Comparison of demographic and clinical characteristics of hospitalized COVID-19 patients with severe/critical illness in the first wave versus the second wave.

Due to current advances and growing experience in the management of coronavirus Disease 2019 (COVID-19), the outcome of COVID-19 patients with severe/critical illness would be expected to be better in the second wave compared with the first wave. As our hospitalization criteria changed in the second wave, we aimed to investigate whether a favorable outcome occurred in hospitalized COVID-19 patients with only severe/critical illness. Among 642 laboratory-confirmed hospitalized COVID-19 patients in the first wave and 1121 in the second wave, those who met World Health Organization (WHO) definitions for severe or critical illness on admission or during follow-up were surveyed. Data on demographics, comorbidities, C-reactive protein (CRP) levels on admission, and outcomes were obtained from an electronic hospital database. Univariate analysis was performed to compare the characteristics of patients in the first and second waves. There were 228 (35.5%) patients with severe/critical illness in the first wave and 681 (60.7%) in the second wave. Both groups were similar in terms of age, gender, and comorbidities, other than chronic kidney disease. Median serum CRP levels were significantly higher in patients in the second wave compared with those in the first wave [109 mg/L (interquartile range [IQR]: 65-157) vs. 87 mg/L (IQR: 39-140); p < 0.001]. However, intensive care unit admission and mortality rates were similar among the waves. Even though a lower mortality rate in the second wave has been reported in previous studies, including all hospitalized COVID-19 patients, we found similar demographics and outcomes among hospitalized COVID-19 patients with severe/critical illness in the first and second wave.

Performance of pneumonia severity index and CURB-65 in predicting 30-day mortality in patients with COVID-19.

OBJECTIVE: The aim of the study was to analyze the usefulness of CURB-65 and the pneumonia severity index (PSI) in predicting 30-day mortality in patients with COVID-19, and to identify other factors associated with higher mortality. METHODS: A retrospective study was performed in a pandemic hospital in Istanbul, Turkey, which included 681 laboratory-confirmed patients with COVID-19. Data on characteristics, vital signs, and laboratory parameters were recorded from electronic medical records. Receiver operating characteristic analysis was used to quantify the discriminatory abilities of the prognostic scales. Univariate and multivariate logistic regression analyses were performed to identify other predictors of mortality. RESULTS: Higher CRP levels were associated with an increased risk for mortality (OR: 1.015, 95% CI: 1.008-1.021; p < 0.001). The PSI performed significantly better than CURB-65 (AUC: 0.91, 95% CI: 0.88-0.93 vs AUC: 0.88, 95% CI: 0.85-0.90; p = 0.01), and the addition of CRP levels to PSI did not improve the performance of PSI in predicting mortality (AUC: 0.91, 95% CI: 0.88-0.93 vs AUC: 0.92, 95% CI: 0.89-0.94; p = 0.29). CONCLUSION: In a large group of hospitalized patients with COVID-19, we found that PSI performed better than CURB-65 in predicting mortality. Adding CRP levels to PSI did not improve the 30-day mortality prediction.

Protease Inhibitors Drug Resistance Mutations in Turkish Patients with Chronic Hepatitis C.

BACKGROUND: Drug resistance development is an expected problem during treatment with protease inhibitors (PIs), this is largely due to the fact that Pls are low-genetic barrier drugs. Resistance-associated variants (RAVs) however may also occur naturally, and prior to treatment with Pls, the clinical impact of this basal resistance remains unknown. In Turkey, there is yet to be an investigation into the hepatitis C (HCV) drug associated resistance to oral antivirals. MATERIALS AND METHODS: 178 antiviral-naïve patients infected with HCV genotype 1 were selected from 27 clinical centers of various geographical regions in Turkey and included in the current study. The basal NS3 Pls resistance mutations of these patients were analyzed. RESULTS: In 33 (18.5%) of the patients included in the study, at least one mutation pattern that can cause drug resistance was identified. The most frequently detected mutation pattern was T54S while R109K was the second most frequently detected. Following a more general examination of the patients studied, telaprevir (TVR) resistance in 27 patients (15.2%), boceprevir (BOC) resistance in 26 (14.6%) patients, simeprevir (SMV) resistance in 11 (6.2%) patients and faldaprevir resistance in 13 (7.3%) patients were detected. Our investigation also revealed that rebound developed in the presence of a Q80K mutation and amongst two V55A mutations following treatment with TVR, while no response to treatment was detected in a patient with a R55K mutation. CONCLUSION: We are of the opinion that drug resistance analyses can be beneficial and necessary in revealing which variants are responsible for pre-treatment natural resistance and which mutations are responsible for the viral breakthrough that may develop during the treatment.