Evidence map›Paper›PMID 30113939›Full record

ArticleClinical orthopaedics and related research2018

American Joint Replacement Registry Risk Calculator Does Not Predict 90-day Mortality in Veterans Undergoing Total Joint Replacement.

Alex H S Harris, Alfred C Kuo, Kevin J Bozic, Edmund Lau, Thomas Bowe, Shalini Gupta, Nicholas J Giori

Abstract read
In one paragraph

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 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 10% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 3 countries.

Alex H S HarrisA H. S. Harris, S. Gupta, T. Bowe, N. J. Giori, Center for Innovation to Implementation, VA Palo Alto Healthcare System, Menlo Park, CA, USA A. C. Kuo, San Francisco Veterans Affairs Medical Center, University of California, San Francisco, CA, USA K. J. Bozic, Dell Medical School at The University of Texas at Austin, Austin, TX, USA E. Lau, Exponent Inc, Menlo Park, CA, USA A. H. S. Harris, N. J. Giori, Department of Orthopaedic Surgery, Stanford University School of Medicine, Stanford, CA, USA A. H. S. Harris, Stanford-Surgical Policy Improvement Research and Education Center, Stanford, CA, USA.
Alfred C Kuo
Kevin J Bozic
Edmund Lau
Thomas Bowe
Shalini Gupta
Nicholas J Giori
Herat University · AFVA Palo Alto Health Care System · US

Funding

Development and Validation of a Risk Calculator for Total Joint ReplacementI01HX001260 · VA · VETERANS ADMIN PALO ALTO HEALTH CARE SYS · PI KUO, ALFRED C · 2016 to 2025
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HSRD VA I01 HX001260HSRD VA IK6 HX002840HSRD VA RCS 14-232
6 · The paper itself

Abstract

backgroundThe American Joint Replacement Registry (AJRR) Total Joint Risk Calculator uses demographic and clinical parameters to provide risk estimates for 90-day mortality and 2-year periprosthetic joint infection (PJI). The tool is intended to help surgeons counsel their Medicare-eligible patients about their risk of death and PJI after total joint arthroplasty (TJA). However, for a predictive risk model to be useful, it must be accurate when applied to new patients; this has yet to be established for this calculator. QUESTIONS/PURPOSES: To produce accuracy metrics (ie, discrimination, calibration) for the AJRR mortality calculator using data from Medicare-eligible patients undergoing TJA in the Veterans Health Administration (VHA), the largest integrated healthcare system in the United States, where more than 10,000 TJAs are performed annually.

methodsWe used the AJRR calculator to predict risk of death within 90 days of surgery among 31,214 VHA patients older than 64 years of age who underwent primary TJA; data was drawn from the Veterans Affairs Surgical Quality Improvement Project (VASQIP) and VA Corporate Data Warehouse (CDW). We then used VHA mortality data to evaluate the extent to which the AJRR calculator estimates distinguished individuals who died compared with those who did not (C-statistic), and graphically depicted the relationship between estimated risk and observed mortality (calibration). As a secondary evaluation of the calculator, a sample of 39,300 patients younger than 65 years old was assigned to the youngest age group available to the user (65-69 years) as might be done in real-world practice.

resultsC-statistics for 90-day mortality for the older samples were 0.62 (95% CI, 0.60-0.64) and for the younger samples they were 0.46 (95% CI, 0.43-0.49), suggesting poor discrimination. Calibration analysis revealed poor correspondence between deciles of predicted risk and observed mortality rates. Poor discrimination and calibration mean that patients who died will frequently have a lower estimated risk of death than surviving patients.

conclusionsFor Medicare-eligible patients receiving TJA in the VA, the AJRR risk calculator had a poor performance in the prediction of 90-day mortality. There are several possible reasons for the model's poor performance. Veterans Health Administration patients, 97% of whom were men, represent only a subset of the broader Medicare population. However, applying the calculator to a subset of the target population should not affect its accuracy. Other reasons for poor performance include a lack of an underlying statistical model in the calculator's implementation and simply the challenge of predicting rare events. External validation in a more representative sample of Medicare patients should be conducted to before assuming this tool is accurate for its intended use. LEVEL OF EVIDENCE: Level I, diagnostic study.

Indexed as

Decision Support TechniquesVeterans HealthAgedArthroplasty, ReplacementFemaleHumansMaleMedicarePredictive Value of TestsReproducibility of ResultsRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeUnited States

Identifiers

PMID30113939
PMCPMC6259803
OpenAlexW2885165793

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.