Development and Initial Validation of a Risk Score for Predicting In‐Hospital and 1‐Year Mortality in Patients With Hip Fractures
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Résumé
UNLABELLED: Our objectives were to better define the rates and determinants of in-hospital and 1-year mortality after hip fracture. We studied a population-based cohort of 3981 hip fracture patients. Using multivariable regression methods, we identified risk factors for mortality (older age, male sex, long-term care residence, 10 prefracture co-morbidities) and calculated a hip fracture-specific score that could accurately predict or risk-adjust in-hospital and 1-year mortality. Our methods, after further validation, may be useful for comparing outcomes across hospitals or regions. INTRODUCTION: Hip fractures in the elderly are common and associated with significant mortality and variations in outcome. The rates and determinants of mortality after hip fracture are not well defined. Our objectives were (1) to define the rate of in-hospital and 1-year mortality in hip fracture patients, (2) to describe co-morbidities at the time of fracture, and (3) to develop and validate a multivariable risk-adjustment model for mortality. MATERIALS AND METHODS: We studied a population-based cohort of 3981 hip fracture patients > or =60 years of age admitted to hospitals in a large Canadian health region from 1994 to 2000. We collected sociodemographic and prefracture co-morbidity data. Main outcomes were in-hospital and 1-year mortality. We used multivariable regression methods to first derive a risk-adjustment model for mortality in 2187 patients treated at one hospital and then validated it in 1794 patients treated at another hospital. These models were used to calculate a score that could predict or risk-adjust in-hospital and 1-year mortality after hip fracture. RESULTS AND CONCLUSIONS: The median age of the cohort was 82 years, 71% were female, and 26% had more than four prefracture co-morbidities. In-hospital mortality was 6.3%; 10.2% for men and 4.7% for women (adjusted odds ratio, 1.8; 95% CI, 1.3-2.4). Mortality at 1 year was 30.8%; 37.5% for men and 28.2% for women (adjusted p < 0.001). Older age, male sex, long-term care residence, and 10 different co-morbidities were independently associated with mortality. Risk-adjustment models based on these variables had excellent accuracy for predicting mortality in-hospital (c-statistic = 0.82) and at 1 year (c-statistic = 0.74). We conclude that 1 in 15 elderly patients with hip fracture will die during hospitalization, and almost one-third of those who survive to discharge will die within the year. The determinants of mortality were primarily older age, male sex, and prefracture co-morbidities. Our hip fracture-specific risk-adjustment tool is pragmatic and reliable, and after further validation, may be useful for comparing outcomes across different hospitals or regions.
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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 | 0,001 |
| 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 découle