The Use of Validated Clinical Outcome Measures in Spinal Surgery: An Analysis of Recent Annual Meeting Abstracts
Notice bibliographique
Résumé
Introduction Recently, the field of outcome assessment for patients undergoing spinal surgery has become the focus of investigation. Health-related quality of life outcome measures are fundamental to our understanding of the impact of surgical intervention on patients. Major spine academic groups have placed increasing emphasis on the use of HRQOL outcome measures, and this is no more obvious that in the requirements for abstract submissions to annual scientific meetings. The purpose of our study was to analyze the use of clinical outcome measures in abstracts accepted to the North American Spine Society (NASS) and Canadian Spine Society (CSS) annual meetings from 2010 to 2013 inclusively. We investigated the disease populations studied, the HRQOL outcome measures used, determined whether those measures had been validated in the specific patient population, and finally, whether the outcome measures used could be linked to the current WHO International Classification of Functioning, Disability, and Health (ICF). Material and Methods Accepted abstracts to NASS and CSS annual meetings from 2010 to 2013 were read. The frequency of abstracts containing clinical outcome measures and the frequency of validated versus non-validated outcome measures were analyzed. A systematic literature search was then performed using the Cochrane Library Database, PubMed, and the NASS evidence-based clinical guidelines. The concepts contained in the items of the 10 most commonly used outcome measures were selected and linked to the most specific ICF categories. Each concept of the outcome measure was linked to the ICF in a step-wise fashion. Results A total of 1,663 abstracts were read from the CSS and NASS from 2010 to 2013 inclusively. Of the abstracts accepted to CSS and NASS, 71 and 53% contained validated outcome measures, respectively. The 10 most commonly used outcome measures were the ODI, VAS, NDI, Eq. 5D, mJOA, AIS, and RMDQ. A total of 40 spinal conditions/surgical approaches were described among the 10 most commonly used health-related outcome measures. The NASS evidence-based clinical guidelines provided validity recommendations for spondylolisthesis, radiculopathy, and spinal stenosis. The Cochrane Library Database published systematic reviews for disc arthroplasty, degenerative disc disease, vertebral fractures, spinal fusion, disc replacement, back pain, cervical spondylotic myelopathy, and thoracolumbar burst fractures. All validity analyses for the remaining conditions/surgical approaches were found through PubMed and Google Scholar. All of the concepts for each outcome measure were linkable to the ICF. Conclusion According to this study, all of the 10 most commonly used outcome measures in abstracts accepted to CSS and NASS from 2010 to 2013 inclusive were validated in the field of spinal surgery. There is, however, still a need for one universal database to determine which outcome measures would be most useful for a given spinal condition or surgical approach. All of the 10 most commonly used outcome measures were linked to the WHO ICF. This provides evidence that over the past 4 years, researchers and clinicians in spinal surgery have identified the importance of utilizing validated HRQOL outcome measures as their health predictors.
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 | 0,068 | 0,308 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,007 |
| Bibliométrie | 0,060 | 0,055 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».