Evidence map›Paper›PMID 36639115›Full record

ReviewThe Journal of arthroplasty2023

Propensity Scores: Confounder Adjustment When Comparing Nonrandomized Groups in Orthopaedic Surgery.

Dirk R Larson, Isabella Zaniletti, David G Lewallen, Daniel J Berry, Hilal Maradit Kremers

Open access · greenAbstract readReview
In one paragraph

Review in The Journal of arthroplasty, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
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.

Dirk R LarsonDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota.
Isabella ZanilettiDepartment of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona.
David G LewallenDepartment of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
Daniel J BerryDepartment of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
Hilal Maradit KremersDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota; Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
Mayo Clinic · USMayo Clinic in Arizona · USMayo Clinic in Florida · US

Funding

Resource CoreP30AR076312 · NIAMS · MAYO CLINIC ROCHESTER · PI Daniel Berry · 2019 to 2026
$5.5M
NIAMS NIH HHS P30 AR076312
6 · The paper itself

Abstract

Many studies in arthroplasty research are based on nonrandomized, retrospective, registry-based cohorts. In these types of studies, patients belonging to different treatment or exposure groups often differ with respect to patient characteristics, medical histories, surgical indications, or other factors. Consequently, comparisons of nonrandomized groups are often subject to treatment selection bias and confounding. Propensity scores can be used to balance cohort characteristics, thus helping to minimize potential bias and confounding. This article explains how propensity scores are created and describes multiple ways in which they can be applied in the analysis of nonrandomized studies. Please visit the following (https://www.youtube.com/watch?v=sqgxl_nZWS4&t=3s) for a video that explains the highlights of the paper in practical terms.

Indexed as

Orthopedic ProceduresBiasHumansPropensity ScoreRetrospective Studiesbiasconfoundinginverse probability of treatmentpropensity scorestatisticstotal joint arthroplasty

Identifiers

PMID36639115
PMCPMC10023476
OpenAlexW4315434914

What OpenQuestion holds

Textmetadata
LicenceTDM
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.