Interventions for preventing falls in elderly people
Notice bibliographique
Résumé
BACKGROUND: Approximately 30 per cent of people over 65 years of age and living in the community fall each year; the number is higher in institutions. Although less than one fall in 10 results in a fracture, a fifth of fall incidents require medical attention. OBJECTIVES: To assess the effects of interventions designed to reduce the incidence of falls in elderly people (living in the community, or in institutional or hospital care). SEARCH STRATEGY: We searched the Cochrane Musculoskeletal Group specialised register (January 2001), Cochrane Controlled Trials Register (The Cochrane Library, Issue 1, 2001), MEDLINE (1966 to February 2001), EMBASE (1988 to 2001 Week 14), CINAHL (1982 to March 2001), The National Research Register, Issue 1, 2001, Current Controlled Trials (www.controlled-trials.com accessed 25 May 2001), and reference lists of articles. We also contacted researchers in the field. SELECTION CRITERIA: Randomised trials of interventions designed to minimise the effect of, or exposure to, risk factors for falling in elderly people. Main outcomes of interest were the number of fallers, or falls. Trials reporting only intermediate outcomes were excluded. DATA COLLECTION AND ANALYSIS: Two reviewers independently assessed trial quality and extracted data. Data were pooled using the fixed effect model where appropriate. MAIN RESULTS: Interventions likely to be beneficial: ~bullet~A programme of muscle strengthening and balance retraining, individually prescribed at home by a trained health professional (3 trials, 566 participants, pooled relative risk (RR) 0.80, 95% confidence interval (95%CI) 0.66 to 0.98). ~bullet~A 15 week Tai Chi group exercise intervention (1 trial, 200 participants, risk ratio 0.51, 95%CI 0.36 to 0.73). ~bullet~Home hazard assessment and modification that is professionally prescribed for older people with a history of falling (1 trial, 530 participants, RR 0.64, 95% CI 0.49 to 0.84). A reduction in falls was seen both inside and outside the home. ~bullet~Withdrawal of psychotropic medication (1 trial, 93 participants, relative hazard 0.34, 95%CI 0.16 to 0.74). ~bullet~Multidisciplinary, multifactorial, health/environmental risk factor screening/intervention programmes, both for unselected community dwelling older people (data pooled from 3 trials, 1973 participants, pooled RR 0.73, 95%CI 0.63 to 0.86), and for older people with a history of falling, or selected because of known risk factors (data pooled from 2 trials, 713 participants, pooled RR 0.79, 95%CI 0.67 to 0.94). Interventions of unknown effectiveness: ~bullet~Group-delivered exercise interventions (9 trials, 2177 participants). ~bullet~Nutritional supplementation (1 trial, 50 participants). ~bullet~Vitamin D supplementation, with or without calcium (3 trials, 679 participants). ~bullet~Home hazard modification in association with advice on optimising medication (1 trial, 658 participants), or in association with an education package on exercise and reducing fall risk (1 trial, 3182 participants). ~bullet~Pharmacological therapy (raubasine-dihydroergocristine, 1 trial, 95 participants). ~bullet~Fall prevention programmes in institutional settings. ~bullet~Interventions using a cognitive/behavioural approach alone (2 trials, 145 participants). ~bullet~Home hazard modification for older people without a history of falling (1 trial, 530 participants). ~bullet~ Hormone replacement therapy (1 trial, 116 participants). Interventions unlikely to be beneficial: ~bullet~Brisk walking in women with an upper limb fracture in the previous two years (1 trial, 165 participants). REVIEWER'S CONCLUSIONS: Interventions to prevent falls that are likely to be effective are now available; less is known about their effectiveness in preventing fall-related injuries. Costs per fall prevented have been established for four of the interventions and careful economic modelling in the context of the local healthcare system is important. Some potential interventions are of unknown effectiveness and further research is indicated.
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 | 0,008 | 0,035 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,004 |
| Bibliométrie | 0,005 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,001 |
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 ».