Competing risk analysis of cardiovascular death in patients with primary gallbladder cancer.

BACKGROUND: Developments in medical technology are resulting in continuous decreases in the cancer mortality rate of patients with gallbladder cancer, while non-cancer deaths in cancer patients are becoming more common. The main cause of this is cardiovascular mortality (CVM). The purpose of this study was to determine the CVM risk in patients with primary gallbladder cancer (PGC). METHODS: We extracted information on patients in the SEER database who were diagnosed with PGC from 2004 to 2015, compared CVM in patients with PGC with the general United States population, and calculated standardized mortality rates (SMRs) and the absolute excess risk. A competing risks model was used to identify and analyze the independent risk factors for cardiovascular death in patients with PGC. RESULTS: This study included 5925 patients, 247 of whom died from cardiovascular disease. The SMR of cardiovascular death in patients with PGC was 15.84 (95% confidence interval: 15.83-15.85), and the SMR was slightly lower in male than female patients. The competing risks analysis indicated that age, marital status, cancer cell differentiation, chemotherapy status, and year of diagnosis were risk factors for cardiovascular death in patients with PGC. CONCLUSIONS: The CVM risk is considerably higher in patients with PGC than in the general population. It is therefore very necessary to apply cardioprotective interventions to patients with PGC.

Associations of HDL-C/LDL-C with myocardial infarction, all-cause mortality, haemorrhagic stroke and ischaemic stroke: a longitudinal study based on 384 093 participants from the UK Biobank.

OBJECTIVE: To explore the correlations of high-density lipoprotein cholesterol (HDL-C)/low-density lipoprotein cholesterol (LDL-C) with myocardial infarction (MI), all-cause mortality, haemorrhagic stroke and ischaemic stroke, as well as the joint association of genetic susceptibility and HDL-C/LDL-C with the MI risk. METHODS AND RESULTS: This study selected 384 093 participants from the UK Biobank (UKB) database. First, restricted cubic splines indicated non-linear associations of HDL-C/LDL-C with MI, ischaemic stroke and all-cause mortality. Second, a Cox proportional-hazards model indicated that compared with HDL-C/LDL-C=0.4-0.6, HDL-C/LDL-C<0.4 and >0.6 were correlated with all-cause mortality (HR=0.97 for HDL-C/LDL-C<0.4, 95% CI=0.939 to 0.999, p<0.05; HR=1.21 for HDL-C/LDL-C>0.6, 95% CI=1.16 to 1.26, p<0.001) after full multivariable adjustment. HDL-C/LDL-C<0.4 was correlated with a higher MI risk (HR=1.36, 95% CI=1.28 to 1.44, p<0.05) and ischaemic stroke (HR=1.12, 95% CI=1.02 to 1.22, p<0.05) after full multivariable adjustment. HDL-C/LDL-C>0.6 was associated with higher risk haemorrhagic stroke risk after full multivariable adjustment (HR=1.25, 95% CI=1.03 to 1.52, p<0.05). Third, after calculating the coronary heart disease Genetic Risk Score (CHD-GRS) of each participant, the Cox proportional-hazards model indicated that compared with low CHD-GRS and HDL-C/LDL-C=0.4-0.6, participants with a combination of high CHD-GRS and HDL-C/LDL-C<0.4 were associated with the highest MI risk (HR=2.45, 95% CI=2.15 to 2.8, p<0.001). Participants with HDL-C/LDL-C<0.4 were correlated with a higher MI risk regardless of whether they had a high, intermediate or low CHD-GRS. CONCLUSION: In UKB participants, HDL-C/LDL-C ratio of 0.4-0.6 was correlated with lower MI risk, all-cause mortality, haemorrhagic stroke and ischaemic stroke. Participants with HDL-C/LDL-C<0.4 were correlated with a higher MI risk regardless of whether they had a high, intermediate or low CHD-GRS. The clinical significance and impact of HDL-C/LDL-C need to be further verified in future studies.

Analysis of Prognostic Factors of Low-Grade Gliomas in Adults Using Time-Dependent Competing Risk Models: A Population Study Based on the Surveillance, Epidemiology, and End Results Database.

BACKGROUND: Because of multiple competing death outcomes and time-varying coefficients, using a Cox regression model to analyze the prognostic factors of low-grade gliomas (LGG) may lead to a possible bias. Therefore, we adopted time-dependent competing risk models to obtain accurate prognostic factors for LGG. METHODS: In this retrospective cohort study, data were extracted from patients enrolled in the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2018. Univariate analysis was performed using the cumulative incidence function (CIF) and Kaplan-Meier (KM) function. Time-dependent competing risk and Cox regression models were used in the multivariable analysis. RESULTS: A total of 2581 patients were diagnosed with low-grade glioma, among whom 889 died from low-grade glioma, 114 died from other causes, and the rest were alive. The time-dependent competing risk models indicated that age, sex, marital status, primary tumor site, histological type, tumor diameter, surgery, and year of diagnosis were significantly associated with low-grade glioma-specific death, and the relative effect of age, tumor diameter, surgery, oligodendroglioma, and mixed glioma on low-grade glioma-specific death changed over time. Compared with the competing risk models, the Cox regression model misestimated the hazard ratio (HR) of covariates on the outcome and even produced false-negative results. CONCLUSIONS: The time-dependent competing risk models were better than the Cox regression model for evaluating the impact of covariates on low-grade glioma-specific mortality in the presence of competing risks and time-varying coefficients. The models identified the prognostic factors of LGG more accurately than the Cox regression model.

Effects of growth trajectory of shock index within 24 h on the prognosis of patients with sepsis.

Background: Sepsis is a serious disease with high clinical morbidity and mortality. Despite the tremendous advances in medicine and nursing, treatment of sepsis remains a huge challenge. Our purpose was to explore the effects of shock index (SI) trajectory changes on the prognosis of patients within 24 h after the diagnosis of sepsis. Methods: This study was based on Medical Information Mart for Intensive Care IV (MIMIC- IV). The effects of SI on the prognosis of patients with sepsis were investigated using C-index and restricted cubic spline (RCS). The trajectory of SI in 24 h after sepsis diagnosis was classified by latent growth mixture modeling (LGMM). Cox proportional hazard model, double robust analysis, and subgroup analysis were conducted to investigate the influence of SI trajectory on in-hospital death and secondary outcomes. Results: A total of 19,869 patients were eventually enrolled in this study. C-index showed that SI had a prognostic value independent of Sequential Organ Failure Assessment for patients with sepsis. Moreover, the results of RCS showed that SI was a prognostic risk factor. LGMM divided SI trajectory into seven classes, and patients with sepsis in different classes had notable differences in prognosis. Compared with the SI continuously at a low level of 0.6, the SI continued to be at a level higher than 1.0, and the patients in the class whose initial SI was at a high level of 1.2 and then declined had a worse prognosis. Furthermore, the trajectory of SI had a higher prognostic value than the initial SI. Conclusion: Both initial SI and trajectory of SI were found to be independent factors that affect the prognosis of patients with sepsis. Therefore, in clinical treatment, we should closely monitor the basic vital signs of patients and arrive at appropriate clinical decisions on basis of their change trajectory.

Association of NAFLD with cardiovascular disease and all-cause mortality: a large-scale prospective cohort study based on UK Biobank.

Objective: Nonalcoholic fatty liver disease (NAFLD) is considered as the hepatic manifestation of metabolic syndrome, sharing the similar cardiometabolic risk factors with cardiovascular disease (CVD). Whether NAFLD by itself is associated with increased cardiovascular events and death remain an issue to debate. This study aimed to further investigate the association between NAFLD and adverse CVD outcomes. Methods: Participants were followed up until the end of 2020 in current analysis. NAFLD is defined using fatty liver index (FLI). Cox proportional hazard model was used to analyze the association between NAFLD and all-cause mortality, major adverse cardiovascular events (MACEs), CVD mortality, fatal/nonfatal acute myocardial infarction (AMI), and fatal/nonfatal stroke. C-index was calculated to evaluate the model enhancement when adding NAFLD factor. Results: After screening the data of 502,492 participants in the original cohort, 215,245 eligible participants were included in this study for MACEs outcome. Compared with non-NAFLD participants, the multivariable adjusted hazard ratios of NAFLD group was 1.25 (1.14-1.36) for MACEs; 1.14 (1.08-1.20) for all-cause mortality; 1.61(1.42-1.82) for CVD mortality; 1.58(1.19-2.11) for AMI mortality; and 1.18 (0.85-1.64) for stroke mortality. When adding FLI, C-index of NAFLD model improved for all-cause mortality, MACEs, and CVD mortality compared with that in the traditional CVD risk factor model. Conclusion: NAFLD is an independent risk factor for all-cause mortality and adverse CVD outcomes. Based on the traditional CVD risk factor model, additionally screening NAFLD could improve the prediction efficiency for adverse CVD outcomes.

Worldwide long-term trends in the incidence of nonalcoholic fatty liver disease during 1990-2019: A joinpoint and age-period-cohort analysis.

Background: Non-alcoholic fatty liver disease (NAFLD) was previously a neglected disease that is now becoming a worldwide pandemic. A better understanding of its incidence and long-term trends will help to increase public awareness of the disease and the development of future prevention strategies. Methods: The incidence rates of NAFLD during 1990-2019 were collected from the Global Burden of Disease Study 2019 database according to the following parameters: sex, age, socio-demographic index, and geographical region. Estimated annual percentage changes and joinpoint models were used to assess the long-term trend of NAFLD, and an age-period-cohort model was used to assess the extents of the age, period, and cohort effects. Results: Adult males, postmenopausal females, Latin American populations, and people in developing countries had a high risk of developing NAFLD. The joinpoint model indicated a new trend of increasing NAFLD incidence in 2005. Age was a risk factor affecting NAFLD incidence, with this effect increasing in more-recent periods. Younger birth cohorts had lower risks of NAFLD. Conclusions: Recent prevention measures for NAFLD have achieved good initial results. However, it remains a high priority to increase the public awareness of this condition, develop its diagnostic criteria, identify cost-effective screening methods, and seek policy support to act against NAFLD, which will be a major public health problem in the future.

Sleep duration, genetic susceptibility, and Alzheimer's disease: a longitudinal UK Biobank-based study.

BACKGROUND: Alzheimer's disease (AD) is the most frequently occurring type of dementia. Concurrently, inadequate sleep has been recognized as a public health epidemic. Notably, genetic and environmental factors are now considered contributors to AD progression. OBJECTIVE: To assess the association between sleep duration, genetic susceptibility, and AD. METHODS AND RESULTS: Based on 483,507 participants from the UK Biobank (UKB) with an average follow-up of 11.3 years, there was a non-linear relationship between AD incidence and sleep duration (P for non-linear < 0.001) by restricted cubic splines (RCS). Sleep duration was categorized into short sleep duration (< 6 h/night), normal sleep duration (6-9 h/night), and long sleep duration (> 9 h/night). No statistically significant interaction was identified between sleep duration and the AD-GRS (Alzheimer's disease genetic risk score, P for interaction = 0.45) using Cox proportional risk model. Compared with the participants who had a low AD-GRS and normal sleep duration, there was associated with a higher risk of AD in participants with a low AD-GRS and long sleep duration (HR = 3.4806; 95% CI 2.0011-6.054, p < 0.001), participants with an intermediate AD-GRS and long sleep duration (HR = 2.0485; 95% CI 1.3491-3.1105, p < 0.001), participants with a high AD-GRS and normal sleep duration (HR = 1.9272; 95% CI 1.5361-2.4176, p < 0.001), and participants with a high AD-GRS and long sleep duration (HR = 5.4548; 95% CI 3.1367-9.4863, p < 0.001).In addition, there was no causal association between AD and sleep duration using Two Sample Mendelian randomization (MR). CONCLUSION: In the UKB population, though there was no causal association between AD and sleep duration analyzed using Two Sample MR, long sleep duration (> 9 h/night) was significantly associated with a higher risk of AD, regardless of high, intermediate or low AD-GRS. Prolonged sleep duration may be one of the clinical predictors of a higher risk of AD.

The relationship between hematocrit and serum albumin levels difference and mortality in elderly sepsis patients in intensive care units-a retrospective study based on two large database.

BACKGROUND: Sepsis still threatens the lives of more than 300 million patients annually and elderly patients with sepsis usually have a more complicated condition and a worse prognosis. Existing studies have shown that both Hematocrit (HCT) and albumin (ALB) can be used as potential predictors of sepsis, and their difference HCT-ALB has a significant capacity to diagnose infectious diseases. Currently, there is no relevant research on the relationship between HCT-ALB and the prognosis of elderly sepsis patients. Therefore, this study aims to explore the association between HCT-ALB and mortality in elderly patients with sepsis. METHODS: This study was a multi-center retrospective study based on the Medical Information Mart for Intensive Care (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD) in elderly patients with sepsis. The optimal HCT-ALB cut-off point for ICU mortality was calculated by the Youden Index based on the eICU-CRD dataset, and multivariate logistic regressions were conducted to explore the association between HCT-ALB and ICU/hospital mortality in the two databases. Subgroup analyses were performed for different parameters and comorbidity status. RESULTS: The number of 16,127 and 3043 elderly sepsis patients were selected from two large intensive care databases (eICU-CRD and MIMIC-IV, respectively) in this study. Depending on the optimal cut-off point, patients in both eICU-CRD and MIMIC-IV were independently divided into low HCT-ALB (< 6.7) and high HCT-ALB (≥ 6.7) groups. The odds ratio (95%confidence interval) [OR (95CI%)] of the high HCT-ALB group were 1.50 (1.36,1.65) and 1.71 (1.58,1.87) for ICU and hospital mortality in the eICU-CRD database after multivariable adjustment. Similar trends in the ICU and hospital mortality [OR (95%CI) 1.41 (1.15,1.72) and 1.27 (1.07,1.51)] were observed in MIMIC-IV database. Subgroup analysis showed an interaction effect with SOFA score in the eICU-CRD database however not in MIMIC-IV dataset. CONCLUSIONS: High HCT-ALB (≥ 6.7) is associated with 1.41 and 1.27 times ICU and hospital mortality risk in elderly patients with sepsis. HCT-ALB is simple and easy to obtain and is a promising clinical predictor of early risk stratification for elderly sepsis patients in ICU.

Antithrombotic Therapy Improves ICU Mortality of Septic Patients with Peripheral Vascular Disease.

Objective: The effectiveness of antithrombotic drugs for treating sepsis is controversial. Here, we explore the association between antithrombotic therapy and intensive care unit (ICU) mortality for septic patients with peripheral vascular disease. Methods: This retrospective cohort study uses data from the Medical Information Mart for Intensive Care (MIMIC)-III database. Kaplan-Meier survival analyses were used to examine mortality among different groups. Cox regression and marginal structural Cox models (MSCMs) were used to adjust for confounding factors. Main Results. The final cohort from the MIMIC-III database included 776 patients, of which 701 survived and 75 perished. The anticoagulant (AC) group and the antiplatelet-anticoagulation (AC-AP) group survived better than the group without antithrombotic treatment (non-AT). The AC and AC-AP groups showed a 0.363-fold and 0.373-fold risk of ICU mortality, respectively, compared with the non-AT group when controlling for age, gender, CRRT, alcohol, heart failure, hypertension, diabetes, obesity, renal failure, liver disease, INR, PT, PPT, and SpO2. Antiplatelet therapy did not reduce ICU mortality. The same trends were apparent from the MSCM. In addition, the AC-AP group exhibited a lower risk of bleeding complications. Conclusion: Although the antithrombotic group (AC and AC-AP groups) demonstrated a higher sequential organ failure assessment (SOFA) score than the group without antithrombotic treatment (non-AT group), the risk of ICU mortality was lower without increasing the risk of bleeding complications. Our study further suggested that anticoagulation therapy may benefit the prognosis of septic patients with peripheral vascular disease.

Using Restricted Cubic Splines to Study the Duration of Antibiotic Use in the Prognosis of Ventilator-Associated Pneumonia.

Background: Ventilator-associated pneumonia (VAP) is the most widespread and life-threatening nosocomial infection in intensive care units (ICUs). The duration of antibiotic use is a good predictor of prognosis in patients with VAP, but the ideal duration of antibiotic therapy for VAP in critically ill patients has not been confirmed. Research is therefore needed into the optimal duration of antibiotic use and its impact on VAP. Methods: The Medical Information Mart for Intensive Care database included 1,609 patients with VAP. Chi-square or Student's t-tests were used to compare groups, and Cox regression analysis was used to investigate the factors influencing the prognoses of patients with VAP. Nonlinear tests were performed on antibiotic use lasting <7, 7-10, and >10 days. Significant factors were included in the model for sensitivity analysis. For the subgroup analyses, the body mass indexes (BMIs) of patients were separated into BMI <30 kg/m2 and BMI ≥30 kg/m2, with the criterion of statistical significance set at p < 0.05. Restricted cubic splines were used to analyze the relationship between antibiotic use duration and mortality risk in patients with VAP. Results: In patients with VAP, the effects of antibiotic use duration on the outcomes were nonlinear. Antibiotic use for 7-10 days in models 1-3 increased the risk of antibiotic use by 2.6020-, 2.1642-, and 2.3263-fold relative to for >10 days, respectively. The risks in models 1-3 for <7 days were 2.6510-, 1.9933-, and 2.5151-fold higher than those in models with >10 days of antibiotic use, respectively. These results were robust across the analyses. Conclusions: The duration of antibiotic treatment had a nonlinear effect on the prognosis of patients with VAP. Antibiotic use durations of <7 days and 7-10 days both presented risks, and the appropriate duration of antibiotic use can ensure the good prognosis of patients with VAP.

Influence of ambulatory blood pressure-related indicators within 24 h on in-hospital death in sepsis patients.

Background: Sepsis is a serious public health problem worldwide. Blood pressure is one of the indicators that is closely monitored in intensive-care units, and it reflects complex interactions between the internal cardiovascular control mechanism and the external environment. We aimed to determine the impact of indicators related to the ambulatory blood pressure on the prognosis of sepsis patients. Methods: This retrospective study was based on the Medical Information Mart for Intensive Care IV database. Relevant information about sepsis patients was extracted according to specific inclusion and exclusion criteria. Examined parameters included the average blood pressure, blood pressure variability (BPV), and circadian rhythm, and the study outcome was in-hospital death. We investigated the effects of these indicators on the risk of in-hospital death among sepsis patients using Cox proportional-hazards models, restricted cubic splines analysis, and subgroup analysis. Results: This study enrolled 10,316 sepsis patients, among whom 2,117 died during hospitalization. All parameters except the nighttime variation coefficient of the diastolic blood pressure (DBP) were associated with in-hospital death of sepsis patients. All parameters except for fluctuations in DBP exhibited nonlinear correlations with the outcome. The subgroup analysis revealed that some of the examined parameters were associated with in-hospital death only in certain subgroups. Conclusion: Indicators related to the ambulatory blood pressure within 24 h are related to the prognosis of sepsis patients. When treating sepsis, in addition to blood pressure, attention should also be paid to BPV and the circadian rhythm in order to improve the prognosis and the survival rate.

Predicting ICU Mortality in Rheumatic Heart Disease: Comparison of XGBoost and Logistic Regression.

Background: Rheumatic heart disease (RHD) accounts for a large proportion of Intensive Care Unit (ICU) deaths. Early prediction of RHD can help with timely and appropriate treatment to improve survival outcomes, and the XGBoost machine learning technology can be used to identify predictive factors; however, its use has been limited in the past. We compared the performance of logistic regression and XGBoost in predicting hospital mortality among patients with RHD from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Methods: The patients with RHD in the MIMIC-IV database were divided into two groups retrospectively according to the availability of data and its clinical significance based on whether they survived or died. Backward stepwise regression was used to analyze the independent factors influencing patients with RHD, and to compare the differences between the two groups. The XGBoost algorithm and logistic regression were used to establish two prediction models, and the areas under the receiver operating characteristic curves (AUCs) and decision-curve analysis (DCA) were used to test and compare the models. Finally, DCA and the clinical impact curve (CIC) were used to validate the model. Results: Data on 1,634 patients with RHD were analyzed, comprising 207 who died during hospitalization and 1,427 survived. According to estimated results for the two models using AUCs [0.838 (95% confidence interval = 0.786-0.891) and 0.815 (95% confidence interval = 0.765-0.865)] and DCA, the logistic regression model performed better. DCA and CIC verified that the logistic regression model had convincing predictive value. Conclusions: We used logistic regression analysis to establish a more meaningful prediction model for the final outcome of patients with RHD. This model might be clinically useful for patients with RHD and help clinicians to provide detailed treatments and precise management.

The association between continuous renal replacement therapy as treatment for sepsis-associated acute kidney injury and trend of lactate trajectory as risk factor of 28-day mortality in intensive care units.

BACKGROUND: Sepsis has high incidence and fatality rates in intensive care units, often leading to renal failure. The effectiveness of continuous renal replacement therapy (CRRT) in sepsis-associated acute kidney injury (S-AKI) patients is currently uncertain. AIM: Joint model was used to determine the association between CRRT and the lactate trajectory trend and how it correlated to 28-day mortality for S-AKI patient in ICU. METHODS: A retrospective study was applied to patients with sepsis and AKI, which were extracted from the MIMIC-III public database, with the endpoint being 28-day mortality. Every lactate level measurement within 28 days was observed and calculated using logarithms. Joint model combined the longitudinal analysis of the natural logarithm of the lactate level [log(lactate)] in longitudinal submodel and Cox regression by trajectory function, demonstrating the effects of CRRT on 28-day survival and log(lactate) changes, and its final relationship with the event status. RESULTS: Among the 717 S-AKI patients, 157 received CRRT. CRRT was not associated with 28-day mortality. After adjustments, the relationship between CRRT use and log(lactate) elevation was statistically significant. The parameter estimation of CRRT and log(lactate) indicated that using CRRT will increase log(lactate) by 0.041 in S-AKI patients. The joint model also instigated a fixed association between changes in the lactate level and the event result, revealing an exp value of (0.755) = 2.12, indicating that an increase of one unit in log(lactate) will increase the risk of 28-day mortality 2.12-times. CONCLUSION: There was no significant association between CRRT use and 28-day survival in S-AKI patients, and JM showed that CRRT use might be associated with elevation of longitudinal lactate levels. Therefore, additional attention should be paid to other treatments to control lactate levels when providing renal support for patients with S-AKI.

Different Trends in the Incidence and Mortality Rates of Prostate Cancer Between China and the USA: A Joinpoint and Age-Period-Cohort Analysis.

PURPOSE: This study used data from the Global Burden of Disease Study 2019 (GBD 2019) to determine the differences in the incidence and mortality of prostate cancer (PCa) between China and the USA from 1990 to 2019. METHOD: The age-standardized incidence rates (ASIRs) and age-standardized death rates (ASDRs) in China and the USA from 1990 to 2019 were extracted from GBD 2019. Annual percentage changes and relative risks of ASIR and ASDR were calculated using joinpoint regression analysis and age-period-cohort models, respectively. RESULTS: The ASIR of PCa in China continually increased from 1990 to 2019, while in the USA it increased from 1990 to 1994 and then continually decreased until 2015, and then slightly increased again until 2019. The ASDR in China did not change, and the trend of ASDR in the USA was similar to the trend of the ASIR in the USA. The incidence of PCa increased with age in China, but decreased after the age of 75 years in the USA. A period effect was present, with the risk of developing PCa increasing continuously over longer time periods. Those born later had a lower risk of PCa or death, indicating a cohort effect. CONCLUSION: PCa is becoming more problematic for Chinese males. Disease trends in the USA indicate that large-scale screening may be beneficial and should be immediately implemented among high-risk groups in China.

Risk factor analysis and nomogram for predicting in-hospital mortality in ICU patients with sepsis and lung infection.

BACKGROUND: Lung infection is a common cause of sepsis, and patients with sepsis and lung infection are more ill and have a higher mortality rate than sepsis patients without lung infection. We constructed a nomogram prediction model to accurately evaluate the prognosis of and provide treatment advice for patients with sepsis and lung infection. METHODS: Data were retrospectively extracted from the Medical Information Mart for Intensive Care (MIMIC-III) open-source clinical database. The definition of Sepsis 3.0 [10] was used, which includes patients with life-threatening organ dysfunction caused by an uncontrolled host response to infection, and SOFA score ≥ 2. The nomogram prediction model was constructed from the training set using logistic regression analysis, and was then internally validated and underwent sensitivity analysis. RESULTS: The risk factors of age, lactate, temperature, oxygenation index, BUN, lactate, Glasgow Coma Score (GCS), liver disease, cancer, organ transplantation, Troponin T(TnT), neutrophil-to-lymphocyte ratio (NLR), and CRRT, MV, and vasopressor use were included in the nomogram. We compared our nomogram with the Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology Score II (SAPSII), the nomogram had better discrimination ability, with areas under the receiver operating characteristic curve (AUROC) of 0.743 (95% C.I.: 0.713-0.773) and 0.746 (95% C.I.: 0.699-0.790) in the training and validation sets, respectively. The calibration plot indicated that the nomogram was adequate for predicting the in-hospital mortality risk in both sets. The decision-curve analysis (DCA) of the nomogram revealed that it provided net benefits for clinical use over using the SOFA score and SAPSII in both sets. CONCLUSION: Our new nomogram is a convenient tool for accurate predictions of in-hospital mortality among ICU patients with sepsis and lung infection. Treatment strategies that improve the factors considered relevant in the model could increase in-hospital survival for these ICU patients.

Relationship between self-reported sleep duration during week-/work-days and metabolic syndrome from NHANES 2013 to 2016.

PURPOSE: This research aimed at determining the relationship between self-reported sleep duration during week-/work-days and metabolic syndrome (MetS) from NHANES 2013 to 2016. METHODS: This study analyzed data from 11,181 people aged 16 or older who took part in the NHANES (National Health and Nutrition Examination Surveys) from 2013 to 2016. A standard questionnaire was used to define self-reported sleep duration, and MetS was defined on the basis of the NCEP (National Cholesterol Education Program)/ATP III revised diagnostic criteria. Logistic regression and restricted cubic splines (RCS) models were used to assess the relationship between self-reported sleep duration and MetS. RESULTS: The overall prevalence of MetS in the study cohort was 26.1%, with 24.8% for males and 27.3% for females. After adjusting for potential confounding factors, MetS was significantly associated with self-reported short sleep duration (odds ratio = 1.16, 95% confidence interval = 1.03-1.31, P = 0.013) but not with long sleep duration (P = 0.117). RCS regression revealed that self-reported sleep duration was nonlinearly related to MetS (P for nonlinearity = 0.0026). The risk of MetS decreased with increased sleep duration for durations of less than 7 h/day, while there was no association for longer sleep durations. CONCLUSION: These results suggest that self-reported short sleep duration is a risk factor for MetS, while long sleep duration is not.

Developing and verifying a multivariate model to predict the survival probability after coronary artery bypass grafting in patients with coronary atherosclerosis based on the MIMIC-III database.

BACKGROUND: Coronary atherosclerosis is one of the main cardiovascular diseases affecting the global population. Coronary artery bypass grafting (CABG) is commonly used to improve the survival probability of patients with coronary atherosclerosis. However, the prognosis of patients after CABG remains unclear. OBJECTIVES: We aimed to construct a novel nomogram comprising readily available indicators to predict the 1-, 2-, and 3-year survival rates after CABG in patients with coronary atherosclerosis. METHODS: We utilized the Medical Information Mart for Intensive Care III (MIMIC-III) database for the study. The calibration plot, concordance index (C-index), net reclassification index (NRI), integrated discrimination improvement (IDI), and area under the receiver operating characteristic curve (AUROC) were used to evaluate the performance of the model, and to compare the nomogram with the Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology Score II (SAPS II) in order to illustrate the clinical effectiveness of the model. RESULTS: The multivariate Cox regression model showed that age, marital status, body mass index, creatinine, platelet count, red cell distribution width, heart rate, intensive-care unit stay time, and Elixhauser Comorbidity Index were risk factors. The C-indexes of the nomogram exceeded 0.75, and its NRI and IDI were both higher than 0. The AUROCs were larger for the nomogram than for the SAPS II and SOFA score. CONCLUSION: Our new nomogram is a personalized tool that helps clinicians choose treatment options and predict the long-term prognosis of patients.

How socioeconomic and clinical factors impact prostate-cancer-specific and other-cause mortality in prostate cancer stratified by clinical stage: Competing-risk analysis.

BACKGROUND: The aim of this study was to analyze the causes of death and risk factors of prostate-cancer-specific mortality (PCSM) and other-cause mortality (OCM) at different clinical stages using data from the Surveillance, Epidemiology, and End Results database. METHODS: The characteristics and cause-specific death classifications of males with prostate cancer (PCa) were extracted. Multivariate competing-risk regression analysis was used to identify significant predictors and quantify the cumulative incidence of PCSM and OCM at different clinical stages. RESULTS: Of the 244,433 PCa patients who were included, 19,274 died from 7356 PCSM, and 11,918 from OCM. The proportion of PCSM gradually increased from 2010 to 2016. The risk factors for PCSM in the localized PCa stage included older age, not being married, living in a county with higher poverty rates, and higher PSA levels and Gleason scores. Meanwhile, Medicaid and lower education levels were the additional risk factors of OCM. The risk factors for PCSM in the regional PCa stage included older age, not being married, Medicaid, living in a county with higher poverty rates, and higher PSA levels and Gleason scores. Meanwhile, the income level did not affect OCM risk. The risk factors for PCSM in the distant metastatic PCa stage included a separated/divorced/widowed marital status, Medicaid, and higher PSA levels and Gleason scores. Meanwhile, older age, an unmarried or separated/divorced/widowed marital status, and higher PSA levels were risk factors for OCM. In addition, receiving both surgery and radiation was worse than just receiving surgery for PCa specific survival in localized and regional PCa patients. CONCLUSION: Some pretreatment and treatment factors may influence OCM that are not identical to those for PCSM at the corresponding stage. Decision-makers and managers should fully consider OCM to maximize treatment benefits for PCa.

Analysis of the correlation between the longitudinal trajectory of SOFA scores and prognosis in patients with sepsis at 72 hour after admission based on group trajectory modeling.

Background: To identify the distinct trajectories of the Sequential Organ Failure Assessment (SOFA) scores at 72 h for patients with sepsis in the Medical Information Mart for Intensive Care (MIMIC)-IV database and determine their effects on mortality and adverse clinical outcomes. Methods: A retrospective cohort study was carried out involving patients with sepsis from the MIMIC-IV database. Group-based trajectory modeling (GBTM) was used to identify the distinct trajectory groups for the SOFA scores in patients with sepsis in the intensive care unit (ICU). The Cox proportional hazards regression model was used to investigate the relationship between the longitudinal change trajectory of the SOFA score and mortality and adverse clinical outcomes. Results: A total of 16,743 patients with sepsis were included in the cohort. The median survival age was 66 years (interquartile range: 54-76 years). The 7-day and 28-day in-hospital mortality were 6.0% and 17.6%, respectively. Five different trajectories of SOFA scores according to the model fitting standard were determined: group 1 (32.8%), group 2 (30.0%), group 3 (17.6%), group 4 (14.0%) and group 5 (5.7%). Univariate and multivariate Cox regression analyses showed that, for different clinical outcomes, trajectory group 1 was used as the reference, while trajectory groups 2-5 were all risk factors associated with the outcome (P < 0.001). Subgroup analysis revealed an interaction between the two covariates of age and mechanical ventilation and the different trajectory groups of patients' SOFA scores (P < 0.05). Conclusion: This approach may help identify various groups of patients with sepsis, who may be at different levels of risk for adverse health outcomes, and provide subgroups with clinical importance.

Obesity Paradox of All-Cause Mortality in 4,133 Patients Treated with Coronary Revascularization.

OBJECTIVES: The purpose of this study was to determine whether there is a dose-response relationship between body mass index (BMI) and all-cause mortality in patients after coronary revascularization. METHODS: The MIMIC-III database (version 1.4) was used as the sample population. For variables with less than 10% of values missing, we used the mice package of R software for multiple imputations. Cox regression was used to determine the risk factors of all-cause mortality in patients. RCSs were used to observe the relationship between BMI and all-cause mortality. Additional subgroup and sensitivity analyses were also performed to explore whether the conclusion can be applied to specific groups. RESULTS: Both univariate and multivariate Cox models indicated that the mortality risk was lower for overweight patients than for normal-weight patients (P < 0.05). In RCS models, BMI had a U-shaped relationship with all-cause mortality of patients after coronary artery bypass grafting (CABG) (P for nonlinearity = 0.0028). There was a weak U-shaped relationship between BMI and all-cause mortality after percutaneous coronary intervention (PCI), but the nonlinear relationship between these two parameters was not significant (P for nonlinearity = 0.1756). CONCLUSIONS: The obesity paradox does exist in patients treated with CABG and PCI. RCS analysis indicated that there was a U-shaped relationship between BMI and all-cause mortality in patients after CABG. After sex stratification, the relationship between BMI and all-cause mortality in male patients who received PCI was L-shaped, while the nonlinear relationship among females was not significant.