Objective Triple-vessel disease (TVD) is a well-established prognostic factor for patients with acute myocardial infarction (AMI). However, there is a paucity of literature regarding the risk factors for in-hospital death in patients with non-ST-segment elevation myocardial infarction (NSTEMI) and TVD. In this retrospective study, we examined the determinants of in-hospital death in patients with NSTEMI and TVD who underwent percutaneous coronary intervention (PCI) for culprit lesions. Methods The primary objective of this study was to identify the factors associated with in-hospital death using a multivariate analysis. We included 253 patients with NSTEMI and TVD and divided them into a survivor group (n=239) and an in-hospital death group (n=14). Results Systolic blood pressure (SBP) at admission was significantly higher in the survivor group than in the in-hospital death group. The estimated glomerular filtration rate (eGFR) was also higher in the survivor group than in the in-hospital death group. In the multivariate logistic regression analysis, in-hospital death was inversely associated with the SBP at admission (odds ratio [OR] 0.984, 95% confidence interval [CI] 0.970-0.999, p<0.035) and eGFR (OR 0.966, 95% CI 0.939-0.994, p=0.019) and was associated with cardiopulmonary arrest (CPA) before PCI (OR 8.448, 95%CI 1.863-38.309, p=0.006). Conclusion In-hospital death was associated with CPA before PCI and inversely associated with the SBP at admission and eGFR in patients with NSTEMI and TVD who underwent PCI for the culprit lesion. It may be important to recognize these high-risk features in order to improve the clinical outcomes of patients with NSTEMI and TVD.

Various scoring systems are available for COVID-19 risk stratification. This study aimed to validate their performance in predicting severe COVID-19 course in a large, heterogeneous Swiss cohort. Scores like the National Early Warning Score (NEWS), CURB-65, 4C mortality score (4C), Spanish Society of Infectious Diseases and Clinical Microbiology score (COVID-SEIMC), and COVID Intubation Risk Score (COVID-IRS) were assessed in patients hospitalized for COVID-19 in 2020 and 2021. Predictive accuracy for severe course (defined as all-cause in-hospital death or invasive mechanical ventilation (IMV)) was evaluated using receiver operating characteristic curves and the area under the curve (AUC). The new \'COVID-COMBI\' score, combining parameters from the top two scores, was also validated. This study included 1,051 patients (mean age 65 years, 60% male), with 162 (15%) experiencing severe course. Among the established scores, 4C had the best accuracy for predicting severe course (AUC 0.76), followed by COVID-IRS (AUC 0.72). COVID-COMBI showed significantly higher accuracy than all established scores (AUC 0.79, p = 0.001). For predicting in-hospital death, 4C performed best (AUC 0.83), and, for IMV, COVID-IRS performed best (AUC 0.78). The 4C and COVID-IRS scores were robust predictors of severe COVID-19 course, while the new COVID-COMBI showed significantly improved accuracy but requires further validation.

OBJECTIVE: Atherogenic indices: Triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, Atherogenic Index of Plasma (AIP), Atherogenic Coefficient (AC), Castelli\'s Risk Index I and II (CRI-I, CRI-II) are used in clinical studies as surrogates of major adverse cardiac and cerebrovascular events (MACCE). Risk prediction of MACCE in patients with acute myocardial infarction (AMI) has vital role in clinical practice. We aimed to assess prognostic value of these indices following AMI.
METHODS: We analyzed patients with AMI with and without T2DM and the prognostic values of atherogenic indices for in-hospital death and MACCE within 12 months after AMI.
RESULTS: Of 2461 patients, 152 in-hospital deaths (6.2 %) were reported (74 patients [7.4 %] with T2DM and 78 [5.3 %] without T2DM; p = 0.042). MACCE occurred in 22.7 % of patients (29.7 % with T2DM and 17.9 % without T2DM; p < 0.001). TG/HDL-C and AIP were higher in T2DM patients compared to those without T2DM (p < 0.001). Long-term MACCE was more prevalent in patients with T2DM (p < 0.001). The AUC-ROC for predicting in-hospital death based on TG/HDL-C and AIP was 0.57 (p = 0.002).
CONCLUSIONS: None of the atherogenic indices was an independent risk factor for in-hospital death or MACCE at 12-month follow-up in patients with AMI. AIP was an independent risk factor for death at 12-month follow-up.

To explore the relationship between Anion Gap (AG), Albumin Corrected AG (ACAG), and in-hospital mortality of Acute Myocardial Infarction (AMI) patients and develop a prediction model for predicting the mortality in AMI patients.
This was a retrospective cohort study based on the Medical Information Mart for Intensive Care (MIMIC)-Ⅲ, MIMIC-IV, and eICU Collaborative Study Database (eICU). A total of 9767 AMI patients who were admitted to the intensive care unit were included. The authors employed univariate and multivariable cox proportional hazards analyses to investigate the association between AG, ACAG, and in-hospital mortality; p < 0.05 was considered statistically significant. A nomogram incorporating ACAG and clinical indicators was developed and validated for predicting mortality among AMI patients.
Both ACAG and AG exhibited a significant association with an elevated risk of in-hospital mortality in AMI patients. The C-index of ACAG (C-index = 0.606) was significantly higher than AG (C-index = 0.589). A nomogram (ACAG combined model) was developed to predict the in-hospital mortality for AMI patients. The nomogram demonstrated a good predictive performance by Area Under the Curve (AUC) of 0.763 in the training set, 0.744 and 0.681 in the external validation cohort. The C-index of the nomogram was 0.759 in the training set, 0.756 and 0.762 in the validation cohorts. Additionally, the C-index of the nomogram was obviously higher than the ACAG and age shock index in three databases.
ACAG was related to in-hospital mortality among AMI patients. The authors developed a nomogram incorporating ACAG and clinical indicators, demonstrating good performance for predicting in-hospital mortality of AMI patients.

Immunosuppression and malnutrition play pivotal roles in the complications of intracerebral hemorrhage (ICH) and are intricately linked to the development of stroke-associated pneumonia (SAP). Inflammatory markers, including NLR (neutrophil-to-lymphocyte ratio), SII (systemic immune inflammation index), SIRI (systemic inflammatory response index), and SIS (systemic inflammation score), along with nutritional indexes such as CONUT (controlling nutritional status) and PNI (prognostic nutritional index), are crucial indicators influencing the inflammatory state following ICH. In this study, our objective was to compare the predictive efficacy of inflammatory and nutritional indices for SAP in ICH patients, aiming to determine and explore their clinical utility in early pneumonia detection. Patients with severe ICH requiring ICU admission were screened from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The outcomes included the occurrence of SAP and in-hospital death. Receiver operating characteristic (ROC) analysis, multivariate logistic regression, smooth curve analysis, and stratified analysis were employed to investigate the relationship between the CONUT index and the clinical outcomes of patients with severe ICH. A total of 348 patients were enrolled in the study. The incidence of SAP was 21.3%, and the in-hospital mortality rate was 17.0%. Among these indicators, multiple regression analysis revealed that CONUT, PNI, and SIRI were independently associated with SAP. Further ROC curve analysis demonstrated that CONUT (AUC 0.6743, 95% CI 0.6079-0.7408) exhibited the most robust predictive ability for SAP in patients with ICH. Threshold analysis revealed that when CONUT < 6, an increase of 1 point in CONUT was associated with a 1.39 times higher risk of SAP. Similarly, our findings indicate that CONUT has the potential to predict the prognosis of patients with ICH. Among the inflammatory and nutritional markers, CONUT stands out as the most reliable predictor of SAP in patients with ICH. Additionally, it proves to be a valuable indicator for assessing the prognosis of patients with ICH.

OBJECTIVE: Acute Physiology and Chronic Health Evaluation II (APACHE II) is based on the data of intensive care unit (ICU) patients and often correlates with disease severity and prognosis. However, no prognostic predictors exist based on ICU admission data for patients with brain tumors, and no studies have reported an association between APACHE II and prognosis in patients with brain tumors. The Japanese Intensive Care Patients Database (JIPAD) was established to improve the quality of care delivered in intensive care medicine in Japan. We used JIPAD to examine factors associated with in-hospital mortality based on available data of postoperative patients with brain tumors admitted to the ICU.
METHODS: Patients aged ≥16 years enrolled in JIPAD between April 2015 and March 2018 after surgical brain tumor resection or biopsy of brain tumors. We examined factors related to outcomes at discharge based on blood tests and medical procedures performed during ICU admission, tumor type, and APACHE II score.
RESULTS: Among the 1454 patients (male:female ratio: 1:1.1, mean age: 62 years) in the study, 32 (2.2 %) died during hospital stay. In multivariate analysis, male sex (odds ratio [OR] 2.70, [95 % confidence interval, CI 1.22-6.00]), malignant tumor (OR 2.51 [95 % CI 1.13-5.55]), and APACHE II score ≥15 (OR 2.51 [95 % CI 3.08-14.3]) were significantly associated with in-hospital mortality.
CONCLUSIONS: By picking up cases with a high risk of in-hospital death at an early stage, it is possible to improve methods of treatment and support for the patient\'s family.

BACKGROUND: Cardiovascular disease is the major cause of morbidity and mortality, particularly in type 2 diabetes mellitus (T2DM). Novel markers of insulin resistance and progression of atherosclerosis include the triglycerides and glucose index (TyG index), the triglycerides and body mass index (Tyg-BMI) and the metabolic score for insulin resistance (METS-IR). Establishing independent risk factors for in-hospital death and major adverse cardiac and cerebrovascular events (MACCE) in patients with myocardial infarction (MI) remains critical. The aim of the study was to assess the risk of in-hospital death and MACCE within 12 months after ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) in patients with and without T2DM based on TyG index, Tyg-BMI and METS-IR.
METHODS: Retrospective analysis included 1706 patients with STEMI and NSTEMI hospitalized between 2013 and 2021. We analyzed prognostic value of TyG index, Tyg-BMI and METS-IR for in-hospital death and MACCE as its components (death from any cause, MI, stroke, revascularization) within 12 months after STEMI or NSTEMI in patients with and without T2DM.
RESULTS: Of 1706 patients, 58 in-hospital deaths were reported (29 patients [4.3%] in the group with T2DM and 29 patients [2.8%] in the group without T2DM; p = 0.1). MACCE occurred in 18.9% of the total study population (25.8% in the group with T2DM and 14.4% in the group without T2DM; p < 0.001). TyG index, Tyg-BMI and METS-IR were significantly higher in the group of patients with T2DM compared to those without T2DM (p < 0.001). Long-term MACCE were more prevalent in patients with T2DM (p < 0.001). The area under the ROC curve (AUC-ROC) for the prediction of in-hospital death and the TyG index was 0.69 (p < 0.001). The ROC curve for predicting in-hospital death based on METS-IR was 0.682 (p < 0.001). The AUC-ROC values for MACCE prediction based on the TyG index and METS-IR were 0.582 (p < 0.001) and 0.57 (p < 0.001), respectively.
CONCLUSIONS: TyG index was an independent risk factor for in-hospital death in patients with STEMI or NSTEMI. TyG index, TyG-BMI and METS-IR were not independent risk factors for MACCE at 12 month follow-up. TyG index and METS-IR have low predictive value in predicting MACCE within 12 months after STEMI and NSTEMI.

BACKGROUND: Vaccination against pneumococci is currently the most effective method of protection against pneumococcal infections. The aim of the study was to analyse changes in hospitalisations and in-hospital deaths due to pneumonia before (2009-2016) and after (2017-2020) the introduction of PCV 10 vaccinations in the National Immunisation Programme in Poland.
METHODS: Data on hospitalisations related to community acquired pneumonia (CAP) in the years 2009-2020 were obtained from the Nationwide General Hospital Morbidity Study. Analyses were made in the age groups: <2, 2-3, 4-5, 6-19, 20-59, 60+ years in 2009-2016 and 2017-2020.
RESULTS: Overall, there were 1,503,105 CAP-related hospitalisations in 2009-2020, 0.7% of which were caused by Streptococcus pneumoniae infections. Children <2 years of age were the most frequently hospitalised for CAP per 100,000 population, followed by patients aged 2-3, 4-5 and 60+ years. In the years 2009-2016, the percentage of CAP hospital admissions increased significantly, and after the year 2017, it decreased significantly in each of the age groups (p<0.001). In the years 2009-2016, a significant increase in hospitalisations for Streptococcus pneumoniae infections was observed in the age groups <2, 2-3 and 4-5 years (p<0.05). A significant reduction in hospitalisations was observed in the age groups <2, 20-59 and 60+ in 2017-2020 (p<0.05). In the years 2009-2020, there were 84,367 in-hospital deaths due to CAP, 423 (0.5%) of which due to Streptococcus pneumoniae, with patients mainly aged 60+.
CONCLUSIONS: Implementation of the PCV vaccination programme has effectively decreased the incidence of CAP hospitalisations, including children <2 years of age. The group that is most at risk of death are persons aged 60+. The results of our study can be useful in evaluating the vaccine efficacy and benefits, and they can be an essential part of public health policy. Effective prevention strategies for CAP should be implemented in different age groups.

BACKGROUND: Postoperative acute kidney injury (AKI) is a common condition after surgery, however, the available data about nationwide epidemiology of postoperative AKI in China from large and high-quality studies are limited. This study aimed to determine the incidence, risk factors and outcomes of postoperative AKI among patients undergoing surgery in China.
METHODS: This was a large, multicentre, retrospective study performed in 16 tertiary medical centres in China. Adult patients (≥18 years of age) who underwent surgical procedures from 1 January 2013 to 31 December 2019 were included. Postoperative AKI was defined by the Kidney Disease: Improving Global Outcomes creatinine criteria. The associations of AKI and in-hospital outcomes were investigated using logistic regression models adjusted for potential confounders.
RESULTS: Among 520 707 patients included in our study, 25 830 (5.0%) patients developed postoperative AKI. The incidence of postoperative AKI varied by surgery type, which was highest in cardiac (34.6%), urologic (8.7%) and general (4.2%) surgeries. A total of 89.2% of postoperative AKI cases were detected in the first 2 postoperative days. However, only 584 (2.3%) patients with postoperative AKI were diagnosed with AKI on discharge. Risk factors for postoperative AKI included older age, male sex, lower baseline kidney function, pre-surgery hospital stay ≤3 days or >7 days, hypertension, diabetes mellitus and use of proton pump inhibitors or diuretics. The risk of in-hospital death increased with the stage of AKI. In addition, patients with postoperative AKI had longer lengths of hospital stay (12 versus 19 days) and were more likely to require intensive care unit care (13.1% versus 45.0%) and renal replacement therapy (0.4% versus 7.7%).
CONCLUSIONS: Postoperative AKI was common across surgery type in China, particularly for patients undergoing cardiac surgery. Implementation and evaluation of an alarm system is important for the battle against postoperative AKI.

OBJECTIVE: This study investigated and compared the implementation of life-support treatment (LST), cardiopulmonary resuscitation (CPR) implementation rates, and the influence of acute illnesses on the introduction of palliative care (PC) to homebound patients with malignant and nonmalignant disease, who subsequently died in an acute hospital setting.
METHODS: Among the homebound patients admitted to the ward in our hospital from 2011 to 2018, we investigated and compared the attributes, underlying diseases, causes of death, and rates of implementation of LST, CPR, and PC between patients with malignant and nonmalignant disease who died in the ward, using data obtained from hospitalization records. Furthermore, acute illnesses related to the introduction of PC were examined.
RESULTS: Of the 551 homebound patients admitted to the ward of an acute hospital, 119 died in the ward. Of the deceased patients, 60 had malignant disease and 59 had nonmalignant disease. Patients with nonmalignant disease had higher rates of LST implementation and CPR and a lower rate of PC. Patients with infectious disease, who required antimicrobial drugs, had significantly lower PC introduction rates.
CONCLUSIONS: Understanding the influence of the timing of PC introduction in acute care for homebound patients with advanced chronic illness are issues to be considered.