Comparisons of surgeon and patient prediction of 1-year outcomes following rotator cuff surgery
Notice bibliographique
Résumé
Background Preoperative patient expectations are thought to be predictors of outcomes in rotator cuff repair (RCR) surgery; however, these expectations lack an objective component. Surgeons are thought to possess the ability to more accurately predict postoperative patient outcomes compared to patients themselves. Surgeon's predictions of outcome could potentially serve to set realistic patient expectations of surgery and thus optimize surgical outcomes. The objective of this study was to describe patient and surgeon predictions of outcomes in those undergoing RCR surgery and determine the degree of agreement between these predictions and actual one-year postoperative outcomes. Methods Data for this study were collected in a healthcare registry as standard of care for all patients undergoing RCR from January 1 to December 31, 2022 at a single surgical center. Surgeries were conducted by fellowship-trained upper extremity surgeons. The primary outcome was the SANE (Single-Assessment Numeric Evaluation) score which required a written response by the patient to the question, "How would you rate your affected shoulder today as a percentage of normal (0% to 100% with 100% being normal)?". Preoperatively, patients completed their current SANE score and the SANE score they predicted to have at one-year postoperatively. The surgeon was asked to predict the patient's one-year SANE score immediately following completion of the surgery. A repeated-measures ANOVA compared surgeon-predicted, patient-predicted, and actual mean one-year postoperative SANE. Tukey's post hoc test was used to adjust for pairwise comparisons. The differences between actual and surgeon predicted SANE and actual and patient predicted SANE were calculated. "Accurate prediction" was defined a priori as a difference being within +/-5% of the actual SANE. Significance level was set to p <0.05. Results Sixty-nine patients were included in this study with a mean age of 60.9 (SD=6.9) years and 77% (N=53) were male. Surgeon-predicted one-year postoperative SANE was 77.6% (Min=60%; Max=95%; SD=6.8%), patient-predicted was 88.7% (Min=50%; Max=100%; SD=11.1%), and actual SANE was 80.6% (Min=8%; Max=100%; SD=19%) (p<0.001). Mean patient-predicted scores were significantly higher than both mean surgeon-predicted (p<0.001) and mean actual postoperative SANE (p=0.002). There was no statistical difference between mean surgeon-predicted and mean actual postoperative SANE. Conclusion On average, surgeons were better able to predict outcomes compared to patients. Patients tended to overestimate their outcomes, while surgeons tended to underestimate patient outcomes. These findings raise the importance of preoperative patient counselling to set more realistic expectations that would potentially improve their achieved outcomes.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| 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) | 0,000 | 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 tête enseignante, 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 ».