Clinical Characteristics Predicting Mortality Risk in Hospitalized Geriatric Patients with COVID-19 Pneumonia: a Retrospective Study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Geriatric patients with COVID-19 are more likely to progress to severe disease, and they are at increased risk of hospitalization and mortality. In this study we aimed to investigate the risk factors for predicting mortality in geriatric patients with COVID 19 by reviewing the clinical data of survivors and non-survivors. METHODS: This was a retrospective study of 189 geriatric patients with COVID- 19 pneumonia who were hospitalized in pulmonology clinic, in Duzce University, Medical Faculty Hospital between March 2020 and January 2021 in Turkey. RESULTS: In the study, 60.3% (n = 114) of the patients were male and the median age was 75. 80.4% (n = 152) of the patients were discharged. The presence of cardiovascular disease, chronic renal failure, malignancy, increased number of comorbidities, complaints of anorexia, no fever, decreased oxygen saturation value, increased pulse rate, high values of maximum (max) D-dimer, aspartate aminotransferase, urea, creatinine, troponin, lactate dehydrogenase (LDH), max LDH, ferritin and max ferritin, C-reactive protein (CRP), max CRP, procalcitonin, max procalcitonin, potassium values and low albumin values, complications as bacterial infection, cardiac disease, acute respiratory distress syndrome, liver function tests failure, arrhythmia and shock, the need for corticosteroid and pulse corticosteroid therapy increased the mortality. According to multiple logistic regression model, the de-velopment of cardiac disease, acute respiratory distress syndrome, bacterial infection, the need for pulse steroids, and the max ferritin value increased the risk of mortality by between 1.001 and 28.715 times. CONCLUSIONS: Both clinical and laboratory parameters predicting mortality in geriatric patients with COVID-19 pneumonia should be monitored very carefully. Complications that develop should be evaluated and multidisciplinary and necessary treatments should be initiated without delay.

Assessment of the dissimilarities of totally 186 countries and regions according to COVID-19 indicators at the end of March 2020.

Background: This study is aimed at evaluating the relationship between the number of days elapsed since a country's first case(s) of coronavirus disease 2019 (COVID-19), the total number of tests conducted, and outbreak indicators such as the total numbers of cases, deaths, and patients who recovered. The study compares COVID-19 indicators among countries and clusters them according to similarities in the indicators. Methods: Descriptive statistics of the indicators were computed and the results were presented in figures and tables. A fuzzy c-means clustering algorithm was used to cluster/group the countries according to the similarities in the total numbers of patients who recovered, deaths, and active cases. Results: The highest numbers of COVID-19 cases were found in Gibraltar, Spain, Switzerland, Liechtenstein and Italy were also of that order with about 1500 cases per million population. Spain and Italy had the highest total number of deaths, which were about 140 and 165 per million population, respectively. In Japan, where exposure to the causative virus was longer than in most other countries, the total number of deaths per million population was less than 0.5. According to cluster analysis, the total numbers of deaths, patients who recovered, and active cases were higher in Western countries, especially in central and southern European countries, which had the highest numbers when compared with other countries. Conclusion: There may be various reasons for the differences between the clusters obtained by fuzzy c-means clustering. These include quarantine measures, climatic conditions, economic levels, health policies, and the duration of the fight against the outbreak.