Effect of older age on treatment decisions and outcomes among patients with traumatic spinal cord injury
Notice bibliographique
Résumé
BACKGROUND: Older people are at increased risk of traumatic spinal cord injury from falls. We evaluated the impact of older age (≥ 70 yr) on treatment decisions and outcomes. METHODS: We identified patients with traumatic spinal cord injury for whom consent and detailed data were available from among patients recruited (2004-2013) at any of the 31 acute care and rehabilitation hospitals participating in the Rick Hansen Spinal Cord Injury Registry. Patients were assessed by age group (< 70 v. ≥ 70 yr). The primary outcome was the rate of acute surgical treatment. We used bivariate and multivariate regression models to assess patient and injury-related factors associated with receiving surgical treatment and with the timing of surgery after arrival to a participating centre. RESULTS: Of the 1440 patients included in our study cohort, 167 (11.6%) were 70 years or older at the time of injury. Older patients were more likely than younger patients to be injured by falling (83.1% v. 37.4%; p < 0.001), to have a cervical injury (78.0% v. 61.6%; p = 0.001), to have less severe injuries on admission (American Spinal Injury Association Impairment Scale grade C or D: 70.5% v. 46.9%; p < 0.001), to have a longer stay in an acute care hospital (median 35 v. 28 d; p < 0.005) and to have a higher in-hospital mortality (4.2% v. 0.6%; p < 0.001). Multivariate analysis did not show that age of 70 years or more at injury was associated with a decreased likelihood of surgical treatment (adjusted odds ratio [OR] 0.48, 95% confidence interval [CI] 0.22-1.07). An unplanned sensitivity analysis with different age thresholds showed that a threshold of 65 years was associated with a decreased chance of surgical treatment (OR 0.39, 95% CI 0.19-0.80). Older patients who underwent surgical treatment had a significantly longer wait time from admission to surgery than younger patients (37 v. 19 h; p < 0.001). INTERPRETATION: We found chronological age to be a factor influencing treatment decisions but not at the 70-year age threshold that we had hypothesized. Older patients waited longer for surgery and had a substantially higher in-hospital mortality despite having less severe injuries than younger patients. Further research into the link between treatment delays and outcomes among older patients could inform surgical guideline development.
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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 | 0,001 | 0,004 |
| 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 ».