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An accurate predictive model could aid identification of high\u2010risk patients, who could be targeted for particular care. This study aims to systematically review existing FD and IH prediction models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Prediction models were identified using pre\u2010specified search terms on SCOPUS, PubMed, and Web of Science. Eligible studies included those conducted in adult patients who underwent any kind of abdominal surgery, and reported model performance. Data from the eligible studies were extracted, and the risk of bias (RoB) was assessed using the PROBAST tool. Pooling of C\u2010statistics was performed using a random\u2010effect meta\u2010analysis. [Registration: PROSPERO (CRD42021282463)].<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Twelve studies were eligible for review; five were FD prediction model studies. Most included studies had high RoB, especially in the analysis domain. The C\u2010statistics of the FD and IH prediction models ranged from 0.69 to 0.92, but most have yet to be externally validated. Pooled C\u2010statistics (95% CI) were 0.80 (0.74, 0.86) and 0.81 (0.75, 0.86) for the FD (external\u2010validation) and IH prediction model, respectively. Some predictive factors such as body mass index, smoking, emergency operation, and surgical site infection were associated with FD or IH occurrence and were included in multiple models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Several models have been developed as an aid for FD and IH prediction, mostly with modest performance and lacking independent validation. New models for specific patient groups may offer clinical utility.<\/jats:p><\/jats:sec>","DOI":"10.1007\/s00268-022-06715-6","type":"journal-article","created":{"date-parts":[[2022,9,14]],"date-time":"2022-09-14T13:04:40Z","timestamp":1663160680000},"page":"2984-2995","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Fascial Dehiscence and Incisional Hernia Prediction Models: A Systematic Review and Meta\u2010analysis"],"prefix":"10.1002","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2040-7970","authenticated-orcid":false,"given":"Amarit","family":"Tansawet","sequence":"first","affiliation":[{"name":"Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital Mahidol University Rama VI Road 10400 Bangkok, Ratchathewi Thailand"},{"name":"Department of Surgery, Faculty of Medicine Vajira Hospital Navamindradhiraj University Bangkok 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