Frequency, distribution and severity of prevalent osteoporotic vertebral fractures in postmenopausal women

• Published in: Turkish neurosurgery Vol. 23; no. 4; pp. 476 - 483
• Main Authors: Kilincer, Cumhur, Kabayel, Derya Demirbag, Cagli, Bekir, Unlu, Ercument, Wicki, Barbara, Ozdemir, Ferda
• Format: Journal Article
• Language: English
• Published: Turkey 2013
• Subjects: Adult; Aged; Aged, 80 and over; Anthropometry; Bone Density; Cohort Studies; Female; Humans; Incidence; Middle Aged; Osteoporosis, Postmenopausal - complications; Osteoporosis, Postmenopausal - epidemiology; Prevalence; Radiography; Retrospective Studies; Socioeconomic Factors; Spinal Fractures - epidemiology; Spinal Fractures - etiology; Spine - diagnostic imaging; Turkey - epidemiology
• ISSN: 1019-5149
• DOI: 10.5137/1019-5149.JTN.7442-12.0

Assessment of previous vertebral fractures provides useful information to predict future fracture risk. This study aimed to determine the frequency, distribution and severity of prevalent osteoporotic vertebral fractures in postmenopausal women.
Data on patient characteristics, bone densitometry values, and spine radiographs (T2-L5) were reviewed in 232 postmenopausal women admitted to our osteoporosis clinic.
Prevalent vertebral fractures were detected in 28 (12.1%) women (95%CI: 7.8 16.3). Fifteen women (6.5%) had mild fractures and 13 (5.6%) had moderate or severe fractures according to Genant's semi-quantitative technique. The T-score was associated with the presence of prevalent vertebral fractures (OR= 0.61; 95%CI: 0.38-0.96, P= 0.034). The most frequently fractured vertebrae were T11 and T12, followed by T7 and T9. Sixty percent of fractures were wedge-type while 40% were biconcave. The frequency of wedge-type fractures at the T11-T12 levels (93.8%) was higher compared to that at all other levels (44.1%) (P= 0.001).
We determined the frequency, distribution, and severity of prevalent fractures and identified certain distribution patterns of fracture locations and types. To verify our results and detect possible predictive factors for fracture risk, population-based larger trials are needed.