Show simple item record

dc.contributor.authorSingh, Pushpa
dc.contributor.authorAdderley, Nicola J
dc.contributor.authorHazlehurst, Jonathan
dc.contributor.authorPrice, Malcolm
dc.contributor.authorTahrani, Abd A
dc.contributor.authorNirantharakumar, Krishnarajah
dc.contributor.authorBellary, Srikanth
dc.date.accessioned2024-10-30T10:21:41Z
dc.date.available2024-10-30T10:21:41Z
dc.date.issued2021-10-18
dc.identifier.citationSingh P, Adderley NJ, Hazlehurst J, Price M, Tahrani AA, Nirantharakumar K, Bellary S. Prognostic Models for Predicting Remission of Diabetes Following Bariatric Surgery: A Systematic Review and Meta-analysis. Diabetes Care. 2021 Nov;44(11):2626-2641. doi: 10.2337/dc21-0166.en_US
dc.identifier.issn0149-5992
dc.identifier.eissn1935-5548
dc.identifier.doi10.2337/dc21-0166
dc.identifier.pmid34670787
dc.identifier.urihttp://hdl.handle.net/20.500.14200/6293
dc.description.abstractBackground: Remission of type 2 diabetes following bariatric surgery is well established, but identifying patients who will go into remission is challenging. Purpose: To perform a systematic review of currently available diabetes remission prediction models, compare their performance, and evaluate their applicability in clinical settings. Data sources: A comprehensive systematic literature search of MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) was undertaken. The search was restricted to studies published in the last 15 years and in the English language. Study selection: All studies developing or validating a prediction model for diabetes remission in adults after bariatric surgery were included. Data extraction: The search identified 4,165 references, of which 38 were included for data extraction. We identified 16 model development and 22 validation studies. Data synthesis: Of the 16 model development studies, 11 developed scoring systems and 5 proposed logistic regression models. In model development studies, 10 models showed excellent discrimination with area under the receiver operating characteristic curve ≥0.800. Two of these prediction models, ABCD and DiaRem, were widely externally validated in different populations, in a variety of bariatric procedures, and for both short- and long-term diabetes remission. Newer prediction models showed excellent discrimination in test studies, but external validation was limited. Limitations: While the key messages were consistent, a large proportion of the studies were conducted in small cohorts of patients with short duration of follow-up. Conclusions: Among the prediction models identified, the ABCD and DiaRem models were the most widely validated and showed acceptable to excellent discrimination. More studies validating newer models and focusing on long-term diabetes remission are needed.en_US
dc.language.isoenen_US
dc.publisherAmerican Diabetes Associationen_US
dc.relation.urlhttps://diabetesjournals.org/careen_US
dc.rights© 2021 by the American Diabetes Association.
dc.subjectDiabetesen_US
dc.subjectSurgeryen_US
dc.subjectEndocrinologyen_US
dc.titlePrognostic models for predicting remission of diabetes following bariatric surgery: a systematic review and meta-analysisen_US
dc.typeArticleen_US
dc.source.journaltitleDiabetes Careen_US
dc.source.volume44
dc.source.issue11
dc.source.beginpage2626
dc.source.endpage2641
dc.source.countryUnited Kingdom
dc.source.countryUnited States
rioxxterms.versionNAen_US
dc.contributor.trustauthorSingh, Pushpa
dc.contributor.trustauthorHazlehurst, Jonathan
dc.contributor.trustauthorBellary, Srikanth
dc.contributor.departmentEndocrinology and Diabetesen_US
dc.contributor.departmentGeneral Medicineen_US
dc.contributor.roleMedical and Dentalen_US
dc.contributor.affiliationUniversity of Birmingham; University Hospitals Birmingham NHS Foundation Trust; Birmingham Health Partners; Midlands Health Data Research; Aston Universityen_US
oa.grant.openaccessnaen_US


This item appears in the following Collection(s)

Show simple item record