Assessing service provision and outcomes at the Canberra Obesity Management Service: A retrospective chart review

Burns, Ryan; Firman, Elise; Hsu, Chia‐Chi

doi:10.1002/oby.23575

Cited by 2 publications

(2 citation statements)

References 40 publications

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“…There is no gold-standard screening tool for OSA in pregnant populations, but some studies have attempted to develop pregnancyspecific tools, to improve the sensitivity and specificity of OSA screening. Facco and colleagues 13 In further exploration of this argument, data from the current study was compared to unpublished data from the Canberra Obesity Management Service (COMS), 19 where patients are systematically screened for OSA and referred to sleep clinic as appropriate. During (Standard Deviation 9.7) and all were screened for OSA.…”

Section: Results For Individuals Who Completed Polysomnography (Psg)mentioning

confidence: 99%

“…In further exploration of this argument, data from the current study was compared to unpublished data from the Canberra Obesity Management Service (COMS), 19 where patients are systematically screened for OSA and referred to sleep clinic as appropriate. During a 12‐month period (July 2018‐June 2019), 82 non‐pregnant women were seen in the COMS aged 17–45, with mean BMI of 51.1 kg/m 2 .…”

Section: Discussionmentioning

confidence: 99%

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Referral practices and treatment of obstructive sleep apnea in pregnancies with obesity

Warhurst,

Georgousopoulou,

Sethna

et al. 2024

Obesity Science & Practice

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ObjectiveObstructive sleep apnea (OSA) affects maternal and neonatal health during pregnancy. This study aimed to identify characteristics and comorbidities associated with sleep clinic referral in high‐risk pregnancies with Body Mass Index (BMI) ≥35 kg/m2.MethodRetrospective cohort study for individuals in a high‐risk pregnancy clinic at a tertiary Australian hospital from 1 January to 31 December 2020 with BMI≥35 kg/m2. The primary outcome measure was sleep clinic referral. Exposure data included multiple comorbidities and formal tools (Epworth Sleepiness Scale and STOP‐BANG). Multivariable analysis was used to identify factors associated with referral. Descriptive data on barriers to diagnosis and treatment were collected.ResultsOf 161 pregnant individuals, 38.5% were screened using formal tools and 13.7% were referred to sleep clinic. Having STOP‐BANG performed was associated with sleep clinic referral (Odds Ratio: 18.04, 95% Confidence Interval:4.5–71.7, p < 0.001). No clinical characteristics were associated with the likelihood of performing STOP‐BANG. The COVID‐19 pandemic was a treatment barrier for three individuals.ConclusionsCurrent screening practices identify pregnant individuals with the highest pre‐test probability of having OSA. Future research should evaluate real‐world strategies to improve identification and management in this high‐risk population.

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Section: Results For Individuals Who Completed Polysomnography (Psg)mentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Referral practices and treatment of obstructive sleep apnea in pregnancies with obesity

Warhurst,

Georgousopoulou,

Sethna

et al. 2024

Obesity Science & Practice

View full text Add to dashboard Cite

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Predictors of ongoing attendance at an Australian publicly funded specialist obesity service

Brightman,

Huang,

Georgousopoulou

2024

Obesity Science & Practice

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IntroductionThere is a demand for publicly funded specialist obesity services in Australia. A range of factors can impact on patient attendance which can result in poorer health outcomes.ObjectiveTo identify patient factors that predict ongoing in‐person attendance following initial medical assessment at the Canberra Obesity Management Service.MethodsData were collated from two retrospective reviews (July 2016–June 2017 and July 2018–June 2019). Predictive modeling was used to determine the likelihood of ongoing attendance.ResultsA total of 396 patients were identified. Mean age was 45.4 years (SD 13.1), mean weight was 139.5 kg (SD 27.8) and mean Body Mass Index was 49.87 kg/m2 (SD 8.7). Demographics and anthropometrics were not predictive of ongoing attendance. Patients with a higher comorbidity burden were more likely to continue attending (p < 0.001). Patients with obstructive sleep apnea (OSA) were 4.9 times more likely to continue attending (p < 0.001). Hypertension was more common among patients who continued attending (p = 0.005); however, this relationship was no longer significant when using a multi‐adjusted model. Comorbid depression and/or anxiety diagnoses were not predictive of ongoing attendance although the p‐value for anxiety severity classification approached significance.ConclusionsFindings are consistent with existing evidence linking OSA and attendance at specialist obesity services. Hypertension was predictive of ongoing attendance and warrants further research. Determining if anxiety is a true barrier to attendance at specialist obesity services may have implications in terms of optimizing diagnosis and treatment prior to referral or in the early stages of obesity management.

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Assessing service provision and outcomes at the Canberra Obesity Management Service: A retrospective chart review

Cited by 2 publications

References 40 publications

Referral practices and treatment of obstructive sleep apnea in pregnancies with obesity

Referral practices and treatment of obstructive sleep apnea in pregnancies with obesity

Predictors of ongoing attendance at an Australian publicly funded specialist obesity service

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