Mortality Factors Research Articles

A Multicenter Home-based Prehabilitation Intervention in Kidney Transplant Candidates.

Frailty is a modifiable risk factor for morbidity and mortality among kidney transplant (KT) candidates. We previously demonstrated that an 8-wk center-based exercise intervention is associated with improved frailty parameters in patients with advanced chronic kidney disease. This study aimed to adapt the intervention for home-based delivery and examine its feasibility, safety, and acceptability in a multicenter cohort of KT candidates. We conducted a prospective pilot study between January 2021 and November 2023 involving KT candidates from Mayo Clinic in Minnesota and Baylor St. Luke's Medical Center in Texas. Adults approved for KT who were (1) frail or prefrail by the Physical Frailty Phenotype and/or (2) had a Short Physical Performance Battery score ≤10 were enrolled. The exercise intervention consisted of an individualized exercise prescription provided by a Mayo Clinic exercise physiologist followed by 8 weekly phone calls. Feasibility was assessed via retention rates, adverse events were recorded, and acceptability was assessed via survey. Baseline characteristics of the 15 enrolled participants included a median age of 64 y, 73.3% were men, and 73.3% were of White race. Sixty percent of participants completed the intervention. No unanticipated adverse events occurred. Most participants strongly agreed that the exercise intervention was beneficial to their overall health. This pilot study demonstrates that a home-based 8-wk exercise intervention is a promising prehabilitation strategy in KT candidates and provides important preliminary data for future larger, randomized studies.

The Impact of Platelet Transfusion on Prognosis in Adult Burn Patients with Thrombocytopenia: A Propensity Score Matching Analysis

Background and ObjectivesThrombocytopenia is common among burn patients. Platelet transfusion is frequently administered to increase platelet counts. However, it is not clear whether platelets affect the outcome after transfusion among adult burn patients with thrombocytopenia or not. Our aim is to explore whether platelet transfusion affects the prognosis of adult burn patients with thrombocytopenia. Materials and MethodsWe undertook a retrospective analysis of 368 adult burn victims with thrombocytopenia from the Department of Burn at the First Affiliated Hospital of Nanchang University, China, from January 2014 to July 2021. Propensity score matching (PSM) was utilized to reduce the selection bias and confounding factors. After PSM, both platelet transfusion group and no platelet transfusion group had 46 patients. Our primary outcome was 30-day all-cause mortality. ResultsLogistic multivariate regression analysis showed that third-degree burn area [β=-0.040, odds ratio (OR) =1.052, 95% confidence interval (CI) =1.015-1.091] and platelet transfusion (OR =2.227, 95% CI =0.473-10.483) were independent risk factors (P<0.05). KaplanMeier risk curve analysis showed that the 30-day mortality of patients in the platelet transfusion group and no platelet transfusion group were 47.8% and 19.6%, respectively (P<0.05) ConclusionPlatelet transfusion was an independent risk factor for 30-day mortality in adult burn patients with thrombocytopenia.

New Insights on Mechanisms and Therapeutic Targets of Cerebral Edema.

Cerebral Edema (CE) is the final common pathway of brain death. In severe neurological disease, neuronal cell damage first contributes to tissue edema, and then Increased Intracranial Pressure (ICP) occurs, which results in diminishing cerebral perfusion pressure. In turn, anoxic brain injury brought on by decreased cerebral perfusion pressure eventually results in neuronal cell impairment, creating a vicious cycle. Traditionally, CE is understood to be tightly linked to elevated ICP, which ultimately generates cerebral hernia and is therefore regarded as a risk factor for mortality. Intracranial hypertension and brain edema are two serious neurological disorders that are commonly treated with mannitol. However, mannitol usage should be monitored since inappropriate utilization of the substance could conversely have negative effects on CE patients. CE is thought to be related to bloodbrain barrier dysfunction. Nonetheless, a fluid clearance mechanism called the glial-lymphatic or glymphatic system was updated. This pathway facilitates the transport of cerebrospinal fluid (CSF) into the brain along arterial perivascular spaces and later into the brain interstitium. After removing solutes from the neuropil into meningeal and cervical lymphatic drainage arteries, the route then directs flows into the venous perivascular and perineuronal regions. Remarkably, the dual function of the glymphatic system was observed to protect the brain from further exacerbated damage. From our point of view, future studies ought to concentrate on the management of CE based on numerous targets of the updated glymphatic system. Further clinical trials are encouraged to apply these agents to the clinic as soon as possible.

Burden of disease attributable to risk factors: Estimates of the Global Burden of Disease from 1990 to 2021

ObjectivesAnalyze the burden of diseases attributable to risk factors (RF) in Brazil according to age, sex, and Brazilian states between 1990 and 2021. MethodsThis study used data from the Global Burden of Disease study 1990 to 2021. The metrics used in this analysis included: mortality rates, disability-adjusted life years (DALYs) and Summary Exposure Value (SEV). A ranking of the risk factors was created by highlighting the changes between 1990 and 2021, according to sex, age group, and Brazilian state. RF were analyzed according to the Socio-Demographic Index (SDI). ResultsDecline the risk factors of tobacco (−50.2 %), environmental: water, sanitation and hand washing (−58.0 %), and air pollution (−45.0 %), as well as an increase in the burden attributable to BMI (+78.4 %), alcohol consumption (+15.7 %). High systolic blood pressure ranked first in all states in 2021, followed by high blood glucose; tobacco ranking third in most states. The burden of diseases attributable to RFs in Brazil varied considerably between men and women, age groups, and states. Trends in the period from 1990 to 2021 showed a strong correlation with the SDI, better results being observed in states with higher SDI. ConclusionsHigh blood pressure, high BMI and tobacco are the main risk factors for mortality and DALYs in 2021. The burden of disease has a high correlation with socio-economic indicator (SDI). It is important to strengthen public policies that promote healthy lifestyles, thus reducing disease and death.

Percutaneous radiofrequency ablation of hepatocellular carcinomas abutting the right posterior diaphragm: factors associated with tumor recurrence and overall survival.

Radiofrequency ablation (RFA) of subphrenic hepatocellular carcinomas (HCCs) using ultrasound (US) guidance presents a challenge. To evaluate local tumor progression (LTP) and overall survival (OS) after RFA of right posterior subphrenic HCCs, and to identify the risk factors for LTP and OS after RFA. We screened patients who underwent US-guided RFA for a single HCC <3 cm in the right posterior subphrenic area. Cumulative rates of LTP and OS were compared between multiple- and single-electrode treatments and artificial pleural effusion versus no-effusion groups using Kaplan-Meier curves and the log-rank test. The risk factors for LTP and OS were assessed. A total of 36 patients were included. The cumulative 5-year and 10-year LTP rates were 32.9% and 39.6%, respectively, and the corresponding OS rates were 72.2% and 48.7%, respectively. The multiple-electrode group had significantly lower cumulative LTP rates compared to the single-electrode group (P < 0.001). The group receiving artificial pleural effusion showed a trend towards lower LTP rates than the no-effusion group (P = 0.076). The albumin-bilirubin (ALBI) grade was the only risk factor for LTP (hazard ratio [HR] = 4.17, 95% confidence interval [CI] = 1.26-14.55; P = 0.020). A lower albumin level was a risk factor for mortality (HR = 0.24, 95% CI = 0.07-0.79; P = 0.020). US-guided RFA with multiple electrodes and artificial pleural effusion tends to be linked with lower LTP rates. The ALBI grade and serum albumin level are risk factors for LTP and OS, respectively.

Differences Between Patients with Probable UIP and Definite UIP on HRCT in Idiopathic Pulmonary Fibrosis: A Real-World Cohort Study

Background: Both a probable usual interstitial pneumonia (UIP) pattern (p-UIP) and a definite UIP pattern (d-UIP) on high-resolution computed tomography (HRCT) are sufficient to establish a diagnosis of idiopathic pulmonary fibrosis (IPF) without the need for a surgical lung biopsy, according to the 2022 IPF guidelines. However, it remains unknown whether patients with p-UIP and d-UIP have similar disease behaviors and clinical courses. Material and Methods: We retrospectively collected clinical data of patients with IPF and divided the patients into two groups according to their HRCT patterns: a p-UIP group and a d-UIP group. The baseline characteristics, survival rates, and pulmonary function tests were compared between the two groups. The risk factors for mortality were determined by Cox regression in p-UIP and d-UIP separately. Results: There were 304 patients in the p-UIP group and 480 patients in the d-UIP group. Patients in the d-UIP group were more likely to have smoking histories (p &lt; 0.001) and had lower baseline FVC% (74% vs. 77%, p = 0.021) and DLCO% (50% vs. 58%, p &lt; 0.001). Survival rates were higher in p-UIP compared with d-UIP (p = 0.004). There were no differences in changes in FVC% or DLCO% between the two groups. Baseline DLCO% was the only independent risk factor for mortality in p-UIP. Baseline FVC% was independently associated with mortality in d-UIP. Symptom of cough was a risk factor for disease progression (OR = 1.2, p = 0.002) in p-UIP, while symptom of dyspnea might be associated with disease progression in d-UIP (OR = 2.7, p = 0.065). Male patients (OR = 1.88, p = 0.002) with a smoking history (OR = 1.16, p = 0.002) were at higher risk of developing d-UIP. Conclusions: We observed the different disease trajectories between p-UIP and d-UIP. P-UIP on HRCT might identify a subgroup of IPF patients who are in the early stage with a better prognosis.

Dynamics of Natural Mortality Factors of Immature Diatraea saccharalis (Fabricius) (Lepidoptera: Crambidae) in Sugarcane Adjacent to Forest Fragments

ABSTRACTPest regulation may be favoured in crop fields adjacent to semi‐natural vegetation such as fragments of the Atlantic Forest in Southeastern Brazil. Therefore, the objective of this study was to analyse the dynamics of mortality factors for eggs and larvae of Diatraea saccharalis (Lepidoptera: Crambidae) in sugarcane adjacent to two types of forest fragments (Plateau and Gallery) at two distances from these fragments during two growing seasons. In each area (seven sugarcane plots), two 50 m long transects were established, parallel and spaced at 5 and 100 m from the field edge, and cohorts of the insect at each stage of development were monitored. The collected data were used to construct an ecological life table and determine the main mortality factors. Natural mortality factors that could not be characterised were grouped as unknown. In both seasons and stages of development observed, there was no difference in mortality between the two types of forest fragments (Plateau and Gallery) or between the two distances from the forest. For the egg stage, the mortality factors were classified as inviable due to infertility, predation, parasitism, desiccation and dislodgement. In both seasons, there was a significant difference in the natural mortality factors of D. saccharalis, with predation distinct from the others. Ants (Hymenoptera: Formicidae) and green lacewings (Neuroptera: Chrysopidae) were the most frequent predatory agents and occurred at both distances and types of forest fragments. For the larval stage, the mortality factors were classified as predation, parasitism, drowning and unknown, with the unknown group differing from the others. Unknown factors might have included predation, larval movement towards other plants and displacement caused by wind after hatching. Overall, predation is a key mortality component of D. saccharalis suppression. Therefore, agricultural practices focused on the conservation of natural enemies such as predators may provide more sustainable management.

Antihypertensive Drug Recommendations for Reducing Arterial Stiffness in Patients With Hypertension: Machine Learning-Based Multicohort (RIGIPREV) Study.

High systolic blood pressure is one of the leading global risk factors for mortality, contributing significantly to cardiovascular diseases. Despite advances in treatment, a large proportion of patients with hypertension do not achieve optimal blood pressure control. Arterial stiffness (AS), measured by pulse wave velocity (PWV), is an independent predictor of cardiovascular events and overall mortality. Various antihypertensive drugs exhibit differential effects on PWV, but the extent to which these effects vary depending on individual patient characteristics is not well understood. Given the complexity of selecting the most appropriate antihypertensive medication for reducing PWV, machine learning (ML) techniques offer an opportunity to improve personalized treatment recommendations. This study aims to develop an ML model that provides personalized recommendations for antihypertensive medications aimed at reducing PWV. The model considers individual patient characteristics, such as demographic factors, clinical data, and cardiovascular measurements, to identify the most suitable antihypertensive agent for improving AS. This study, known as the RIGIPREV study, used data from the EVA, LOD-DIABETES, and EVIDENT studies involving individuals with hypertension with baseline and follow-up measurements. Antihypertensive drugs were grouped into classes such as angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), β-blockers, diuretics, and combinations of diuretics with ACEIs or ARBs. The primary outcomes were carotid-femoral and brachial-ankle PWV, while the secondary outcomes included various cardiovascular, anthropometric, and biochemical parameters. A multioutput regressor using 6 random forest models was used to predict the impact of each antihypertensive class on PWV reduction. Model performance was evaluated using the coefficient of determination (R2) and mean squared error. The random forest models exhibited strong predictive capabilities, with internal validation yielding R2 values between 0.61 and 0.74, while external validation showed a range of 0.26 to 0.46. The mean squared values ranged from 0.08 to 0.22 for internal validation and from 0.29 to 0.45 for external validation. Variable importance analysis revealed that glycated hemoglobin and weight were the most critical predictors for ACEIs, while carotid-femoral PWV and total cholesterol were key variables for ARBs. The decision tree model achieved an accuracy of 84.02% in identifying the most suitable antihypertensive drug based on individual patient characteristics. Furthermore, the system's recommendations for ARBs matched 55.3% of patients' original prescriptions. This study demonstrates the utility of ML techniques in providing personalized treatment recommendations for antihypertensive therapy. By accounting for individual patient characteristics, the model improves the selection of drugs that control blood pressure and reduce AS. These findings could significantly aid clinicians in optimizing hypertension management and reducing cardiovascular risk. However, further studies with larger and more diverse populations are necessary to validate these results and extend the model's applicability.

Sex Differences in Clinical Features in Gout: A Nationwide Retrospective Cohort Study

Background: Patients with gout have several coexisting conditions that impact mortality. We analyzed the differences in clinical manifestations among Korean patients with gout and compared the causes of death based on sex using data from the Korean National Health Insurance Service-National Sample Cohort database. Methods: We included adults with gout receiving urate-lowering therapy (ULT) from 2002 until 2019. The clinical features and causes of death were compared between male and female patients. Multivariate Cox regression was performed to identify the risk factors contributing to all-cause mortality. Results: The results showed that female patients were older at the start of ULT and had more comorbidities. The most common cause of death among all patients with gout was chronic kidney disease (CKD). When observed separately by sex, lung cancer is the leading cause in males, versus CKD in females. Multivariate Cox analysis showed that old age at ULT start, low body mass index (BMI), current smoking, diabetes, CKD, cerebrovascular disease, malignancy, and low hemoglobin were significant risk factors for all-cause mortality in males; however, old age at ULT start, low BMI, CKD, malignancy, and low hemoglobin were significant risk factors in females. Conclusions: The clinical features and cause of death were different between male and female patients with gout, suggesting that treatment strategies for gout should be established differently depending on sex.

Extraperitoneal Open Radical Cystectomy: A New Standard in Frail Patients with Muscle-Invasive Bladder Cancer?

Background/Objectives: Radical cystectomy (RC) represents one of the most complex and morbid surgical procedures in the field of Urology. Extraperitoneal open RC has emerged as an alternative to the traditional transperitoneal approach for the treatment of muscle-invasive bladder cancer. Frailty is one of the most important risk factors for perioperative morbidity and mortality, and this category of patients can benefit the most from the extraperitoneal approach. The purpose of this study was to evaluate the feasibility and the safety of extraperitoneal open RC in our experience; Methods: We retrospectively collected the data of 75 frail patients who underwent an extraperitoneal open RC, performed by a single experienced surgeon. We assessed their frailty status using the simplified frailty index (sFI). We recorded data regarding general characteristics, intraoperative, pathological, and postoperative complications, and mortality (within 90 days); Results: We analyzed 61 males and 14 females with an sFI equal to or higher than 3. The median age was 77 years. Fifty-one patients had an ASA score of 3 or more. Sixty procedures were with radical intention, while fifteen were palliative. Cutaneous ureterostomy was performed in 70 cases and extraperitonized ileal conduit in five cases. The median operative time was 150 min. The median blood loss was 400 mL. The median time to flatus was 2 days. The median postoperative stay was 7 days. Thirteen patients had Clavien-Dindo III or IV complications. Two patients died in first 90 days postoperatively; Conclusions: The extraperitoneal open RC in frail patients was demonstrated to be a feasible and safe alternative approach in definitive treatment or a palliative setting in our experience.

Comparative Ten-Year Outcomes in Chronic and Acute Coronary Syndrome Patients Undergoing Invasive Diagnostics - Insights from the KORONEF Registry

Background: This study aimed to characterize acute coronary syndrome (ACS) patients undergoing invasive diagnostics and to evaluate prognostic factors for all-cause mortality over a 10-year follow-up period. Methods: The KORONEF study was a prospective, observational, single-center study that enrolled 492 patients, of whom 467 had confirmed coronary artery disease (CAD). Baseline demographic, clinical, laboratory, and procedural data were analyzed, focusing on the differences between ACS and chronic coronary syndrome (CCS) patients. Results: Males made up the majority of both the CCS and ACS groups (62.2% vs. 63.6%, p = 0.773), with no statistically significant difference in patient age between the CCS and ACS subpopulations (64.9 ± 9.5 vs. 63.7 ± 10.3, p = 0.106). The 10-year all-cause mortality was 29.8%, with no statistically significant difference between ACS and CCS patients. However, statistically significantly more patients with CCS underwent CABG in the follow-up than ACS patients (9.9% vs. 4.6%, p = 0.042). In a multivariable analysis, in the ACS subgroup, statistically significant predictors of all-cause mortality at 10 years included being between 75 and 90 years old (HR 4.99), not having had a previous stroke (HR 0.27), the absence of cardiac arrest (HR 0.20), and a left ventricular ejection fraction &gt; 60% (HR 0.23). Conclusions: The long-term outcomes of the ACS patients highlight age and left ventricular function as significant prognostic factors, underscoring the importance of these parameters in risk stratification.

Prognostic effects of glycaemic variability on diastolic heart failure and type 2 diabetes mellitus: insights and 1-year mortality machine learning prediction model

BackgroundDiastolic heart failure (DHF) and type 2 diabetes mellitus (T2DM) often coexist, causing increased mortality rates. Glycaemic variability (GV) exacerbates cardiovascular complications, but its impact on outcomes in patients with DHF and T2DM remains unclear. This study examined the relationships between GV with mortality outcomes, and developed a machine learning (ML) model for long-term mortality in these patients.MethodsPatients with DHF and T2DM were included from the Medical Information Mart for Intensive Care IV, with admissions (2008–2019) as primary analysis cohort and admissions (2020–2022) as external validation cohort. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to evaluate the associations of GV with 90-day, 1-year, and 3-year all-cause mortality. The primary analysis cohort was split into training and internal validation cohorts, then developing ML models for predicting 1-year all-cause mortality in training cohort, which were validated using the internal and external validation cohorts.Results2,128 patients with DHF and T2DM were included in primary analysis cohort (meidian age 71.0years [IQR: 62.0–79.0]; 46.9% male), 498 patients with DHF and T2DM were included in the external validation cohort (meidian age 75.0years [IQR: 67.0–81.0]; 54.0% male). Multivariate Cox proportional hazards models showed that high GV tertiles were associated with higher risk of 90-day (T2: HR 1.45, 95%CI 1.09–1.93; T3: HR 1.96, 95%CI 1.48–2.60), 1-year (T2: HR 1.25, 95%CI 1.02–1.53; T3: HR 1.54, 95%CI 1.26–1.89), and 3-year (T2: HR 1.31, 95%CI: 1.10–1.56; T3: HR 1.48, 95%CI 1.23–1.77) all-cause mortality, compared with lowest GV tertile. Chronic kidney disease, creatinine, potassium, haemoglobin, and white blood cell were identified as mediators of GV and 1-year all-cause mortality. Additionally, GV and other clinical features were pre-selected to construct ML models. The random forest model performed best, with AUC (0.770) and G-mean (0.591) in internal validation, with AUC (0.753) and G-mean (0.599) in external validation.ConclusionGV was determined as an independent risk factor for short-term and long-term all-cause mortality in patients with DHF and T2DM, with a potential intervention threshold around 25.0%. The ML model incorporating GV demonstrated strong predictive performance for 1-year all-cause mortality, highlighting its importance in early risk stratification management of these patients.

Anatomic and non-anatomic substrates in infants with two ventricles undergoing aortic arch repair.

We sought to examine the relative importance of surgical lesion complexity versus the presence of genetic/syndromic/extracardiac anomalies (GSAs) in determining survival, morbidity or need for reinterventions following repair for aortic arch hypoplasia. A single-centre, retrospective cohort study of infants undergoing biventricular aortic arch repair via sternotomy from 2010 to 2021 was conducted. Survival analysis was performed using Kaplan-Meier methods, with additional Bayesian survival modelling for subgroups. Composite morbidity comprised respiratory, renal, neurologic, or sepsis-related complications. Of 83 included infants, n = 13/83 (15.7%) had complex repairs; 27/83 (32.5%) were GSA+. Operative mortality was significantly higher in GSA+ versus GSA- patients (18.5% vs. 1.8%; p = 0.01), though not for complex versus non-complex repairs. Overall 10-year Kaplan-Meier survival was 86.7%. Bayesian modelling suggested equivalent post-discharge attrition in non-complex/GSA+ and complex/GSA- patients, with the poorest outcomes in complex/GSA+ patients; non-complex/GSA- patients had 100% survival. GSA+ patients exhibited higher composite morbidity (44.4% vs. 7.1% in GSA- p < 0.001), with their mode of death seemingly related to a high incidence of respiratory and neurological morbidity, notably in Dandy-Walker syndrome. The 10-year freedom from arch reinterventions was 87.7%; neither complexity, GSA status, nor post-repair peak arch velocity predicted the need for arch reinterventions. Whilst anatomic complexity may have been somewhat neutralised as a risk factor for operative mortality, in contrast to GSA+ status, there is further post-discharge attrition attributable to complexity or GSA+ status, with additive risk effects. Morbidity directly related to certain syndromes underlies some of this risk. Non-anatomic substrates represent a persistent limitation to outcomes of surgical aortic arch repair in infants.

Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models

BackgroundSuicidal behaviors, which may lead to death (suicide) or survival (suicide attempt), are influenced by various factors. Identifying the specific risk factors for suicidal behavior mortality is critical for improving prevention strategies and clinical interventions. Predicting the outcomes of suicidal behaviors can help identify individuals at higher risk of death, enabling timely and targeted interventions. This study aimed to determine the critical risk factors associated with suicidal behavior mortality and identify an effective classification model for predicting suicidal behavior outcomes.Materials and methodsThis study utilized data recorded in the suicidal behavior registry system of hospitals in Ilam Province. In the first phase, duplicate records were removed, and the data was numerically encoded via Python version 3.11; then, the data was analyzed using chi-square and Fisher’s exact tests in SPSS version 22 software to identify the factors influencing suicidal behavior mortality. In the second phase, missing data were removed, and the dataset was standardized. Five binary classification algorithms were utilized, including Random Forest, Logistic Regression, and Decision Trees, with hyperparameters optimized using the area under the receiver operating characteristic curve (AUC) and F1 score metrics. These models were compared based on accuracy, recall, precision, F1 score, and AUC.ResultsAmong 3833 cases of suicidal behavior in various hospitals in Ilam Province, the results indicated that the method of suicidal behavior (P < 0.001), reason for suicidal behavior (P < 0.001), age group (P < 0.001), education level (P < 0.001), marital status (P = 0.004), and employment status (P = 0.042) were significantly associated with suicide. Variables such as the season of suicidal behavior, gender, father’s education, and mother’s education were not significantly related to suicidal behavior mortality. Furthermore, the random forest model demonstrated the highest area under the ROC curve (0.79) and the highest classification accuracy and F1 score on both the training data (0.85 and 0.2, respectively) and test data (0.86 and 0.31, respectively) for predicting suicidal behaviors outcomes among the models tested.ConclusionThis study identified key factors such as older age, lower education, divorce or widowhood, employment, physical methods, and socioeconomic issues as significant predictors of suicidal behavior outcomes. A combination of statistical models for feature selection and machine learning algorithms for prediction was used, with Random Forest showing the best performance. This approach highlights the potential of integrating statistical methods with machine learning to improve suicide risk prediction and intervention strategies.

Prevalence and risk factors of mortality among heart failure patients in low resource setting hospitals: a multicenter prospective observational study

Prevalence and risk factors of mortality among heart failure patients in low resource setting hospitals: a multicenter prospective observational study

Establishment and validation of clinical prediction model and prognosis of perioperative pneumonia in elderly patients with hip fracture complicated with preoperative acute heart failure

BackgroundElderly hip fracture was a common orthopedic emergency with high perioperative complication risks. Combined with preoperative acute heart failure, the risk increases further, with pneumonia being a common complication. The aim of this study was to construct and evaluate risk factor prediction models for perioperative pneumonia in these patients and to explore prognostic factors.MethodsA retrospective study design was used to collect data on elderly patients with hip fracture combined with preoperative acute heart failure at the Third Hospital of Hebei Medical University from January 2020 to December 2022. The feature variables were screened by logistic regression and nomogram was constructed. The receiver operating characteristics curve (ROC), decision curve analysis (DCA), and calibration curve were employed to assess the predictive power of the model. Correlation heatmaps and shapley additive explanation (SHAP) were employed to assess key variables and their impact. Employing the Kaplan-Meier curve and Cox regression, the patients’ prognosis was ultimately evaluated.Results535 elderly patients with hip fracture combined with preoperative acute heart failure were included in this study. Logistic regression analysis was used to identify combined respiratory disease, hemoglobin, albumin, neutrophils, and blood glucose as independent danger factors for perioperative pneumonia (p < 0.05). The nomogram was designed to display the outcomes instinctively, with an AUC of 0.819. The model was internally validated by initiating self-sampling 1000 times. The calibration curve indicated that the model had excellent treaty. The DCA curve showed that the model had good validity and clinical practicability. Correlation heatmaps and SHAP were visualized and analyzed. The K-M curves indicated that the prognosis of the non-pneumonia group was better than that of the pneumonia group (p = 0.014). COX regression analysis found that the major risk factors for all-cause mortality in patients with acute heart failure(AHF) were age, brain natriuretic peptide, platelet count, and combined respiratory failure (p < 0.05).ConclusionThe prediction model, established in this study, was highly accurate and proved a potent instrument for clinical evaluation of the perioperative pneumonia risk of elderly hip fracture patients with preoperative acute heart failure. We hope that this study can reduce the occurrence of perioperative pneumonia in patients and improve the prognosis of patients.

Short-Term and Long-Term Mortality Risk After Preterm Birth

Preterm birth (PTB) is a leading cause of neonatal mortality. However, evidence on mortality beyond the neonatal period is limited, especially in North America. To examine associations of PTB with all-cause and cause-specific mortality from birth through 23 to 36 years of age. This population-based matched cohort study of live births in Canada included individuals born between January 1, 1983, and December 31, 1996, and followed up until December 31, 2019. Data were analyzed from June 1, 2023, to April 30, 2024. PTBs, between 24 and 37 weeks' gestation (with gestational age [GA]-specific subcategories of 24 to 27 weeks, 28 to 31 weeks, 32 to 33 weeks, and 34 to 36 weeks) compared with term births (37-41 weeks' gestation). All-cause mortality and cause-specific mortality were the main outcomes. Risk differences (RDs) and risk ratios (RRs) were estimated for all-cause mortality using log-binomial regressions and hazard ratios were estimated for cause-specific mortality using Cox proportional hazards regression models (censoring individuals who died from other causes) within prespecified age intervals (ages 0-11 months and ages 1-5, 6-12, 13-17, 18-28, and 29-36 years). Observed confounding was accounted for using coarsened exact matching on baseline characteristics. Of 4 998 560 births (54.2% male), 6.9% were born preterm (with GA-specific subcategories of 0.3% born at 24-27 weeks, 0.6% at 28-31 weeks, 0.8% at 32-33 weeks, and 5.1% at 34-36 weeks). During a median of 29 years of follow-up, 72 662 individuals died (14 312 born preterm and 58 350 at term). PTB was associated with an increased risk of death in all age intervals, with the highest RDs and RRs from birth through infancy (ages 0-11 months) (RD, 2.29% [95% CI, 2.23%-2.35%]; RR, 11.61 [95% CI, 11.09-12.15]) and in early childhood (ages 1-5 years) (RD, 0.34% [95% CI, 0.31%-0.36%]; RR, 2.79 [95% CI, 2.61-2.98]) and the lowest RDs and RRs among those between ages 18 and 28 years (RD, 0.07% [95% CI, 0.04%-0.10%]; RR, 1.13 [95% CI, 1.07-1.19]). We identified increased risks of mortality associated with several causes, including respiratory, circulatory, and digestive system disorders; nervous system, endocrine, and infectious diseases; cancers; congenital malformations; and conditions originating in the perinatal period. No associations were found for external causes of deaths. Associations by GA categories suggested lower risks with higher GA. The findings of this population-based matched cohort study suggest that individuals born preterm were at an increased risk of death from birth until their third and fourth decades of life, with higher risks as GA decreased. Some of these associations may have been partly due to underlying health determinants that affected PTB and mortality. These findings suggest that PTB should be recognized as a risk factor for mortality and could inform preventive strategies.

Prevalence and risk factors associated with mortalities in COVID-19 patients in Jeddah, Kingdom of Saudi Arabia

Background: Since the declaration of COVID-19 as a pandemic; researchers have been trying to discern the risk factors determining mortality of the disease. This study aims to explore the risk factors associated with mortalities among COVID-19 patients in Jeddah governorate, Kingdom of Saudi Arabia. Methodology: Through a record-based retrospective study, laboratory-confirmed cases were included in the study. Results: Out of all respondents (n=381) Most of them were symptomatic (82.9%); mainly cough (44.4%), fever (41.2%), sore throat (22.0%), and runny nose (13.1%). The case mortality rate (CMR) accounted for 19(5.0%); it was higher in males (6.0%), non-Saudis (6.1%), and symptomatic patients (5.4%), however, these differences are not statically significant p&gt;0.05 p&lt;0.05. The binary logistic regression revealed that age was the only significant predictor for mortality, and being old age almost doubles the likelihood of mortality with odds ratio (OR=2.318; 95% CI= 1.806-6.672; p=0.007) Conclusion: The current findings add more evidence to the risk factors of mortality in COVID-19 patients. Age is a significant predictor of mortality, which emphasizes the necessity for targeted care for elderly people to reduce their risk of complications, facilitate recovery, and protect their health and well-being during the pandemic.

Evaluation of risk factors for 14-day and 30-day mortality among treatment regimens against Pseudomonas aeruginosa resistant to carbapenem but susceptible to traditional antipseudomonal non-carbapenem β-lactam agents.

Pseudomonas aeruginosa associated with hospital-acquired infection is often resistant to various antibiotics and is associated with high mortality worldwide. The appropriate treatment of Pseudomonas aeruginosa resistant to carbapenems but susceptible to traditional antipseudomonal non-carbapenem β-lactam agents (Car-R/NonCar-S P. aeruginosa) remains unclear. This retrospective study evaluated risk factors for 14-day and 30-day mortality among treatment regimens against Car-R/NonCar-S P. aeruginosa. This study enrolled 180 patients with Car-R/NonCar-S P. aeruginosa infection at Phramongkutklao Hospital between January 2019 and December 2023. The 14-day and 30-day mortality rates were 18.3% and 28.9%, respectively. Bloodstream infection (OR 1.97, 95% CI 0.88-4.43), septic shock (OR 3.3, 95% CI 1.30-8.40), Acute Physiology and Chronic Health Evaluation (APACHE) II < 14 (OR 0.13, 95% CI 0.03-0.54), Sequential Organ Failure Assessment (SOFA) <7 (OR 0.25, 95% CI 0.11-0.56), and Pitt bacteremia score <4 (OR 0.16, 95% CI 0.05-0.47) were associated with 14-day mortality. There was a higher 14-day and 30-day mortality in patients treated with piperacillin/tazobactam or aminoglycosides but there was no significant difference among antipseudomonal antimicrobial agents in the treatment of Car-R/NonCar-S P. aeruginosa infection. We supported the use of traditional antipseudomonal β-lactam agents to treat Car-R/NonCar-S P. aeruginosa infections, however the use of piperacillin/tazobactam might be concerned in some cases and further investigations were needed.

Survivorship in CAR T-cell Therapy Recipients: Infections, Secondary Malignancies, and Non-Relapse Mortality.

Chimeric antigen receptor (CAR) T cell therapy has significantly advanced the treatment of hematologic malignancies, offering curative potential for patients with relapsed or refractory disease. However, the long-term survivorship of these patients is marked by unique challenges, particularly immune deficits and infectious complications, second primary malignancies (SPMs), and non-relapse mortality (NRM). Understanding and addressing these risks is paramount to improving patient outcomes and quality of life. This review explores the incidence and risk factors for non-relapse mortality and long-term complications following CAR T cell therapy. Infections are the leading cause of NRM, accounting for over 50% of cases, driven by neutropenia, hypogammaglobulinemia, and impaired cellular immunity. SPMs, including secondary myeloid and T-cell malignancies, are increasingly recognized, prompting the FDA to issue a black box warning, although their direct link to CAR T cells remains disputed. While CAR T cell-specific toxicities like CRS and ICANS contribute to morbidity, they represent only a minority of NRM cases. The management of these complications is critical as CAR T cell therapy is being evaluated for broader use, including in earlier treatment lines and for non-malignant conditions like autoimmune diseases. CAR T cell therapy has revolutionized cancer treatment, but survivorship is complicated by infections, SPMs, and ultimately endangered by NRM. Prophylactic strategies, close monitoring, and toxicity management strategies are key to improving long-term outcomes.