Methodology for the Systematic Reviews on an Evidence-Based Approach for the Management of Chronic Low Back Pain
Notice bibliographique
Résumé
STUDY DESIGN: Systematic review. OBJECTIVE: To provide a detailed description of the methods undertaken in the systematic search and analytical summary of chronic low back pain (CLBP) management issues and to describe the process used to develop clinical recommendations regarding challenges in the management of patients with CLBP. SUMMARY OF BACKGROUND DATA: We present methods used in conducting the systematic, evidence-based reviews and development of expert panel recommendations on key challenges to CLBP assessment and management. Our intent is that clinicians will combine the information from these reviews with an understanding of their own capacities and experience to better manage patients with chronic LBP and to consider future research that identifies patients or subgroups that respond differently with regard to benefits and safety to various treatment interventions. METHODS: A systematic search and critical review of the English language literature was undertaken for articles published on the classification, measurement, and management of CLBP. Citations were screened for relevance using a priori criteria, and relevant studies were critically reviewed. Whether an article was included for review depended on whether the study question was descriptive, one of therapy, one of prognosis, or one of diagnosis. When evaluating differential treatment benefits by specific disease, sociodemographic, and psychological subgroups, we sought to evaluate the heterogeneity of treatment effects. Studies were included if they made the treatment comparison and presented treatment effects by the predefined subgroup. The strength of evidence for the overall body of literature in each topic area was determined by two independent reviewers considering risk of bias, consistency, directness, and precision of results using a modification of the Grades of Recommendation Assessment, Development and Evaluation (GRADE) criteria. Disagreements were resolved by consensus. Findings from studies meeting inclusion criteria were summarized. From these summaries, clinical recommendations were formulated from consensus achieved among subject experts through a modified Delphi process. RESULTS: We identified and screened 2845 citations in 13 topic areas relating to the classification, measurement, and management of CLBP. Of these, 118 met our predetermined inclusion criteria and were used to attempt to answer specific clinical questions within each topic area. Some of the highlights of the analysis revealed a limited number of studies meeting inclusion criteria for topics evaluating therapy, use of magnetic resonance imaging, and classification systems. Few studies comparing surgical fusion to nonoperative care were identified that presented treatment effects by subgroups limiting the evaluation of heterogeneity of treatment effects. CONCLUSION: We undertook systematic reviews to understand the classification, measurement, and management of CLBP and to provide clinical recommendations. This article reports the methods used in the reviews. CLINICAL RECOMMENDATIONS: Clinical recommendations were made where appropriate using the GRADE/Agency for Healthcare Research and Quality approach, which imparts a deliberate separation between the quality of the evidence (i.e., high, moderate, low, or inconclusive) from the strength of the recommendation. The quality of evidence plays only a part as the strength of the recommendation reflects the extent to which we can, across the range of patients for whom the recommendations are intended, be confident that desirable effects of a management strategy outweigh undesirable effects.
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 | 0,333 | 0,476 |
| Méta-épidémiologie (sens strict) | 0,007 | 0,006 |
| Méta-épidémiologie (sens large) | 0,024 | 0,032 |
| Bibliométrie | 0,045 | 0,035 |
| Études des sciences et des technologies | 0,004 | 0,006 |
| Communication savante | 0,013 | 0,010 |
| Science ouverte | 0,010 | 0,011 |
| Intégrité de la recherche | 0,011 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,037 | 0,009 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».