Keywords:
Osteoporosis, Calcifications / Calculi, Instrumentation, CT, Absorptiometry / Bone densitometry, Musculoskeletal bone, Cardiovascular system
Authors:
A. Kokov, V. L. Masenko, S. E. Semenov, O. Barbarash; Kemerovo/RU
Results
Among the patients had a high prevalence of osteopenia syndrome (87.1%).
According to X-ray absorptiometry T-score values of lumbar vertebrae -1.07 [-1.54; -0.40],
T-score of the proximal femur -2.01 [-2.71; -1.49].
We also found a large amount of calcification of the coronary arteries according MSCT: calcium score (CS) 471.8 [118.2; 916,8].
Severe calcification of the coronary arteries is predominant in the examined group of patients (fig.1).
Calcification of the carotid arteries in patients of the study group was less pronounced: CS 113.9 [44.5; 300.8],
but noted significant direct relationship between the degree of calcification of different vascular beds (r=0,35,
p<0,05).
We have data on the significant inverse association between bone density and a coronary artery calcification (r=-0,29,
p<0,05),
and the carotid artery (r=-0,22,
p<0,05) by using Spearman rank correlations.
Factors that affect the probability of osteopenic syndrome (according X-ray absorptiometry) in patients with known rates of calcification of the coronary and carotid arteries were obtained by regression analysis.
These factors were coronary CS (p=0.012),
carotid CS (p=0.034),
the mass of calcifications of the carotid arteries (p=0.025) and the presence of a stenosis of the carotid arteries (p=0.026).
The predictive model for estimating the probability of the presence of osteopenia in patients with multifocal atherosclerosis has been is designed using regression coefficients of each of the factors.
Predictive probability of having osteopenia (P) varies from 0 to 1.
If the value of P> 0.5,
then the patient is referred to a group of patients with osteopenia (table 1).
As a result,
ROC-analysis of the area under the ROC-curve for this prediction model was 0.792 (p=0.0001) (fig.2).
The model was tested in the study sample.
The specificity of the model was 72.1%,
sensitivity of the model was 80.2%.