Consensus on a standardised treatment pathway algorithm for lumbar spinal stenosis: an international Delphi study
Notice bibliographique
Résumé
BACKGROUND: Lumbar spinal stenosis (LSS) is a common degenerative spinal condition in older adults associated with disability, diminished quality of life, and substantial healthcare costs. Individual symptoms and needs vary. With sparse and sometimes inconsistent evidence to guide clinical decision-making, variable clinical care may lead to unsatisfactory patient outcomes and inefficient use of healthcare resources. METHODS: A three-phase modified Delphi study comprising four consensus rounds was conducted on behalf of the International Taskforce for the Diagnosis and Management of LSS to develop a treatment algorithm based on multi-professional international expert consensus. Participants with expertise in the assessment and management of people with LSS were invited using an international distribution process used for two previous Delphi studies led by the Taskforce. Separate treatment pathways for patients with different symptom types and severity were developed and incorporated into a proposed treatment algorithm through consensus rounds 1 to 3. Agreement with the proposed algorithm was evaluated in the final consensus round. RESULTS: The final algorithm combines stratified and stepped approaches. When indicated, immediate investigation and surgery is advocated. Otherwise, a stepped approach is suggested when self-directed care is unsatisfactory. This starts with tailored rehabilitation, then more complex multidisciplinary care, investigations and surgery options if needed. Treatment options in each step depend on clinical phenotype and symptom severity. Treatment response guides pathway entrance and exit points. Of 397 study participants, 86% rated their agreement ≥ 4 for the proposed algorithm on a 0-6 scale, of which 22% completely agreed. Only 7% disagreed. Over 70% of participants felt that the algorithm would be useful for clinicians in public healthcare (both primary care and specialist settings) and in private healthcare settings, and that a simplified version would help patients in shared decision-making. CONCLUSIONS: International and multi-professional agreement was achieved for a proposed LSS treatment algorithm developed through expert consensus. The algorithm advocates different pathway options depending on clinical indications. It is not intended as a treatment protocol and will require evaluation against current care for clinical and cost-effectiveness. It may, however, serve as a clinical guide until evidence is sufficient to inform a fully stratified care model.
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 | 0,001 |
| 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) | 0,001 | 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 ».