Open AccessValidation of a score chart to predict the risk of chronic mesenteric ischemia and development of an updated score chart
Author(s) -
Dijk Louisa JD,
Noord Desirée,
Geelkerken Robert H,
Harki Jihan,
Berendsen Sophie A,
Vries Annemarie C,
Moelker Adriaan,
Vergouwe Yvonne,
Verhagen Hence JM,
Kolkman Jeroen J,
Bruno Marco J
Publication year - 2019
Publication title -
ueg journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.667
H-Index - 35
eISSN - 2050-6414
pISSN - 2050-6406
DOI - 10.1177/2050640619856765
Subject(s) - medicine , chart , cohort , discriminative model , framingham risk score , statistic , statistics , artificial intelligence , disease , computer science , mathematics
Background and objective The objective of this article is to externally validate and update a recently published score chart for chronic mesenteric ischemia (CMI). Methods A multicenter prospective cohort analysis was conducted of 666 CMI‐suspected patients referred to two Dutch specialized CMI centers. Multidisciplinary consultation resulted in expert‐based consensus diagnosis after which CMI consensus patients were treated. A definitive diagnosis of CMI was established if successful treatment resulted in durable symptom relief. The absolute CMI risk was calculated and discriminative ability of the original chart was assessed by the c ‐statistic in the validation cohort. Thereafter the original score chart was updated based on the performance in the combined original and validation cohort with inclusion of celiac artery (CA) stenosis cause. Results In 8% of low‐risk patients, 39% of intermediate‐risk patients and 94% of high‐risk patients of the validation cohort, CMI was diagnosed. Discriminative ability of the original model was acceptable ( c ‐statistic 0.79). The total score of the updated chart ranged from 0 to 28 points (low risk 19% absolute CMI risk, intermediate risk 45%, and high risk 92%). The discriminative ability of the updated chart was slightly better ( c ‐statistic 0.80). Conclusion The CMI prediction model performs and discriminates well in the validation cohort. The updated score chart has excellent discriminative ability and is useful in clinical decision making.