Department of Integrated Traditional Chinese and Western Medicine, Sichuan Provincial Pancreatitis Center and West China-Liverpool Biomedical Research Center, West China Hospital, Sichuan University, Chengdu, China.
Department of Gastroenterology, First Affiliated Hospital of Nanchang University, Nanchang, China.
HPB (Oxford). 2022 Nov;24(11):1907-1920. doi: 10.1016/j.hpb.2022.05.1347. Epub 2022 Jun 6.
Early prediction of persistent organ failure (POF) is important for triage and timely treatment of patients with acute pancreatitis (AP).
All AP patients were consecutively admitted within 48 h of symptom onset. A nomogram was developed to predict POF on admission using data from a retrospective training cohort, validated by two prospective cohorts. The clinical utility of the nomogram was defined by concordance index (C-index), decision curve analysis (DCA), and clinical impact curve (CIC), while the performance by post-test probability.
There were 816, 398, and 880 patients in the training, internal and external validation cohorts, respectively. Six independent predictors determined by logistic regression analysis were age, respiratory rate, albumin, lactate dehydrogenase, oxygen support, and pleural effusion and were included in the nomogram (web-based calculator: https://shina.shinyapps.io/DynNomapp/). This nomogram had reasonable predictive ability (C-indexes 0.88/0.91/0.81 for each cohort) and promising clinical utility (DCA and CIC). The nomogram had a positive likelihood ratio and post-test probability of developing POF in the training, internal and external validation cohorts of 4.26/31.7%, 7.89/39.1%, and 2.75/41%, respectively, superior or equal to other prognostic scores.
This nomogram can predict POF of AP patients and should be considered for clinical practice and trial allocation.
早期预测持续性器官衰竭(POF)对于急性胰腺炎(AP)患者的分诊和及时治疗非常重要。
所有 AP 患者均在症状出现后 48 小时内连续入院。使用回顾性训练队列中的数据开发了一个列线图,以在入院时预测 POF,并通过两个前瞻性队列进行验证。通过一致性指数(C 指数)、决策曲线分析(DCA)和临床影响曲线(CIC)定义列线图的临床实用性,而通过后验概率定义其性能。
训练、内部和外部验证队列中分别有 816、398 和 880 例患者。逻辑回归分析确定的六个独立预测因素为年龄、呼吸频率、白蛋白、乳酸脱氢酶、氧支持和胸腔积液,并包含在列线图中(网络计算器:https://shina.shinyapps.io/DynNomapp/)。该列线图具有合理的预测能力(每个队列的 C 指数分别为 0.88/0.91/0.81)和有前途的临床实用性(DCA 和 CIC)。该列线图在训练、内部和外部验证队列中发生 POF 的阳性似然比和后验概率分别为 4.26/31.7%、7.89/39.1%和 2.75/41%,优于其他预后评分。
该列线图可预测 AP 患者的 POF,应考虑用于临床实践和试验分配。