Premorbid and concurrent predictors of TMD onset and persistence
Notice bibliographique
Résumé
BACKGROUND: Multiple risk factors predict temporomandibular disorders (TMD) onset, but temporal changes in risk factors and their contribution to risk of TMD have not been evaluated. The study aims were to (a) describe changes occurring in premorbid TMD risk factors when re-measured at TMD onset and 6 months later, and (b) determine if measures of change improve accuracy in predicting TMD incidence compared to premorbid measures alone. METHODS: In this observational prospective cohort study at four university research clinics, 3,258 community-based, 18- to 44-year-olds without TMD were enrolled. During the 3-year median follow-up, 260 incident cases of first-onset TMD were identified, and 196 TMD-free subjects were selected as matched controls. Six-months later, 147 of 260 incident cases (56.6%) were re-examined revealing 72 (49%) with 'persistent TMD' and 75 (51%) whose condition had resolved ('transient TMD'). Virtually all (126) of the 127 re-examined controls remained without TMD. Questionnaires and clinical measurements evaluated risk factors from clinical, health, psychological and behavioural and neurosensory domains. RESULTS: Most risk factors across all four domains increased with TMD onset, remained elevated in the persistent group and declined in the transient group (i.e., significant ANOVA interactions, p < .05). Accuracy in predicting first-onset TMD, quantified as area under the receiver operating characteristic curve was 0.71 (95% CL 0.68, 0.73) using only premorbid measures of risk factors, which increased to 0.91 (95% CL 0.89, 0.94) after addition of change measures. CONCLUSIONS: TMD pain onset and persistence appear to be determined by enduring characteristics of the person as well as mutually interactive with temporally evolving variables. SIGNIFICANCE: TMD is known to be a complex disorder, in which onset and persistence are associated with disease-related variables in multiple domains, including environmental exposure, clinical, psychological, health status, and pain processing variables. Using a more dynamic approach in order to capture change across time, many aspects of those domains were found to worsen prior to the reporting of pain, with bidirectional influences between domains and pain emergence likely. TMD onset appears to represent the cumulative effect of multiple system dysregulation.
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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 | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| 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 ».