Evidence map›Paper›PMID 30039237›Full record

ArticleObesity surgery2018

The Use of Predictive Markers for the Development of a Model to Predict Weight Loss Following Vertical Sleeve Gastrectomy.

Samuel Cottam, Daniel Cottam, Austin Cottam, Hinali Zaveri, Amit Surve, Christina Richards

Abstract read
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In one paragraph

Article in Obesity surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 11% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
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  9. Weight Loss Prediction after Metabolic and Bariatric Surgery.Journal of obesity & metabolic syndrome · 2023
    Review
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  11. Observational
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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

6 authors at 2 institutions in 2 countries.

Samuel CottamBariatric Medicine Institute, 1046 East 100 South, Salt Lake City, UT, 84102, USA.
Daniel CottamBariatric Medicine Institute, 1046 East 100 South, Salt Lake City, UT, 84102, USA. drdanielcottam@yahoo.com.ORCID http://orcid.org/0000-0001-8830-0291
Austin CottamBariatric Medicine Institute, 1046 East 100 South, Salt Lake City, UT, 84102, USA.
Hinali ZaveriBariatric Medicine Institute, 1046 East 100 South, Salt Lake City, UT, 84102, USA.
Amit SurveBariatric Medicine Institute, 1046 East 100 South, Salt Lake City, UT, 84102, USA.
Christina RichardsBariatric Medicine Institute, 1046 East 100 South, Salt Lake City, UT, 84102, USA.
Reproductive Medicine Institute · USYahoo (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAverage percent excess weight loss data is commonly discussed preoperatively to guide patient expectations following surgery. However, there is a wide range and variation in weight loss following vertical sleeve gastrectomy (SG). Unfortunately, most surgeons and even fewer patients have heard of using predictive models to help guide their decisions on procedure choice. We have developed a predictive model for SG to help patient choice prior to this major life-changing decision.

objectivePredict weight loss results for SG patients at 1 year using preoperative data.

settingPrivate practice.

methodsThree hundred and seventy-one SG patients met the criteria for our study. These patients underwent surgery between October 2008 and June 2016. Non-linear regressions were performed to interpolate individual patient weights at 1 year. Multivariate analysis was used to find factors that affected weight loss. A model was constructed to predict weight loss performance.

resultsVariables that affect weight loss were found to be preoperative body mass index (BMI), age, hypertension, and diabetes. Diabetes and hypertension together were found to significantly affect weight loss.

conclusionPatient weight loss can be accurately predicted by simple preoperative factors. These findings should be used to help patients and surgeons decide if the SG is an appropriate surgery for each patient. Using this model, most patients can avoid failure by choosing an appropriate surgical approach for their personal circumstances.

Indexed as

Obesity, MorbidBariatric SurgeryBiomarkersBody Mass IndexGastrectomyHumansHypertensionWeight LossBiomarkersAgeBMIDiabetesHypertensionPredictive modelingSleeve gastrectomy

Identifiers

PMID30039237
OpenAlexW2883977907

What OpenQuestion holds

Textmetadata
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.