Risk Factors for Persistent Problems Following Acute Whiplash Injury: Update of a Systematic Review and Meta-analysis
Notice bibliographique
Résumé
STUDY DESIGN: Systematic review and meta-analysis. OBJECTIVE: To update a previous review and meta-analysis on risk factors for persistent problems following whiplash secondary to a motor vehicle accident. BACKGROUND: Prognosis in whiplash-associated disorder (WAD) has become an active area of research, perhaps owing to the difficulty of treating chronic problems. A previously published review and meta-analysis of prognostic factors included primary sources up to May 2007. Since that time, more research has become available, and an update to that original review is warranted. METHODS: A systematic search of international databases was conducted, with rigorous inclusion criteria focusing on studies published between May 2007 and May 2012. Articles were scored, and data were extracted and pooled to estimate the odds ratio for any factor that had at least 3 independent data points in the literature. RESULTS: Four new cohorts (n = 1121) were identified. In combination with findings of a previous review, 12 variables were found to be significant predictors of poor outcome following whiplash, 9 of which were new (n = 2) or revised (n = 7) as a result of additional data. The significant variables included high baseline pain intensity (greater than 5.5/10), report of headache at inception, less than postsecondary education, no seatbelt in use during the accident, report of low back pain at inception, high Neck Disability Index score (greater than 14.5/50), preinjury neck pain, report of neck pain at inception (regardless of intensity), high catastrophizing, female sex, WAD grade 2 or 3, and WAD grade 3 alone. Those variables robust to publication bias included high pain intensity, female sex, report of headache at inception, less than postsecondary education, high Neck Disability Index score, and WAD grade 2 or 3. Three existing variables (preaccident history of headache, rear-end collision, older age) and 1 additional novel variable (collision severity) were refined or added in this updated review but showed no significant predictive value. CONCLUSION: This review identified 2 additional prognostic factors and refined the estimates of 7 previously identified factors, bringing the total number of significant predictors across the 2 reviews to 12. These factors can be easily identified in a clinical setting to provide estimates of prognosis following whiplash.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,011 | 0,013 |
| 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 ».