Oral Presentation Australian and New Zealand Obesity Society Annual Scientific Conference 2023

Developing a Decision Aid for Clinical Obesity Services in the real world: the DACOS pilot study (98287)

Evan Atlantis 1 , Nick Kormas 2 3 , Milan Piya 4 5 , Mehdi Sahebol-Amri 6 , Kathryn Williams 7 8 , Hsin-Chia Carol Huang 9 10 11 , Ramy Bishay 12 , Viral Chikani 13 , Teresa Girolamo 14 , Ante Prodan 15 , Paul Fahey 16
  1. School of Health Sciences, Western Sydney University, Campbelltown, NSW, Australia
  2. Endocrinology, Campbelltown and Camden Hospitals, Campbelltown and Camden, NSW
  3. Endocrinology, Concord Hospital, Concord, NSW
  4. South Western Sydney Metabolic Rehabilitation and Bariatric Program, , Camden and Campbelltown Hospitals , Campbelltown, NSW, Australia
  5. School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
  6. Ryde Hospital, Northern Sydney Local Health District, Ryde, NSW, Australia
  7. Dept Endocrinology, Nepean Hospital, Nepean Blue Mountains Local Health District,, Kingswood, NSW , Australia
  8. Charles Perkins Centre-Nepean, The University of Sydney, Sydney, NSW , Australia
  9. Respiratory & Sleep Medicine, Canberra Hospital, Garran , ACT , Australia
  10. Canberra Obesity Management Service, Canberra Health Services, Belconnen , ACT , Australia
  11. College of Health and Medicine, Australian National University, Acton , ACT , Australia
  12. Metabolic & Weight Loss Clinic, University Clinics, Western Sydney University, Blacktown Hospital, Blacktown, New South Wales, Australia
  13. Dept of Diabetes and Endocrinology , Princess Alexandra Hospital, Brisbane, QLD, Australia
  14. Re:You | Adelaide weight management and wellness, Adelaide, SA, Australia
  15. Western Sydney University, Penrith, NSW, Australia
  16. School of Health Sciences, Western Sydney University, Campbelltown campus, NSW, Australia

Aims: Clinical obesity services in public hospitals and private clinics offer more intensive treatments and care for obesity, with varying success. We aimed 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.

Materials and methods: We analysed de-identified patient record data (aged 16+years) of initial review between 2015 and 2020 with 6-months (n=219) and 9 or 12-months (n=153) follow-ups at eight clinical obesity services nationwide. The primary outcome was percentage weight loss in the first 6-months and 9 or 12-months after initial review. 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. The accuracy of predictions was measured using percentage of predictions ±5% of the observed value, and sensitivity and specificity for predicting target weight loss of 5% for non-surgical care and 15% for bariatric surgery.

Results: Bariatric surgery resulted in greater observed weight loss than non-surgical care at 6-months (19% vs. 5%) and 9 or 12-months (22% vs. 5%). The predicted weight loss at 6-months was: 6%,+15% if bariatric surgery,+2% if T2D, –3% if ≥10 alcohol drinks/week, –2% if current smoker,–2% if depression history,–2% if eating disorder history, and–1% if anxiety history. Accuracy was 55% (120/219), sensitivity was 53%, and specificity was 78%. The predicted weight loss at 9-12-months was: 5%,+16% if bariatric surgery,+6% if eating disorder history,+5% if T2D,–3% if osteoarthritis,–3% if sleep disorder, and–2% if depression history. Accuracy was 50% (77/153), sensitivity was 85%, and specificity was 51%.

Conclusions: The DACOS scoring system can help clinicians set realistic goals for obesity management by considering several predictors of weight loss. Further research is needed to improve the predictive power of the scoring tool.