Mortality Risk Assessment Research Articles

Age-adjusted visceral adiposity index (VAI) is superior to VAI for predicting mortality among US adults: an analysis of the NHANES 2011-2014.

The association of visceral adiposity with mortality in older adults is conflicting. Whether age influences the predicting ability of visceral adiposity(VAI) for mortality remains unknown. This study uncovered the relationship between age-adjusted visceral adiposity index and mortality through the data of NHANES 2011-2014. This study obtained data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014. The age-adjusted visceral adiposity index (AVAI) scores were expressed as quartiles. Receiver operating characteristics (ROC) curve analysis was also applied to compare the predictive ability for mortality. Multivariate weighted Cox regression models were constructed to explore the association between AVAI and mortality. Kaplan-Meier survival curves were conducted for survival analyses. Smooth curve fittings and two-piecewise linear models were applied to explore the relationships between AVAI and mortality. This study recruited 4281 subjects aged ≥ 18years from the NHANES 2011-2014. The AUCs of AVAI were 0.82 (0.79, 0.86) and 0.89 (0.85, 0.92) for predicting all-cause mortality and cardiovascular mortality, which were superior to BMI, WC and VAI (all p < 0.05). AVAI is still an independent predictor for mortality adjusted for confounders. The associations of AVAI with all-cause and cardiovascular mortalities were dose-responsive, with higher AVAI scores indicating higher mortality risks. Age significantly improves the ability of VAI for predicting all-cause and cardiovascular mortality. Age-adjusted VAI is independently associated with mortality risk, and thus could be considered a reliable parameter for assessing mortality risk.

Risk assessment for mortality in patients with ST-elevation myocardial infarction undergoing primary percutaneous coronary intervention: A retrospective cohort study.

Primary percutaneous coronary intervention (PCI) is the treatment of choice in ST-elevation myocardial infarction (STEMI) patients. This study aims to evaluate predictors of in-hospital and long-term mortality among patients with STEMI undergoing primary PCI. In this registry-based study, we retrospectively analyzed patients with STEMI undergoing primary PCI enrolled in the primary angioplasty registry of Sina Hospital. Independent predictors of in-hospital and long-term mortality were determined using multivariate logistic regression and Cox regression analyses, respectively. A total of 1123 consecutive patients with STEMI were entered into the study. The mean age was 59.37 ± 12.15 years old, and women constituted 17.1% of the study population. The in-hospital mortality rate was 5.0%. Multivariate analyses revealed that older age (odds ratio [OR]: 1.06, 95% confidence interval [CI]: 1.02-1.10), lower ejection fraction (OR: 0.97, 95% CI: 0.92-0.99), lower mean arterial pressure (OR: 0.95, 95% CI: 0.93-0.98), and higher white blood cells (OR: 1.17, 95% CI: 1.06-1.29) as independent risk predictors for in-hospital mortality. Also, 875 patients were followed for a median time of 21.8 months. Multivariate Cox regression demonstrated older age (hazard ratio [HR] = 1.04, 95% CI: 1.02-1.06), lower mean arterial pressure (HR = 0.98, 95% CI: 0.97-1.00), and higher blood urea (HR = 1.01, 95% CI: 1.00-1.02) as independent predictors of long-term mortality. We found that older age and lower mean arterial pressure were significantly associated with the increased risk of in-hospital and long-term mortality in STEMI patients undergoing primary PCI. Our results indicate a necessity for more precise care and monitoring during hospitalization for such high-risk patients.

Development of the Umbilical Cord Blood Transplantation-Specific Non-Relapse Mortality Risk Assessment Score: A Study from the Donor/Source and Transplant Complication Working Groups of Jstct

Development of the Umbilical Cord Blood Transplantation-Specific Non-Relapse Mortality Risk Assessment Score: A Study from the Donor/Source and Transplant Complication Working Groups of Jstct

Establishing a High-Quality Pediatric Cardiac Surgery Program in Post-Conflict Regions: A Model for Limited Resource Countries.

Congenital Heart Disease stands as a prominent cause of infant mortality, with notable disparities in surgical outcomes evident between high-income and low- to middle-income countries. This study presents a collaborative partnership between a local governmental entity and an international private organization to establish a high-quality Pediatric Cardiac Surgery Program in a post-conflict limited resource country, Iraq. A descriptive retrospective study analyzed pediatric cardiac surgery procedures performed by a visiting pediatric heart surgery team from October 2021 to October 2022, funded by the Ministry of Health (MOH). We used the STS-EACTS complexity scoring model (STAT) to assess mortality risks associated with surgical procedures. A total of 144 patients underwent 148 procedures. Infants comprised 58.3% of the patients. The most common anomalies included tetralogy of Fallot, ventricular septal defect, and various single ventricle categories, constituting 76% of the patient cohort. The overall surgical mortality rate was 4.1%, with an observed/expected surgical mortality rate of 1.1 (95% CI 0.5, 2.3). There was no significant difference between our observed surgical mortality in Category 2, 3, and 4 and those expected/reported by the STS-EACTS Database (p = 0.07, p = 0.72, and p = 0.12, respectively). The expenses incurred by the MOH for conducting surgeries in Iraq were lower than the alternative of sending patients abroad for the same procedures. The partnership model between a local public entity committed to infrastructure development and funding and an international private organization delivering clinical and training services can provide the foundation for building sustainable, high-quality in situ programs in upper-middle-income countries.

Serum ferritin levels can predict long-term outcomes in patients with metabolic dysfunction-associated steatotic liver disease

ObjectiveHyperferritinaemia is associated with liver fibrosis severity in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), but the longitudinal implications have not been thoroughly investigated. We assessed the role of...

Predicting mortality risk in hospitalized COVID-19 patients: an early model utilizing clinical symptoms

BackgroundDespite global efforts to control the COVID-19 pandemic, the emergence of new viral strains continues to pose a significant threat. Accurate patient stratification, optimized resource allocation, and appropriate treatment are crucial in managing COVID-19 cases. To address this, a simple and accurate prognostic tool capable of rapidly identifying individuals at high risk of mortality is urgently needed. Early prognosis facilitates predicting treatment outcomes and enables effective patient management. The aim of this study was to develop an early predictive model for assessing mortality risk in hospitalized COVID-19 patients, utilizing baseline clinical factors.MethodsWe conducted a descriptive cross-sectional study involving a cohort of 375 COVID-19 patients admitted and treated at the COVID-19 Patient Treatment Center in Military Hospital 175 from October 2021 to December 2022.ResultsAmong the 375 patients, 246 and 129 patients were categorized into the survival and mortality groups, respectively. Our findings revealed six clinical factors that demonstrated independent predictive value for mortality in COVID-19 patients. These factors included age greater than 50 years, presence of multiple underlying diseases, dyspnea, acute confusion, saturation of peripheral oxygen below 94%, and oxygen demand exceeding 5 L per minute. We integrated these factors to develop the Military Hospital 175 scale (MH175), a prognostic scale demonstrating significant discriminatory ability with an area under the curve (AUC) of 0.87. The optimal cutoff value for predicting mortality risk using the MH175 score was determined to be ≥ 3 points, resulting in a sensitivity of 96.1%, specificity of 63.4%, positive predictive value of 58%, and negative predictive value of 96.9%.ConclusionsThe MH175 scale demonstrated a robust predictive capacity for assessing mortality risk in patients with COVID-19. Implementation of the MH175 scale in clinical settings can aid in patient stratification and facilitate the application of appropriate treatment strategies, ultimately reducing the risk of death. Therefore, the utilization of the MH175 scale holds significant potential to improve clinical outcomes in COVID-19 patients.Trial registrationAn independent ethics committee approved the study (Research Ethics Committee of Military Hospital 175 (No. 3598GCN-HDDD; date: October 8, 2021), which was performed in accordance with the Declaration of Helsinki, Guidelines for Good Clinical Practice.

Deep learning-based prediction of in-hospital mortality for sepsis

As a serious blood infection disease, sepsis is characterized by a high mortality risk and many complications. Accurate assessment of mortality risk of patients with sepsis can help physicians in Intensive Care Unit make optimal clinical decisions, which in turn can effectively save patients’ lives. However, most of the current clinical models used for assessing mortality risk in sepsis patients are based on conventional indicators. Unfortunately, some of the conventional indicators have been shown to be inapplicable in the accurate clinical diagnosis nowadays. Meanwhile, traditional evaluation models only focus on a small amount of personal data, causing misdiagnosis of sepsis patients. We refine the core indicators for mortality risk assessment of sepsis from massive clinical electronic medical records with machine learning, and propose a new mortality risk assessment model, DGFSD, for sepsis patients based on deep learning. The DGFSD model can not only learn individual clinical information about unassessed patients, but also obtain information about the structure of the similarity graph between diagnosed patients and patients to be assessed. Numerous experiments have shown that the accuracy of the DGFSD model is superior to baseline methods, and can significantly improve the efficiency of clinical auxiliary diagnosis.

Development of an umbilical cord blood transplantation–specific nonrelapse mortality risk assessment score

AbstractHigher rate of nonrelapse mortality (NRM) remains yet to be resolved in umbilical cord blood transplantation (UCBT). Considering that UCBT has some unique features compared with allogeneic hematopoietic cell transplantation from other graft sources, a UCBT-specific NRM risk assessment system is required. Thus, in this study, we sought to develop a UCBT-specific NRM Risk Assessment (CoBRA) score. Using a nationwide registry database, we retrospectively analyzed 4437 recipients who had received their first single-unit UCBT. Using the backward elimination method, we constructed the CoBRA score in a training cohort (n = 2687), which consisted of recipients age ≥55 years (score 2), hematopoietic cell transplantation–specific comorbidity index ≥3 (score 2), male recipient, graft-versus-host disease prophylaxis other than tacrolimus in combination with methotrexate, performance status (PS) 2 to 4, HLA allele mismatch ≥ 2, refined Disease Risk Index high risk, myeloablative conditioning, and CD34+ cell doses < 0.82 × 105/kg (score 1 in each). The recipients were categorized into 3 groups: low (0-4 points), intermediate (5-7 points), and high (8-11 points) groups according to the CoBRA score. In the validation cohort (n = 1750), the cumulative incidence of NRM at 2 years was 14.9%, 25.5%, and 47.1% (P < .001), and 2-year overall survival (OS) was 74.2%, 52.7%, and 26.3% (P < .001) in the low, intermediate, and high groups, respectively. In summary, the CoBRA score could predict the NRM risk as well as OS after UCBT. Further external validation will be needed to confirm the significance of the CoBRA score.

Sentinel lymph node biopsy is unreliable in predicting melanoma mortality for both younger and older patients.

Melanoma disease patterns vary with patient age. To evaluate sentinel lymph node biopsy (SLNB) in managing melanoma at differing patient ages. Online prediction tools were applied to compare SLNB positivity (SLNB+) and survival risk at patient ages 20-80. Tübingen melanoma data were used to determine variations in the hazard ratio of SLNB+ for mortality at different patient ages. Regardless of tumour thickness, predicted SLNB+ rates were markedly higher than mortality rates for 20-year-old patients. For 80-year-old patients, it is the opposite. If 1000 20-year-olds with a 0.4 mm thickness non-ulcerated melanoma underwent SLNB, 100 would likely be positive. If all 100 were to be offered adjuvant drug therapy (ADT), fewer than three more melanoma deaths in those 1000 patients would be avoided. In total, 97 patients would have received medication they may never have needed. If 1000 80-year-olds with a 3 mm thickness non-ulcerated melanoma underwent SLNB, only 40 would likely be positive. In total, 274 patients would be predicted to die of melanoma, 245 being SLNB negative and 29 SLNB+. ADT linked to SLNB+ could deny treatment to 89% of these high-risk patients. The authors relied on published risk data. SLNB has poor specificity at predicting mortality in young melanoma patients and poor sensitivity in older patients. SLNB is not indicated in managing cutaneous melanoma for patients under 40 or over 60 years of age. Many such patients could be managed with wide local excision alone in their clinician's office-based practice. For all cutaneous melanoma patients at all ages, linking ADT to BAUSSS biomarker, (an algorithm of Breslow thickness, age, ulceration, subtype, sex and Site) rather than SLNB+ is likely more appropriate. BAUSSS provides a more accurate melanoma-specific mortality risk assessment for patients without burdening them with added surgery, hospitalization, costs or morbidity risk.

Association of systemic inflammation response index with mortality risk in older patients with hip fracture: a 10-year retrospective cohort study.

With a rapidly aging global population, the assessment of mortality risk following hip fracture in older adults has received increasing attention. Recently, the system inflammation response index (SIRI) has been identified as a novel prognostic marker to reflect both systemic inflammation and immune status. However, it is not yet known whether SIRI is a potential predictor of subsequent death in hip fracture patients. Therefore, this study aimed to investigate the association between SIRI and mortality in older patients with hip fracture. A total of 1,206 older hip fracture patients undergoing surgery between January 2013 and December 2022 were consecutively derived from our longitudinal database. Patients were divided into three groups according to SIRI tertiles, calculated as neutrophil × monocyte / lymphocyte. Survival status was obtained from medical records or telephone interviews, and the study outcome was all-cause mortality after hip fracture at the longest follow-up. Multivariate Cox proportional hazard model and restricted cubic spline (RCS) regression model were used to evaluate the association between SIRI and mortality. Moreover, a series of sensitivity analyses were conducted to further validate the robustness of the association. During a median follow-up of 43.85 months, 337 patients (27.94%) died. After full adjustment, each unit increase in SIRI was significantly associated with a 2.2% increase in overall mortality (95% confidence interval [CI]: 1.001-1.042, p = 0.029). Similarly, compared with the first tertile of SIRI, the second and third tertile showed a 1.335-fold (95% CI: 1.011-1.762, p = 0.042) and 1.447-fold (95% CI, 1.093-1.917, p = 0.010) higher risk of death. Sensitivity analyses confirmed the stability of the association. Moreover, RCS analysis revealed a positive non-linear relationship between SIRI and mortality (P for nonlinearity = 0.021). High SIRI level at admission was significantly and positively associated with an increased risk of death, suggesting that SIRI may be an independent predictor of mortality in older patients with hip fracture.

Mortality Risk Assessment by SNAP-II and SNAPPE-II among Very Low Birth Weight Newborns- An Observational Study

Introduction: Very Low Birth Weight (VLBW) babies are those with a birth weight of less than 1500 gm and require special care, attention, and resources. However, despite all efforts, their mortality rate remains high. Proper assessment of these neonates is crucial to identify high-risk cases and take early steps to reduce mortality. In addition to technical advances in neonatal care, severity scores have been developed to predict neonatal mortality. Richardson developed the Score for Neonatal Acute Physiology (SNAP-II) and SNAP with Perinatal Extension (SNAPPE-II) as scoring systems for predicting mortality in the Neonatal Intensive Care Unit (NICU). Aim: To assess the usefulness of SNAP-II and SNAPPE-II as predictors of mortality in VLBW neonates. Materials and Methods: This was an observational cross-sectional study involving 145 VLBW neonates admitted to the NICU of North Bengal Medical College and Hospital (NBMCH) from May 2019 to April 2020. Relevant data were collected to assess the mortality risk scores SNAP-II and SNAPPE-II. The outcome of discharge or death was recorded. Data entry was performed using MS excel and analysed using Statistical Package for Social Sciences (SPSS) version 20.0. The relationship between newborn survival and SNAP-II or SNAPPE-II final scores was determined using the Mann- Whitney U test, and the relationship between survival and various SNAP-II and SNAPPE-II score categories was determined using Fisher’s-Exact Test. A p-value of less than 0.05 was considered statistically significant. An ROC curve was generated to determine the best cutoff score for predicting mortality. Results: The mean scores of SNAP-II and SNAPPE-II were higher in babies who expired compared to those who survived. The mean (±SD) SNAP-II scores were 8.96 (±13.865) for survived newborns and 41.08 (±23.174) for expired newborns. The mean (±SD) SNAPPE-II scores were 20.01 (±14.54) for survived newborns and 48.85 (±25.02) for expired newborns. The optimal cutoff values for SNAP-II and SNAPPE-II in predicting mortality were 31.5 and 36, respectively. The sensitivity and specificity of SNAP-II were 83.0% and 89.1%, while for SNAPPE-II they were 69.8% and 89.1%, respectively. Conclusion: The mean SNAP-II and SNAPPE-II scores were higher among expired VLBW neonates compared to those who survived. A SNAP-II score of 31.5 and SNAPPE-II score of 36 were associated with higher mortality, indicating that both scores are effective predictors of mortality regardless of Gestational Ages (GA) and birth weight.

Mortality risk and mood stabilizers in bipolar disorder: a propensity-score-weighted population-based cohort study in 2002-2018.

Accumulating studies have assessed mortality risk associated with mood-stabilizers, the mainstay treatment for bipolar disorder (BD). However, existing data were mostly restricted to suicide risk, focused on lithium and valproate and rarely adequately adjusted for potential confounders. This study aimed to assess comparative mortality risk with all, natural and unnatural causes between lithium, valproate and three frequently prescribed second-generation antipsychotics (SGA), with adjustment for important confounders. This population-based cohort study identified 8137 patients with first-diagnosed BD, who had exposed to lithium (n = 1028), valproate (n = 3580), olanzapine (n = 797), quetiapine (n = 1975) or risperidone (n = 757) between 2002 and 2018. Data were retrieved from territory-wide medical-record database of public healthcare services in Hong Kong. Propensity-score (PS)-weighting method was applied to optimize control for potential confounders including pre-existing chronic physical diseases, substance/alcohol use disorders and other psychotropic medications. PS-weighted Cox proportional-hazards regression was conducted to assess risk of all-, natural- and unnatural-cause mortality related to each mood-stabilizer, compared to lithium. Three sets of sensitivity analyses were conducted by restricting to patients with (i) length of cumulative exposure to specified mood-stabilizer ≥90 days and its medication possession ratio (MPR) ≥90%, (ii) MPR of specified mood-stabilizer ≥80% and MPR of other studied mood-stabilizers <20% and (iii) monotherapy. Incidence rates of all-cause mortality per 1000 person-years were 5.9 (95% confidence interval [CI]: 4.5-7.6), 8.4 (7.4-9.5), 11.1 (8.3-14.9), 7.4 (6.0-9.2) and 12.0 (9.3-15.6) for lithium-, valproate-, olanzapine-, quetiapine- and risperidone-treated groups, respectively. BD patients treated with olanzapine (PS-weighted hazard ratio = 2.07 [95% CI: 1.33-3.22]) and risperidone (1.66 [1.08-2.55]) had significantly higher all-cause mortality rate than lithium-treated group. Olanzapine was associated with increased risk of natural-cause mortality (3.04 [1.54-6.00]) and risperidone was related to elevated risk of unnatural-cause mortality (3.33 [1.62-6.86]), relative to lithium. The association between olanzapine and increased natural-cause mortality rate was consistently affirmed in sensitivity analyses. Relationship between risperidone and elevated unnatural-cause mortality became non-significant in sensitivity analyses restricted to low MPR in other mood-stabilizers and monotherapy. Valproate- and lithium-treated groups did not show significant differences in all-, natural- or unnatural-cause mortality risk. Our data showed that olanzapine and risperidone were associated with higher mortality risk than lithium, and further supported the clinical guidelines recommending lithium as the first-line mood-stabilizer for BD. Future research is required to further clarify comparative mortality risk associated with individual SGA agents to facilitate risk-benefit evaluation of alternative mood-stabilizers to minimize avoidable premature mortality in BD.

A prospective cohort study evaluating the TRISS and TRISS-SpO2 scoring systems for assessing mortality risk in trauma study participants in India.

Globally, trauma cases have significant morbidity and mortality. Hence, various scoring systems have been designed to improve the prognosis in trauma cases. Trauma and Injury Severity Score (TRISS) is one of the widely used models to predict mortality; however, it has certain limitation. We have aimed to evaluate the survival prediction of new model TRISS-oxygen saturation (SpO2) and to compare with original TRISS score in trauma study participants. This was a prospective cohort study conducted on 380 trauma study participants admitted to the surgery department from January 20, 2021, to November 28, 2021. The proposed model includes TRISS-SpO2 which replaces pulse SpO2 instead of revised trauma score in the original TRISS score. Probability of survival (Ps) was calculated for both models using coefficients derived from Walker-Duncan regression analysis analyzed from the Major Trauma Outcome Study. Receiver operating characteristic curve analysis was used to predict model performance and the accuracy was calculated. The mortality rate in the present study was 30 (7.9%). The predictive accuracy of original TRISS score which calculated Ps based on respiratory rate was 97.11%, and for the proposed model of TRISS score which calculated Ps based on SpO2 was found 97.11%, and thus there is no significant difference in the performance. The new proposed model TRISS-SpO2 showed a good accuracy which is similar to original TRISS score. However, the new tool TRISS-SpO2 might be easier to use for robust performance in the clinical setting.

Meta-meta-analysis of the mortality risk associated with MRSA compared to MSSA bacteraemia.

Staphylococcus aureus bacteraemia (SAB) is a bloodstream infection that carries a high risk of exacerbating a diseased state and may result in an increased death rate. The aim of this study was to assess mortality risk in Methicillin Resistant Staphylococcus aureus (MRSA) bacteraemia compared to Methicillin Susceptible Staphylococcus aureus (MSSA) bacteraemia through meta-meta-analyses. The study followed PRISMA guidelines, conducting a comprehensive search in Scopus, PubMed, and Google Scholar. It included full-text systematic reviews and meta-analyses comparing MRSA vs. MSSA bacteraemia, excluding reviews without data pooling and unclear selection criteria. Validity was assessed using QUOROM and AMSTAR. Edwards' Venn diagrams were used to visualized overlaps between primary studies. Aggregated odds ratio (OR) and risk ratios with 95% confidence intervals were calculated using the random-effect model. Heterogeneity was evaluated using the Higgins I2 statistic. The study included 3 meta-analysis studies, a total of 38,159 patients, with 9,056 having MRSA bacteraemia and 29,103 having MSSA bacteraemia. Data were collected from 46 different outcome studies published between 2001 and 2022. The meta-analyses used 7 to 33 primary studies from 1990 to 2020, with no overlap. Odds ratios (ORs) ranged from 1.78 to 2.92, while relative risks (RR) ranged from 1.57 to 2.37 for the included meta-anlysis. The pooled analysis confirmed a higher risk of mortality in patients with MRSA bacteraemia (OR: 2.35, RR: 2.01, HR: 1.61) compared to MSSA bacteraemia. Heterogeneity among the studies was considerable (I2: 90-91%). The study strongly supports that most patient deaths from SAB are linked to MRSA rather than MSSA. This highlights the significant public health problem posed by SAB, with difficult and often unsuccessful treatment leading to increased mortality and high healthcare costs.

Prognostic utility of Fibrosis-4 Index for risk of subsequent liver and cardiovascular events, and all-cause mortality in individuals with obesity and/or type 2 diabetes: a longitudinal cohort study

The Fibrosis-4 Index (FIB-4) is used as a non-invasive tool for the presence of advanced liver fibrosis in metabolic dysfunction-associated steatotic liver disease and type 2 diabetes. However, evidence for an association between FIB-4 and risk of mortality and/or liver-related clinical outcomes is limited. The aim of this study was to investigate the association between FIB-4 and subsequent liver events, cardiovascular events, and all-cause mortality in individuals with obesity and/or type 2 diabetes examined in routine general practice. This was a longitudinal cohort study in which eligible adults had obesity and/or type 2 diabetes and ≥1 FIB-4 score calculable from UK Clinical Practice Research Datalink GOLD after 1 January 2001. No alcohol-related disorders and/or chronic liver diseases (except non-alcoholic fatty liver disease) and/or no prescriptions of drugs inducing liver disease were permitted. Individuals were followed until time of first event, 10 years, or 1 January 2020. Analyses were conducted using Aalen-Johansen cumulative incidence functions and Cox proportional hazards models. Among 44,481 included individuals (mean age 58·8 years; 54% female), there were 979 liver, 6002 cardiovascular,and 8971 mortality events during the 10 years of follow-up. At 10 years, the cumulative incidence of liver events in the high (>2·67), indeterminate (1·30-2·67), and low (<1·30) baseline FIB-4 risk groups were 15%, 3%, and 1%, respectively. Age- and sex-adjusted hazard ratios (HRs) for liver events were elevated in high (16·46; 95%confidence interval [CI] 13·65-19·85) and indeterminate (2·45; 95% CI 2·07-2·90) versus low FIB-4 risk groups. Similar results were found for cardiovascular events and all-cause mortality. Among 20,433 individuals with ≥2 FIB-4 measurements, increase/decrease in FIB-4 12 months after baseline was directly associated with risk of liver events: compared with individuals with low baseline FIB-4 and no change in FIB-4 (reference), the adjusted HR (95% CI) for those with high baseline FIB-4 was 24·27 (16·98-34·68) with a one-unit FIB-4 increase, and 10·90 (7·90-15·05) with a one-unit decrease. In addition to its value as a diagnostic tool, FIB-4 has clinical utility as a prognostic biomarker. Sequential measurement provides a pragmatic, tractable monitoring biomarker that refines risk assessment for liver events, cardiovascular events, and mortality. Novo Nordisk A/S.

Associations of remnant cholesterol with cardiovascular and cancer mortality in a nationwide cohort

The health significance of triglyceride-rich lipoproteins, also known as remnant cholesterol, has been increasingly recognized. However, evidence of their associations with cause-specific mortality in the general population was previously insufficient. To explore these associations and their heterogeneities across subgroups, a prospective cohort study was conducted including 3,403,414 community-based participants from ChinaHEART, an ongoing government-funded public health program throughout China, from November 2014 through December 2022. The study assessed mortality risk of all-cause mortality, cardiovascular disease (CVD) mortality (including mortality from ischemic heart diseases (IHD), ischemic stroke (IS), and hemorrhagic stroke (HS), separately), and cancer mortality (including lung cancer, stomach cancer, and liver cancer, separately). During the 4-year follow-up, 23,646 individuals died from CVD (including 8807 from IHD, 3067 from IS, and 5190 from HS), and 20,318 from cancer (including 6208 from lung cancer, 3013 from liver cancer, and 2174 from stomach cancer). Compared with individuals with remnant cholesterol <17.9 mg/dL, multivariable-adjusted mortality hazard ratios (HRs) for individuals with remnant cholesterol ≥27.7 mg/dL were 1.03 (1.00–1.05) for all-cause mortality, 1.17 (1.12–1.21) for CVD (1.19 (1.12–1.27) for IHD mortality, and 1.22 (1.09–1.36) for IS mortality), and 0.90 (0.87–0.94) for all-cancer mortality (0.94 (0.87–1.02) for lung cancer, 0.59 (0.53–0.66) for liver cancer, and 0.73 (0.64–0.83) for stomach cancer). In summary, this study revealed a correlation between increased remnant cholesterol levels and an elevated risk of cardiovascular disease mortality, as well as a reduced risk of mortality for certain types of cancer.

Validity of the Mean Platelet Volume and Revised Clinical Risk Index for Babies (CRIB-II) Score to Assess Mortality Risk in Preterm Infants

Objective: This study aimed to investigate the validity of the mean platelet volume (MPV) alone and MPV combined with the revised Clinical Risk Index for Babies (CRIB II) score to predict neonatal mortality in preterm infants. Materials and Methods: This retrospective observational study performed between May 2018 and June 2021 included preterm neonates (gestational age 23–32 weeks) admitted to a tertiary neonatal intensive care unit (NICU) within 12 hours of birth, who were followed up until death or discharge. MPV was recorded at admission and within 72 hours before death or discharge. The CRIB II score variables were assessed within 12 hours of birth, and the area under the receiver operating characteristic curve (AUC) was calculated for the MPV and CRIB II scores to predict neonatal mortality. Results: We investigated 404 newborns, of whom 28 (6.9%) died. The mean neonatal gestational age was 28.6±2.8 weeks. The MPV was significantly higher in non-survivors than in survivors (p=0.001). The AUC for the MPV and the CRIB II score was 0.68 (95% CI: 0.55–0.80) and 0.85 (95% CI: 0.79–0.91), respectively. The AUC for the MPV combined with the CRIB II score was 0.91 (95% CI 0.87–0.95). The difference in MPV at birth between survivors and non-survivors was statistically non-significant. Conclusion: MPV was found to be a poorer predictor of neonatal mortality than the CRIB II score; however, MPV combined with the CRIB II score demonstrated significantly improved predictive ability for preterm infant mortality risk.

Machine learning for the prediction of sepsis-related death: a systematic review and meta-analysis

Background and objectivesSepsis is accompanied by a considerably high risk of mortality in the short term, despite the availability of recommended mortality risk assessment tools. However, these risk assessment tools seem to have limited predictive value. With the gradual integration of machine learning into clinical practice, some researchers have attempted to employ machine learning for early mortality risk prediction in sepsis patients. Nevertheless, there is a lack of comprehensive understanding regarding the construction of predictive variables using machine learning and the value of various machine learning methods. Thus, we carried out this systematic review and meta-analysis to explore the predictive value of machine learning for sepsis-related death at different time points.MethodsPubMed, Embase, Cochrane, and Web of Science databases were searched until August 9th, 2022. The risk of bias in predictive models was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST). We also performed subgroup analysis according to time of death and type of model and summarized current predictive variables used to construct models for sepsis death prediction.ResultsFifty original studies were included, covering 104 models. The combined Concordance index (C-index), sensitivity, and specificity of machine learning models were 0.799, 0.81, and 0.80 in the training set, and 0.774, 0.71, and 0.68 in the validation set, respectively. Machine learning outperformed conventional clinical scoring tools and showed excellent C-index, sensitivity, and specificity in different subgroups. Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) are the preferred machine learning models because they showed more favorable accuracy with similar modeling variables. This study found that lactate was the most frequent predictor but was seriously ignored by current clinical scoring tools.ConclusionMachine learning methods demonstrate relatively favorable accuracy in predicting the mortality risk in sepsis patients. Given the limitations in accuracy and applicability of existing prediction scoring systems, there is an opportunity to explore updates based on existing machine learning approaches. Specifically, it is essential to develop or update more suitable mortality risk assessment tools based on the specific contexts of use, such as emergency departments, general wards, and intensive care units.

Assessment of mortality risks due to a strong cold spell in 2022 in China.

With the intensification of global climate warming, extreme low temperature events such as cold spells have become an increasingly significant threat to public health. Few studies have examined the relationship between cold spells and mortality in multiple Chinese provinces. We employed health impact functions for temperature and mortality to quantify the health risks of the first winter cold spell in China on November 26th, 2022, and analyzed the reasons for the stronger development of the cold spell in terms of the circulation field. This cold spell was a result of the continuous reinforcement of the blocking high-pressure system in the Ural Mountains, leading to the deepening of the cold vortex in front of it. Temperature changes associated with the movement of cold fronts produced additional mortality risks and mortality burdens. In general, the average excess risk (ER) of death during the cold spell in China was 2.75%, with a total cumulative excess of 369,056 deaths. The health risks associated with temperatures were unevenly distributed spatially in China, with the ER values ranging from a minimum of 0.14% to a maximum of 5.72%, and temperature drops disproportionately affect southern regions of China more than northern regions. The cumulative excess deaths exibited the highest in eastern and central China, with 87,655 and 80,230 respectively, and the lowest in northwest China with 27,474 deaths. Among the provinces, excess deaths pronounced the highest in Shandong with 29,492 and the lowest in Tibet with only 196. The study can provide some insight into the mortality burden of cold spells in China, while emphasising the importance of understanding the complex relationship between extreme low temperature events and human health. The outcomes could provide valuable revelations for informing pertinent public health policies.

Assessment of Inpatient Mortality in the Peri-Transplant Period in Elderly Allogeneic Stem Cell Transplant Recipients with Co-Existing Mental Health Illnesses

Background Allogeneic hematopoietic stem cell transplant (alloHCT) is a potentially curative treatment for patients with hematological malignancies and nonmalignant conditions. AlloHCT involves invasive procedures, conditioning chemotherapy regimens, and prolonged isolation during hospitalization, which is physically and emotionally challenging. Transplant related mortality is higher in older individuals. Careful assessment of mortality risk before transplant is essential for optimal patient selection and informed decision-making, especially in elderly patients. Hematopoietic cell transplantation-specific comorbidity index (HCT-CI), an important prognostic scoring tool used in patients before alloHCT, includes psychiatric comorbidity as one of the scoring criteria. Patients with depression or anxiety disorders receive one point on the scoring scale, with the assumption that the two groups of patients are at an equivalent risk. However, there is literature showing decreased overall survival and worse inpatient outcomes in patients receiving alloHCT with co-morbid depression. Our primary objective was to evaluate the inpatient outcomes of elderly patients undergoing allogeneic stem cell transplant with a concurrent diagnosis of depression and patients with anxiety and adjustment disorders. Methods: Patients of ages ≥ 60 years, admitted with a principal procedure code of allogeneic stem cell transplant, were recruited from the 2016-2020 National Inpatient Sample. Three cohorts were created based on ICD-10 diagnostic codes for Depression and Anxiety and adjustment disorders: patients without depression and anxiety disorders, patients with depression only, and patients with anxiety and adjustment disorders only. Patients with diagnoses of other mental illnesses were excluded. The patient characteristics between the three cohorts were evaluated. Multiple Logistic Regression models were used to determine the impact of depression and anxiety disorders on inpatient mortality. Results: We evaluated 11655 hospital admissions with the primary procedure code for Allogeneic Stem Cell Transplant in patients aged 60 years and above. 8375 patients did not have any mental illness. 800 patients (9.5%) had a diagnosis of Depression, and 1640 patients (19.5%) had a diagnosis of Anxiety and adjustment disorders. Comparing the primary outcomes in patients with and without Depression, the length of stay was 31.3 days vs 28.2 days (p&amp;lt;0.01), the mean hospital charge was 558398.01 USD vs 498971.9 USD (p &amp;lt;0.01), and in-patient mortality was 8.1% vs 5.9% (aOR = 1.359, 95% CI 1.010-1.829, p=0.04). Utilization of mechanical ventilation was more prevalent in patients with depression (8.8 %vs 5.8 %, p &amp;lt;0.01). Out of different infectious complications, pneumonia was more common in patients with depression (14.4 % vs 9.8 %, p &amp;lt;0.01) (Table 1a). Baseline socio-demographic characteristics that were associated with having depression included: Female gender, White race, and Medicare insurance. Patients with depression had an increased prevalence of congestive heart failure, prior stroke, Obesity with BMI &amp;gt;= 35, chronic kidney disease, and COPD compared to patients without depression (p&amp;lt;0.01). For the primary outcomes in patients with and without anxiety and adjustment disorders, the length of stay was 29.15 days vs 28.2 days (p &amp;lt;0.01), the mean hospital charge was 474274.71 USD vs 498971.94 USD (p 0.612), and the in-patient mortality was 4% vs 5.9 % (aOR=0.61, 95% CI 0.45-0.83, p&amp;lt;0.01). Baseline socio-demographic characteristics that were prevalent in patients with anxiety and adjustment disorders were: female gender, white race, and Medicare as the most common insurance (P&amp;lt;0.01) (Table 1b). Conclusion We found that in elderly patients admitted for alloHCT, depression was independently associated with worse inpatient outcomes, while anxiety was not. Patients with depression were noted to have an increased incidence of infectious complications as compared to those without depression, possibly accounting for their increased mortality. Prognostic scoring systems like HCT-CI may need to be modified to assign more weight to depression as a psychiatric co-morbidity. Elderly transplant recipients with depressive disorders are a vulnerable group and multidisciplinary teams such as psychiatry and palliative care should be involved in their care.