Introduction: Since the beginning of the pandemic, factors associated with mortality in patients with corona virus infection disease 2019 (COVID-19) have been investigated. Comorbidities and increased age have been frequently reported to be associated with mortality. We aimed to evaluate the factors associated with unfavorable outcome of patients with COVID-19 at an early period of the pandemic.
Methodology: This single center, retrospective, observational study was conducted among laboratory confirmed COVID-19 patients hospitalized between March 11 and May 5, 2020, at Umraniye Training and Research Hospital, Istanbul, Turkey. The effects of the severity of illness, comorbidities, symptoms, and laboratory findings on the clinical outcome were evaluated. Factors associated with unfavorable outcome (necessity of mechanical ventilation or death) were examined using Cox proportional hazards models.
Results: Out of a total of 728 patients, 53.8% were men and median age 54 years. The 30-day mortality rate was 4.9% among all hospitalized patients. A logistic regression model identified six predictors of unfavorable clinical outcome: age, severity of illness, the numbers of comorbidities, lymphopenia, high levels of C-reactive protein, and procalcitonin.
Conclusions: The mortality rate was lower among the patients with COVID-19, hospitalized during the early period of the pandemic. Older age, higher severity score on admission, the numbers of comorbidities, higher levels of C-reactive protein, procalcitonin, and lymphopenia were identified to be associated with unfavorable outcome of the hospitalized patients with COVID-19.
Next-generation sequencing (NGS) is used increasingly in hereditary cancer patients' (HCP) management. While enabling evaluation of multiple genes simultaneously, the technology brings to light the dilemma of variant interpretation. Here, we aimed to reveal the underlying reasons for the discrepancy in the evidence titles used during variant classification according to ACMG guidelines by two different bioinformatic specialists (BIs) and two different clinical geneticists (CGs). We evaluated final reports of 1920 cancer patients and 189 different variants from 285 HCP were enrolled to the study. A total of 173 of these variants were classified as pathogenic (n = 132) and likely pathogenic (n = 41) by the BI and an additional 16 variants, that were classified as VUS by at least one interpreter and their classification would change the clinical management, were compared for their evidence titles between different specialists. The attributed evidence titles and the final classification of the variants among BIs and CGs were compared. The discrepancy between P/LP final reports was 22.5%. The discordance between CGs was 30% whereas the discordance between two BIs was almost 75%. The use of PVS1, PS3, PP3, PP5, PM1, PM2, BP1, BP4 criteria markedly varied from one expert to another. This difference was particularly noticeable in PP3, PP5, and PM1 evidence and mostly in the variants affecting splice sites like BRCA1 (NM_007294.4) c.4096 + 1 G > A and CHEK2(NM_007194.4) c.592 + 3 A > T. With recent advancements in precision medicine, the importance of variant interpretations is emerging. Our study shows that variant interpretation is subjective process that is in need of concrete definitions for accurate and standard interpretation.
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