Cluster analysis in subjects living with obesity and association with bariatric surgery outcomes: The severe obesity outcome network cohort.
Obesity is a heterogeneous condition encompassing different phenotypes that may respond differently to bariatric surgery. We sought to identify homogeneous groups of patients who might require specific management adapted to their characteristics. We use the Severe Obesity Outcome Network (SOON) pros...
| Publicado en: | Clinical Nutrition Vol. 54; pp. 210 - 220 |
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| Autores principales: | , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Nov2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=189076086&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189076086 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02615614 8IC jtl: Clinical Nutrition issn: 02615614 maglogo: N pubinfo: dt: Nov2025 vid: 54 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 189076086 189076086 189076086 10.1016/j.clnu.2025.09.022 189076086 ppf: 210 ppct: 10 formats: tig: atl: Cluster analysis in subjects living with obesity and association with bariatric surgery outcomes: The severe obesity outcome network cohort. aug: au: Borel, Anne-Laure Van Ngo, Thi Hong Coumes, Sandrine Pépin, Jean-Louis Abba, Julio tamisier, Renaud Tonetti, Gabrielle Suzeau, Pauline Reche, Fabian Bailly, Sébastien affil: Département of Endocrinology Diabetology Nutrition, CHU Grenoble Alpes, CS10217, Grenoble Cedex 9, 38043, France sug: subj: Cluster Analysis Obesity, Morbid Surgery Bariatric Surgery Treatment Outcomes Human Probability Sample Structural Equation Modeling Time Factors Postoperative Period Male Female Comorbidity Body Mass Index Adult Middle Age Aged Weight Loss Phenotype Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Obesity is a heterogeneous condition encompassing different phenotypes that may respond differently to bariatric surgery. We sought to identify homogeneous groups of patients who might require specific management adapted to their characteristics. We use the Severe Obesity Outcome Network (SOON) prospective cohort of subjects with class II and III obesity to identify groups of people with homogenous characteristics. An unsupervised probabilistic clustering method, latent class analysis, was used. The clusters obtained with this analysis were compared for their outcomes after bariatric surgery up to 5-years postoperatively. 965 subjects were analyzed, enabling five clusters to be described. Cluster 1: middle-aged women with few comorbidities. Cluster 2: young, healthy women. Cluster 3: men and women with the highest BMI and frequent comorbidities. Cluster 4: relatively healthy young men. Cluster 5: older men and women with very high frequency of comorbidities. Cluster 2 had the best total body weight loss. Cluster 3, which had the most severe medical and socio-economic profile, had also the smallest total body weight loss after bariatric surgery. Surgery complications' rates were not different between clusters. Subjects with obesity can be attributed to five different phenotypes that can be identified in routine clinical practice. Subjects of cluster 2, young healthy women, had the best weight loss after bariatric surgery. Cluster 3, comprising men and women with the highest BMI and frequent comorbidities, had poorer results after bariatric surgery. Subjects in this cluster should therefore benefit from more intensive management. ClinicalTrials.gov NCT02264431. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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