Patient Specific Factors Affecting the Decision for Surgery for a First Time Anterior Shoulder Dislocation (SS‐09)
Notice bibliographique
Résumé
Introduction Recurrent instability following a first‐time anterior shoulder dislocation (FTASD) is very common and approaches 100% in some reports. Arthroscopic stabilization can decrease the rate of recurrent instability and improve outcomes, but the decision for surgery remains complex. Multiple patient and provider specific factors exist that affect this treatment algorithm. In this paper, we examine the interaction of these complex factors and provide threshold values at which either surgery or non‐operative treatment is preferred. Methods A Markov Monte Carlo decision model comparing non‐operative versus surgical treatment for a FTASD was constructed using TreeAge Pro (Williamstown, MA, 2007). Four health states were incorporated into the model: initial dislocation, stable shoulder, recurrent instability and revision stabilization. Input parameters included patient‐specific variables (age, gender, activity level, time lost from work or sport, and coping with instability) and physician‐specific variables such as success of surgery as well as outcome probabilities and effectiveness. Values were derived from the literature or estimated by expert opinion where necessary. The primary outcome, treatment‐related quality of life years, was calculated based upon the Western Ontario Shoulder Instability index (WOSI). Specific factors examined were age, gender, time lost from work or sport, surgical success rate, activity level and ability to cope with instability. Multivariate sensitivity analyses were performed to identify key variables that influenced the preferred treatment strategy. Results Surgery for a FTASD was preferred for all men age 15‐35 and for women age 30 and younger. For high‐risk patients such as overhead athletes, surgery was preferred for all men age 15‐35 and women age 33 and younger. Non‐operative management was preferred when the relative risk of dislocation after surgery rises above 0.7 and 0.5, for men and women, respectively. Non‐operative management was preferred for men with an unstable shoulder when they were comfortable with a 14 point drop in WOSI score or when the WOSI benefit of surgery lasted 2.1 years or less. For women these values were 8 WOSI points and 3.6 years. Time lost from work or sport strongly effected the decision for surgery. This relationship is displayed in Figure 1, a two‐way sensitivity analysis of time lost from work or sport against age at first dislocation. Conclusion Surgery for a first time anterior shoulder dislocation resulted in improved outcomes (WOSI) for all men and women under age 30 and was therefore the preferred treatment. Beyond age 30, patient and provider specific factors exerted strong influences on the decision for surgery. Our study clarified the relationship among these factors and indicated threshold values at which surgery resulted in improved outcomes. These thresholds could potentially be useful for guiding clinical decision‐making, designing future studies, or benchmarking.
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 | 0,004 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».