCUSSION: The findings demonstrated that the optimal SII threshold for predicting 30-day mortality was 1416.97, with an AUC of 0.633 (95% CI: 0.559-0.708) and a P value of <0.001. For 90-day mortality, the optimal SII threshold was 994.59, yielding an AUC of 0.628 (95% CI: 0.56-0.697) and a P value of <0.001. Noteworthy statistical distinctions emerged in dyspnea, cyanosis, and oxygenation index among patients with varying SII levels. Additionally, invasive mechanical ventilation, non-invasive ventilation, and extended infection duration independently constituted 30-day and 90-day mortality risk factors. Elevated heart rate and higher SII levels emerged as independent risk factors for 90-day mortality. CONCLUSION: To some extent, SII levels exhibit correlations with the clinical manifestations in patients grappling with interstitial lung disease complicated by pneumonia. Notably, a high SII level is an independent predictor for an unfavorable prognosis in these patients. Nevertheless, these findings warrant further validation through prospective cohort studies.

Survival Analysis of Risk Factors for Mortality of Patients with Cardiovascular Diseases at Tikur Anbessa Specialized Tertiary Referral Hospital, Ethiopia: A Retrospective.

Background: Cardiovascular diseases (CVD) represent a leading cause of global mortality, necessitating proactive identification of risk factors for preventive strategies. This study aimed to uncover prognostic factors influencing cardiovascular patient survival. Methods: This study, which used a sample size of 410, showed how to analyze data using simple random sampling. It was conducted at the Tikur Anbessa Specialist Hospital in Addis Ababa, Ethiopia, between September 2012 and April 2016. The Cox PH and stratified Cox regression models were used for the analysis. Results: Findings disclosed a patient cohort where 200 patients (48.8%) persisted through subsequent evaluation, while 210 patients (51.2%) succumbed. Blood pressure (BP), specific CVD, and education levels (EL) exhibited nonproportionalities in scaled Schoenfeld residuals (P < 0.001), prompting necessary stratification. Inadequacies in the Cox proportional hazards model led to favoring the stratified Cox model. Notably, EL, BP, cholesterol level (CL), alcohol use (AU), smoking use (SU), and pulse rate (PR) exhibited statistical significance (P < 0.001). Acceptability of the absence of interaction in the model, with disease types as strata, was established. Different cardiovascular conditions served as distinct groups, where EL, AU, BP, PR, CL, and SU emerged as variables with statistically substantiated significance associated with the mortality of patients with CVD. Conclusion: Implications stress the imperative of widespread awareness among policymakers and the public concerning cardiovascular disease incidence. Such awareness is pivotal in mitigating identified risk factors, guiding more effective healthcare interventions tailored to the multifaceted challenges posed by cardiovascular health.

Effect of marital status on the survival outcomes of cervical cancer: a retrospective cohort study based on SEER database.

BACKGROUND: Cervical cancer is the fourth most common malignant tumor troubling women worldwide. Whether marital status affects the prognosis of cervical cancer is still unclear. Here, we investigate the prognostic value of marital status in patients with cervical cancer based on the seer database. MATERIAL/METHODS: The demographic and clinical data of patients with cervical cancer were extracted from the Surveillance, Epidemiology, and End Results (SEER) database from 1975 to 2017. Patients were divided into two groups (married and unmarried) according to marital status, and then the clinical characteristics of each group were compared using the chi-square test. Propensity score matching (PSM) was used to reduce differences in baseline characteristics. The overall survival (OS) and cervical cancer-specific survival (CCSS) were assessed by the Kaplan-Meier method, univariate and multivariate Cox regression models, and stratified analysis. Moreover, univariate and multivariate competing risk regression models were performed to calculate hazard ratios (HR) of death risk. RESULTS: A total of 21,148 patients were included in this study, including 10,603 married patients and 10,545 unmarried patients. Married patients had better OS(P < 0.05) and CCSS (P < 0.05) compared to unmarried patients, and marital status was an independent prognostic factor for both OS (HR: 0.830, 95% CI: 0.798-0.862) and CCSS (HR: 0.892, 95% CI: 0.850-0.937). Moreover, after eliminating the competing risk, married patients (CCSD: HR:0.723, 95% CI: 0.683-0.765, P < 0.001) had a significantly decreased risk of death compared to unmarried patients. In stratified analysis, the married patients showed better OS and CCSS than the unmarried patients diagnosed in 1975-2000 and 2001-2017. CONCLUSIONS: Being married was associated with a favorable prognosis of cervical cancer, and marital status was an independent prognostic factor for cervical cancer.

Magnetocardiography at rest predicts cardiac death in patients with acute chest pain.

Introduction: Sudden cardiac arrest is a major cause of morbidity and mortality worldwide and remains a major public health problem for which better non-invasive prediction tools are needed. Primary preventive therapies, such as implantable cardioverter defibrillators, are not personalized and not predictive. Most of these devices do not deliver life-saving therapy during their lifetime. The individual relationship between fatal arrhythmias and cardiac function abnormalities in predicting cardiac death risk has rarely been explored. Methods: We retrospectively analyzed the measurements at rest for 191 patients with acute chest pain (ACP) magnetocardiographically. Our recently introduced analyses are able to detect inhomogeneities of the depolarization and repolarization. Moreover, electrically silent phenomena-intracellular ionic currents as well as vortex currents-can be measured and quantified. All included ACP patients were recruited in 2009 at Yonsei University Hospital and were followed up until 2022. Results: During half of the follow-up period (6.5 years), 11 patients died. Out of all the included nine clinical, eight magnetocardiographical, and nine newly introduced magnetoionographical parameters we tested in this study, three parameters revealed themselves to be outstanding at predicting death: heart rate-corrected QT (QTc) prolongation, depression of repolarization current IKr + IKs, and serum creatinine (all significant in Cox regression, p < 0.05). They clearly predicted cardiac death over the 6.5 years duration (sensitivity 90.9%, specificity 85.6%, negative predictive accuracy 99.4%). Cardiac death risk was more than ninefold higher in patients with low repolarization reserve and QTc prolongation in comparison with the remaining patients with ACP (p < 0.001). The non-parametric Kaplan-Meier statistics estimated significantly lower survival functions from their lifetime data (p < 0.001). Discussion: To the best of our knowledge, these are the first data linking magnetocardiographical and magnetoionographical parameters and subsequent significant fatal events in people, suggesting structural and functional components to clinical life-threatening ventricular arrhythmogenesis. The findings support investigation of new prevention strategies and herald those new non-invasive techniques as complementary risk stratification tools.

Seven oxidative stress-related genes predict the prognosis of hepatocellular carcinoma.

Predicting the prognosis of hepatocellular carcinoma (HCC) is a major medical challenge and of guiding significance for treatment. This study explored the actual relevance of RNA expression in predicting HCC prognosis. Cox's multiple regression was used to establish a risk score staging classification and to predict the HCC patients' prognosis on the basis of data in the Cancer Genome Atlas (TCGA). We screened seven gene biomarkers related to the prognosis of HCC from the perspective of oxidative stress, including Alpha-Enolase 1(ENO1), N-myc downstream-regulated gene 1 (NDRG1), nucleophosmin (NPM1), metallothionein-3, H2A histone family member X, Thioredoxin reductase 1 (TXNRD1) and interleukin 33 (IL-33). Among them we measured the expression of ENO1, NGDP1, NPM1, TXNRD1 and IL-33 to investigate the reliability of the multi-index prediction. The first four markers' expressions increased successively in the paracellular tissues, the hepatocellular carcinoma samples (from patients with better prognosis) and the hepatocellular carcinoma samples (from patients with poor prognosis), while IL-33 showed the opposite trend. The seven genes increased the sensitivity and specificity of the predictive model, resulting in a significant increase in overall confidence. Compared with the patients with higher-risk scores, the survival rates with lower-risk scores are significantly increased. Risk score is more accurate in predicting the prognosis HCC patients than other clinical factors. In conclusion, we use the Cox regression model to identify seven oxidative stress-related genes, investigate the reliability of the multi-index prediction, and develop a risk staging model for predicting the prognosis of HCC patients and guiding precise treatment strategy.

A practical recurrence risk model based on Lasso-Cox regression for gastric cancer.

INTRODUCTION: Gastric cancer remains huge cancer threat worldwide. Detecting the recurrence of gastric cancer after treatment is especially important in improving the prognosis of patients. We aim to fit different risk models with different clinical variables for patients with gastric cancer, which further provides applicable guidance to clinical doctors for their patients. METHODS: We collected the primary data from the medical record system in Lanzhou University Second Hospital and further cleaned the primary data via assessing data integrity artificially; meanwhile, detailed conclusion criteria and exclusion criteria were made. We used R software (version 4.1.3) and SPSS 25.0 to analyze data and build models, in which SPSS was used to analyze the correlation and difference of different items in the training set and testing set, and different R packages were used to run LASSO regression, Cox regression and nomogram for variable selection, model construction and model validation. RESULT: A total of 649 patients were included in our data analysis and model building. In LASSO regression selection, seven variables, pathological stage, tumor size, the number of total lymph nodes, the number of metastatic lymph nodes, intraoperative blood loss (IBL), the level of AFP and CA199, showed their correlation to the dependent variable. The multivariable Cox regression model fitted using these seven variables showed medium prediction ability, with an AUC of 0.840 in the training set and 0.756 in the testing set. CONCLUSIONS: Pathological stage, tumor size, the number of total lymph nodes, the number of metastatic lymph nodes, IBL, the level of AFP and CA199 are significant in identifying recurrence risk for gastric cancer patients after radical gastrectomy.

Survival times of HIV/AIDS in different AIDS Diagnostic and Treatment Guidelines from 2006 to 2020 in Liuzhou, China.

BACKGROUND: To compare the survival rates of four timing of treatment initiation for people living with HIV/AIDS provided in China in 2006, 2011, 2015, and 2018, and to investigate the factors impacting survival time. METHODS: A people living with HIV/AIDS retrospective cohort study was in Liuzhou City from April 2006 to December 2020. The information was obtained from the National Comprehensive AIDS Prevention and Control Information System. Life tables and the Kaplan-Meier method were used to calculate participant survival rates and time. The univariate and multivariate Cox regression models were used to investigate the factors related to survival. RESULTS: 18,543 participants were included in this study. In four periods, the 1-year survival rates were 81%, 87%, 95%, and 95%. The 2-year survival rates were 76%, 85%, 93%, and 94%. The 3-year survival rates were 73%, 84%, 92%, and 94%. Results of multivariate Cox regression showed that sex, age of HIV diagnosis, ethnicity, household registration, occupation, marital status, the timing of treatment, education level, route of HIV transmission, whether receiving antiretroviral therapy (ART), and the count of CD4+T cells at baseline (count of CD4+T cells at HIV diagnosis) were factors that are significantly correlated with mortality caused by HIV infection. CONCLUSIONS: With the Guidelines updated from 2006 to 2020, the 1-, 2-, and 3-year survival rates of people living with HIV/AIDS in four periods tended to increase. The timing of treatment initiation of the updated edition of the AIDS Diagnostic and Treatment Guidelines (Guidelines) significantly prolonged the survival time of people living with HIV/AIDS.

Predictive value of triglycerides to high-density lipoprotein cholesterol and triglyceride glycemic index for diabetes incidence in pre-diabetes patients: a prospective cohort study.

BACKGROUND: The triglyceride glucose (TyG) and triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-c) are the indices that can predict the progression of pre-diabetes to type 2 diabetes mellitus (T2DM). This study aimed to examine the relationship between TyG and TG/HDL-c indices with the incidence of T2DM in pre-diabetes patients. METHODS: A total of 758 pre-diabetic patients aged 35-70 years who were enrolled in a prospective Fasa Persian Adult Cohort were followed up for 60 months. TyG and TG/HDL-C indices were obtained at baseline data and divided into quartiles. The 5-year cumulative incidence of T2DM was analyzed by Cox proportional hazards regression analysis while controlling for baseline covariates. RESULTS: During 5 years of follow-up, there were 95 incident cases of T2DM, with an overall incidence rate of 12.53%. After adjusting for age, sex, smoking, marital status, socioeconomic status, body mass index, waist circumference, hip circumference, hypertension, total cholesterol, and dyslipidemia, the multivariate-adjusted hazard ratios (HRs) demonstrated that patients with the highest TyG and TG/HDL-C indices quartile were at higher risk of T2DM (HR = 4.42, 95%CI 1.75-11.21) and (HR = 2.15, 95%CI 1.04-4.47), respectively, compared to participants in the lowest quartile. As the quantiles of these indices increase, the HR value shows a significant increment (P < 0.05). CONCLUSION: The results of our study showed that the TyG and TG/HDL-C indices can be important independent predictors for the progression of pre-diabetes to T2DM. Therefore, controlling the components of these indicators in pre-diabetes patients can prevent developing T2DM or delay its occurrence.

Influence of chronic diseases on the occurrence of depression: A 13-year follow-up study from the Survey of Health, Ageing and Retirement in Europe.

The causal association between chronic diseases and depression remains unclear. This study aimed to explore the effects of types and number of chronic diseases on the risk of depression using data from the Survey of Health, Ageing and Retirement in Europe (SHARE). A self-admitted questionnaire was used to obtain data on 14 predefined chronic diseases and the European-Depression Scale (EURO-D) was used to assess depression. Among the 16,080 baseline depression-free participants aged 50+, 31.29% (5032) developed depression over 13 years. Multivariate Cox regression models showed that individuals with any chronic diseases were at higher risk of new onset depression compared to disease-free participants. The risk of new onset depression increased with an increasing number of diseases among both younger (50-64) and older (65+) adults. Individuals with heart attack, stroke, diabetes, chronic lung disease, and arthritis were at increased risk of depression across age groups. However, some age-specific associations were observed, with cancer increasing depression risk among younger- and peptic ulcer, Parkinson's disease and cataracts increasing depression risk among older adults. These findings highlight the importance of managing chronic diseases, especially among those with more than two diseases, to prevent the development of depression among middle-aged and older adults.

Safety and feasibility of laparoscopic liver resection for intrahepatic cholangiocarcinoma: a propensity score-matched study.

BACKGROUND: Laparoscopic liver resection (LLR) is controversial in treating intrahepatic cholangiocarcinoma (ICC). Therefore, this study aimed to evaluate the safety and feasibility of LLR for the treatment of ICC and explored the independent factors affecting the long-term prognosis of ICC. METHODS: We included 170 patients undergoing hepatectomy for ICC from December 2010 to December 2021 and divided them into LLR group and open liver resection (OLR) group. We used propensity score matching (PSM) analysis to reduce the impact of data bias and confounding variables and then compared the short-term and long-term prognosis of LLR and OLR in treating ICC; Cox proportional hazards regression model was adopted to explore the independent factors affecting the long-term prognosis of ICC. RESULTS: A total of 105 patients (70 in the LLR group and 35 in the OLR group) were included after 2:1 PSM analysis. There was no difference in demographic characteristics and preoperative indexes between the two groups. The perioperative results of the OLR group were worse than those of the LLR group, that is, the intraoperative blood transfusion rate (24 (68.6) vs 21 (30.0)), blood loss (500 (200-1500) vs 200 (100-525)), and the morbidity of major postoperative complications (9 (25.7) vs 6 (8.5)) in the OLR group were worse than those in LLR group. LLR could enable patients to obtain an equivalent long-term prognosis compared to OLR. The Cox proportional hazards regression model exhibited that no matter before or after PSM, preoperative serum CA12-5 and postoperative hospital stay were independent factors affecting overall survival, while only lymph node metastasis independently influenced recurrence-free survival. CONCLUSIONS: Compared with ICC treated by OLR, the LLR group obtained superior perioperative period outcomes. In the long run, LLR could enable ICC patients to receive an equivalent long-term prognosis compared to OLR. In addition, ICC patients with preoperative abnormal CA12-5, lymph node metastasis, and more extended postoperative hospital stay might suffer from a worse long-term prognosis. However, these conclusions still need multicenter extensive sample prospective research to demonstrate.

Low Serum Vascular Endothelial Growth Factor Level Predicts Adverse Outcomes in Neonates with Respiratory Distress Syndrome.

Objective: Preterm neonates are susceptible to neonatal respiratory distress syndrome (NRDS). Lower levels of cord blood vascular endothelial growth factor (VEGF) are implicated in NRDS. This study aims to explore whether the serum VEGF level has prognostic values on neonates with respiratory distress syndrome (RDS). Methods: A total of 80 infants diagnosed with NRDS were enrolled, with 70 preterm neonates without NRDS as controls. Cord blood samples before treatment and venous blood samples after treatment were collected and clinical information was recorded. The serum VEGF level was measured using enzyme-linked immunosorbent assay kits. Receiver operating characteristic (ROC) curve was used to evaluate whether serum VEGF is a biomarker of NRDS. Newborns were followed up for 1 month to collect survival information. The influence of VEGF levels on overall survival was analyzed using the Kaplan-Meier method. The univariate and multivariate Cox regression models were adopted to assess the prognostic factor of NRDS. Results: VEGF level was decreased in sera of neonates with RDS. The area under the ROC curve of VEGF level in distinguishing neonates with RDS from neonates without RDS was 0.949, with a cutoff value of 39.72 (87.50% sensitivity, 87.14% specificity). Serum VEGF was a biomarker of NRDS. Neonates with RDS with high VEGF levels had longer periods of survival than those with low VEGF levels. NRDS grade and VEGF level were independent prognostic factors affecting the overall survival of neonates with RDS. Conclusion: Decreased serum VEGF level in RDS neonates can predict the poor prognosis of NRDS, and VEGF level might be an independent prognostic factor for the overall survival of RDS neonates. Clinical Trial Registration No. 201901A.

Development and validation of an [18F]FDG-PET/CT radiomic model for predicting progression-free survival for patients with stage II - III thoracic esophageal squamous cell carcinoma who are treated with definitive chemoradiotherapy.

BACKGROUND: Radiomics is a method for extracting a large amount of information from images and used to predict treatment outcomes, side effects and diagnosis. In this study, we developed and validated a radiomic model of [18F]FDG-PET/CT for predicting progression-free survival (PFS) of definitive chemoradiotherapy (dCRT) for patients with esophageal cancer. MATERIAL AND METHODS: Patients with stage II - III esophageal cancer who underwent [18F]FDG-PET/CT within 45 days before dCRT between 2005 and 2017 were included. Patients were randomly assigned to a training set (85 patients) and a validation set (45 patients). Radiomic parameters inside the area of standard uptake value ≥ 3 were calculated. The open-source software 3D slicer and Pyradiomics were used for segmentation and calculating radiomic parameters, respectively. Eight hundred sixty radiomic parameters and general information were investigated.In the training set, a radiomic model for PFS was made from the LASSO Cox regression model and Rad-score was calculated. In the validation set, the model was applied to Kaplan-Meier curves. The median value of Rad-score in the training set was used as a cutoff value in the validation set. JMP was used for statistical analysis. RStudio was used for the LASSO Cox regression model. p < 0.05 was defined as significant. RESULTS: The median follow-up periods were 21.9 months for all patients and 63.4 months for survivors. The 5-year PFS rate was 24.0%. In the training set, the LASSO Cox regression model selects 6 parameters and made a model. The low Rad-score group had significantly better PFS than that the high Rad-score group (p = 0.019). In the validation set, the low Rad-score group had significantly better PFS than that the high Rad-score group (p = 0.040). CONCLUSIONS: The [18F]FDG-PET/CT radiomic model could predict PFS for patients with esophageal cancer who received dCRT.

Thin highly cross-linked polyethylene liners combined with large femoral heads in primary total hip arthroplasty show excellent survival and low wear rates at a mean follow-up of 12.8 years.

AIMS: Several short- and mid-term studies have shown minimal liner wear of highly cross-linked polyethylene (HXLPE) in total hip arthroplasty (THA), but the safety of using thinner HXLPE liners to maximize femoral head size remains uncertain. The objective of this study was to analyze clinical survival and radiological wear rates of patients with HXLPE liners, a 36 mm femoral head, and a small acetabular component with a minimum of ten years' follow-up. METHODS: We retrospectively identified 55 patients who underwent primary THA performed at a single centre, using HXLPE liners with 36 mm cobalt-chrome heads in acetabular components with an outer diameter of 52 mm or smaller. Patient demographic details, implant details, death, and all-cause revisions were recorded. Cox regression and Kaplan-Meier survival was used to determine all-cause and liner-specific revision. Of these 55 patients, 22 had a minimum radiological follow-up of seven years and were assessed radiologically for linear and volumetric wear. RESULTS: Overall survival rate for all-cause revision was 94.5% (95% confidence interval (CI) 81.7% to 97.2%) at a mean follow-up of 12.8 years (10.9 to 18.7). Three patients were revised, none for liner wear, fracture, or dissociation. A total of 22 patients were included in the radiological analysis (mean follow-up 9.9 years (7.5 to 13.7)). Mean linear liner wear was 0.085 mm (95% CI -0.086 to 0.257) and the volumetric wear rate was 11.097 mm3/year (95% CI -6.5 to 28.7). CONCLUSION: Using HXLPE liners with 36 mm heads in 52 mm acetabular components or smaller is safe, with excellent survival and low rates of linear and volumetric wear at medium-term follow-up. Patients did not require revision surgery for liner complications such as fracture, dissociation, or wear. Our results suggest that the advantages of using larger heads outweigh the potential risks of using thin HXLPE liners.Cite this article: Bone Joint J 2023;105-B(1):29-34.

Correlation analysis and prognostic value of miR-29a-3p expression and CYP2C19 genotypes in exfoliated cells from tongue coating of patients with gastroesophageal reflux disease.

BACKGROUND: Gastroesophageal reflux disease (GERD) is a highly prevalent and troublesome disease. Several differentially expressed microRNAs (miRNAs) have been found in GERD. OBJECTIVE: This study was to analyze the correlation of miR-29a-3p expression and CYP2C19 genotypes in exfoliated cells from tongue coating of GERD patients and its prognostic value. METHODS: Tongue coating specimens were collected from 130 GERD patients and 70 healthy volunteers and their clinical baseline information was recorded. miR-29a-3p expression in exfoliated cells from tongue coating was determined via RT-qPCR, and its diagnostic efficiency on GERD was evaluated via receiver operating characteristic curve. CYP2C19 genotypes and their correlation with miR-29a-3p were analyzed via polymerase chain reaction restriction fragment length polymorphism technique. The adverse events of patients were documented via 12-month follow-up. The impact of miR-29a-3p expression on the healing rate of patients was analyzed via Kaplan-Meier method. Qualification of miR-29a-3p as an independent prognostic factor of GERD patients was analyzed via multivariate Cox regression analysis. RESULTS: miR-29a-3p was highly-expressed in exfoliated cells from tongue coating of GERD patients. miR-29a-3p expression had high specificity and sensitivity in diagnosing GERD. CYP2C19 genotypes in GERD patients comprised rapid metabolizers, intermedia metabolizers, and poor metabolizers. miR-29a-3p expression showed a correlation with CYP2C19 genotypes. Higher miR-29a-3p expression predicted higher cumulative incidences of adverse outcomes. Highly-expressed miR-29a-3p was an independent prognostic factor for adverse outcomes of GERD patients. CONCLUSION: High expression of miR-29a-3p aided the diagnosis and predicted poor prognosis of GERD patients.

Demographic Factors and Instantaneous Lower Extremity Injury Occurrence in a National Collegiate Athletic Association Division I Population.

CONTEXT: Temporal prediction of the lower extremity (LE) injury risk will benefit clinicians by allowing them to better leverage limited resources and target those athletes most at risk. OBJECTIVE: To characterize the instantaneous risk of LE injury by demographic factors of sex, sport, body mass index (BMI), and injury history. DESIGN: Descriptive epidemiologic study. SETTING: National Collegiate Athletic Association Division I athletic program. PATIENTS OR OTHER PARTICIPANTS: A total of 278 National Collegiate Athletic Association Division I varsity student-athletes (119 males, 159 females; age = 19.07 ± 1.21 years, height = 175.48 ± 11.06 cm, mass = 72.24 ± 12.87 kg). MAIN OUTCOME MEASURE(S): Injuries to the LE were tracked for 237 ± 235 consecutive days. Sex-stratified univariate Cox regression models were used to investigate the association between time to first LE injury and sport, BMI, and LE injury history. The instantaneous LE injury risk was defined as the injury risk at any given point in time after the baseline measurement. Relative risk ratios and Kaplan-Meier curves were generated. Variables identified in the univariate analysis were included in a multivariate Cox regression model. RESULTS: Female athletes displayed similar instantaneous LE injury risk to male athletes (hazard ratio [HR] = 1.29; 95% CI= 0.91, 1.83; P = .16). Overweight athletes (BMI >25 kg/m2) had similar instantaneous LE injury risk compared with athletes with a BMI of <25 kg/m2 (HR = 1.23; 95% CI = 0.84, 1.82; P = .29). Athletes with previous LE injuries were not more likely to sustain subsequent LE injury than athletes with no previous injury (HR = 1.09; 95% CI = 0.76, 1.54; P = .64). Basketball (HR = 3.12; 95% CI = 1.51, 6.44; P = .002) and soccer (HR = 2.78; 95% CI = 1.46, 5.31; P = .002) athletes had a higher risk of LE injury than cross-country athletes. In the multivariate model, instantaneous LE injury risk was greater in female than in male athletes (HR = 1.55; 95% CI = 1.00, 2.39; P = .05), and it was greater in male athletes with a BMI of >25 kg/m2 than that in all other athletes (HR = 0.44; 95% CI = 0.19, 1.00; P = .05), but these findings were not significantly different. CONCLUSIONS: In a collegiate athlete population, previous LE injury was not a contributor to the risk of future LE injury, whereas being female or being male with a BMI of >25 kg/m2 resulted in an increased risk of LE injury. Clinicians can use these data to extrapolate the LE injury risk occurrence to specific populations.