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Background: Predicting mortality in emergency departments (EDs) using machine learning models presents challenges, particularly in balancing simplicity with performance. This study aims to develop models that are both simple and effective for predicting short- and long-term mortality in ED patients. Our approach uses a minimal set of variables derived from one single blood sample obtained at admission. Methods: Data from three cohorts at two large Danish university hospitals were analyzed, including one retrospective and two prospective cohorts where prognostic models were applied to predict individual mortality risk, spanning the years 2013–2022. Routine biochemistry analyzed in blood samples collected at admission was the primary data source for the prediction models. The outcomes were mortality at 10, 30, 90, and 365 days after admission to the ED. The models were developed using Light Gradient Boosting Machines. The evaluation of mortality predictions involved metrics such as Area Under the Receiver Operating Characteristic Curve (AUC), sensitivity, specificity, negative predictive values, positive predictive values, and Matthews correlation coefficient (MCC). Results: A total of 43,648 unique patients with 65,484 admissions were analyzed. The models showed high accuracy, with very good to excellent AUC values between 0.87 and 0.93 across different time intervals. Conclusions: This study demonstrates that a single assessment of routine clinical biochemistry upon admission can serve as a powerful predictor for both short-term and long-term mortality in ED admissions. [ABSTRACT FROM AUTHOR]

Background: Cardiac troponin I (TnI) is a specific marker of myocardial damage used in the diagnosis of acute coronary syndrome (ACS). TnI levels can also be elevated in patients without ACS, which is linked to a worse prognosis and mortality. We evaluated the clinical implications and prognostic significance of serum TnI levels in critically ill non-cardiac patients admitted to the intensive care unit (ICU) at a tertiary-level hospital. Materials and Methods: A three-year retrospective study including the years 2017–2020 was conducted to evaluate in-hospital mortality during ICU stay and mortality rates at 28 and 90 days, as well as one and two years after admission, in 557 patients admitted to the medical ICU for non-cardiac causes. Results: TnI levels were elevated in 206 (36.9%) patients. Patients with elevated TnI levels were significantly older and had higher rates of comorbidities, including chronic heart failure, coronary heart disease, and chronic kidney disease (p < 0.05 for all). Patients with elevated TnI levels required more invasive mechanical ventilation, vasopressor infusion, and dialysis in the ICU and experienced more shock within the first 72 h (p = 0.001 for all). High TnI levels were associated with higher Acute Physiological and Chronic Health Evaluation (APACHE) II (27.6 vs. 20.3, p = 0.001) and Sequential Organ Failure assessment (8.8 vs. 5.26, p = 0.001) scores. Elevated TnI levels were associated with higher mortality rates at 28 days (58.3% vs. 19.4%), 90 days (69.9% vs. 35.0%), one year (78.6% vs. 46.2%), and two years (82.5% vs. 55.6%) (p < 0.001 for all). Univariate logistic regression analysis revealed that high TnI levels were a strong independent predictor of mortality at all time points: 28 days (OR = 1.2, 95% CI: 1.108–1.3, p < 0.001), 90 days (OR = 1.207, 95% CI: 1.095–1.33, p = 0.001), one year (OR = 1.164, 95% CI: 1.059–1.28, p = 0.002), and two year (OR = 1.119, 95% CI: 1.026–1.22, p = 0.011). Multivariate analysis revealed that age, albumin level, APACHE II score, and requirements for dialysis and vasopressor use in the ICU were important predictors of mortality across all timeframes, but elevated TnI levels were not. Conclusions: Elevated TnI levels in critically ill non-cardiac patients are markers of disease severity. While elevated TnI levels were significant predictors of mortality in the univariate analysis, they lost significance in the multivariate model when adjusted for other factors. Patients with elevated TnI levels had higher mortality rates across all timeframes, from 28 days to two years. [ABSTRACT FROM AUTHOR]

Background/Objectives: Acute decompensated heart failure (ADHF) presents a significant clinical challenge characterized by frequent hospitalizations, high mortality rates, and substantial healthcare costs. The united index of hemoglobin, albumin, lymphocytes and platelets (HALP) is a new indicator that reflects systemic inflammation and nutritional status. This study aimed to investigate the prognostic utility of the HALP score and hematological parameters in predicting short-term mortality among ADHF patients admitted to the coronary care unit (CCU). Methods: This investigation adopts a retrospective observational design, encompassing a cohort of patients with ADHF who were followed in the CCU at our medical institution between January 2019 and April 2024. Results: The cohort of 227 individuals was dichotomized into two subsets based on the presence or absence of short-term mortality in the hospital, resulting in 163 (71.8%) and 64 (28.2%) individuals in the survivor and exitus groups, respectively. Age was significantly higher in the exitus group (p-value = 0.004). Hemoglobin, lymphocyte count, platelet count, albumin, and HALP score were significantly higher in the survivor group (all p-values < 0.001). No significant difference was observed between the groups in terms of gender, diabetes mellitus (DM), coronary artery disease (CAD), or ejection fraction (EF), although hypertension (HT) prevalence was significantly higher in the exitus group (p-value = 0.038). ROC analysis demonstrated that hemoglobin, lymphocyte, albumin, and HALP score had significant discriminative power, with albumin showing the highest AUC (0.814). Conclusions: In conclusion, the HALP score and hematological parameters represent valuable prognostic feature for short-term mortality prediction in ADHF patients admitted to the CCU. These findings underscore the importance of early risk stratification and targeted interventions guided by comprehensive biomarker assessments in optimizing patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Spontaneous bacterial peritonitis (SBP) is a severe complication in cirrhosis patients with ascites, leading to high mortality rates if not promptly treated. However, specific prediction models for SBP are lacking. Aims: This study aimed to compare commonly used cirrhotic prediction models (CTP score, MELD, MELD-Na, iMELD, and MELD 3.0) for short-term mortality prediction and develop a novel model to improve mortality prediction. Methods: Patients with the first episode of SBP were included. Prognostic values for mortality were assessed using AUROC analysis. A novel prediction model was developed and validated. Results: In total, 327 SBP patients were analyzed, with HBV infection as the main etiologies. MELD 3.0 demonstrated the highest AUROC among the traditional models. The novel model, incorporating HRS, exhibited superior predictive accuracy for in-hospital in all patients and 3-month mortality in HBV-cirrhosis, with AUROC values of 0.827 and 0.813 respectively, surpassing 0.8. Conclusions: MELD 3.0 score outperformed the CTP score and showed a non-significant improvement compared to other MELD-based scores, while the novel SBP model demonstrated impressive accuracy. Internal validation and an HBV-related cirrhosis subgroup sensitivity analysis supported these findings, highlighting the need for a specific prognostic model for SBP and the importance of preventing HRS development to improve SBP prognosis. [ABSTRACT FROM AUTHOR]

Background and Objectives: The purpose of this study is to investigate the predictive factors for intrahospital mortality in ischemic stroke patients. We will examine the association between a range of clinical and demographic factors and intrahospital mortality, including age, sex, comorbidities, laboratory values, and medication use. Materials and Methods: This retrospective, longitudinal, analytic, observational cohort study included 243 patients over 18 years old with a new ischemic stroke diagnosis who were hospitalized in Cluj-Napoca Emergency County Hospital. Data collected included the patient demographics, baseline characteristics at hospital admission, medication use, carotid artery Doppler ultrasound, as well as cardiology exam, and intrahospital death. Results: Multivariate logistic regression was used to determine which variables were independently associated with intrahospital death. An NIHSS score > 9 (OR—17.4; p < 0.001) and a lesion volume > 22.3 mL (OR—5.8; p = 0.003) were found to be associated with the highest risk of death. In contrast antiplatelet treatment (OR—0.349; p = 0.04) was associated with lower mortality rates. Conclusions: Our study identified a high NIHSS score and large lesion volume as independent risk factors for intrahospital mortality in ischemic stroke patients. Antiplatelet therapy was associated with lower mortality rates. Further studies are needed to explore the potential mechanisms underlying these associations and to develop targeted interventions to improve patient outcomes. [ABSTRACT FROM AUTHOR]

The visceral adiposity index (VAI) is related to the occurrence of various cardiometabolic diseases, atherosclerosis, and stroke. However, few studies have analyzed the impact on the short-term prognosis of stroke. We assessed the effect of VAI on short-term prognoses in patients with acute ischemic stroke through a retrospective cohort study of 225 patients with acute stroke who were admitted to the neurological intensive care unit of our hospital. We collected metabolic indicators (blood pressure, fasting glucose, lipids), National Institutes of Health Stroke Scale (NIHSS) scores, symptomatic intracranial hemorrhage, and other disease evaluation indicators on 197 patients who were screened for inclusion. VAI was calculated by using baseline data (sex, height, weight, waist circumference (WC)). We assessed functional recovery according to modified Rankin scale scores after 90 days. The receiver operating characteristic (ROC) curve was used to calculate the VAI cutoff value that affects short-term outcomes. A nomogram that can predict the risk of short-term mortality in patients with acute ischemic stroke was drawn. In total, 28 patients died within 90 days. Those patients had higher VAI (p = 0.000), higher triglyceride (TG) (p = 0.020) and NIHSS scores (p = 0.000), and lower high-density lipoprotein cholesterol (HDL-C) (p = 0.000) than patients who survived. VAI had higher predictive value of short-term mortality than did body mass index (BMI), body fat mass index (BFMI), and WC. VAI and NIHSS scores were independent risk factors for the short-term mortality of patients with stroke. Patients with a VAI > 2.355 had a higher risk of short-term mortality. VAI has a predictive value higher than that of traditional metabolic indicators such as BMI, BFMI, and WC. The nomogram, composed of NIHSS, VAI, HDL-C, and TG, may predict the short-term mortality of cerebral infarction patients. [ABSTRACT FROM AUTHOR]

Background: Excess cardiovascular (CV) morbidity and mortality has been observed in patients with COVID-19. Both interleukin-32 (IL-32) and interleukin-34 (IL-34) have been hypothesized to contribute to CV involvement in COVID-19. Methods: This prospective, observational study of patients with laboratory-confirmed COVID-19 infection was conducted from 6 June to 22 December 2020 in a tertiary care hospital in Vienna, Austria. IL-32 and IL-34 levels on admission were collected and tested for their association with CV disease and short-term mortality in patients with COVID-19. CV disease was defined by the presence of coronary artery disease, heart failure, stroke or atrial fibrillation and patients were stratified by CV disease burden. Results: A total of 245 eligible patients with COVID-19 were included, of whom 37 (15.1%) reached the primary endpoint of 28-day mortality. Of the total sample, 161 had no CV disease (65.7%), 69 had one or two CV diseases (28.2%) and 15 patients had ≥three CV diseases (6.1%). Median levels of IL-32 and IL-34 at admission were comparable across the three groups of CV disease burden. IL-32 and IL-34 failed to predict mortality upon both univariable and multivariable Cox regression analysis. The two CV disease groups, however, had a significantly higher risk of mortality within 28 days (one or two CV diseases: crude HR 4.085 (95% CI, 1.913–8.725), p < 0.001 and ≥three CV diseases: crude HR 13.173 (95% CI, 5.425–31.985), p < 0.001). This association persisted for those with ≥three CV diseases after adjustment for age, gender and CV risk factors (adjusted HR 3.942 (95% CI, 1.288–12.068), p = 0.016). Conclusion: In our study population of hospitalized patients with COVID-19, IL-32 and IL-34 did not show any associations with CV disease or 28-day mortality in the context of COVID-19. Patients with multiple CV diseases, however, had a significantly increased risk of short-term mortality. [ABSTRACT FROM AUTHOR]

Background: The ongoing COVID-19 pandemic has put a constant strain on hospital resources, so there is a dire need for investigation methods that are widely available and that can predict mortality and the need for critical care. Hematological indices, which can be easily calculated from a complete blood count (CBC), are useful in determining a patient's inflammatory response to infectious diseases. Aim: This was a prospective cohort study that aimed to assess the prognostic value of scores based on CBCs in hospitalized patients with mild or moderate COVID-19 and medical comorbidities regarding the need for intensive care unit (ICU) therapy and short-term mortality. Methods: We included 607 patients with confirmed COVID-19, followed up for the need for ICU admission (15.5%) and 30 day mortality post-discharge (21.7%). CBC-derived scores were tested upon emergency department (ED) admission and after a median of 8 days. Results: In a multivariate model, elevated followed-up neutrophil-to-lymphocyte ratio (NLR) predicted increased odds for ICU admission (OR: 1.14 [95%CI: 1.06–1.22], p < 0.001) and short-term mortality (OR: 1.30 [95%CI: 1.09–1.57], p = 0.005). Monocyte-to-lymphocyte ratio (MLR) predicted 2.5-fold increased odds for ICU admission and 2.2-fold increased odds for mortality. Conclusion: NLR and MLR followed up 8 days post-admission are predictive for adverse outcomes in mild or moderate COVID-19 patients. [ABSTRACT FROM AUTHOR]

Recent studies have attempted to measure differences in lifestyle quality across the world. This paper contributes to this strand of literature by extending the indicator introduced in Milevsky (2020), i.e., "longevity-risk-adjusted global age" (LRaG age), to deal with the new short-term mortality fluctuation data series freely available from the Human Mortality Database. The new weekly data on mortality allow measuring weekly biological age. The weekly differences between biological and chronological ages across countries were used to assess country resilience to the COVID-19 pandemic in terms of excess mortality and health expenditure. Countries with a biological age lower than the chronological age had a lower excess mortality in 2020–2021 and a lower health expenditure, thus indicating some resilience to the shock of COVID-19. [ABSTRACT FROM AUTHOR]