Social determinants of health influence clinical outcomes of patients undergoing rotator cuff repair: a systematic review
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,050 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,013 |
| Bibliométrie | 0,008 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».