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Introduction: The aim of the present study was to assess the predictive value of the age, creatinine, ejection fraction score for in-hospital mortality in patients with cardiogenic shock secondary to ST-elevation myocardial infarction. Material and methods: This single-center, retrospective study was based on a comprehensive analysis of the hospital records of 318 consecutive cardiogenic shock patients. The age, creatinine, ejection fraction score was calculated for each patient using the equation of age/ejection fraction +1 if creatinine level is >2 mg/dl. The study population was stratified into tertiles: T1, T2, and T3, based on the age, creatinine, ejection fraction score. The primary endpoint of the study was the incidence of in-hospital mortality. Results: The incidence of in-hospital mortality was significantly greater in patients with a high age, creatinine, ejection fraction score (T3 group) compared with the intermediate (T2 group) or the low score group (T1 group) [86.8% (n = 92 patients) vs. 57.5% (n = 61 patients) vs. 34.9% (n = 37 patients), respectively; P < 0.05 for each]. In multivariable models, after adjusting for all covariables, the risk of in-hospital mortality was 3.21 (95% confidence interval: 2.29–4.58) for patients allocated to the T3 group. The optimal cutoff for the age, creatinine, ejection fraction score for in-hospital mortality was 2.24, with a sensitivity of 74% and a specificity of 77%. Conclusion: To the best of our knowledge, this is the first study that has demonstrated a prognostic value of the age, creatinine, ejection fraction score in patients with ST-elevation myocardial infarction-related cardiogenic shock.

Background: This study examined the possible association between the prognostic nutritional index (PNI) and in-hospital mortality rates in cases with a high cardiovascular risk burden and hospitalized with the diagnosis of coronavirus disease 2019 . Material and Methods: This retrospective and cross-sectional study included 294 COVID-19 patients hospitalized in a tertiary referral pandemic center. The study cohort was grouped into tertiles based on the initial PNI values as T1, T2, and T3. The PNI was calculated for each case and the prognostic value of this index was compared to CURB-65 and 4C mortality risk scores in predicting in-hospital mortality. Results: Patients stratified into the T1 tertile had a lower lymphocyte count, serum albumin level, and PNI values. In a multivariate analysis, the PNI (OR: 0.688,%95CI: 0.586À0.808, p < 0.001) was an independent predictor for all-cause in-hospital death. After adjusting for confounding independent parameters, patients included in the T1 tertile were found to have 11.2 times higher rates of in-hospital mortality compared to the T3 group, which was presumed as the reference group. In addition, we found that the area under curve (AUC) value of PNI was significantly elevated than that of serum albumin level and total lymphocyte counts alone. [(AUC):0.79 vs AUC:0.75 vs AUC:0.69; respectively). Conclusion: This study demonstrated that the PNI is independently related with in-hospital mortality in patient with COVID-19 and cardiovascular risk factors. The power of the PNI was also validated using wellaccepted risk scores of COVID-19 such as CURB-65 and 4C mortality risk scores.

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Background Pro‐inflammatory pathways play an important role in the follow‐ups of patients with intracardiac defibrillators (ICDs) for heart failure (HF) reduced with ejection fraction (HFrEF). A newly defined index ‐ the systemic immune‐inflammation index (SII)—has recently been reported to have prognostic value in patients with cardiovascular disease. This study's aim is to evaluate the SII value regarding its association with long‐term mortality and appropriate ICD therapy during a 10‐year follow‐up. Methods This retrospective study included 1011 patients with ICD for HFrEF. The SII was calculated as the neutrophil—to—lymphocyte ratio × total platelet count in the peripheral blood. The study population was divided into two groups according to the SII's optimal cut‐off value to predict long‐term mortality. The long‐term prognostic impact of SII on these patients was evaluated regarding mortality and appropriate ICD therapy. Results The patients with a higher SII (≥1119) had significantly higher long‐term mortality and appropriate ICD therapy rates. After adjustment for all confounding factors, the long‐term mortality rate was 5.1 for a higher SII. (95% CI: 2.9–8.1). The long‐term appropriate ICD therapy rate was 2.0 for a higher SII (95% CI: 1.4–3.0). Conclusion SII may be an independent predictive marker for both long‐term mortality and appropriate ICD therapy in patients with HFrEF.