Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.
Background: The COVID-19 pandemic is challenging healthcare systems worldwide. Dermatology had to re-prioritize visits, guarantee urgent care, and ensure continuity for chronic patients. Objectives: To evaluate the COVID-19 impact on dermatologic surgery outpatient management. Material and methods: In this real-life retrospective observational study, we evaluated both major and minor outpatient surgeries (MaOS and MiOS) performance in 2020, before and during the first month of lockdown declaration, in a primary referral center in Northern Italy. During the lockdown, all lifesaving and cancer surgery, (approximately 80% of our usual activities), were continued. Data from 2020 were compared with the 2019 corresponding periods to assess the real-life impact of COVID-19 in dermatologic surgical activities. Results: From January 1st to April 3rd, 2020 we performed 769 interventions, compared to 908 over the corresponding 2019 period. After the lockdown, scheduled surgeries were reduced by 14.8%; overall performed ones displayed a reduction of 46.5% (51.6% MaOS, 44.2% MiOS). 52.9% and 12.5% procedures were canceled due to patients' renunciation and due to confirmed/suspected COVID-19, respectively. Conclusions: While reduced in number, dermatologic surgeries, similarly to other surgical specialties, remained operative to provide oncological and/or life-saving procedures.
Introduction. The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. Materials and Methods. In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients ( F 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. Results. At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) ( χ 2 10.4; p < 0.001 ), neutrophil-to-lymphocyte (NL) ratio ( χ 2 7.6; p = 0.006 ), and platelet count ( χ 2 5.39; p = 0.02 ), along with age ( χ 2 87.6; p < 0.001 ) and gender ( χ 2 17.3; p < 0.001 ), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a NL ratio > 4.68 was characterized by an odds ratio for in-hospital mortality OR = 3.40 (2.40-4.82), while the OR for a RDW > 13.7 % was 4.09 (2.87-5.83); a platelet count > 166,000 /μL was, conversely, protective (OR: 0.45 (0.32-0.63)). Conclusion. Our findings arise the opportunity of stratifying COVID-19 severity according to simple lab parameters, which may drive clinical decisions about monitoring and treatment.
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