Sociodemographic Variables Are Rarely Reported in Studies Investigating Ulnar Collateral Ligament Reconstruction: A Systematic Review

Abstract

Purpose

To evaluate the reporting of sociodemographic variables in studies related to ulnar collateral ligament (UCL) reconstruction.

Methods

A systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed, Embase, and Scopus were searched on April 9, 2024, using the terms “medial ulnar collateral ligament reconstruction,” “ulnar collateral ligament reconstruction,” “ulnar collateral ligament surgery,” or “Tommy John Surgery.” Studies were included if they were randomized controlled trials, case control studies, cross-sectional studies, cohort studies, and case series in English. The presence of sociodemographic variables, including sex or gender and age, as well as the presence of sociodemographic variables, including race, ethnicity, insurance status, income, housing status, work status, and level of education were collected. Descriptive statistics and χ² tests or Fisher exact tests were used for analysis.

Results

The initial database search yielded 1,504 studies, with 831 duplicates removed and an additional 598 studies excluded after title and abstract screening. Of the remaining 75 studies, 31 were excluded after full-text screening, leaving 44 studies for inclusion, all published between 2006 and 2024. Among these, sociodemographic variables (e.g., race: 0/44, ethnicity: 0/44, insurance status: 0/44, level of education: 10/44, income: 0/44, work status: 12/44) were reported significantly less frequently than demographic factors such as age (42/44; 95.5%), and sex or gender (24/44; 54.5%; P < 0.05). There was no significant difference in reporting of any sociodemographic variables among included journals (P = .83) or by year of publication (P = .67).

Conclusions

This systematic review highlights a critical lack in the reporting of sociodemographic variables within studies examining UCL reconstruction, with a significantly greater rate of reporting of demographic factors, such as age and sex or gender, compared with sociodemographic variables like race and ethnicity.

Level of Evidence

Level IV, systematic review of level II-IV studies.

Baseball pitchers and other overhead throwing athletes frequently experience medial elbow pain, commonly attributed to ulnar collateral ligament (UCL) injury.1, 2, 3, 4 Elbow injuries are the most common reason for prolonged absences among collegiate pitchers (more than 10 days) and account for 7% to 8% of all injuries among baseball players in the National Collegiate Athletic Association.⁵ Since its introduction, ulnar collateral ligament reconstruction (UCLR) has been one of the most effective techniques for treating UCL injury. Socioeconomic variables can impact the timing of diagnosis and treatment for UCL injury and UCLR, resulting in challenges in producing equitable outcomes for all patients.⁶

Disparities in health care outcomes manifest in various ways, including differences in access to care, the quality of care received, and the ultimate health outcomes achieved.⁶ Understanding the underlying origins of these disparities is important to effectively design measures for addressing them. Differences in treatment and outcomes after undergoing orthopaedic procedures, including but not limited to UCLR, are frequently influenced by social determinants of health.^7,8 Identifying the demographic and socioeconomic factors that affect orthopaedic care for UCL deficiency allows surgeons to have the opportunity to intervene earlier in disease progression, improving long-term outcomes. However, these variables often have been overlooked or under-reported in the orthopaedic literature.⁷

Studies by Kamalapathy et al.⁸ and Fiscella and Sanders⁹ and found that lower education levels were associated with greater rates of readmission and major complications after hip and ankle fracture management. Economic disparities also increased the risk of readmission, revision, and infection postoperatively. These findings highlight the challenge of distinguishing surgical outcomes from patient-specific factors. To ensure the validity of study results, it is crucial to account for sociodemographic variables such as sex, gender, race, ethnicity, insurance status, housing status, and income. The purpose of this study was to evaluate the reporting of sociodemographic variables in studies related to UCL reconstruction. We hypothesized that UCLR studies would significantly under-report these variables, limiting the generalizability of their findings.

Methods

This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed, Embase, and Scopus were searched by 2 independent reviewers (E.L.B. and K.T.N.) for the terms “medial ulnar collateral ligament reconstruction,” “ulnar collateral ligament reconstruction,” “ulnar collateral ligament surgery,” or “Tommy John Surgery” on April 9, 2024. Studies were included if they were randomized clinical trials (RCT), case control studies, cross-sectional studies, cohort studies, and case series investigating UCL reconstruction published in English. Studies were excluded if they were not published in English, did not have the full-text available, were cadaver studies, systematic reviews, technique articles, or study designs other than RCTs, case control studies, cross sectional studies, cohort studies, and case series.

Data Collection

All identified studies were uploaded into Covidence systematic review software. The title, journal, and year of publication for each study were recorded. Two authors (E.L.B. and K.T.N.) thoroughly reviewed each manuscript to determine the presence of demographic variables including sex or gender and age, as well as the presence of sociodemographic variables including race, ethnicity, insurance status, income, housing status, work status, and level of education. The term “employment” was considered for the work status variable and for the income variable, “socioeconomic status” was also considered. The information was collected in a binary manner, categorizing whether each variable was present or absent as either “yes” or “no,” respectively. The Risk of Bias in Non-Randomized Studies–of Interventions tool was used to evaluate the risk of bias in observational studies, cross-sectional research, systematic reviews, and nonrandomized trials.¹⁰

Statistical Analysis

Data were analyzed using descriptive statistics. χ² tests were used to compare 2 categorical variables. Fisher exact tests were used to compare three or more categorical variables. P < .05 was considered statistically significant.

Results

The initial database search identified 1,504 studies, of which 831 duplicates were removed. An additional 598 studies were removed after title and abstract screening because they did not meet the inclusion criteria. Of the remaining 75 studies, 31 were excluded for the reasons specified in Figure 1. Forty-four studies met inclusion criteria and were included in the systematic review (Fig 1, Table 1).11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54

Fig 1.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart.

Table 1.

Study Design Characteristics of Included Studies

Title	Level of Evidence	Study Design	Sample Size
Arner 201911	III	Cohort study	51 patients (specified 46 male, 5 female)
Begly 201812	IV	Case series	26 MLB players (specified 26 male)
Bowman 202313	IV	Survey study	45 baseball players (assumed 45 male)
Cain 201014	IV	Case series	1,281 athletes (specified 1,253 male, 28 female)
Cinque 202215	IV	Case series	42 professional and collegiate baseball pitchers (specified 42 male)
Desai 202316	III	Retrospective cohort study	35 baseball players (assumed 35 male)
Dines 201217	IV	Case Series	10 javelin throwers
Dodson 200618	IV	Case Series	100 consecutive overhead-throwing athletes (specified 100 male)
Domb 201019	II	Cohort Study	55 professional baseball players (specified 55 male)
Donohue 201920	IV	Retrospective case series	324 athletes (specified 290 male, 34 female)
Erickson 201921	III	Cohort Study	191 professional baseball players (assumed 191 male)
Erickson 201622	III	Cohort Study	85 athletes who underwent UCLR (specified 78 male, 7 female)
Fury 202123	III	Case-control study	63 MLB pitchers who underwent primary UCLR (assumed 63 male)
Gerard 202424	IV	Case series	15 female athletes (specified)
Gibson 200725	II	Cohort study	68 major league pitchers (assumed 68 male)
Griffith 202226	IV	Case series	717 professional baseball pitchers (assumed 717 male)
Hadley 202227	IV	Case series	16 javelin throwers (specified 14 male, 2 female)
Hechtman 201028	IV	Case series	34 baseball players, of which 29 were pitchers (assumed 34 male)
Jack 201829	III	Cohort study	33 MLB players (assumed 33 male)
Jack 202130	IV	Case series	67 nonprofessional baseball players (specified 67 male)
Jones 201431	IV	Case series	55 skeletally mature adolescent athletes. The majority of patients were baseball players (n = 47), there were 3 gymnasts and 5 javelin throwers (specified 51 male, 4 female)
Keller 201432	III	Case-control study	168 MLB pitchers (assumed 168 male)
Kennon 202033	IV	Case series	25 patients who were laborers or nonelite (not collegiate or professional) athletes (specified 17 male, 8 female)
Kodde 201234	IV	Case series	20 nonprofessional athletes (specified 7 male, 13 female)
Koh 200635	IV	Case series	20 high-level baseball players (13 professional and 7 collegiate) (specified 20 male)
Lansdown 201436	IV	Case series	80 MLB pitchers (assumed 80 male)
Lynch 202337	III	Cohort study	30 patients (specified 26 male, 4 female)
Makhni 201438	III	Cohort study	147 MLB pitchers (assumed 147 male)
Marshall 201839	III	Case-control study	Twenty-five professional catchers (assumed 25 male)
Merolla 201440	IV	Case series	15 patients (specified 12 male, 3 female)
O’Brien 201541	IV	Case series	33 athletes, 30 baseball players and 3 javelin throwers (specified 31 male, 2 female)
Osbahr 201442	IV	Case series	256 competitive baseball players (assumed 256 male)
Paletta 200643	IV	Case series	25 elite professional or scholarship collegiate baseball players (specified 25 male)
Park 201844	IV	Case series	161 patients (specified 161 male)
Peterson 201845	III	Cohort study	87 MLB pitchers (specified 87 male)
Platt 202146	IV	Case series	46 MLB pitchers (assumed 46 male)
Portney 201947	III	Case-control study	140 MLB pitchers (assumed 140 male)
Prodromo 201648	III	Case-control study	114 MLB pitchers (assumed 114 male)
Rao 202149	IV	Case series	22 baseball players (15 high school, 7 collegiate) (specified 22 male)
Rothermich 202250	IV	Case series	37 nonthrowing athletes (specified 12 male, 16 female)
Saper 201851	IV	Case series	140 adolescent baseball players (assumed 140 male)
Vaswani 202252	IV	Case series	10 baseball pitchers (assumed 10 male)
Whiteside 201653	III	Case-control study	104 MLB pitchers (assumed 104 male)
Yoshida 202154	IV	Case series	20 baseball pitchers (specified 20 male: 5 high school, 5 collegiate, 8 nonprofessional, and 2 professional pitchers)

MLB, Major League Baseball, UCL, ulnar collateral ligament; UCLR, ulnar collateral ligament reconstruction.

The included studies were published in various journals from 2006 to 2024, including the American Journal of Sports Medicine (AJSM), Journal of Shoulder and Elbow Surgery (JSES), Orthopaedic Journal of Sports Medicine, JSES Reviews, Reports, and Techniques, Arthroscopy, Musculoskeletal Surgery, Sports Medicine, and Arthroscopy, Sports Medicine, and Rehabilitation (ASMAR). Demographic variables including age and sex were variably reported in the included studies. Forty-two of 44 studies (95.5%) included the age of patients, whereas sex or gender was reported in only 24 (54.5%) studies. None of the 35 studies included sociodemographic variables including race, ethnicity, or income. Twelve of 44 (27.3%) studies included work status and 10 (22.7%) included the greatest level of education obtained by patients. Insurance status and housing status were not mentioned in any study (Tables 2 and 3). Sociodemographic variables (e.g., race: 0/44, ethnicity: 0/44, insurance status: 0/44, level of education: 10/44, income: 0/44, work status: 12/44) were reported in the included studies significantly less frequently than demographic factors such as age (42/44; 95.5%) and sex or gender (24/44; 54.5%) (P < .05).

Table 2.

Characteristics of Included Studies

Title	Journal	Level of Evidence	Year of Publication	Age (Yes/No)	Gender/Sex (Yes/No)	Race (Yes/No)	Ethnicity (Yes/No)	Insurance Status (Yes/No)	Housing Status (Yes/No)	Work Status (Yes/No)	Level of Education (Yes/No)	Income/Socioeconomic Status (Yes/No)
Arner 201911	AJSM	Level III	2018	Yes	Yes	No	No	No	No	No	No	No
Begly 201812	JSES	Level IV	2018	Yes	Yes	No	No	No	No	Yes	No	No
Bowman 202313	JSES	Level IV	2023	Yes	Not specified	No	No	No	No	Yes	No	No
Cain 201014	AJSM	Level IV	2010	Yes	Yes	No	No	No	No	No	No	No
Cinque 202215	AJSM	Level IV	2022	Yes	Yes	No	No	No	No	Yes	No	No
Desai 202316	ASMR	Level III	2023	Yes	Not specified	No	No	No	No	No	No	No
Dines 201217	AJSM	Level IV	2012	Yes	Not specified	No	No	No	No	No	No	No
Dodson 200618	AJSM	Level IV	2006	Yes	Yes	No	No	No	No	Yes	Yes	No
Domb 201019	AJSM	Level II	2010	Yes	Yes	No	No	No	No	Yes	No	No
Donohue 201920	Sports Medicine	Level IV	2010	No	Yes	No	No	No	No	No	Yes	No
Erickson 201921	AJSM	Level III	2019	Yes	Not specified	No	No	No	No	Yes	No	No
Erickson 201622	OJSM	Level III	2016	Yes	Yes	No	No	No	No	No	Yes	No
Fury 202123	OJSM	Level III	2021	Yes	Not specified	No	No	No	No	Yes	No	No
Gerard 202424	OJSM	Level IV	2024	Yes	Yes	No	No	No	No	No	Yes	No
Gibson 200725	AJSM	Level II	2007	Yes	Not specified	No	No	No	No	Yes	No	No
Griffith 202226	AJSM	Level IV	2022	Yes	Not specified	No	No	No	No	Yes	No	No
Hadley 202227	JSES	Level IV	2022	Yes	Yes	No	No	No	No	No	Yes	No
Hechtman 201028	JSES	Level IV	2010	Yes	Not specified	No	No	No	No	No	No	No
Jack 201829	AJSM	Level III	2018	Yes	Not specified	No	No	No	No	Yes	No	No
Jack 202130	OJSM	Level IV	2021	Yes	Yes	No	No	No	No	No	Yes	No
Jones 201431	AJSM	Level IV	2013	Yes	Yes	No	No	No	No	No	No	No
Keller 201432	JSES	Level III	2014	Yes	Not specified	No	No	No	No	No	No	No
Kennon 202033	OJSM	Level IV	2020	Yes	Yes	No	No	No	No	No	No	No
Kodde 201234	JSES	Level IV	2012	Yes	Yes	No	No	No	No	No	No	No
Koh 200635	Arthroscopy	Level IV	2006	Yes	Yes	No	No	No	No	Yes	No	No
Lansdown 201436	OJSM	Level IV	2014	Yes	Not specified	No	No	No	No	No	No	No
Lynch 202337	AJSM	Level III	2023	Yes	Yes	No	No	No	No	No	No	No
Makhni 201438	AJSM	Level III	2014	Yes	Not specified	No	No	No	No	No	No	No
Marshall 201839	Arthroscopy	Level III	2018	Yes	Not specified	No	No	No	No	Yes	No	No
Merolla 201440	Musculoskeletal Surgery	Level IV	2014	Yes	Yes	No	No	No	No	No	No	No
O’Brien 201541	JSES	Level IV	2015	Yes	Yes	No	No	No	No	No	No	No
Osbahr 201442	AJSM	Level IV	2014	Yes	Not specified	No	No	No	No	No	Yes	No
Paletta 200643	AJSM	Level IV	2006	Yes	Yes	No	No	No	No	No	No	No
Park 201844	JSES	Level IV	2018	Yes	Yes	No	No	No	No	No	Yes	No
Peterson 201845	OJSM	Level III	2018	Yes	Yes	No	No	No	No	No	No	No
Platt 202146	JSES	Level IV	2021	Yes	Not specified	No	No	No	No	No	No	No
Portney 201947	OJSM	Level III	2019	Yes	Not specified	No	No	No	No	No	No	No
Prodromo 201648	OJSM	Level III	2016	No	Not specified	No	No	No	No	No	No	No
Rao 202149	OJSM	Level IV	2021	Yes	Yes	No	No	No	No	No	No	No
Rothermich 202250	AJSM	Level IV	2022	Yes	Yes	No	No	No	No	No	Yes	No
Saper 201851	OJSM	Level IV	2018	Yes	Not specified	No	No	No	No	No	No	No
Vaswani 202252	JSES Tech	Level IV	2022	Yes	Not specified	No	No	No	No	No	No	No
Whiteside 201653	AJSM	Level III	2016	Yes	Not specified	No	No	No	No	No	No	No
Yoshida 202154	OJSM	Level IV	2021	Yes	Yes	No	No	No	No	No	Yes	No

AJSM, The American Journal of Sports Medicine; ASMR, Arthroscopy, Sports Medicine, and Rehabilitation; JSES, Journal of Shoulder and Elbow Surgery; JSES Tech, JSES Reviews, Reports, and Techniques; OJSM, Orthopaedic Journal of Sports Medicine.

Table 3.

Inclusion of Sociodemographic and Demographic Variables in Studies Relation to Ulnar Collateral Ligament Reconstruction

Factor	Included in Any Section, n (%)
Age	42 (95.5%)
Sex or gender	24 (54.5%)
Race	0 (0.0%)
Ethnicity	0 (0.0%)
Insurance status	0 (0.0%)
Housing status	0 (0.0%)
Work status	12 (27.3%)
Level of education	10 (22.7%)
Income	0 (0.0%)

There was no significant difference in reporting of any sociodemographic variables among included journals (P = .83; Fig 2) or by year of publication (P = .67; Fig 3).

Fig 2.

Rate of reporting sociodemographic variables in any section of the manuscript by journal.

Fig 3.

Sociodemographic variable inclusion in any section of the manuscript by publication year.

Risk-of-Bias Assessment

The Risk of Bias in Non-Randomized Studies–of Interventions tool was applied to all 44 studies included in this review (Table 4). Most studies showed strong methodologic quality and had low concern for bias due to the selection of participants, classification of interventions, deviations from intended interventions, missing data, measurement outcomes, and selection of the reported results. Thus, all of the studies had only low-to-moderate concerns for overall bias.

Table 4.

Quality and Risk of Bias Assessment Using the Risk of Bias in Non-Randomized Studies – of Interventions (ROBINS-I) tool

First Author	Year Published	Bias Due to Confounding	Bias in Selection of Participants Into the Study	Bias in Classification of Interventions	Bias Due to Deviations From Intended Interventions	Bias Due to Missing Data	Bias in Measurement Outcomes	Bias in Selection of the Reported Results	Overall Bias
Arner11	2019	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
Begly12	2018	Moderate	Low	Low	Low	Low	Moderate	Low	Low
Bowman13	2023	Moderate	Moderate	Low	Low	Low	Moderate	Low	Moderate
Cain14	2010	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
Cinque15	2022	Low	Low	Low	Low	Low	Low	Low	Low
Desai16	2023	Moderate	Low	Low	Low	Low	Low	Low	Low
Dines17	2012	Moderate	Low	Low	Low	Low	Low	Low	Low
Dodson18	2006	Moderate	Low	Low	Low	Low	Low	Low	Moderate
Domb19	2010	Serious	Low	Low	Low	Low	Low	Low	Moderate
Donohue20	2019	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
Erickson21	2019	Moderate	Low	Low	Low	Moderate	Moderate	Low	Moderate
Erickson22	2016	Moderate	Low	Low	Low	Low	Moderate	Low	Low
Fury23	2021	Low	Moderate	Low	Low	Low	Moderate	Low	Low
Gerard24	2024	Low	Low	Low	Low	Low	Low	Low	Low
Gibson25	2007	Low	Low	Low	Low	Low	Low	Low	Low
Griffith26	2022	Low	Moderate	Low	Low	Low	Low	Low	Low
Hadley27	2022	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
Hecthman28	2011	Low	Moderate	Low	Low	Low	Low	Low	Low
Jack29	2018	Low	Low	Low	Low	Low	Low	Low	Low
Jack30	2021	Low	Moderate	Low	Low	Low	Low	Low	Low
Jones31	2014	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
Keller32	2014	Low	Low	Low	Low	Low	Low	Low	Low
Kennon33	2020	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
Kodde34	2012	Moderate	Moderate	Low	Low	Low	Low	Moderate	Moderate
Koh35	2006	Moderate	Moderate	Low	Low	Low	Moderate	Low	Moderate
Lansdown36	2014	Low	Low	Low	Low	Moderate	Moderate	Low	Moderate
Lynch37	2023	Low	Low	Low	Low	Low	Low	Low	Low
Makhni38	2014	Low	Low	Low	Low	Low	Low	Low	Low
Marshall39	2018	Low	Low	Low	Low	Low	Low	Low	Low
Merolla40	2014	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
O’Brien41	2015	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
Osbahr42	2014	Low	Low	Low	Low	Moderate	Moderate	Moderate	Moderate
Paletta43	2006	Moderate	Moderate	Low	Low	Moderate	Moderate	Low	Moderate
Park44	2018	Low	Moderate	Low	Low	Low	Low	Low	Low
Peterson45	2018	Low	Low	Low	Low	Low	Low	Low	Low
Platt46	2021	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
Portney47	2019	Low	Low	Low	Low	Low	Low	Low	Low
Prodromo48	2016	Low	Low	Low	Low	Low	Low	Low	Low
Rao49	2021	Moderate	Moderate	Low	Low	Low	Moderate	Low	Moderate
Rothermich50	2022	Low	Low	Low	Low	Low	Moderate	Low	Low
Saper51	2018	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate
Vaswani52	2022	Serious	Moderate	Low	Low	Low	Low	Low	Moderate
Whiteside53	2016	Low	Moderate	Low	Low	Low	Low	Low	Low
Yoshia54	2021	Moderate	Moderate	Low	Low	Low	Low	Low	Moderate

Discussion

In this study, we found that, despite the growing recognition of sociodemographic factors as essential to understanding health outcomes, few UCLR studies report these variables. Our findings show a marked disparity: although demographic information including patient sex and age was relatively well-documented, essential sociodemographic data—race, ethnicity, insurance status, housing status, and income—were absent across all studies. This absence highlights a critical gap, as sociodemographic variables are fundamental to ensuring the applicability and equity of research outcomes across diverse populations.

The under-reporting of sociodemographic data in UCLR studies mirrors patterns identified in orthopaedic literature at large. For instance, Crnkovic et al.⁷ examined all research articles with human cohorts in the 2 highest-ranked U.S. general orthopaedics journals—Clinical Orthopaedics and Related Research and The Journal of Bone & Joint Surgery—and observed that only 21% of studies included data on race, whereas just 12% reported on ethnicity, underscoring a general trend within orthopaedic surgery to under-report these variables.⁷ This contrasts with public health research, where sociodemographic reporting is more consistent, although still not universal. Orkin et al.⁵⁵ also assessed the thoroughness of reporting sociodemographic variables in randomized clinical trials and found significant variation in sociodemographic reporting across high-impact health journals, reflecting a broader need for standardized practices across health care research. Our findings align closely with these orthopaedic and public health studies, suggesting that sociodemographic data reporting remains underprioritized in UCLR research specifically, and in orthopaedic literature more generally.

Our findings also reveal a lack of reporting on income, insurance status, and housing stability within UCLR literature. These variables, although increasingly reported in studies related to other orthopaedic procedures, remain largely absent in UCLR studies, limiting the scope of demographic data available for comprehensive analyses. In 2016, Hodgins et al.⁵⁶ evaluated the epidemiologic trends of UCL reconstruction and noted that orthopaedic studies outside of UCLR have begun to include insurance status as a standard variable to assess patient accessibility and representation.

Both demographic and sociodemographic factors have been shown to affect outcomes of UCLR. A study by Dodson et al.² reported that athletes younger than the age of 25 years had a postsurgery return-to-play rate of 90%, compared with just 67% for those older than 25 years (P < .001). In addition, sex differences have also been shown to affect injury pattern, treatment, and outcomes after UCLR.⁵⁷ These findings highlight that both patient age and sex or gender have a significant impact on patient outcomes after UCLR after injury, and thus it is expected that these variables be included in the literature.⁵⁸

The omission of race and ethnicity from UCL studies is particularly problematic, given that these factors can significantly influence both the access to and outcomes of surgical interventions. A comprehensive analysis by Bi et al.⁵⁹ showed that African American patients underwent UCLR with a greater rate of Medicaid insurance, which was a significant predictor for overall complications within 90 days (P = .011) compared with their White counterparts. Insurance status often plays a critical role in determining both the access to and the quality of medical care received, particularly in elective surgeries such as UCLR. Studies have shown substantial differences in patient outcomes based on insurance type. For example, a study by Hodgins et al.⁵⁶ reported that patients with private insurance were 25 times more likely to undergo UCLR than those with Medicaid (P = .0014). The study also found that patients on Medicaid experienced more complications postsurgery, underscoring the critical role of insurance status in determining the success of UCLR.

Our study highlights a significant gap in the reporting of race, ethnicity, insurance status, and housing status within research on UCLR. Recognizing the importance of these sociodemographic factors, journals have started to address these concerns. For example, beginning in 2024, the Journal of Bone & Joint Surgery implemented guidelines requiring the reporting of race and ethnicity to help address health care disparities and enhance the external validity of study findings across diverse populations.⁶⁰ Public health research emphasizes including variables like housing status to ensure inclusivity and capture comprehensive patient demographics.^61,62 Adopting consistent socioeconomic reporting in UCLR studies would align them with broader orthopaedic research, enabling better interstudy comparisons and more accurate representation of patient diversity.

Limitations

This study has several limitations. The exclusion of non-English language studies may limit the generalizability of findings, as important data from other linguistic contexts might be overlooked. In addition, studies may not have included race or ethnicity if these differences were known to have negligible effect on the intervention. Furthermore, we did not assess the relevance of reporting specific variables within the context of each article. For example, some studies that did not explicitly report sex or gender focused on Major League Baseball players, a population known to be exclusively male. Thus, the absence of these variables does not necessarily reflect a lack of rigor but may align with the study’s specific focus. The variability in study designs and patient populations also complicates the ability to draw definitive conclusions across different settings. Furthermore, the risk of bias in the included studies may have influenced our findings, as variability in study design, sample selection, and reporting practices could impact the completeness and consistency of demographic and sociodemographic data documentation.

Conclusions

This systematic review highlights a critical lack in the reporting of sociodemographic variables within research related to UCLR, with a significantly greater rate of reporting of demographic factors, such as age and sex or gender, compared with sociodemographic variables like race and ethnicity.

Disclosures

The authors (E.L.B., K.T.N., W-K.W.K., S.M.S., M.K.M.) declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.