Evaluation of Decision Rules for Referring Women for Bone Densitometry by Dual-Energy X-ray Absorptiometry
Notice bibliographique
Résumé
CONTEXT: Identification of women with low bone mineral density (BMD) is an important strategy in reducing the incidence of osteoporotic fractures. However, screening all women is not recommended. OBJECTIVES: To assess the diagnostic properties of 4 decision rules--Simple Calculated Osteoporosis Risk Estimation (SCORE), Osteoporosis Risk Assessment Instrument (ORAI), Age, Body Size, No Estrogen (ABONE), and body weight less than 70 kg (weight criterion)--for selecting women for dual-energy x-ray absorptiometry (DXA) testing and to compare results with recommendations made in the National Osteoporosis Foundation (NOF) practice guidelines. DESIGN AND SETTING: Analysis of data from the Canadian Multicentre Osteoporosis Study, a population-based community sample, collected from 9 study centers across Canada between February 1996 and September 1997. PARTICIPANTS: Postmenopausal women aged 45 years or older (N = 2365) without bone disease who had DXA data for the femoral neck, data to apply selection criteria, and who were not currently taking estrogens or who had been taking hormone replacement therapy for 5 or more years. MAIN OUTCOME MEASURES: Sensitivity, specificity, and area under the receiver operating characteristic (AUROC) curve of each of the 4 decision rules and the NOF guidelines for identifying women with a BMD T score of less than -1.0 SD, less than -2.0 SD, and no more than -2.5 SD at the femoral neck, and percentages of women recommended for testing, stratified by BMD level and age. RESULTS: The percent of women with a BMD T score less than -1, less than -2, and no more than -2.5 were 68.3%, 25.4%, and 10.0%, respectively. The AUROC curves were greatest using SCORE and ORAI. The sensitivity for identifying women with a BMD T score of less than -2.0 was 93.7% (95% confidence interval [CI], 91.8%-95.6%) using the NOF guidelines and was 97.5% (95% CI, 96.3%-98.8%), 94.2% (95% CI, 92.3%-96.1%), 79.1% (95% CI, 75.9%-82.3%), and 79.6% (95% CI, 76.4%-82.8%), respectively, using the SCORE, ORAI, ABONE, and weight criterion. However, the NOF guidelines also resulted in 74.4% (95% CI, 71.3%-77.6%) of women with a normal BMD (T score of -1.0 or higher) being tested compared with 69.2% (95% CI, 65.9%-72.5%), 56.3% (95% CI, 52.7%-59.8%), 35.8% (95% CI, 32.4%-39.2%), and 38.1% (95% CI, 34.6%-41.6%), respectively, using the 4 decision rules. Assessments suggest that ABONE and weight criterion are not useful case-finding approaches. CONCLUSION: The SCORE and ORAI decision rules are better than the NOF guidelines at targeting BMD testing in high-risk patients. The acceptability of these rules in clinical practice merits further investigation given their potential effect on the use of densitometry services.
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 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 | 0,004 | 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) | 0,000 | 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 ».