Osawa Eduardo Atsushi, Maciel Alexandre Toledo
Research Department, Imed Group, Sao Paulo, Brazil.
Adult Intensive Care Unit, Sao Camilo Hospital-Unidade Pompeia, Sao Paulo, Brazil.
Acute Crit Care. 2022 Nov;37(4):580-591. doi: 10.4266/acc.2022.00283. Epub 2022 Sep 8.
We aimed to characterize patients hospitalized for coronavirus disease 2019 (COVID-19) and identify predictors of invasive mechanical ventilation (IMV).
We performed a retrospective cohort study in patients with COVID-19 admitted to a private network in Sao Paulo, Brazil from March to October 2020. Patients were compared in three subgroups: non-intensive care unit (ICU) admission (group A), ICU admission without receiving IMV (group B) and IMV requirement (group C). We developed logistic regression algorithm to identify predictors of IMV.
We analyzed 1,650 patients, the median age was 53 years (42-65) and 986 patients (59.8%) were male. The median duration from symptom onset to hospital admission was 7 days (5-9) and the main comorbidities were hypertension (42.4%), diabetes (24.2%) and obesity (15.8%). We found differences among subgroups in laboratory values obtained at hospital admission. The predictors of IMV (odds ratio and 95% confidence interval [CI]) were male (1.81 [1.11-2.94], P=0.018), age (1.03 [1.02-1.05], P<0.001), obesity (2.56 [1.57-4.15], P<0.001), duration from symptom onset to admission (0.91 [0.85-0.98], P=0.011), arterial oxygen saturation (0.95 [0.92- 0.99], P=0.012), C-reactive protein (1.005 [1.002-1.008], P<0.001), neutrophil-to-lymphocyte ratio (1.046 [1.005-1.089], P=0.029) and lactate dehydrogenase (1.005 [1.003-1.007], P<0.001). The area under the curve values were 0.860 (95% CI, 0.829-0.892) in the development cohort and 0.801 (95% CI, 0.733-0.870) in the validation cohort.
Patients had distinct clinical and laboratory parameters early in hospital admission. Our prediction model may enable focused care in patients at high risk of IMV.
我们旨在对因2019冠状病毒病（COVID-19）住院的患者进行特征描述，并确定有创机械通气（IMV）的预测因素。
我们对2020年3月至10月在巴西圣保罗一家私立网络医院收治的COVID-19患者进行了一项回顾性队列研究。将患者分为三个亚组进行比较：非重症监护病房（ICU）入院患者（A组）、入住ICU但未接受IMV的患者（B组）和需要IMV的患者（C组）。我们开发了逻辑回归算法来确定IMV的预测因素。
我们分析了1650例患者，中位年龄为53岁（42 - 65岁），986例患者（59.8%）为男性。从症状出现到入院的中位时间为7天（5 - 9天），主要合并症为高血压（42.4%）、糖尿病（24.2%）和肥胖（15.8%）。我们发现入院时获得的实验室值在亚组之间存在差异。IMV的预测因素（比值比和95%置信区间[CI]）为男性（1.81[1.11 - 2.94]，P = 0.018）、年龄（1.03[1.02 - 1.05]，P < 0.001）、肥胖（2.56[1.57 - 4.15]，P < 0.001）、从症状出现到入院的时间（0.91[0.85 - 0.98]，P = 0.011）、动脉血氧饱和度（0.95[0.92 - 0.99]，P = 0.012）、C反应蛋白（1.005[1.002 - 1.008]，P < 0.001）、中性粒细胞与淋巴细胞比值（1.046[1.005 - 1.089]，P = 0.029）和乳酸脱氢酶（1.005[1.003 - 1.007]，P < 0.001）。在开发队列中曲线下面积值为0.860（95%CI，0.829 - 0.892），在验证队列中为0.801（95%CI，0.733 - 0.870）。
患者在入院早期有不同的临床和实验室参数。我们的预测模型可能有助于对有IMV高风险的患者进行重点护理。
