Related Experiment Videos
How Are We Matching in ACL Reconstruction Research? A Systematic Review of Methods, Reporting, and Covariate
Jay R Patel1, Alejandro M Holle1, Brooke S Halpin1
1Mayo Clinic Alix School of Medicine, Phoenix, Arizona, USA.
Orthopaedic Journal of Sports Medicine
|July 8, 2026
Summary
Matching practices in anterior cruciate ligament reconstruction (ACLR) research are inconsistent, with limited justification for covariate selection. Standardized reporting is needed to improve study quality and comparability.
Area of Science:
- Orthopedic surgery research
- Biostatistics in clinical research
- Observational study methodology
Background:
- Matching techniques like propensity score matching (PSM) and direct covariate matching are common in anterior cruciate ligament reconstruction (ACLR) research.
- However, the selection of covariates, reporting consistency, and matching strategies lack clarity.
- This variability hinders the interpretation and comparability of ACLR study findings.
Purpose of the Study:
- To systematically review and evaluate covariate matching practices in ACLR literature.
- Assess the types and number of covariates used, methodological transparency, and trends in matching strategies.
- Identify areas for improvement in ACLR research methodology.
Main Methods:
- A systematic literature search was conducted across PubMed, EMBASE, and Cochrane databases.
- 97 studies meeting eligibility criteria were included for data extraction.
- Descriptive and comparative statistics were used to analyze matching techniques, covariate inclusion, and reporting practices.
Main Results:
- Propensity score matching (PSM) was used in 42.3% of studies, direct matching in 57.7%.
- PSM and database studies utilized more covariates than direct matching and single-center studies, respectively.
- Justification for covariate selection was reported in only 6.2% of studies, with inconsistent reporting of pre-matching data.
Conclusions:
- Matching practices in ACLR research are highly variable and lack methodological transparency.
- Standardized reporting of covariate selection, matching algorithms, and balance diagnostics is crucial.
- Implementing consistent reporting standards will enhance the quality, reproducibility, and generalizability of ACLR research.
Related Concept Videos
01:20Comparing the Survival Analysis of Two or More Groups
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
01:25Strategies for Assessing and Addressing Confounding
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...