Semaglutide and Tirzepatide in a Remote Weight Management Program: 12-Month Retrospective Observational Study
Notice bibliographique
Résumé
BACKGROUND: Obesity affects >890 million adults worldwide, and traditional lifestyle interventions often lack long-term success. While glucagonlike peptide-1 receptor agonists (GLP-1RAs) have shown strong weight loss outcomes, access to specialist care is limited by cost and capacity. OBJECTIVE: This study evaluated the effectiveness, feasibility, acceptability, and potential cost-effectiveness of a 12-month remote GLP-1RA-supported weight management program, comparing outcomes between tirzepatide and semaglutide. METHODS: This retrospective analysis included 339 participants (n=278, 82% women) who completed a 12-month remote weight management program using either tirzepatide (n=209, 61.7%) or semaglutide (n=130, 38.3%) between February and June 2024. The program combined medication, app-based behavioral support, coaching from registered dietitians and nutritionists, and clinical oversight. It featured 5 phases with evidence-based behavior change techniques, monthly monitoring, and safety protocols. Primary outcomes were mean weight change and proportions achieving ≥10% and ≥15% weight loss. Secondary outcomes included behavior changes, side effects, acceptability, feasibility, and estimated cost-effectiveness compared to National Health Service care. RESULTS: Mean weight change at 12 months was -22.9 kg (-22.1% of baseline weight, SD 8%; P<.001) in the tirzepatide cohort and -18.1 kg (-17.1% of baseline weight, SD 8.1%; P<.001) in the semaglutide cohort. Achievement of ≥10% weight loss occurred in 95.2% (199/209) of participants using tirzepatide and 83.1% (108/130) of participants using semaglutide, whereas ≥15% weight loss was achieved by 83.7% (175/209) and 56.2% (73/130) of the participants, respectively. The proportion of inactive participants (no weekly exercise) decreased substantially in both cohorts (tirzepatide: 31/209, 14.8% to 14/209, 6.7%; semaglutide: 29/130, 22.3% to 7/130, 5.4%; P<.001). Side effects decreased significantly over the 12-month period, with participants who reported no side effects increasing from 41.6% (87/209) to 60.3% (126/209; P<.001) in the tirzepatide cohort and from 53.8% (70/130) to 67.7% (88/130) in the semaglutide cohort (P=.02), whereas common initial side effects, including constipation, nausea, and fatigue, showed significant reductions (P<.001). Economic modeling suggested a 60% to 70% cost saving compared to specialist weight management services and a 10% to 60% cost saving compared to primary care in the National Health Service. CONCLUSIONS: This real-world evaluation demonstrates that remotely delivered, GLP-1RA-supported weight management programs can achieve weight loss outcomes that align closely with clinical trial results while potentially reducing health care costs by 10% to 70% compared to traditional UK services. Both the tirzepatide and semaglutide cohorts exceeded clinically significant weight loss thresholds with acceptable safety profiles and positive behavior changes. These findings support the feasibility and effectiveness of digital delivery models for expanding access to specialist obesity treatment within resource-constrained health care systems, with outcomes that compare favorably to pharmacological intervention alone.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».