Evidence map›Paper›PMID 30260862›Full record

ArticleClinical orthopaedics and related research2018

Statistical Methods Dictate the Estimated Impact of Body Mass Index on Major and Minor Complications After Total Joint Arthroplasty.

Mary J Kwasny, Adam I Edelstein, David W Manning

Abstract readEvaluation Study
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Article in Clinical orthopaedics and related research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mary J KwasnyM. J. Kwasny, Department of Preventive Medicine, Division of Biostatistics, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA A. I. Edelstein, Department of Orthopaedic Surgery, Medical College of Wisconsin, Milwaukee, WI, USA D. W. Manning, Department of Orthopaedic Surgery, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA.
Adam I Edelstein
David W Manning

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElevated body mass index (BMI) is considered a risk factor for complications after THA and TKA. Stakeholders have proposed BMI cutoffs for those seeking arthroplasty. The research that might substantiate BMI cutoffs is sensitive to the statistical methods used, but the impact of the statistical methods used to model BMI has not been defined. QUESTIONS/PURPOSES: (1) How does the estimated postarthroplasty risk of minor and major complications vary as a function of the statistical method used to model BMI? (2) What is the prognostic value of BMI for predicting complications with each statistical method?

methodsUsing the American College of Surgeons National Surgical Quality Improvement Program from 2005 to 2012, we investigated the impact of BMI on major and minor complication risk for THA and TKA. Analyses were weighted with covariate-balancing propensity scores to account for the differential rate of comorbidities across the range of BMI. We specified BMI in two ways: (1) categorically by World Health Organization (WHO) BMI classes; and (2) as a smooth, continuous variable using splines. Models of risk for major complications (deep surgical site infection [SSI], pulmonary embolism, stroke, cardiac arrest, myocardial infarction, wound disruption, implant failure, unplanned intubation, > 48 hours on a ventilator, acute renal insufficiency, coma, sepsis, reoperation, or mortality) and minor complications (superficial SSI, pneumonia, urinary tract infection, deep vein thrombosis, or peripheral nerve injury) were constructed and were adjusted for confounding variables known to correlate with complications (eg, American Society of Anesthesiologists classification). Results were compared for different specifications of BMI. Receiver operating characteristic (ROC) curves were compared to determine the additive prognostic value of BMI.

resultsThe type of BMI parameterization leads to different assessments of risk of postarthroplasty complications for BMIs > 30 kg/m and < 20 kg/m with the spline specification showing better fit in all adjusted models (Akaike Information Criteria favors spline). Modeling BMI categorically using WHO classes indicates that BMI cut points of 40 kg/m for TKA or 35 kg/m for THA are associated with higher risks of major complications. Modeling BMI continuously as a spline suggests that risk of major complications is elevated at a cut point of 44 kg/m for TKA and 35 kg/m for THA. Additionally, in these models, risk does not uniformly increase with increasing BMI. Regardless of the method of modeling, BMI is a poor prognosticator for complications with area under the ROC curves between 0.51 and 0.56, false-positive rates of 96% to 97%, and false-negative rates of 2% to 3%.

conclusionsThe statistical assumptions made when modeling the effect of BMI on postarthroplasty complications dictate the results. Simple categorical handling of BMI creates arbitrary cutoff points that should not be used to inform larger policy decisions. Spline modeling of BMI avoids arbitrary cut points and provides a better model fit at extremes of BMI. Regardless of statistical management, BMI is an inadequate independent prognosticator of risk for individual patients considering total joint arthroplasty. Stakeholders should instead perform comprehensive risk assessment and avoid use of BMI as an isolated indicator of risk. LEVEL OF EVIDENCE: Level III, diagnostic study.

Indexed as

Body Mass IndexModels, StatisticalAgedArthroplasty, ReplacementArthroplasty, Replacement, HipArthroplasty, Replacement, KneeDatabases, FactualFemaleHumansMaleMiddle AgedPatient SelectionPostoperative ComplicationsPredictive Value of TestsQuality ImprovementReference Standards

Identifiers

PMID30260862
PMCPMC6259884

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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.