Developing a Decision Aid for Clinical Obesity Services in the Real World: the DACOS Nationwide Pilot Study.
Decision support model
Management
Obesity
Weight loss
Journal
Obesity surgery
ISSN: 1708-0428
Titre abrégé: Obes Surg
Pays: United States
ID NLM: 9106714
Informations de publication
Date de publication:
11 Mar 2024
11 Mar 2024
Historique:
received:
05
10
2023
accepted:
22
02
2024
revised:
20
02
2024
medline:
12
3
2024
pubmed:
12
3
2024
entrez:
12
3
2024
Statut:
aheadofprint
Résumé
The purpose of this study is to develop a decision aid tool using "real-world" data within the Australian health system to predict weight loss after bariatric surgery and non-surgical care. We analyzed patient record data (aged 16+years) from initial review between 2015 and 2020 with 6-month (n=219) and 9-/12-month (n=153) follow-ups at eight clinical obesity services. Primary outcome was percentage total weight loss (%TWL) at 6 months and 9/12 months. Predictors were selected by statistical evidence (p<0.20), effect size (±2%), and clinical judgment. Multiple linear regression and bariatric surgery were used to create simple predictive models. Accuracy was measured using percentage of predictions within 5% of the observed value, and sensitivity and specificity for predicting target weight loss of 5% (non-surgical care) and 15% (bariatric surgery). Observed %TWL with bariatric surgery vs. non-surgical care was 19% vs. 5% at 6 months and 22% vs. 5% at 9/12 months. Predictors at 6 months with intercept (non-surgical care) of 6% include bariatric surgery (+11%), BMI>60 (-3%), depression (-2%), anxiety (-2%), and eating disorder (-2%). Accuracy, sensitivity, and specificity were 58%, 69%, and 56%. Predictors at 9/12 months with intercept of 5% include bariatric surgery (+15%), type 2 diabetes (+5%), eating disorder (+4%), fatty liver (+2%), atrial fibrillation (-4%), osteoarthritis (-3%), sleep/mental disorders (-2-3%), and ≥10 alcohol drinks/week (-2%). Accuracy, sensitivity, and specificity were 55%, 86%, and 53%. Clinicians may use DACOS to discuss potential weight loss predictors with patients after surgery or non-surgical care.
Identifiants
pubmed: 38467898
doi: 10.1007/s11695-024-07123-6
pii: 10.1007/s11695-024-07123-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s).
Références
World Health Organization. Obesity and overweight. 2021 14 October 2021]; Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight .
Wolfenden L et al. The challenge for global health systems in preventing and managing obesity. Obes Rev. 2019;20(Suppl 2):185–93.
doi: 10.1111/obr.12872
pubmed: 31317659
Atlantis E et al. Usefulness of the Edmonton Obesity Staging System for stratifying the presence and severity of weight-related health problems in clinical and community settings: a rapid review of observational studies. Obes Rev. 2020;21(11):e13120.
doi: 10.1111/obr.13120
pubmed: 32812345
Atlantis E et al. Comparing the predictive ability of the Edmonton Obesity Staging System with the body mass index for use of health services and pharmacotherapies in Australian adults: a nationally representative cross-sectional study. Clin Obes. 2020;10(4):e12368.
doi: 10.1111/cob.12368
pubmed: 32419298
Semlitsch T et al. Management of overweight and obesity in primary care-a systematic overview of international evidence-based guidelines. Obes Rev. 2019;20(9):1218–30.
doi: 10.1111/obr.12889
pubmed: 31286668
pmcid: 6852048
Caterson ID et al. Gaps to bridge: misalignment between perception, reality and actions in obesity. Diabetes, Obes Metab. 2019;21(8):1914–24.
doi: 10.1111/dom.13752
pubmed: 31032548
Nordmo M, Danielsen YS, Nordmo M. The challenge of keeping it off, a descriptive systematic review of high-quality, follow-up studies of obesity treatments. Obes Rev. 2020;21(1):e12949.
doi: 10.1111/obr.12949
pubmed: 31675146
Atlantis E et al. Enablers and barriers to implementing obesity assessments in clinical practice: a rapid mixed-methods systematic review. BMJ Open. 2022;12(11):e063659.
doi: 10.1136/bmjopen-2022-063659
pubmed: 36446466
pmcid: 9710371
Atlantis E et al. Clinical obesity services in public hospitals (COSiPH) in Australia: a position statement based on expert consensus. Obes Rev. 2020;21(11):e13120.
Brightman L, Huang H-CC, Dugdale P. Determining patient attendance, access to interventions and clinical outcomes in a publicly funded obesity programme: results from the Canberra Obesity Management Service. Clin Obes. 2019;9(4):e12325.
doi: 10.1111/cob.12325
pubmed: 31207135
Sumithran P et al. Review of 3-year outcomes of a very-low-energy diet-based outpatient obesity treatment programme. Clin Obes. 2016;6(2):101–7.
doi: 10.1111/cob.12135
pubmed: 26841953
Atlantis E et al. Physical capacity outcomes in patients with severe obesity after 12 months of physician-led multidisciplinary team care: a case series from a public hospital clinical obesity service. Clin Obes. 2019;9(6):e12337.
doi: 10.1111/cob.12337
pubmed: 31475476
Williams K et al. Impact of specialized obesity management services on the reduction in the use of acute hospital services. Clin Obes. 2023;13(5):e12592.
Karpińska IA et al. Is it possible to predict weight loss after bariatric surgery?-External validation of predictive models. Obes Surg. 2021;31(7):2994–3004.
doi: 10.1007/s11695-021-05341-w
pubmed: 33712937
pmcid: 8175311
Nakagawa S, Schielzeth H, O'Hara RB. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol. 2013;4(2):133–42.
doi: 10.1111/j.2041-210x.2012.00261.x
Grieco A et al. Metabolic and bariatric surgery accreditationand quality improvement program: bariatric surgical risk/benefit calculator: 1-year comorbidity remission. Surg Obes Relat Dis. 2023;26:S1550–7289(23)00708-6.
Aceves-Martins M et al. A systematic review of UK-based long-term nonsurgical interventions for people with severe obesity (BMI ≥35 kg m(-2) ). J Hum Nutr Diet. 2020;33(3):351–72.
doi: 10.1111/jhn.12732
pubmed: 32027072
pmcid: 7317792
Backman B, Brown D, Cottrell J, Campbell A, Clancy W, Halim Shah YJ, Chadwick C, Budin A, MacCormick A, Caterson I and Brown W. The bariatric surgery registry annual report, 2020. Monash University, Department of Epidemiology and Preventive Medicine. 2020. p. 8.
Gloy VL et al. Bariatric surgery versus non-surgical treatment for obesity: a systematic review and meta-analysis of randomised controlled trials. BMJ : Br Med J. 2013;347:f5934.
doi: 10.1136/bmj.f5934
Chopra S et al. Predictors of successful weight loss outcomes amongst individuals with obesity undergoing lifestyle interventions: a systematic review. Obes Rev. 2021;22(3):e13148.
doi: 10.1111/obr.13148
pubmed: 33200547
Sharman MJ et al. Review of publicly-funded bariatric surgery policy in Australia-lessons for more comprehensive policy making. Obes Surg. 2016;26(4):817–24.
doi: 10.1007/s11695-015-1806-4
pubmed: 26227395
Doumouras AG et al. A longitudinal analysis of wait times for bariatric surgery in a publicly funded, regionalized bariatric care system. Obes Surg. 2020;30(3):961–8.
doi: 10.1007/s11695-019-04259-8
pubmed: 31705416
Gilis-Januszewska A et al. Determinants of weight outcomes in type 2 diabetes prevention intervention in primary health care setting (the DE-PLAN project). BMC Public Health. 2018;18(1):97.
doi: 10.1186/s12889-017-4977-1
pubmed: 29291708
pmcid: 5749019
Dhurandhar NV et al. Predictors of weight loss outcomes in obesity care: results of the national ACTION study. BMC Public Health. 2019;19(1):1422.
doi: 10.1186/s12889-019-7669-1
pubmed: 31666040
pmcid: 6820914
Kassel LE et al. Insulin dose adjustment following bariatric surgery, a review of available literature. J Diabetes Sci Technol. 2022;16(6):1560–6.
doi: 10.1177/19322968211028886
pubmed: 34210197
Hilbert A et al. Nonnormative eating behaviors and eating disorders and their associations with weight loss and quality of life during 6 years following obesity surgery. JAMA Netw Open. 2022;5(8):e2226244–4.
doi: 10.1001/jamanetworkopen.2022.26244
pubmed: 35951326
pmcid: 9372790
Sherwood NE, Jeffery RW, Wing RR. Binge status as a predictor of weight loss treatment outcome. Int J Obes Relat Metab Disord. 1999;23(5):485–93.
doi: 10.1038/sj.ijo.0800846
pubmed: 10375051
Chao AM et al. Binge eating and weight loss outcomes in individuals with type 2 diabetes: 4-year results from the look AHEAD study. Obesity. 2017;25(11):1830–7.
doi: 10.1002/oby.21975
pubmed: 29086498
Grilo CM et al. Rapid response predicts 12-month post-treatment outcomes in binge-eating disorder: theoretical and clinical implications. Psychol Med. 2012;42(4):807–17.
doi: 10.1017/S0033291711001875
pubmed: 21923964
Wharton S et al. Two-year effect of semaglutide 2.4 mg on control of eating in adults with overweight/obesity: STEP 5. Obesity (Silver Spring). 2023;31(3):703–15.
doi: 10.1002/oby.23673
pubmed: 36655300
Legenbauer T et al. Depression and anxiety: their predictive function for weight loss in obese individuals. Obes Facts. 2009;2(4):227–34.
doi: 10.1159/000226278
pubmed: 20054228
pmcid: 6515937
de Zwaan M et al. Anxiety and depression in bariatric surgery patients: a prospective, follow-up study using structured clinical interviews. J Affect Disord. 2011;133(1):61–8.
doi: 10.1016/j.jad.2011.03.025
pubmed: 21501874
Yarigholi F et al. Predictors of weight regain and insufficient weight loss according to different definitions after sleeve gastrectomy: a retrospective analytical study. Obes Surg. 2022;32(12):4040–6.
doi: 10.1007/s11695-022-06322-3
pubmed: 36260221
Blume CA et al. Development and validation of a predictive model of success in bariatric surgery. Obes Surg. 2021;31(3):1030–7.
doi: 10.1007/s11695-020-05103-0
pubmed: 33190175
Chao AM et al. Alcohol intake and weight loss during intensive lifestyle intervention for adults with overweight or obesity and diabetes. Obesity (Silver Spring). 2019;27(1):30–40.
doi: 10.1002/oby.22316
pubmed: 30421851
Parikh M, Johnson JM, Ballem N. ASMBS position statement on alcohol use before and after bariatric surgery. Surg Obes Relat Dis. 2016;12(2):225–30.
doi: 10.1016/j.soard.2015.10.085
pubmed: 26968500
Huang CW et al. Predicted weight loss result of laparoscopic sleeve gastrectomy: review of the first 82 consecutive patients in an Asian bariatric unit. Asian J Surg. 2019;42(1):373–8.
doi: 10.1016/j.asjsur.2018.06.003
pubmed: 30585171
Kubat E et al. Osteoarthritis in veterans undergoing bariatric surgery is associated with decreased excess weight loss: 5-year outcomes. Surg Obes Relat Dis. 2016;12(7):1426–30.
doi: 10.1016/j.soard.2016.02.012
pubmed: 27260653
Kerver GA et al. Pain is adversely related to weight loss maintenance following bariatric surgery. Surg Obes Relat Dis. 2021;17(12):2026–32.
doi: 10.1016/j.soard.2021.08.025
pubmed: 34600842
pmcid: 8612986
Kalia NK et al. Motivational effects of coronary artery calcium scores on statin adherence and weight loss. Coron Artery Dis. 2015;26(3):225–30.
doi: 10.1097/MCA.0000000000000207
pubmed: 25514570
Pathak RK et al. Long-term effect of goal-directed weight management in an atrial fibrillation cohort: a long-term follow-up study (LEGACY). J Am Coll Cardiol. 2015;65(20):2159–69.
doi: 10.1016/j.jacc.2015.03.002
pubmed: 25792361
Perdomo CM et al. Contemporary medical, device, and surgical therapies for obesity in adults. Lancet. 2023;401(10382):1116–30.
doi: 10.1016/S0140-6736(22)02403-5
pubmed: 36774932