Department of Emergency Medicine, Emergency Medicine and Difficult Diseases Institute, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Department of Emergency Medicine, Changsha Central Hospital, University of South China, Changsha, Hunan, China.
Am J Med Sci. 2022 Apr;363(4):322-332. doi: 10.1016/j.amjms.2021.08.009. Epub 2021 Oct 4.
Acute respiratory distress syndrome (ARDS) associated with high mortality is the common complication in acute pancreatitis (AP). The aim of this study was to formulate and validate an individualized predictive nomogram for in-hospital incidence of ARDS in Patients with AP.
From January 2017 to December 2018, 779 individuals with AP were involved in this study. They were randomly distributed into primary cohort (n = 560) and validation cohort (n = 219). Based on the primary cohort, risk factors were identified by logistic regression model and a nomogram was performed. The nomogram was validated in the primary and validation cohort by the bootstrap validation method. The calibration curve was applied to evaluate the consistency between the nomogram and the ideal observation.
There were 728 patients in the non-ARDS group and 51 in the ARDS group, with an incidence of about 6.55%. Five independent factors including white blood cell counts (WBC), prothrombin time (PT), albumin (ALB), serum creatinine (SCR) and triglyceride (TG) were associated with in-hospital incidence of ARDS in Patients with AP. A nomogram was constructed based on the five independent factors with primary cohort of AUC = 0.821 and validation cohort of AUC = 0.823. Calibration curve analysis indicated that the predicted probability was in accordance with the observed probability in both primary and validation cohorts.
The study developed an intuitive nomogram with easily available laboratory parameters for the prediction of in-hospital incidence of ARDS in patients with AP. The incidence of ARDS for an individual patient can be fast and conveniently evaluated by our nomogram.
与高死亡率相关的急性呼吸窘迫综合征（ARDS）是急性胰腺炎（AP）的常见并发症。本研究的目的是制定和验证一种个体化预测模型，用于预测 AP 患者住院期间 ARDS 的发生率。
本研究纳入了 2017 年 1 月至 2018 年 12 月期间的 779 名 AP 患者。他们被随机分为主要队列（n=560）和验证队列（n=219）。基于主要队列，使用逻辑回归模型确定危险因素，并建立预测模型。使用 bootstrap 验证方法对预测模型进行了验证，分别在主要和验证队列中进行验证。校准曲线用于评估预测模型与理想观察之间的一致性。
非 ARDS 组有 728 例，ARDS 组有 51 例，发生率约为 6.55%。白细胞计数（WBC）、凝血酶原时间（PT）、白蛋白（ALB）、血清肌酐（SCR）和甘油三酯（TG）等五个独立因素与 AP 患者住院期间 ARDS 的发生率有关。根据这五个独立因素建立了一个预测模型，主要队列的 AUC 为 0.821，验证队列的 AUC 为 0.823。校准曲线分析表明，主要和验证队列的预测概率与观察概率相符。
本研究开发了一种基于易于获得的实验室参数的直观预测模型，用于预测 AP 患者住院期间 ARDS 的发生率。通过我们的预测模型，可以快速方便地评估个体患者 ARDS 的发生率。
