Advanced

Systematic review of risk prediction models for diabetes after bariatric surgery

Zhang, R.; Borisenko, O.; Telegina, I.; Hargreaves, J.; Ahmed, A. R.; Sanchez Santos, R.; Pring, C.; Funch-Jensen, P.; Dillemans, B. and Hedenbro, J. L. LU (2016) In British Journal of Surgery 103(11). p.1420-1427
Abstract

Background: Diabetes remission is an important outcome after bariatric surgery. The purpose of this study was to identify risk prediction models of diabetes remission after bariatric surgery. Methods: A systematic literature review was performed in MEDLINE, MEDLINE-In-Process, Embase and the Cochrane Central Register of Controlled Trials databases in April 2015. All English-language full-text published derivation and validation studies for risk prediction models on diabetic outcomes after bariatric surgery were included. Data extraction included population, outcomes, variables, intervention, model discrimination and calibration. Results: Of 2330 studies retrieved, eight met the inclusion criteria. Of these, six presented development of... (More)

Background: Diabetes remission is an important outcome after bariatric surgery. The purpose of this study was to identify risk prediction models of diabetes remission after bariatric surgery. Methods: A systematic literature review was performed in MEDLINE, MEDLINE-In-Process, Embase and the Cochrane Central Register of Controlled Trials databases in April 2015. All English-language full-text published derivation and validation studies for risk prediction models on diabetic outcomes after bariatric surgery were included. Data extraction included population, outcomes, variables, intervention, model discrimination and calibration. Results: Of 2330 studies retrieved, eight met the inclusion criteria. Of these, six presented development of risk prediction models and two reported validation of existing models. All included models were developed to predict diabetes remission. Internal validation using tenfold validation was reported for one model. Two models (ABCD score and DiaRem score) had external validation using independent patient cohorts with diabetes remission assessed at 12 and 14 months respectively. Of the 11 cohorts included in the eight studies, calibration was not reported in any cohort, and discrimination was reported in two. Conclusion: A variety of models are available for predicting risk of diabetes following bariatric surgery, but only two have undergone external validation.

(Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
British Journal of Surgery
volume
103
issue
11
pages
1420 - 1427
publisher
John Wiley & Sons
external identifiers
  • scopus:84983447405
  • wos:000384671500003
ISSN
0007-1323
DOI
10.1002/bjs.10255
language
English
LU publication?
yes
id
0bca91a9-4038-47c8-b5a4-2087b60ecb80
date added to LUP
2016-10-10 12:16:21
date last changed
2017-10-13 00:01:00
@article{0bca91a9-4038-47c8-b5a4-2087b60ecb80,
  abstract     = {<p>Background: Diabetes remission is an important outcome after bariatric surgery. The purpose of this study was to identify risk prediction models of diabetes remission after bariatric surgery. Methods: A systematic literature review was performed in MEDLINE, MEDLINE-In-Process, Embase and the Cochrane Central Register of Controlled Trials databases in April 2015. All English-language full-text published derivation and validation studies for risk prediction models on diabetic outcomes after bariatric surgery were included. Data extraction included population, outcomes, variables, intervention, model discrimination and calibration. Results: Of 2330 studies retrieved, eight met the inclusion criteria. Of these, six presented development of risk prediction models and two reported validation of existing models. All included models were developed to predict diabetes remission. Internal validation using tenfold validation was reported for one model. Two models (ABCD score and DiaRem score) had external validation using independent patient cohorts with diabetes remission assessed at 12 and 14 months respectively. Of the 11 cohorts included in the eight studies, calibration was not reported in any cohort, and discrimination was reported in two. Conclusion: A variety of models are available for predicting risk of diabetes following bariatric surgery, but only two have undergone external validation.</p>},
  author       = {Zhang, R. and Borisenko, O. and Telegina, I. and Hargreaves, J. and Ahmed, A. R. and Sanchez Santos, R. and Pring, C. and Funch-Jensen, P. and Dillemans, B. and Hedenbro, J. L.},
  issn         = {0007-1323},
  language     = {eng},
  number       = {11},
  pages        = {1420--1427},
  publisher    = {John Wiley & Sons},
  series       = {British Journal of Surgery},
  title        = {Systematic review of risk prediction models for diabetes after bariatric surgery},
  url          = {http://dx.doi.org/10.1002/bjs.10255},
  volume       = {103},
  year         = {2016},
}