Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Objective: To develop a simple and easy-to-use tool for identifying osteoporotic women (femoral neck bone mineral density [BMD] T-scores
Design: Retrospective study involving review of medical records.
Setting: Osteoporosis clinics in 6 Latin American countries.
Patients: Postmenopausal women ages >or=50 in Latin America who had femoral neck BMD measurements.
Measurements And Main Results: A risk index was developed from 1,547 patients based on least square regression using age, weight, history of fractures, and other variables as predictors for BMD T-score. The final model was simplified by reducing the number of predictors; sensitivity and specificity were evaluated before and after reducing the number of predictors to assess performance of the index. The final model included age, weight, country, estrogen use, and history of fractures as significant predictors for T-score. The resulting scoring index achieved 91% sensitivity and 47% specificity. Simplifying the index by using only age and weight yielded similar performance (sensitivity, 92%; specificity, 45%). Three risk categories were identified based on OsteoRisk, the index using only age and body weight: high-risk patients (index <=-2; 65.6% were osteoporotic), moderate-risk patients (-2< index <=1; 26.7% were osteoporotic), and low-risk patients (index>1; 8% were osteoporotic). Similar results were seen in a validation sample of 279 women in Brazil.
Conclusion: Age and weight alone performed well for predicting the risk of osteoporosis among postmenopausal women. The OsteoRisk is an easy-to-use tool that effectively targets the vast majority of osteoporotic patients in Latin America for evaluation with BMD.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1490071 | PMC |
http://dx.doi.org/10.1111/j.1525-1497.2005.40900.x | DOI Listing |
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