Mortality Factors Research Articles

CT parameters of psoas muscle predicts 28-day mortality in older patients with sepsis: a retrospective study

OdjectivesTo investigate the predictive value of computed tomography (CT)-based transverse diameter (TD) and longitudinal diameter (LD) of the psoas muscle at the level of third lumbar vertebra for 28-day mortality in older patients with sepsis.MethodsThis retrospective single-center cohort study included 115 septic patients aged over 65 years old who were admitted to ICU in Beijing-Chaoyang Hospital between July 2017 and July 2022. The TD and LD of psoas muscle were obtained by measurement on abdominal CT images. Logistic regression analysis was conducted to identify the prognostic factors for 28-day mortality in older patients with sepsis, and their predictive performances were evaluated using the receiver operating characteristic (ROC) curve.ResultsMultivariable logistic analysis indicated that TD (OR: 0.405, 95% CI: 0.190–0.864) was a protective factor for 28-day mortality in older patients with sepsis, whereas LD was not. The areas under the curve (AUCs) of TD, APACHE II, and SOFA were 0.666 (95% CI: 0.565–0.767), 0.660 (95% CI: 0.561–0.760), and 0.679 (95% CI: 0.581–0.777), respectively. Furthermore, the AUCs for the combination of TD with APACHE II or SOFA were 0.766 (95% CI: 0.679–0.853, P < 0.001) and 0.765 (95% CI: 0.679–0.852, P < 0.001).ConclusionsTD of psoas muscle was a predictor for 28-day mortality in older patients with sepsis. The combination of TD with APACHE II or SOFA scores enhances the early identification of patients at high risk for poor prognosis.Clinical trial numbernot applicable.

Risk Factors for Chronic Kidney Disease in Adult Patients with Congenital Heart Disease and Its Relationship with Cardiovascular Mortality.

Background: Patients with congenital heart disease (CHD) show risk factors for chronic kidney disease (CKD) and it is well known that CKD has a large negative impact on survival. Methods: Observational and prospective cohort study. Adult CHD patients and controls were matched for age and sex. Results: A total of 657 CHD adult patients (cases) and 1954 controls were studied. Median age in CHD patients was 30 (17-62) years and 373 (57%) were male. The prevalence of CKD (Glomerular filtration rate (GFR) < 60 mL/min/1.73 m2) was 0.2% and 4.5% in the control and CHD groups, respectively. Binary logistic regression analysis determined as risk factors for CKD in CHD patients: age [1.54 (1.04-1.28), p = 0.009], dyslipidemia [19.8 (1.35-301.1), p = 0.031], low iron concentration [0.96 (0.96-0.93), p = 0.048], cyanosis [25.7 (1.60-411.8), p = 0.022], and Down syndrome [46.8 (8.09-2710), p = 0.003]. During a follow-up time of 6.8 (1.2-10.5) years, cardiovascular mortality occurred in 31 patients with CHD showing, through the Kaplan-Meier test, a worse outcome among patients with CKD (p < 0.05) as was also seen in the univariate Cox regression survival analysis. However, after adjusting for other variables, this significance was lost, with age remaining as the unique independent prognostic factor. Conclusions: The prevalence of CKD was much higher in patients with CHD than in the control group; age, cyanosis, and Down syndrome were the predictors of a higher risk of CKD among CHD patients. Although CKD was associated with worse survival in CHD patients, only age was identified as an independent prognostic factor for cardiovascular mortality.

Perioperative and Neurological Complications after Open Thoracic Aortic Surgery in a High-Volume Aortic Surgery Center

Objective: Thoracic aortic surgery is associated with an increased risk of mortality and complications. The present study aimed to evaluate the incidence of 30-day mortality and perioperative major complications after open thoracic aortic surgery in a high-volume aortic center. Materials and Methods: The present study was a retrospective analysis and included patients who underwent open thoracic aortic surgery with cardiopulmonary bypass (CPB) between December 2018 and November 2020. Demographics and perioperative data were analyzed. The incidence of 30-day mortality and risk factors of perioperative and neurological complications were determined. Results: One hundred ninety-five patients were included in the present study. Most were male, at 67.2%, with a mean age of 59.3±14.5 years. The incidence of 30-day mortality was 4.6%, with a 95% confidence interval (CI) 2.5 to 8.5. The major complication characterized by the Clavien-Dindo classification was 40.5%. The multivariable analysis identified aortic arch surgery (adjusted odds ratio (aOR) 2.86, 95% CI 1.11 to 7.33, p=0.029), maximum vasoactive-inotropic (VISmax) score greater than 10 (aOR 2.58, 95% CI 1.01 to 6.64, p=0.049), and VISmax score greater than 20 (aOR 5.54, 95% CI 1.67 to 18.34, p=0.005) as significant risk factors for postoperative major complications. In addition, aortic arch surgery, preoperative neurological complications (aOR 4.01, 95% CI 1.47 to 10.95, p=0.007), cerebral desaturation of greater than 20% reduction of regional cerebral oxygen saturation rScO₂ during CPB (aOR 4.60, 95% CI 1.49 to 14.15, p=0.008), and red blood cell transfusions of more than one blood volume (aOR 4.19, 95% CI 1.01 to 17.36, p=0.048) were identified as risk factors for postoperative stroke. Conclusion: The present study demonstrated a 30-day mortality rate of 4.6% after thoracic aortic surgery. Operations of the aortic arch and VISmax score of greater than 10 are associated with an increased risk of major postoperative complications. Reduction of rScO₂ during CPB is strongly associated with postoperative stroke.

Red blood cell distribution width to albumin ratio as a predictor of mortality in ICU patients with community acquired bacteremia

Bloodstream infections are globally occurring life-threatening diseases that impose significant societal and economic burdens. This study explored the red cell distribution width (RDW) to albumin ratio (RAR), a novel index derived from RDW, to investigate its relationship with prognosis of bacteremia using propensity score matching (PSM). This retrospective observational cohort study included patients with bacteremia admitted to Yantai Yuhuangding Hospital’s intensive care units from June 2019 to December 2022. PSM was performed to adjust for confounding factors. The relationship between RAR and mortality was assessed using receiver operating characteristic curves, multivariate, and Kaplan–Meier analyses. A total of 411 patients were included. The RAR threshold of 5.824% /g/dL was determined by maximizing the Youden index; the study population was divided into two groups based on this cutoff value. After PSM, 125 pairs of score-matched patients were generated. Using logistic regression analysis, patients with RAR ≥ 5.824% /g/dL exhibited significantly higher mortality than did those with RAR ＜ 5.824% /g/dL in the entire cohort (OR = 3.926, 95% confidence interval (CI): 2.408–6.400, p < 0.001) and the PSM subset (OR = 2.460, 95% CI: 1.411–4.289, p = 0.040). RAR results were consistent when treated as continuous or four-categorical variables (based on quartiles). Similar outcomes were found for 28- and 90-day mortality and septic shock. The areas under the curves of RAR were 0.735, significantly higher than those of albumin or RAR alone. RAR emerges as an independent risk factor for mortality and septic shock in critically ill patients with community-acquired bacteremia, whether considered a continuous or categorized variable, irrespective of PSM adjustment.

Can simple measures from clinical practice serve as a proxy for sarcopenic obesity and identify mortality risk?

BackgroundSarcopenic obesity is a condition where loss of muscle mass occurs alongside fat gain, and it is considered a risk factor for mortality. However, the use of various definitions for this condition has led to conflicting results.AimTo investigate whether the coexistence of low muscle mass and abdominal obesity, defined using two simple measures employed in clinical practice, is a risk factor for mortality in individuals aged 50 or older.MethodsA longitudinal study with a 14-year follow-up was conducted involving 5,440 participants of the English Longitudinal Study of Ageing. Abdominal obesity and low muscle mass were respectively defined based on high waist circumference and low skeletal muscle mass index (SMMI) determined by an equation. The sample was divided into four groups: non-low muscle mass/non-abdominal obesity (NLMM/NAO), non-low muscle mass/abdominal obesity (NLMM/AO), low muscle mass/non-abdominal obesity (LMM/NAO), and low muscle mass/abdominal obesity (LMM/AO). Cox regression models were used to estimate the mortality risk as a function of muscle mass and abdominal obesity status.ResultsLMM/AO increased the risk of death by 83% (HR:1.83; 95%CI: 1.35–2.66) compared to those in the NLMM/NAO group. AO alone was not associated with a greater risk of mortality (HR:1.09; 95%CI: 0.93–1.27), whereas LMM alone increased the risk by 40% (HR:1.40; 95%CI:1.18–1.66).ConclusionsIdentifying LMM/AO in individuals aged 50 or older can be crucial for predicting the risk of mortality. Simple and easily applicable measures can serve as a proxy for sarcopenic obesity and aid in implementing the necessary interventions.

Long-term accuracy of the National Emergency Laparotomy Audit risk score: Analysis of the impact of comorbidities on mortality 5 years after emergency laparotomy.

The National Emergency Laparotomy Audit (NELA) risk prediction tool has demonstrated superiority in predicting 30-day mortality after emergency laparotomy (EL). The aim of our study was to evaluate the accuracy of NELA in calculating long-term (5 year) mortality and determine factors predicting long-term risk of death after EL. This retrospective cohort study included consecutive patients who underwent EL for any indication other than trauma between May 2012 and June 2017 at a large tertiary and academic teaching center. The primary outcome was all-cause postoperative mortality at 1 and 5 years. The c statistic (<1.0, excellent; <0.90, good; 0.80, fair; 0.70, poor) was used to assess accuracy of the NELA. Multivariable regression was used to identify independent risk factors for 5-year mortality after EL. From a total of 758 patients, observed mortality continued to increase from 15.4% at 1 year up to 31.4% at 5 years. The NELA risk score accurately classified deceased patients at both 1 year (c = 0.82; 95% confidence interval [CI], 0.78-0.85) and 5 years (c = 0.82, 0.79-0.85) after EL. History of ascites (adjusted odds ratio [aOR], 3.3; 1.0-11.3; p = 0.048), chronic obstructive pulmonary disease (aOR, 1.9; 1.1-3.4; p = 0.030), congestive heart failure (aOR, 3.6; 1.2-11.5; p = 0.025), myocardial infarction (aOR, 2.6; 1.5-4.6; p = 0.001), and a new cancer diagnosis (aOR, 2.8; 1.7-4.8; p < 0.0001) were independent prognostic factors for death 5 years after EL. Long-term prognosis after EL remains poor for at least 5 years postoperatively. The NELA score is accurately able to predict risk of death up to 5 years after EL. History of ascites, chronic obstructive pulmonary disease, congestive heart failure, myocardial infarction, and a new diagnosis of cancer were independent prognostic factors for long-term mortality after EL. Prognostic and Epidemiological; Level IV.

Predictive factors for early mortality after EUS-guided gastroenterostomy in malignant gastric outlet obstruction

Background and study aim: Endoscopic ultrasound-guided gastroenterostomy (EUS-GE) has recently emerged as a potential treatment option for malignant gastric outlet obstruction (mGOO), with a relatively long duration of patency and low rate of reintervention. Its intrinsic risk for serious adverse events and high procedure cost mandates careful patient selection beyond the common safety profiles. This study aimed to assess for predictors of early post-EUS-GE mortality. Patients and methods: We conducted a retrospective analysis of all patients with unresectable mGOO who underwent EUS-GE. Predictive factors for postoperative 30-day mortality with crude and adjusted hazard ratios were examined using univariate and multivariate penalized likelihood Firth logistic regression analyses. Results: Technical and clinical success was achieved in 96.7% and 93.1% of the patients, respectively. The 30-day mortality rate after the procedure was 11.7%, and no procedural complications were observed. The 30-day mortality group had a significantly low rate of initial clinical success (66.7% vs. 96.2%, p=0.007). Univariate analysis identified significantly higher postoperative 30-day mortality in patients with poor baseline ECOG performance status scale (≥2) and ascites. The presence of grade 2 ascites was confirmed as an independent predictive factor in the multivariate analysis (adjusted hazard ratio 52.41, 95% confidence interval 1.55 to 1775.64, p=0.024). Conclusion: EUS-GE should be carefully considered for patients with ascites which was an independent predictor for early mortality after procedure in mGOO, especially those with grade 2 or higher level of ascites.

Risk Factors associated with In-Hospital Death in Adult COVID-19 Patients in Karachi, Pakistan: A Retrospective Chart Review

Objective: To identify the risk factors associated with in-hospital mortality of COVID-19 patients in the largest Navy hospitals in Pakistan. Study Design: Retrospective chart review. Place and Duration of Study: Department of Medicine, Pakistan Navy Station Shifa Hospital, Karachi Pakistan, from Apr to May 2020. Methodology: All patients who died in the Intensive care unit of Pakistan Navy Station Shifa Hospital, Karachi during study period, having polymerase chain reaction positive COVID-19 infection were included. The data recorded included basic demographics (age, gender and length of stay in hospital), documentation of co-morbidities (e.g. diabetes mellitus, ischemic heart disease and other medical and surgical problems), need for mechanical ventilation and most probably cause or contributory factor to the death of the patient. Descriptive statistics were used for calculating mean and frequencies. Chi-square test was used to determine the association between variables of the study, Results: A total of 22 cases were included. There were 21 males. The mean age was 65.7 years. Most 12(56.5%) of the patients were more than 65 years of age. Diabetes Mellitus was the most common risk factor in 15(69%) patients followed by hyperten-sion 13(59%) and ischemic heart disease in 10(45%). The hospital admission ranged from 1 to 19 days with a mean of 7.13 days. Conclusion: We identified length of stay, mechanical ventilation, age &gt;65 years, pneumonia and DIC are the potential risk factors for in-hospital mortality in severely ill COVID-19 patients. This audit can guide the clinicians working in resource constrained areas, ....

Prognostic value of inflammation-related model in hepatitis B acute-on-chronic liver failure.

Acute-on-chronic liver failure (ACLF) is characterized by rapid onset, rapid development and a high short-term mortality rate. Systemic inflammation exerts an effect on the disease progression of ACLF. The purposes of this study were to explore the clinical significance that the inflammatory response has on the disease process of hepatitis B virus acute-on-chronic liver failure (HBV-ACLF) patients, to further compare the values of different inflammation-related biomarkers in the prognosis evaluation of HBV-ACLF patients, and to combine inflammatory-related markers to establish a new prediction model. Baseline admission data and 90-day outcomes were collected from 247 patients who met the inclusion criteria. According to the 90-day survival situation, they were divided into a survival group and a death group. The differences in baseline data and inflammation levels between the 2 groups were compared. A regression model was used to analyze the risk factors for 90-day mortality and establish a new model. The study found that the differences between the survival group and the death group were statistically significant in terms of age, total bilirubin (Tbil), prothrombin time (PT), international standardized ratio (INR), inflammation level, and model for end-stage liver disease (MELD) series scores (p < 0.05). The monocyte-to-lymphocyte ratio (MLR)-integrated iMELD model (MLR-iMELD) can effectively predict the 90-day survival rate of HBV-ACLF patients. The area under the receiver operating characteristic (ROC) curve (AUROC) of the new model was 0.792, and the best cutoff for predicting the prognosis of 90 days for patients was -0.33 (sensitivity 0.577 and specificity 0.898). The higher the level of inflammation in patients with HBV-ACLF, the greater the risk of 90-day death. Compared with other inflammation-related markers, the MLR-iMELD model can better predict the 90-day survival rate of HBV-ACLF patients.

Using Machine Learning and Feature Importance to Identify Risk Factors for Mortality in Pediatric Heart Surgery.

Background: The objective of this IRB-approved retrospective monocentric study was to identify risk factors for mortality after surgery for congenital heart defects (CHDs) in pediatric patients using machine learning (ML). CHD belongs to the most common congenital malformations, and remains the leading mortality cause from birth defects. Methods: The most recent available hospital encounter for each patient with an age <18 years hospitalized for CHD-related cardiac surgery between the years 2011 and 2020 was included in this study. The cohort consisted of 1302 eligible patients (mean age [SD]: 402.92 [±562.31] days), who were categorized into four disease groups. A random survival forest (RSF) and the 'eXtreme Gradient Boosting' algorithm (XGB) were applied to model mortality (incidence: 5.6% [n = 73 events]). All models were then applied to predict the outcome in an independent holdout test dataset (40% of the cohort). Results: RSF and XGB achieved average C-indices of 0.85 (±0.01) and 0.79 (±0.03), respectively. Feature importance was assessed with 'SHapley Additive exPlanations' (SHAP) and 'Time-dependent explanations of machine learning survival models' (SurvSHAP(t)), both of which revealed high importance of the maximum values of serum creatinine observed within 72 h post-surgery for both ML methods. Conclusions: ML methods, along with model explainability tools, can reveal interesting insights into mortality risk after surgery for CHD. The proposed analytical workflow can serve as a blueprint for translating the analysis into a federated setting that builds upon the infrastructure of the German Medical Informatics Initiative.

Depression in Cardiac Patients Is a Major Cardiovascular Event Risk Factor: A 12-Month Observational Study.

Background: Depression is a known factor in poor cardiovascular outcomes but is often underassessed in cardiac units. This study evaluates the impact of depression on cardiovascular outcomes in patients undergoing cardiac interventions. Methods: The study included 133 patients who underwent uncomplicated procedures for degenerative aortic valve stenosis (n = 40), acute coronary syndrome (n = 29), or chronic coronary artery disease (n = 64). Depression was assessed using the Beck Depression Inventory (BDI) and Hamilton Depression Rating Scale (HAM-D). The primary endpoint was a major adverse cardiac and cerebrovascular event (MACCE). Patients were followed up for 12 months. Cox proportional hazards analysis was used to identify MACCE risk factors. Results: Depression was more frequently screened by HAM-D than BDI (42.9% vs. 30.8%, p < 0.001). During follow-up, 26 (19.5%) MACCEs occurred. In univariate analysis, risk factors included BDI score ≥ 11, HAM-D score ≥ 8, diabetes on insulin, anticoagulant use, atrial fibrillation, and serum creatinine level ≥ 130 µmol/L. Depression in the BDI increased the risk of the MACCE 3.6-fold (95%CI: 1.64-8.0, p = 0.001), whereas in the HAM-D, it increased the risk 4.9-fold (95%CI: 1.97-12.24, p < 0.001). Multivariate analysis showed HAM-D score ≥ 8 as the strongest predictor of MACCE (HR: 3.08, 95%CI: 1.18-8.08). Conclusions: Depression is a common finding in cardiovascular patients, and it is a strong risk factor for one-year cardiovascular mortality and adverse event risk. Therefore, we believe that common guidelines should be elaborated between relevant psychiatry and cardiology scientific societies.

Association between D-dimer-to-albumin ratio and 28-days all-cause mortality in patients with sepsis

We aimed to investigate the correlation between the serum D-dimer (D-D) to albumin (ALB) ratio (DAR) and 28-day all-cause mortality in patients with sepsis. Data from sepsis patients admitted to the intensive care unit (ICU) of Wuhan Fourth Hospital from October 2021 to January 2024 were collected. Univariate cox analysis was performed for mortality factors in sepsis patients, and multiple cox regression models were used to analyze independent mortality risk factors. The receiver operating characteristics (ROC) curve was used to analyze the value of DAR in predicting sepsis mortality, and the Kaplan–Meier method was used to plot the survival curve. A total of 833 patients with sepsis in the ICU of our hospital were selected and divided into alive group (n = 574) and death group (n = 171) according to their 28-day survival. In the death group, D-D and DAR levels were higher, while ALB levels was lower than in the alive group. Spearman analysis found that DAR level were positively correlated with APACHE II and SOFA scores. Multivariate cox regression analysis showed that DAR was an independent predictor of all-cause mortality within 28 days of admission for sepsis patients (HR = 17.956, 95% CI 3.435–93.851, p < 0.001). The ROC curve results showed that the cut-off value of DAR was 0.068, with a sensitivity of 78.4% and a Youden index of 0.375, predicting mortality in sepsis patients, with an area under curve (AUC) of 0.767 (95% CI 0.744–0.790, P < 0.001). Further analysis divided patients into low DAR (DAR < 0.068) and high DAR (DA ≥ 0.068) groups based on the optimal cut-off value. Kaplan–Meier analysis found higher mortality in the high DAR group. DAR is an independent predictor of all-cause mortality within 28 days of admission in sepsis patients. Combining these two indicators can improve clinical treatment guidance and reduce the risk of death.

Hypothermia-Prevalence and risk factors in neonates admitted to a neonatal unit in Tanzania.

We aimed to study the prevalence of hpyothermia among neonates, the association between admission temperature and neonatal mortality, and the impact of radiant warmers. In an observational prospective study, we included 1988 neonates born at Haydom Lutheran Hospital, Tanzania, and admitted to the neonatal unit from 1 January 2018 to 31 December 2022. We explored risk factors for hypothermia (<36.0°C, primary outcome) and newborn mortality by admission temperature (secondary outcome) with adjusted odds ratios (aOR) and 95% confidence intervals (CI) for birth weight and bag and mask ventilation. Hypothermia was present in 47.0% (n = 935) at admission, 46.9% (n = 932) were normothermic or mildly hypothermic (36.0-37.5°C), and 6.1% (n = 121) hyperthermic. Of those admitted to the neonatal unit, 217 (10.9%) died. For every 1°C increase in temperature, neonatal mortality decreased by 31% (aOR 0.69, 95% CI 0.59-0.82). Admission temperature <34.5°C was strongly associated with mortality (aOR 3.56, 1.87-6.79). Mild hypothermia (36.0-36.5°C) was not associated with mortality (aOR 1.30, 0.72-2.37). Risk factors for hypothermia were bag and mask ventilation (aOR 2.53, 2.07-3.11) and low birth weight. The introduction of radiant warmers from 1 May 2022 was associated with a decrease in hypothermia (aOR 0.54, 0.41-0.72). Hypothermia is prevalent even in tropical settings and maintaining normothermia after birth is critical and achievable for reducing neonatal mortality.

Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study

BackgroundHeart failure combined with hypertension is a major contributor for elderly patients (≥ 65 years) to in-hospital mortality. However, there are very few models to predict in-hospital mortality in such elderly patients. We aimed to develop and test an individualized machine learning model to assess risk factors and predict in-hospital mortality in in these patients.MethodsFrom January 2012 to December 2021, this study collected data on elderly patients with heart failure and hypertension from the Chongqing Medical University Medical Data Platform. Least absolute shrinkage and the selection operator was used for recognizing key clinical variables. The optimal predictive model was chosen among eight machine learning algorithms on the basis of area under curve. SHapley Additive exPlanations and Local Interpretable Model-agnostic Explanations was employed to interpret the outcome of the predictive model.ResultsThis study ultimately comprised 4647 elderly individuals with hypertension and heart failure. The Random Forest model was chosen with the highest area under curve for 0.850 (95% CI 0.789–0.897), high accuracy for 0.738, recall 0.837, specificity 0.734 and brier score 0.178. According to SHapley Additive exPlanations results, the most related factors for in-hospital mortality in elderly patients with heart failure and hypertension were urea, length of stay, neutrophils, albumin and high-density lipoprotein cholesterol.ConclusionsThis study developed eight machine learning models to predict in-hospital mortality in elderly patients with hypertension as well as heart failure. Compared to other algorithms, the Random Forest model performed significantly better. Our study successfully predicted in-hospital mortality and identified the factors most associated with in-hospital mortality.

Establishing a Multifaceted Comprehensive Maternity Cohort Facilitates Understanding of How Environmental Exposures Impact Perinatal Health.

China's "three-child policy", implemented in response to population aging, has made the protection of maternal and infant health an urgent priority. In this environmental and medical big-data era, the Zhejiang Environmental and Birth Health Research Alliance (ZEBRA) maternity cohort was established with the aim of identifying risk factors for perinatal morbidity and mortality from the perspectives of both observational epidemiology and experimental etiology. Compared with conventional birth cohorts, the inclusion of a maternity cohort allows greater scope for research and places an emphasis on maternal health. In particular, it allows us to focus on pregnant women with a history of pregnancy-related illnesses and those planning to have a second or third child. There are currently many pressing issues in perinatal health, including the risk associations between exogenous together with endogenous factors and the occurrence of perinatal abnormalities, pregnancy complications, and adverse pregnancy outcomes. It is crucial to explore the interaction between environmental exposures and genetic factors affecting perinatal health if we are to improve it. It is also worthwhile to assess the feasibility of the early stage prediction of major perinatal abnormalities. We hope to study this in the ZEBRA cohort and also seek nationwide and international collaborations to establish a multicenter cohort consortium, with the ultimate goal of contributing epidemiological evidence to literature and providing evidence-based insights for global maternal and child healthcare.

Modified Textbook Outcome was a Predictor for Early Mortality After Oral Cancer Surgery.

To explore prognostic factors for early mortality among patients undergoing surgery for oral cavity cancer (OCC) and identify valuable strategies to improve patient outcomes. A total of 397 patients treated by primary tumor resection and neck dissection between 2017 and 2021 were retrospectively analyzed. Univariate and multivariate Cox regression analysis were used to explore the relationships between the study factors and early death (within 12months). Predictors were further incorporated into a nomogram for estimation of 1-year overall survival (OS). The mean age was 57.2 (SD, 9.8)years and 92.9% patients were male. The early death rate was 12.6% overall, 35.6% in patients with pN2-3, 22.3% in patients with tumor size > 3 cm, and 36.2% in patients with lymphovascular invasion. A non-modified textbook outcome (mTO), pN2-3, tumor size > 3 cm, and lymphovascular permeation were independent prognosticators for early mortality. A nomogram with the above-mentioned four factors were created with good discrimination and calibration. Among the pN2-3 or tumor size > 3 cm subgroup, a non-mTO, cancer resource center (CRC) visits, perineural invasion, and lymphovascular permeation were independent prognostic factors for early death. In addition to traditional clinicopathological features, a non-mTO and CRC visits could serve as prognostic factors for early death in OCC. A novel nomogram had good discrimination and calibration. Quality improvements in terms of mTO and patients demanding resource support could improve survival outcomes in OCC.

Analysis of Prognostic Factors for Mortality in Patients With Gastrointestinal Bleeding: Application of Machine Learning Tools

Introduction: Treatment of upper gastrointestinal bleeding (UGIB) is a complex challenge due to the wide range of causes and factors affecting hospitalization outcomes.Objective: To study the impact of various factors on 30-day hospital outcomes using machine learning (ML) tools.Materials and methods: We compiled a retrospective data set that includes clinical, laboratory, and imaging data of 101 patients. The database was divided into 2 groups by UGIB etiology: ulcer and variceal bleedings. Both etiological groups were processed using ML tools in 2 steps: imputation by the MICE (multiple imputation by chained equations) model and factor importance analysis using the Random Forest model.Results: Analysis revealed that the most prognostically valuable parameters in both groups were well-known mortality predictors and emerging predictive factors, such as creatinine, blood pressure, activated partial thromboplastin time, level of consciousness, urea, lactate, comorbidity status, procalcitonin, ferritin, and total protein.Conclusions: The application of advanced tools confirmed the significance of popular and validated mortality predictors and contributed to the development of predictors, both explored and unexplored ones.

Renal tubular damage as an independent risk factor for all-cause and cardiovascular mortality in a community-based population: the Takahata study.

Renal tubular damage plays a crucial role in the development of end-stage kidney disease, a risk factor for cardiovascular events and mortality. However, the relationship between renal tubular damage and all-cause and cardiovascular mortality rates in the general population remains unclear. To address this gap, we conducted a cohort study in the general population using the urinary β2-microglobulin-creatinine ratio (UBCR) as a marker of renal tubular damage. This study included 3427 residents aged ≥ 40years in Takahata, Japan. We examined the association between the UBCR values in single-spot urine samples at enrollment and all-cause and cardiovascular mortality rates within a median follow-up of 9.2years. The participants were divided into two groups based on their UBCR levels (< 300μg/g and ≥ 300μg/g groups). Kaplan-Meier analysis showed a significantly higher incidence of all-cause and cardiovascular mortality rates in the high UBCR group (log-rank P < 0.01). Multivariable Cox proportional hazards model adjusted for age, sex, estimated glomerular filtration rate (eGFR), urine albumin level, smoking, and comorbidities showed a significantly higher hazard ratio of 1.49 (95% confidence interval (CI) 1.10-2.03, P = 0.01) for all-cause mortality and a hazard ratio of 1.73 (95% CI 1.00-2.98, P = 0.048) for cardiovascular mortality in the high-UBCR group. The net reclassification index was significantly improved by adding a high UBCR to the conventional risk factors. UBCR is an independent risk factor for all-cause and cardiovascular mortality in the general population, independent of eGFR and urinary albumin levels.

Risk factors and prognostic impact of new decompensated events in hospitalized patients with decompensated cirrhosis

BackgroundDecompensated cirrhosis (DC) is prone to recurrent episodes of decompensation following the initial event. This study aimed to identify the risk factors for subsequent decompensation and assess their impact on the outcomes of patients hospitalized for DC.MethodsPatients with DC were divided into two groups based on the occurrence of new decompensated events during hospitalization. Logistic regression analysis was employed to identify risk factors for new decompensation. The Cox proportional hazards model was used to evaluate the relationship between new decompensation and short-term mortality risk in these patients.ResultsThe study cohort consisted of 339 patients with DC, with a median age of 57 years. During hospitalization, 83 patients (24.5%) experienced new decompensated events, with bacterial infections (BIs) being the most common (n = 46, 13.6%). Multivariate analysis revealed that the Model for End-Stage Liver Disease (MELD) score at admission (OR = 1.06, 95% CI: 1.02–1.11, P = 0.005) was the sole risk factor for new decompensation during hospitalization. Patients who experienced new decompensation had significantly higher 28-day (28.9% vs. 7.0%, P < 0.001) and 90-day (33.7% vs. 15.2%, P < 0.001) transplant-free mortality compared to those who did not. After adjusting for white cell count, C-reactive protein, and MELD score, new decompensation during hospitalization was identified as an independent risk factor for 28-day and 90-day mortality (HR = 2.63, 95% CI: 1.42–4.87, P = 0.002 and HR = 1.73, 95% CI: 1.04–2.88, P = 0.033, respectively).ConclusionsPatients with high MELD scores are susceptible to new decompensation during hospitalization, and the occurrence of new decompensation adversely affects short-term mortality in patients with DC.

Surgical Outcomes of Patients With Heterotaxy Syndrome - The Japanese Congenital Cardiovascular Surgery Database.

Cardiac malformations are a major component of heterotaxy syndrome and result in significant mortality and morbidity. This multicenter nationwide Japanese study evaluated mortality and morbidity after initial surgical palliation for patients with heterotaxy syndrome and determined predictors for mortality and morbidity among patients enrolled in the study. The Japanese Congenital Cardiovascular Surgery Database (JCCVSD) collects clinical data from 119 domestic institutions specializing in congenital heart disease, covering almost all major congenital heart surgery programs in Japan. Clinical data on preoperative, operative, and postoperative characteristics and survival data within 30 and 90 days were available from the JCCVSD database. Of the 561 patients with heterotaxy syndrome who underwent any of 8 specific initial cardiovascular surgeries, 45 (8.2%) and 75 (13.4%) had died at 30 and 90 days, respectively. Preoperative emergency transport, type of heterotaxy syndrome, low hospital volume, the repair of total anomalous pulmonary vein connection, and the repair of a common atrioventricular valve were identified as significant predictive factors for operative mortality. Improvements in some medical circumstances, such as fetal diagnosis and the patient transport system, will be needed to improve outcomes for severely ill patients with heterotaxy syndrome. This study describes early outcomes for the largest number of main cardiovascular surgeries to date in infants with heterotaxy syndrome.