Evidence map›Paper›PMID 31651309›Full record

Observational studyBMC health services research2019

A predictive model for non-completion of an intensive specialist obesity service in a public hospital: a case-control study.

Evan Atlantis, Fang Lin, Sulak Anandabaskaran, Paul Fahey, Nic Kormas

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 21 citations in OpenAlex.

  1. Review
  2. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Evan AtlantisSchool of Nursing and Midwifery, Western Sydney University, Penrith, New South Wales, Australia. E.Atlantis@westernsydney.edu.au.ORCID http://orcid.org/0000-0001-5877-6141
Fang LinCampbelltown and Camden Hospitals, Campbelltown, New South Wales, Australia.
Sulak AnandabaskaranCampbelltown and Camden Hospitals, Campbelltown, New South Wales, Australia.
Paul FaheySchool of Science and Health, Western Sydney University, Penrith, New South Wales, Australia.
Nic KormasCampbelltown and Camden Hospitals, Campbelltown, New South Wales, Australia.
Camden and Campbelltown Hospitals · AUThe University of Adelaide · AUWestern Sydney University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the growing evidence base supporting intensive lifestyle and medical treatments for severe obesity, patient engagement in specialist obesity services is difficult to achieve and poorly understood. To address this knowledge gap, we aimed to develop a model for predicting non-completion of a specialist multidisciplinary service for clinically severe obesity, termed the Metabolic Rehabilitation Programme (MRP).

methodUsing a case-control study design in a public hospital setting, we extracted data from medical records for all eligible patients with a body mass index (BMI) of ≥35 kg/m

resultsOut of the 219 eligible patient records, 78 (35.6%) non-completion cases were identified. Significant differences between non-completers versus completers were: age (47.1 versus 54.5 years, p < 0.001); residential distance from the clinic (21.8 versus 17.1 km, p = 0.018); obstructive sleep apnoea (OSA) (42.9% versus 56.7%, p = 0.050) and CPAP therapy (11.7% versus 28.4%, p = 0.005). The probability of non-completion could be independently associated with age, residential distance, and either OSA or CPAP. There was no statistically significant difference in performance between the alternate models (69.5% versus 66.4%, p = 0.57).

conclusionsNon-completion of intensive specialist obesity management services is most common among younger patients, with fewer complex care needs, and those living further away from the clinic. Clinicians should be aware of these potential risk factors for dropping out early when managing outpatients with severe obesity, whereas policy makers might consider strategies for increasing access to specialist obesity management services.

Indexed as

AnxietyBlood PressureBody Mass IndexCase-Control StudiesContinuous Positive Airway PressureDepressionDiabetes Mellitus, Type 2FemaleHospitalizationHospitals, PublicHumansLife StyleMaleMiddle AgedObesity ManagementObesity, MorbidAttritionDropoutMultidisciplinarySevere obesityWeight-lossWeight management

Identifiers

PMID31651309
PMCPMC6814104
OpenAlexW2981415504

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.