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Combined clinical risk indices with quantitative ultrasound calcaneus measurement for identifying osteoporosis in Thai postmenopausal women.

Pongchaiyakul, Chatlert; Panichkul, Suthee; Songpatanasilp, Thawee.
Artículo en Inglés | IMSEAR | ID: sea-39579

OBJECTIVE:

To examine the diagnostic performance of clinical risk indices combined with quantitative ultrasound calcaneus measurement (QUS) for identifying osteoporosis in Thai postmenopausal women. MATERIAL AND

METHOD:

The present study was designed as a cross-sectional investigation in 300 Thai women, aged between 38 and 85 years (mean age 58). Femoral neck bone mineral density (BMD) was measured by DXA (Hologic QDR-4500; Hologic, Bedford, MA, USA). A BMD T-scores < or = -2.5 was defined as "osteoporosis"; otherwise, "non-osteoporosis". QUS was measured by Achilles+ (GE Lunar, Madison, WI, USA) and converted to T-score. The OSTA and KKOS score was calculated for each woman using her age and weight Women with OSTA/KKOS scores < or = -1 and > -1 were classified as "high risk" and "low risk", respectively.

RESULTS:

Using DXA as the gold standard, the sensitivity of QUS to identify osteoporosis was lower than the sensitivity of OSTA/KKOS (60 vs. 71/74%) but the specificity and PPV of QUS were higher than OSTA/KKOS. The sensitivity increased when using OSTA/KKOS combined with QUS to identify osteoporosis (approximately 87-89%) while the specificity, PPV and NPV were comparable with using clinical risk indices alone. The risk (odds ratio; OR) of osteoporosis when QUS T-score < or = -2.5 alone was 9.94 (95%CI 4.74-20.87), which was higher than high risk by OSTA/KKOS alone (OR 6.35, 95%CI 2.99-13.47 for OSTA and 8.15, 95%CI 3.76-17.66 for KKOS). Furthermore, individuals were classified "high risk" from OSTA/KKOS with QUS T-score < or = -2.5SD, the risk of osteoporosis was increased (OR 43.68, 95%CI 13.89-137.36 and OR 60.92, 95%CI 17.69-209.76 for OSTA and KKOS, respectively).

CONCLUSION:

Using the clinical risk indices combined with QUS could improve the accuracy of osteoporosis identification. This approach could be used in a primary care setting or community-based hospital where a DXA machine is not available.