OBJECTIVE:The aim of this study was to investigate the performance of controlling nutritional status (CONUT) index, geriatric nutritional risk index (GNRI), and prognostic nutritional index (PNI) scores in predicting the long-term prognosis of patients with non-ST-elevated myocardial infarction (NSTEMI) who underwent percutaneous coronary intervention (PCI). METHODS: A total of 915 patients with NSTEMI (female: 48.4%; mean age: 73.1±9.0 years) who underwent PCI at Adana Numune Training and Research Hospital, Cardiology Clinic between January 2014 and January 2015 were included in this cross-sectional and retrospective study. CONUT, GNRI, and PNI scores were calculated based on the admission data derived from samples of peripheral venous blood. The mean follow-up duration was 64.5±15.4 months. RESULTS:During follow-up (mean 64.5±15.4 months), 179 patients (19.6%) died. The mean GNRI and PNI scores were significantly lower in the nonsurvivor group; however, the median CONUT score was significantly higher in the nonsurvivor group compared with the survivor group. The receiver operating characteristic (ROC) curve analyses have shown that GNRI score has similar performance to the CONUT score and has better performance than PNI score in predicting 5-year mortality. The Kaplan-Meier curve analysis has shown that patients with lower PNI or GNRI had higher cumulative mortality than the patients with higher PNI or GNRI. Also, the patients with higher CONUT scores had higher cumulative mortality compared with those with lower scores. The multivariate analyses have shown that GNRI (HR: 0.973), PNI (HR: 0.967), CONUT score (HR: 1.527), and body mass index (BMI) (HR: 0.818) were independent predictors of the 5-year mortality in patients with NSTEMI. CONCLUSION:In this study, we have shown that CONUT score, GNRI, and PNI values were associated with the long-term mortality in patients with NSTEMI who underwent PCI, and GNRI yielded similar results to CONUT score but was better than PNI.

Background Computed tomography (CT) gives an idea about the prognosis in patients with COVID-19 lung infiltration. Purpose To evaluate the success rates of various scoring methods utilized in order to predict survival periods, on the basis of the imaging findings of COVID-19. Another purpose, on the other hand, was to evaluate the agreements among the evaluating radiologists. Material and Methods A total of 100 cases of known COVID-19 pneumonia, of which 50 were deceased and 50 were living, were included in the study. Pre-existing scoring systems, which were the Total Severity Score (TSS), Chest Computed Tomography Severity Score (CT-SS), and Total CT Score, were utilized, together with the Early Decision Severity Score (ED-SS), which was developed by our team, to evaluate the initial lung CT scans of the patients obtained at their initial admission to the hospital. The scans were evaluated retrospectively by two radiologists. Area under the curve (AUC) values were acquired for each scoring system, according to their performances in predicting survival times. Results The mean age of the patients was 61 ± 14.85 years (age range = 18–87 years). There was no difference in co-morbidities between the living and deceased patients. The survival predicted AUC values of ED-SS, CT-SS, TSS, and Total CT Score systems were 0.876, 0.823, 0.753, and 0.744, respectively. Conclusion Algorithms based on lung infiltration patterns of COVID-19 may be utilized for both survival prediction and therapy planning.

Background: This study aimed to analyze the associations between no-reflow (NR) phenomenon development and whole-blood viscosity in patients with ST-elevated myocardial infarction. Methods: A total of 217 patients with ST-elevated myocardial infarction were included. whole-blood viscosity values were assessed using hematocrit and total protein values, and low shear rate (LSR) and high shear rate (HSR) were calculated. Results: The average LSR and HSR values of the study group were significantly higher than the control group (p < 0.001). Multivariate logistic regression analysis showed that both HSR (odds ratio: 4.957; p < 0.001) and LSR (odds ratio: 1.114; p < 0.001) were independent predictors for NR development. Conclusion: This study found that increased blood viscosity was an independent predictor for NR development.