Does Smoking Affect Treatment Allocation and Outcomes in Patients with Rotator Cuff Tears?
Notice bibliographique
Résumé
Objectives: The objectives of this study were (1) to assess the influence of smoking status on treatment allocation (surgical versus non-surgical management) and (2) to compare the short-term functional outcomes of surgical and non-surgical treatment of rotator cuff tears between smokers and non-smokers. Methods: In the context of a prospective pragmatic cohort study we included 196 subjects with known full-thickness rotator cuff tears who were followed prospectively for 48 weeks. The Western Ontario Rotator Cuff Index (WORC), American Shoulder and Elbow Surgeons (ASES) score, and visual analogue pain scores were collected at baseline, 4, 8, 16, 32, and 48 weeks. Multivariate logistic regression was used to determine predictors of treatment allocation. Generalized linear models and t-tests were used to assess the effect of smoking on outcome measures at baseline. Mixed-effects repeated measures regression models were used to assess the effect of smoking on the outcomes after surgical and non-surgical management of rotator cuff tears. Results: The non-smoking group was older than the smoking group (61.4 years vs. 54.2, p=0.0004). Twenty-two percent of the surgical group and 12% of the non-surgical group were smokers. There was no significant difference between smokers and non-smokers in regards to the proportion of patients who were obese, had diabetes, had experienced rotator cuff tear symptoms for more than a year, had utilized physical therapy, had a large RCT, or who had received workers’ compensation. Smoking status was not significantly associated with allocation to surgical versus non-surgical treatment (OR=0.85, p= 0.762). After adjustment for covariates, subjects who smoked reported less favorable baseline adjusted WORC scores (40.9 vs. 54.5, p=0.0008), lower ASES scores (43.0 vs. 59.9, p=0.0001), as well as worse pain scores (59.5 vs. 42.9, p=0.0001). Within the non-surgical management group, smokers reported significantly lower adjusted WORC scores (38.0 vs. 56.8, p=0.0127), lower ASES scores (39.2 vs. 61.6, p=0.0872), and worse pain (61.9 vs. 42.1, p=0.0176) over 48 months. Similarly, in patients who underwent rotator cuff repair, smokers reported significantly lower adjusted WORC scores (31.1 vs. 40.4, p=0.0352), lower ASES scores (37.7 vs. 50.0, p=0.0143), and worse pain scores (63.2 vs. 51.5, p=0.0408) over the 48-week follow-up period. Conclusion: Subjects who smoked reported worse pain and function scores at baseline and over the course of one year, regardless of whether they received surgical or nonsurgical management. Smoking was not a significant predictor of treatment allocation in this cohort. The disparity in reported function and pain in smokers was less pronounced in those who underwent surgical repair than those who received non-surgical management therapy. Further follow up is needed to more clearly elucidate the influence of smoking on the management and outcome of rotator cuff tears.
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 | 0,008 | 0,037 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».