Department of Translational Medicine, Università del Piemonte Orientale UPO, Via Solaroli 17, 28100, Novara, NO, Italy.
Azienda Ospedaliero Universitaria "Maggiore Della Carita", Novara, Italy.
Sci Rep. 2020 Nov 26;10(1):20731. doi: 10.1038/s41598-020-77698-4.
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 PaO/FiO 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.
新型冠状病毒病（COVID-19）的临床特征和自然史在不同国家和大流行的不同阶段有很大差异。在这里，我们旨在评估 2020 年 3 月 1 日至 4 月 28 日期间意大利北部三家医院收治的 COVID-19 患者队列的病死率（CFR），并确定死亡的预测因素。所有这些患者均通过分子方法确诊为 SARS-CoV-2 感染。在研究期间，有 504/1697 名患者死亡；因此，总病死率为 29.7%。我们在有足够临床数据的 486 名患者（239 名男性，59%；中位年龄 71 岁）亚组中寻找死亡的预测因素。在所考虑的人口统计学和临床变量中，年龄、癌症诊断、肥胖和当前吸烟是独立预测死亡的因素。当将实验室数据添加到另一组患者的模型中时，年龄、癌症诊断和基线 PaO/FiO 比值被确定为死亡的独立预测因素。总之，COVID-19 大流行上升阶段意大利北部住院患者的 CFR 接近 30%。识别死亡预测因素可能有助于更好地对个体患者的风险进行分层。
