1
|
Atlantis E, Kormas N, Piya M, Sahebol-Amri M, Williams K, Huang HCC, Bishay R, Chikani V, Girolamo T, Prodan A, Fahey P. Developing a Decision Aid for Clinical Obesity Services in the Real World: the DACOS Nationwide Pilot Study. Obes Surg 2024; 34:2073-2083. [PMID: 38467898 PMCID: PMC11127827 DOI: 10.1007/s11695-024-07123-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 03/13/2024]
Abstract
PURPOSE 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. MATERIALS AND METHODS 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). RESULTS 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%. CONCLUSION Clinicians may use DACOS to discuss potential weight loss predictors with patients after surgery or non-surgical care.
Collapse
Affiliation(s)
- Evan Atlantis
- School of Health Sciences, Western Sydney University, Campbelltown Campus, Locked Bag 1797, Penrith, NSW, Australia.
| | - Nic Kormas
- Department of Endocrinology, Concord Hospital, Concord, New South Wales, Australia
- South Western Sydney Metabolic Rehabilitation and Bariatric Program, Camden and Campbelltown Hospitals, Campbelltown, New South Wales, Australia
| | - Milan Piya
- South Western Sydney Metabolic Rehabilitation and Bariatric Program, Camden and Campbelltown Hospitals, Campbelltown, New South Wales, Australia
- School of Medicine, Western Sydney University, Campbelltown, New South Wales, Australia
| | - Mehdi Sahebol-Amri
- Ryde Hospital, Northern Sydney Local Health District, Ryde, New South Wales, Australia
| | - Kathryn Williams
- Department of Endocrinology, Nepean Hospital, Nepean Blue Mountains Local Health District, Kingswood, New South Wales, Australia
- Charles Perkins Centre-Nepean, The University of Sydney, Kingswood, New South Wales, Australia
| | - Hsin-Chia Carol Huang
- Respiratory & Sleep Medicine, Canberra Hospital, Garran, Canberra, Australian Capital Territory, Australia
- Canberra Obesity Management Service, Canberra Health Services, Belconnen, Canberra, Australian Capital Territory, Australia
- College of Health and Medicine, Australian National University, Acton, Australian Capital Territory, Australia
| | - Ramy Bishay
- School of Medicine, Western Sydney University, Campbelltown, New South Wales, Australia
- Metabolic & Weight Loss Clinic, University Clinics, Western Sydney University, Blacktown Hospital, Blacktown, New South Wales, Australia
| | - Viral Chikani
- Department of Diabetes and Endocrinology, Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Teresa Girolamo
- Re:You Health, Adelaide Weight Management and Wellness, Adelaide, South Australia, Australia
| | - Ante Prodan
- School of Computer, Data and Mathematical Sciences, Western Sydney University, Sydney, Australia
| | - Paul Fahey
- School of Health Sciences, Western Sydney University, Campbelltown Campus, Locked Bag 1797, Penrith, NSW, Australia
| |
Collapse
|
2
|
Termaat J, Piya MK, McBride KA. Community-based care needs for adults with class III obesity before and after tertiary weight management: An exploratory study. Obes Sci Pract 2024; 10:e732. [PMID: 38213316 PMCID: PMC10782639 DOI: 10.1002/osp4.732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 11/27/2023] [Accepted: 12/04/2023] [Indexed: 01/13/2024] Open
Abstract
Objective Class 3 obesity (severe obesity) is defined by a body mass index ≥40 kg/m2. Tertiary weight-management programs (WMPs) are hospital-based multidisciplinary services that aim to support individuals with severe obesity. Severe shortage of WMPs has led to waitlists and pressure on clinicians to discharge patients. Community obesity management often fails to support patients in maintaining weight loss/health gains. This study aimed to explore the needs of patients for community-based obesity care. Methods A qualitative study was undertaken via a tertiary WMP in Sydney, Australia. Semi-structured interviews/focus groups explored perceptions of purposively sampled patients and their clinicians on the community-based support needs of people with severe obesity. Data were audio-recorded, transcribed verbatim, and then thematically analyzed. Results Eleven patients and seven clinicians were interviewed. Four themes were identified: the importance of accountability and motivation to maintain weight-loss/health gains; limitations within community-based obesity management for those with severe obesity; perspectives on structured community programs for patients transitioning into/out of tertiary WMPs; and impact of mental health, stigma, and social isolation on engagement with community-based services. Conclusions Community-based programs are needed to support those awaiting access to tertiary WMPs and to help maintain health gains once discharged. Such programs should address issues of social isolation and integrate with current models of tertiary metabolic and primary health care.
Collapse
Affiliation(s)
- Jillian Termaat
- School of MedicineWestern Sydney UniversityPenrithNew South WalesAustralia
| | - Milan K. Piya
- School of MedicineWestern Sydney UniversityPenrithNew South WalesAustralia
- South Western Sydney (SWS) Metabolic Rehabilitation and Bariatric ProgramCamden and Campbelltown HospitalsCamdenNew South WalesAustralia
- Translational Health Research InstituteWestern Sydney UniversityPenrithNew South WalesAustralia
| | - Kate A. McBride
- School of MedicineWestern Sydney UniversityPenrithNew South WalesAustralia
- Translational Health Research InstituteWestern Sydney UniversityPenrithNew South WalesAustralia
| |
Collapse
|