Evidence map›Paper›PMID 42416047›Full record

ReviewOrthopaedic journal of sports medicine2026

How Are We Matching in ACL Reconstruction Research? A Systematic Review of Methods, Reporting, and Covariate Selection.

Jay R Patel, Alejandro M Holle, Brooke S Halpin, Sailesh V Tummala, Karan A Patel, Anikar Chhabra

Abstract readReview
In one paragraph

Review in Orthopaedic journal of sports medicine, 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.

Jay R PatelMayo Clinic Alix School of Medicine, Phoenix, Arizona, USA.ORCID https://orcid.org/0009-0006-7029-320X
Alejandro M HolleMayo Clinic Alix School of Medicine, Phoenix, Arizona, USA.ORCID https://orcid.org/0009-0004-1936-9155
Brooke S HalpinMayo Clinic Alix School of Medicine, Phoenix, Arizona, USA.
Sailesh V TummalaDepartment of Orthopaedic Surgery, Mayo Clinic, Phoenix, Arizona, USA.ORCID https://orcid.org/0000-0002-8907-3542
Karan A PatelDepartment of Orthopaedic Surgery, Mayo Clinic, Phoenix, Arizona, USA.
Anikar ChhabraDepartment of Orthopaedic Surgery, Mayo Clinic, Phoenix, Arizona, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Matching techniques such as direct covariate matching and propensity score matching (PSM) are increasingly used in anterior cruciate ligament reconstruction (ACLR) research to reduce bias in observational study designs. However, the rationale for covariate selection, consistency in methodological reporting, and patterns of matching practices remain unclear. Purpose: To systematically evaluate covariate matching practices in ACLR literature, including the types and number of covariates used, methodological transparency, and trends in matching strategies. Study Design: Systematic review. Methods: A systematic literature search of the PubMed, EMBASE, and Cochrane databases was conducted to evaluate covariate matching practices in the ACLR literature. A comprehensive search identified 798 unique studies, of which 97 met eligibility criteria. Data were extracted on study design, matching technique, covariate inclusion, reporting practices, and matching ratios. Descriptive and comparative statistics were used to summarize trends. Results: The 97 included studies encompassed 91,165 ACLRs. Most studies were retrospective (90.7%) and cohort in design (92.8%). PSM was used in 41 studies (42.3%), while 56 (57.7%) used direct matching. A total of 60 unique covariates were used across 76 different combinations. PSM studies used significantly more covariates than direct matching studies (6.17 ± 2.79 vs 3.75 ± 1.63; Conclusion: Matching practices in ACLR studies remain highly variable, with limited justification provided for covariate selection. PSM and database-based studies tend to incorporate a greater number of covariates, yet reporting of matching methodology is often inconsistent. To enhance the quality, reproducibility, and comparability of ACLR research, future studies should adopt standardized reporting practices for matching, including explicit descriptions of covariate selection, matching algorithms, balance diagnostics, and match ratios. These steps can serve as a foundation for a more unified research framework, enabling future studies to collectively generate higher quality, generalizable evidence for ACLR outcomes.

Indexed as

ACL reconstructionconfounderscovariatesmatchingmethodology

Identifiers

PMID42416047
PMCPMC13338535

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.