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Weight Loss Trajectories After Bariatric Surgery for Obesity: Mathematical Model and Proof-of-Concept Study.

AbstractBACKGROUND:
Obesity surgery has proven its effectiveness in weight loss. However, after a loss phase of about 12 to 18 months, between 20% and 40% of patients regain weight. Prediction of weight evolution is therefore useful for early detection of weight regain.
OBJECTIVE:
This proof-of-concept study aimed to analyze the postoperative weight trajectories and to identify "curve families" for early prediction of weight regain.
METHODS:
This was a monocentric retrospective study with calculation of the weight trajectory of patients having undergone gastric bypass surgery. Data on 795 patients after a 2-year follow-up allowed modeling of weight trajectories according to a hierarchical cluster analysis (HCA) tending to minimize the intragroup distance according to Ward. Clinical judgement was used to finalize the identification of clinically relevant representative trajectories. This modeling was validated on a group of 381 patients for whom the observed weight at 18 months was compared to the predicted weight.
RESULTS:
Two successive HCA produced 14 representative trajectories, distributed among 4 clinically relevant families: Of the 14 weight trajectories, 6 decreased systematically over time or decreased and then stagnated; 4 decreased, increased, and then decreased again; 2 decreased and then increased; and 2 stagnated at first and then began to decrease. A comparison of observed weight and that estimated by modeling made it possible to correctly classify 98% of persons with excess weight loss (EWL) >50% and more than 58% of persons with EWL between 25% and 50%. In the category of persons with EWL >50%, weight data over the first 6 months were adequate to correctly predict the observed result.
CONCLUSIONS:
This modeling allowed correct classification of persons with EWL >50% and could identify early after surgery the patients with potentially less that optimal weight loss. Further studies are needed to validate this model in other populations, with other types of surgery, and with other medical-surgical teams.
AuthorsChloe Dimeglio, Guillaume Becouarn, Philippe Topart, Rodolphe Bodin, Jean Christophe Buisson, Patrick Ritz
JournalJMIR medical informatics (JMIR Med Inform) Vol. 8 Issue 3 Pg. e13672 (Mar 09 2020) ISSN: 2291-9694 [Print] Canada
PMID32149710 (Publication Type: Journal Article)
Copyright©Chloe Dimeglio, Guillaume Becouarn, Philippe Topart, Rodolphe Bodin, Jean Christophe Buisson, Patrick Ritz. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 09.03.2020.

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