A Clinical Prediction Rule for Functional Outcomes in Patients Undergoing Surgery for Severe Degenerative Cervical Myelopathy: Analysis of an International AOSpine Prospective Multicentre Dataset of 254 Subjects
Notice bibliographique
Résumé
Introduction Patients with cervical spondylotic myelopathy (CSM) may be severely impaired, have reduced quality of life and present with deleterious signs and symptoms. Patients with severe myelopathy (mJOA < 12) often improve following surgery; however, some may not achieve a minimum clinically important difference (MCID), whereas others may have exceptional outcomes. Due to varying prognoses among this group, it is important to predict outcome in these patients and use this knowledge to manage expectations. This study aims to determine the most important clinical predictors of surgical outcome in patients with severe CSM. Material and Methods Of the 757 patients enrolled in the CSM-North America or International studies, 254 (33.55%) presented with severe myelopathy as classified by a mJOA < 12 points. A prediction model was developed to distinguish between patients who improve to mild or moderate myelopathy postoperatively (mJOA≥12) and those who remain significantly impaired (mJOA < 12). Univariate analyses evaluated the relationship between this outcome and various clinical predictors. Multivariate Poisson regression was used to formulate the final prediction model and to compute the relative risks. A secondary model was constructed to predict which patients would achieve a MCID on the mJOA, defined as a change score of three or more points in patients with severe disease. Results Our cohort consisted of 153 men and 101 women with ages ranging from 28 to 86 (mean: 60.09 ± 12.06 years). The mean preoperative mJOA was 9.42 ± 1.67. One hundred and fifty-four (60.63%) patients improved to a score ≥12 at 1-year postoperative, whereas 145 (57.09%) achieved a MCID on the mJOA. Baseline severity score (RR: 1.07, 95%C.I.: 1.02–1.13), hyperreflexia (RR: 0.83, 95%C.I.: 0.72–0.96), lower limb spasticity (RR: 0.75, 95%C.I.: 0.65–0.86), and age (RR: 0.97, 95%C.I.: 0.95–0.99) were significant predictors of a mJOA≥12 following univariate analysis. The final model consisted of three statistically significant variables and one clinically relevant predictor: baseline severity score (RR: 1.09, 95%C.I.: 1.03–1.15), duration of symptoms (RR: 0.94, 95%C.I.: 0.89–0.99), co-morbidity score (RR: 0.96, 95%C.I.: 0.91–1.00) and the sign lower limb spasticity (RR: 0.76, 95%C.I.: 0.66–0.87). The AUC for this model was 0.75 (95%C.I.: 0.67, 0.83). Improvement by the MCID could not be effectively predicted by a combination of clinical variables. Conclusion Severe patients were more likely to achieve a score ≥12 on the mJOA if they had a higher preoperative mJOA score and a shorter duration of symptoms; a lower co-morbidity score (fewer and less severe concomitant disease); and did not have lower limb spasticity.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 ».