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Record W4306180921 · doi:10.1016/j.jse.2022.09.007

Social determinants of health influence clinical outcomes of patients undergoing rotator cuff repair: a systematic review

2022· review· en· W4306180921 on OpenAlexaboutno aff
Krishna Mandalia, Andrew Ames, James C Parzick, Katharine Ives, Glen Ross, Sarav S. Shah

Bibliographic record

VenueJournal of Shoulder and Elbow Surgery · 2022
Typereview
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRotator cuffPhysical therapySystematic reviewMEDLINESurgeryPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

BACKGROUND: Social determinants of health (SDOH) are the collection of environmental, institutional, and intrinsic conditions that may bias access to, and utilization of, health care across an individual's lifetime. The effects of SDOH are associated with disparities in patient-reported outcomes after hip and knee arthroplasty, but its impact on rotator cuff repair (RCR) is poorly understood. This study aimed to investigate the influences that SDOH have on accessing appropriate orthopedic treatment, as well as its effects on patient-reported outcomes following RCR. METHODS: This systematic review was performed in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and guidelines outlined by the Cochrane Collaboration. A search of PubMed, the Cochrane Library, and Embase from inception until March 2022 was conducted to identify studies reporting at least 1 SDOH and its effect on access to health care, clinical outcomes, or patient-reported outcomes following RCR. The search term was created with reference to the PROGRESS-Plus framework. Methodological quality of included primary studies was appraised using the Newcastle-Ottawa Scale (NOS) for nonrandomized studies, and the Cochrane Risk of Bias Tool for randomized studies. RESULTS: Thirty-two studies (level I-IV evidence) from 18 journals across 7 countries, published between 1999 and 2022, met inclusion criteria, including 102,372 patients, 669 physical therapy (PT) clinics, and 71 orthopedic surgery practices. Multivariate analysis revealed female gender, labor-intensive occupation and worker's compensation claims, comorbidities, tobacco use, federally subsidized insurance, lower education level, racial or ethnic minority status, low-income place of residence and low-volume surgery regions, unemployment, and preoperative narcotic use contribute to delays in access to health care and/or more severe disease state on presentation. Black race patients were found to have significantly worse postoperative clinical and patient-reported outcomes and experienced more pain following RCR. Furthermore, Black and Hispanic patients were more likely to present to low-volume surgeons and low-volume facilities. A lower education level was shown to be an independent predictor of poor surgical and patient-reported outcomes as well as increased pain and worse patient satisfaction. Patients with federally subsidized insurance demonstrated significantly worse postoperative clinical and patient-reported outcomes CONCLUSIONS: The impediments created by SDOH lead to worse clinical and patient-reported outcomes following RCR including increased risk of postoperative complications, failed repair, higher rates of revision surgery, and decreased ability to return to work. Orthopedic surgeons, policy makers, and insurers should be aware of the aforementioned SDOH as markers for characteristics that may predispose to inferior outcomes following RCR.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.212
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0120.004
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.106
GPT teacher head0.425
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations75
Published2022
Admission routes1
Has abstractyes

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