Table_2_Novel models for early prediction and prevention of acute respiratory distress syndrome in patients following hepatectomy: A clinical translational study based on 1,032 patients.docx

BackgroundAcute respiratory distress syndrome (ARDS) is a serious organ failure and postoperative complication. However, the incidence rate, early prediction and prevention of postoperative ARDS in patients undergoing hepatectomy remain unidentified.MethodsA total of 1,032 patients undergoing hepatectomy between 2019 and 2020, at the Eastern Hepatobiliary Surgery Hospital were included. Patients in 2019 and 2020 were used as the development and validation cohorts, respectively. The incidence rate of ARDS was assessed. A logistic regression model and a least absolute shrinkage and selection operator (LASSO) regression model were used for constructing ARDS prediction models.ResultsThe incidence of ARDS was 8.8% (43/490) in the development cohort and 5.7% (31/542) in the validation cohort. Operation time, postoperative aspartate aminotransferase (AST), and postoperative hemoglobin (Hb) were all critical predictors identified by the logistic regression model, with an area under the curve (AUC) of 0.804 in the development cohort and 0.752 in the validation cohort. Additionally, nine predictors were identified by the LASSO regression model, with an AUC of 0.848 in the development cohort and 0.786 in the validation cohort.ConclusionWe reported the incidence of ARDS in patients undergoing hepatectomy and developed two simple and practical prediction models for early predicting postoperative ARDS in patients undergoing hepatectomy. These tools may improve clinicians’ ability to early estimate the risk of postoperative ARDS and timely prevent its emergence.

背景急性呼吸窘迫综合征（ARDS）是一种严重的器官衰竭及术后并发症。然而，在行肝切除术患者中，术后ARDS的发病率、早期预测及预防尚待明确。方法本研究纳入了2019年至2020年在东方肝胆外科医院接受肝切除术的共1,032名患者。将2019年和2020年的患者分别用作开发集和验证集。评估了ARDS的发病率。采用逻辑回归模型和最小绝对收缩和选择算子（LASSO）回归模型构建ARDS预测模型。结果在开发集中，ARDS的发病率为8.8%（43/490），在验证集中为5.7%（31/542）。手术时间、术后天冬氨酸转氨酶（AST）和术后血红蛋白（Hb）均为逻辑回归模型识别出的关键预测因素，开发集中的曲线下面积（AUC）为0.804，验证集中的AUC为0.752。此外，LASSO回归模型还识别出九个预测因素，开发集中的AUC为0.848，验证集中的AUC为0.786。结论本研究报告了行肝切除术患者中ARDS的发病率，并开发了两个简单实用的预测模型，用于早期预测行肝切除术患者的术后ARDS。这些工具可能提高临床医生早期评估术后ARDS风险并及时预防其发生的能力。