Mental and physical health disorders following paediatric traumatic injury: a population-based longitudinal study in Manitoba, Canada
Notice bibliographique
Résumé
IMPORTANCE: Paediatric traumatic injury (PTI) is a leading cause of hospitalisation among children. Little is known about subsequent mental and physical health disorders while accounting for pre-injury health. OBJECTIVE: To compare pre-injury and post-injury mental and physical disorders in survivors of PTI with an uninjured matched cohort from the general population. This study hypothesised injured youth will have increased rates of mental and physical disorders relative to matched uninjured youth in the post-injury period. DESIGN: Retrospective longitudinal cohort study using linked administrative health data to examine paediatric patients hospitalised for injury between 1 January 2004 and 31 December 2016, measured 2 years pre-injury and 2 years post-injury. SETTING: Population-based study in Manitoba, Canada. PARTICIPANTS: Youth<18 years old who survived to discharge after an injury requiring hospitalisation in the study period (n=9551) were matched 1:5 (age, sex and region) to youth from the general uninjured population (n=47 755). EXPOSURES: PTI that required hospitalisation. MAIN OUTCOMES AND MEASURES: Mental disorders (anxiety, depression and substance use) and physical disorders (arthritis, cancer, diabetes, gastrointestinal, hypertension and total respiratory morbidity) were measured at physician visits and hospitalisations 2 years pre-injury and post-injury. Generalised estimating equations were used to estimate adjusted rate ratios (ARR). RESULTS: This study examined 9551 in the injured cohort and 47 755 matches in the uninjured cohort. Injured individuals had increased ARRs for all mental disorders (p<0.0006) pre-injury (anxiety=1.30 (95% CI, 1.16 to 1.47); depression=2.00 (95% CI, 1.73 to 2.32); substance use=4.99 (95% CI, 3.08 to 5.20); any mental disorder=1.50 (95% CI, 1.37 to 1.66)) and post-injury (anxiety=1.66 (95% CI, 1.51 to 1.82); depression=2.87 (95% CI, 2.57 to 3.21); substance use=3.25 (95% CI, 2.64 to 3.99); any mental disorder=1.90 (95% CI, 1.76 to 2.04)). For physical disorders, injured individuals had increased ARRs (p<0.0006) pre-injury for arthritis (1.50 (95% CI, 1.39 to 1.60)), cancer (1.97 (95% CI, 1.35 to 2.88)), gastrointestinal (1.12 (95% CI, 1.06 to 1.18)) and any physical disorder (1.14 (95% CI, 1.11 to 1.18)). Post-injury, the injured had higher ARRs (p<0.0006) for arthritis (2.02 (95% CI, 1.91 to 2.15)), cancer (1.97 (95% CI, 1.35 to 2.88)), diabetes (1.76 (95% CI, 1.33 to 2.32)), gastrointestinal (1.19 (95% CI, 1.12 to 1.27)), hypertension (2.36 (95% CI, 1.83 to 3.06)) and any physical disorder (1.33 (95% CI, 1.29 to 1.37)). Comparing the pre-injury and post-injury periods, ARRs for injured showed a difference over time for all mental disorders except substance use and all physical disorders except gastrointestinal and total respiratory morbidity compared with matched uninjured. Greater injury severity was associated with two times greater ARR for developing any mental health disorder, and the injured had three times the ARR for dying by suicide (p<0.0006). CONCLUSIONS AND RELEVANCE: Child survivors of traumatic injury had increased relative rates of mental and physical disorders compared with a matched uninjured cohort. These findings support targeted intervention strategies for this population at the time of hospitalisation.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 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 ».