Prognostic implications of the Quebec Task Force classification of back-related leg pain: an analysis of longitudinal routine clinical data
Notice bibliographique
Résumé
BACKGROUND: Low back pain (LBP) patients with related leg pain have a more severe profile than those with local LBP and a worse prognosis. Pain location above or below the knee and the presence of neurological signs differentiate patients with different profiles, but knowledge about the prognostic value of these subgroups is sparse. The objectives of this study were (1) to investigate whether subgroups consisting of patients with Local LBP only, LBP + leg pain above the knee, LBP + leg pain below the knee, and LBP + leg pain and neurological signs had different prognoses, and (2) to determine if this was explained by measured baseline factors. METHODS: Routine clinical data were collected during the first visit to an outpatient department and follow-ups were performed after 3 and 12 months. Patients were divided into the four subgroups and associations between subgroups and the outcomes of activity limitation, global perceived effect (GPE) after 3 months, and sick leave after 3 months were tested by means of generalised estimating equations. Models were univariate (I), adjusted for duration (II), and adjusted for all baseline differences (III). RESULTS: A total of 1,752 patients were included, with a 76% 3-month and 70% 12-month follow-up. Subgroups were associated with activity limitation in all models (p < 0.001). Local LBP had the least and LBP + neurological signs the most severe limitations at all time-points, although patients with neurological signs improved the most. Associations with GPE after 3 months were only significant in Model I. Subgroups were associated with sick leave after 3 months in model I and II, with sick leave being most frequent in the subgroup with neurological signs. No significant differences were found in any pairwise comparisons of patients with leg pain above or below the knee. CONCLUSIONS: Subgrouping LBP patients, based on pain location and neurological signs, was associated with activity limitation and sick leave, but not with GPE. The presence of neurological signs and pain in the leg both have prognostic implications but whether that leg pain without neurological signs is above or below the knee does not.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».