Anemia in the Elderly and the Risk of Injurious Falls.
Notice bibliographique
Résumé
Abstract Background: Anemia commonly occurs in the elderly (≥65), and has been associated with a number of adverse consequences. Thirty percent of the community-dwelling elderly fall annually and this risk increases to 50% by the age of 80. Serious injuries caused by a fall, such as fractures and head injuries, are sustained by about 10% of the elderly and often lead to functional disability, increased health care costs, and increased mortality. Identification of reversible risk factors is critical for the management of falls and related injuries. The purpose of the current study is to investigate whether anemia increases the risk of injurious falls (IF) in the elderly. Methods: Health claims data from over 30 health plans from 01/1999 through 04/2004 were used. Patients ≥65 years with ≥1 hemoglobin (Hb) measurement were selected. IF were defined as a fall claim followed by an injurious event claim within 30 days after the fall. Injurious events were defined as fractures of the hip, pelvis, femur, vertebrae, ribs, humerus, and lower limbs, Colle’s fracture, head injuries, or hematomas. An open-cohort design was employed to classify patients’ observation periods by: (1) by anemia status based on WHO criteria (< 12 g/dL for women; < 13 g/dL for men), and (2) by Hb level: <10, 10-<12, 12-<13, and ≥13 g/dL. The incidence rates (IF events / person-years of observation) were compared by anemia status and Hb levels, respectively. Subset analyses based on IF of the hip (including pelvis and femur) and the head were further conducted. The association of IF with anemia and Hb levels, respectively, was analyzed using both univariate and multivariate (adjusted for age, gender, health plan, comorbidities, concomitant medications) approaches. Results: Among the 47,530 study subjects, a statistically significant linear trend of increasing risk of falls (i.e., IF and non-IF events) with decreasing Hb was observed (p<.0001). The incidence of IF was 15.8, 14.0, 9.8, and 6.5 per 1,000 person-years for Hb levels of <10, 10-<12, 12-<13, and ≥13 g/dL, respectively (trend: p<.0001). Based on the univariate analysis, anemia increased the risk of IF by 1.66 times (95% CI: 1.41–1.95) compared to no anemia, and the effects of anemia on IF of the hip and head were more pronounced (rate ratio (RR)=2.25 [95% CI: 1.74–2.89] and 1.77 [95% CI: 1.22–2.55], respectively, (p<.01 for both)). Multivariate analysis revealed that Hb levels were significantly associated with the risk of IF (RR = 1.57, 1.48, 1.17 for Hb levels of <10, 10-<12, 12-<13 g/dL, respectively, compared to Hb≥ 13 g/dL), and the negative linear trend of the risk of IF by Hb levels remained statistically significant (p<.0001). In the subset of hip and head IF, the association with anemia was even stronger (Hip: RR=3.37, 1.83, 1.36 for Hb levels of <10, 10-<12, 12-<13 g/dL, respectively; Head: RR=1.65, 1.47, 1.18, respectively), with a statistically significant linear trend observed (Hip: p<.0001; Head: p=0.07). Anemia (esp. Hb < 10) had comparable risk to other well-known risk factors for falls such as Alzheimer’s disease, Parkinson’s disease, and osteoarthritis. Conclusion: Anemia was significantly and independently associated with an increasing risk for IF, especially IF to the hip and head, in elderly persons. Furthermore, the risk of IF increased as the anemia worsened. The impact of anemia correction on the risk of falls and IF needs to be evaluated.
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 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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,001 | 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 ».