What Factors Are Associated with Symptomatic Rotator Cuff Tears: A Meta-analysis
Notice bibliographique
Résumé
BACKGROUND: Rotator cuff tears are common. A previous systematic review reported on factors associated with rotator cuff tears; however, it included relatively few studies and few variables, and in addition, it had considerable heterogeneity. To identify the factors associated with symptomatic rotator cuff tears and to help guide clinicians to potentially modifiable factors, we felt a broader and more inclusive meta-analysis would be useful. QUESTIONS/PURPOSES: In this systematic review and meta-analysis, we asked what (1) demographic, (2) disease, and (3) imaging factors are associated with symptomatic rotator cuff tears? METHODS: PubMed, Embase, and Web of Science were searched, and the search period were from the inception of each database through February 2021. The keywords included "risk factor," "rotator cuff injury," "rotator cuff tears," and "rotator cuff tendinitis." All comparative studies on symptomatic rotator cuff tears were included. We considered that the diagnosis of rotator cuff tear could be made by any imaging tool (MRI or ultrasound). We considered either partial- or full-thickness tears to be a rotator cuff tear. No language restrictions were applied. Twenty-six articles from 14 countries involving 9809 individuals, consisting of 3164 patients and 6645 controls, were included. The Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality (AHRQ) scale were used to evaluate the risk of bias of the included studies, and the highest scores were 9 and 11, respectively. The Newcastle-Ottawa Scale was used for retrospective comparative studies, and the AHRQ was used to evaluate prospective comparative studies. The eight retrospective comparative studies we included were scored from 4 to 9. The quality score of the 18 prospective comparative studies ranged from 6 to 9. Publication bias was explored using the Egger test. Heterogeneity was estimated using the I2 value. If there was no heterogeneity (I2 ≤ 50%), a fixed-effects model was used to determine the overall effect size; if there was heterogeneity (I2 > 50%), a random-effects model was used to merge the effect values. A meta-analysis was performed with RevMan 5.3, and the risk ratio (RR) and weighted mean difference of related factors were calculated. RESULTS: Our meta-analysis identified the following demographic factors associated with an increased risk of rotator cuff tears: older age (mean difference 3.1 [95% CI 1.4 to 4.8]; p < 0.001), greater BMI (mean difference 0.77 [95% CI 0.37 to 1.17]; p < 0.001), smoking (RR 1.32 [95% CI 1.17 to 1.49]; p < 0.001), dominant arm (RR 1.15 [95% CI 1.06 to 1.24]; p < 0.001), greater height (mean difference 0.9 [95% CI 0.4 to 1.4]; p < 0.001), and heavier weight (mean difference 2.24 [95% CI 0.82 to 3.66]; p = 0.002). Regarding disease factors, we found that traumatic events (RR 1.91 [95% CI 1.40 to 2.54]; p < 0.001) and hypertension (RR 1.50 [95% CI 1.32 to 1.70]; p < 0.001) were associated with symptomatic rotator cuff tears. Regarding imaging factors, we found that the following three factors were associated with symptomatic rotator cuff tears: greater acromion index (mean difference 0.11 [95% CI 0.06 to 0.16]; p < 0.001), greater critical shoulder angle (mean difference 1.9 [95% CI 1.5 to 2.3]; p < 0.001), and smaller glenoid version angle (mean difference -1.3 [95% CI -1.9 to -0.8]; p < 0.001). We found no association between the patient's sex or the presence or absence of thyroid disease and the likelihood of a rotator cuff tear being present. CONCLUSION: This study identified several factors associated with symptomatic rotator cuff tears, including blood glucose, blood pressure, weight, and smoking. Clinicians may seek to modify these factors, possibly in patients with symptomatic rotator cuff tears, but also in symptomatic patients who have not yet been diagnosed with rotator cuff tears because there would be no harm or risk associated with modifying any of the factors we identified. Future research should further study whether addressing these factors can delay the progression and size of rotator cuff tears.Level of Evidence Level III, prognostic study.
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 | 0,017 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,018 | 0,068 |
| Bibliométrie | 0,006 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».