Evidence map›Paper›PMID 42761404›Full record

ArticleObesity science & practice2026

Real-World Outcomes of Telemedicine Shared Medical Appointments in Obesity Management.

Keerthana Haridas, Jeffrey Wei, Lei Lei, Derek Pham, Nicholas Jackson, Na Shen

Abstract read
In one paragraph

Article in Obesity science & practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Keerthana HaridasDivision of Endocrinology, Diabetes and Metabolism David Geffen School of Medicine UCLA Los Angeles California USA.ORCID https://orcid.org/0000-0003-0305-8585
Jeffrey WeiDivision of Endocrinology, Diabetes and Metabolism David Geffen School of Medicine UCLA Los Angeles California USA.
Lei LeiDivision of Endocrinology, Diabetes and Metabolism David Geffen School of Medicine UCLA Los Angeles California USA.
Derek PhamDivision of General Internal Medicine and Health Services Research UCLA Los Angeles California USA.ORCID https://orcid.org/0000-0001-5786-6911
Nicholas JacksonDivision of General Internal Medicine and Health Services Research UCLA Los Angeles California USA.ORCID https://orcid.org/0000-0002-9515-5050
Na ShenDivision of Endocrinology, Diabetes and Metabolism David Geffen School of Medicine UCLA Los Angeles California USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Shared Medical Appointments (SMAs) have recently emerged as a novel tool in weight management as they are efficient, bypass logistic barriers to physical attendance, decrease attrition, and are cost-effective. This study aimed to observe outcomes among patients enrolled in an insurance-based weight loss program, called Program for Reducing Obesity (PRO), utilizing telemedicine SMAs during a 12 month period of chronic weight management. Methods: Patients of age ≥ 18 years with BMI ≥ 30 kg/m Results: One hundred and nine patients, who had been enrolled in the program for about 18 months, were included in the study. The mean age was 62.40 ± 12.5 years. 73% were treated with obesity management medications. Patients attended an average of 10 classes through SMAs. 51% of patients had prediabetes, and 25% had Type 2 Diabetes Mellitus (DM). The mean weight of patients at baseline was 97.54 ± 19 kg, with an average weight loss of 2.38 ± 4.78 kg (2.43%) and 4.47 ± 7.77 kg (4.55%) at 6 and 12 months ( Conclusion: This study showed that telemedicine SMAs are an effective and efficient method for promoting weight loss, even in the ongoing maintenance phase.

Identifiers

PMID42761404
PMCPMC13586656

What OpenQuestion holds

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Registered trials

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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.