Poster 104: Lower trapezius tendon transfer improves range of motion, function, and restores external rotation in patients with a massive, irreparable, posterosuperior rotator cuff tear
Notice bibliographique
Résumé
Objectives: Massive, irreparable rotator cuff tears can cause severe pain and weakness. In younger, more active patients, joint salvage interventions are the preferred treatment. Over the last decade, lower trapezius tendon transfer (LTTT) has increasingly been used to reduce pain and improve function in patients with massive posterosuperior rotator cuff tears. Few studies have reported outcomes following LTTT or examined risk factors for failure and poor patient reported outcomes The objective of this study was to report on failure rate, patient reported outcomes, and possible risk factors up to 2-years postoperative in those undergoing LTT in the management of massive, irreparable, posterosuperior rotator cuff tears. Methods: This is a prospective longitudinal observational study conducted between 2018 and 2023. All patients undergoing arthroscopic assisted LTTT by 2 fellowship trained upper extremity surgeons from two sites were screened. Inclusion criteria were patients with massive (2+ tendons), irreparable rotator cuff tears in the primary or revision setting. Irreparable was defined as two or more of the following: grade 3 or higher fatty infiltration, patte grade 3, tendon length < 15mm, previous rotator cuff repair surgery. Exclusion criteria were prisoners, military, non-English speakers, and patients <18 years old. Consented patients completed a demographic form, the Single Assessment Numeric Score (SANE), 4-point satisfaction scale (poor, fair, good, excellent), and the American Shoulder and Elbow Surgeon test at baseline at 12- and 24-months postoperative. A clinical assessment was conducted at all time points including range of motion and lag sign. Surgical failure was defined as reoperation, LTTT failure, SANE score of <50%, or forward flexion of less than 90°. Descriptive statistics were generated for all measures. Independent t tests were performed between time points for patient-reported outcomes. Exploratory logistic regression was conducted to evaluate risks of failure with age, sex, workers’ compensation benefits (WCB), primary or revision surgery, subscapularis status, and subscapularis repair as possible predictors. Linear regression was conducted to evaluate possible predictors of 12-month postoperative SANE scores including WCB status and revision or primary surgery. Results: Seventy-four patients were recruited to this study and completed 1-year follow-up. Fifty-one patients reached 24 months of follow-up. Twenty-six had previous rotator cuff procedures before undergoing LTTT. The mean (SD) age was 58.3 (7.8) years with 17 (23%) females and 57 (77%) males. Seven patients were WCB clients and 10 patients were smokers. Five patients had a complete full tear of subscapularis and 19 had a tear of the upper 50% or less. Ten (14%) LTTT surgeries were considered failures by 24-months postoperative, of which 5 had a subscapularis repair during their LTTT procedure, and 5 had a normal subscapularis. Table 1 presents patient reported outcomes and active range of motion scores pre- and postoperatively. Lag sign was positive in 42 of 74 patients preoperatively, with 32 patients corrected with surgery, 4 patients remaining positive, and 6 patients who did not attend in-person postoperative follow-up. The 4 patients with persistent lags were identified as failures. A complete full-thickness subscapularis tear was predictive of failure (p=0.009) despite full repair. WCB status was predictive of 12-month SANE score (p=0.006). Other variables were not predictive. Conclusions: Most patients experience improved range of motion, functional outcomes and restoration of external rotation at up to 2 years post-LTTT surgery. However, those that have a complete full-thickness subscapularis tear may be at greater risk of failure despite undergoing repair, and WCB patients may have lower SANE scores at 12-months postoperative.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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 ».