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Title: Assessment of methods aiming to predict selected results of surgical treatment in patients with morbid obesity
Abstract:
Bariatric surgery is the most effective treatment for obesity and comorbidities, yet outcomes vary and complications remain a risk. Various predictive models have been proposed, but their clinical utility is unclear. This study aimed to identify and evaluate tools predicting weight loss, diabetes remission and postoperative complications, with emphasis on accuracy and practical use. We reviewed the literature and retrospectively analysed 1329 patients who underwent RYGB or SG (2009-2021) with 1-year followup. Median BMI dropped from 45 to 32.5kg/m2, EWL reached 63%, and diabetes remission occurred in 68.7% (partial) and 21.8% (complete). Complications occurred in 8.4%, severe in 2.8%. Twelve weight-loss models, five diabetes remission scores and ten complication algorithms were identified. All correlated with observed outcomes but showed limited accuracy. Weight-loss models tended to overestimate results; the best explained only 24% of variance. DiaBetter showed the best performance for diabetes remission (AUROC 0.81) with good calibration. Gupta and MBSAQIP achieved acceptable accuracy for severe complications but none predicted overall morbidity reliably. In conclusion, current models provide modest predictive value. DiaBetter is most useful for diabetes remission, while Gupta and MBSAQIP may help assess severe complications. Further research is needed to improve tools, espec ; ially for weight loss and general morbidity prediction.
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Rada Dyscypliny Nauki medyczne
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Last modified:
Apr 15, 2026
In our library since:
Apr 15, 2026
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http://149.156.57.56:8080/publication/6146
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| Edition name | Date |
|---|---|
| ZB-144224 | Apr 15, 2026 |
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