Prognostic Value of T wave Positivity in Lead aVR in COVID-19 Pneumonia (preprint)

Background: T wave positivity in the lead aVR is a marker of ventricular repolarization abnormality and provides information on short and long-term cardiovascular mortality in patients who have heart failure, anterior myocardial infarction, and receive hemodialysis for various reasons. The aim of this study was to investigate the relationship between T wave positivity in the lead aVR on superficial ECG and mortality from COVID-19 pneumonia. Methods: This study retrospectively included 130 patients who were diagnosed with COVID-19 and treated as an outpatient or in the thoracic diseases ward in a single center between January 2021 and June 2021. All patients included in the study had clinical and radiological features and signs of COVID-19 pneumonia. The COVID-19 diagnosis of all patients was confirmed by polymerase chain reaction (PCR) studied from an oropharyngeal swab Results: A total of 130 patients were included in this study. Patients were divided into 2 groups: survived and deceased. There were 55 patients (with a mean age of 64.76-14.93 years, 58.18% male, 41.12% female) in the survived group, while there were 75 patients (with a mean age of 65-15 years, 58.67% male, 41.33% female) in the deceased group. The univariate and multivariate regression analyses showed that positive TAVR (OR: 5.151, 95% CI: 1.001-26.504, p: 0.0012), lactate dehydrogenase (LDH) (OR: 1.006, 95% CI: 1.001-1.010, p: 0.012) and D-dimer (OR:1.436, 95% CI: 1.115-1.848, p: 0.005) were independent risk factors for mortality Conclusions: positive TAaVR is useful in risk stratification for COVID-19 pneumonia mortality. KEY WORLD:Electrocardıographıa, positive TAaVR, COVID-19 pneumonia, mortality

Ankara City Hospital COVID-19 Severity Score (ACCSES):A Calculation Tool in the Prediction of Severe Illness Requiring Intensive Care Follow-up (preprint)

Aim: The aim of this study is to develop and explain an easy-to-use severity score calculation tool to predict severe COVID-19 cases that would need intensive care unit (ICU) follow-up.Material method: The study was carried out in patients with laboratory-confirmed COVID-19 hospitalized in Ankara City Hospital between March 15, 2020, and June 15, 2020. The outcome was severe illness that required ICU follow-up. Univariate and binary logistic regression were used to create a prediction model by using potential predictive parameters obtained on the day of hospitalization. Youden’s J index was calculated with receiver-operator characteristic curves analysis in order to evaluate cut-off points, and predicted probability was calculated. The accuracy of the prediction model was tested by calculating the area under curve (AUC). Results: Of the total of 1022 patients, 152 had a severe illness and required ICU follow-up. Among 68 variables, 20 parameters met the potential predictive factor condition for severe illness and were included in the development process for ANKARA CITY HOSPITAL COVID-19 SEVERITY SCORE (ACCSES). The ACCSES calculation tool was created by the final 9 parameters (sex, oxygen saturation, hemoglobin, platelet count, glomerular filtration rate, aspartate transaminase, procalcitonin, ferritin, and D-dimer). AUC was 0.96 (95% CI, 0.95-0.98).Conclusion: We developed a simple, accessible, easy to use calculation tool, ACCSES, with good distinctive power for a severe illness that required ICU follow-up. The clinician can easily predict the course of COVID-19 and decide the procedure and facility of further follow-up simply using available clinical and laboratory values of patients upon admission.