Assessment of Bone Mineral Density in Patients Undergoing Hemodialysis; An Iranian Population-Based Study
Bibliographic record
Abstract
Background: End-stage renal disease (ESRD) is a condition in which bone turnover and metabolism is impaired; thus, osteoporosis and low bone density are subsequently inevitable. We aimed to determine bone mineral density (BMD) and biochemical markers, and associated factors in hemodialysis (HD) patients. Methods: Patients aged 30-70 years undergoing HD between 2015 to 2019 were enrolled in this cross-sectional study. BMD measured by dual energy x-ray absorptiometry (DEXA) and biochemical laboratory tests were assessed in 200 patients undergoing HD. Statistical analysis was based on t test, Pearson, regression and Mann-Whitney tests using SPSS 16. Results: Two hundred patients were investigated. Sixty percent of the patients were female. Mean ± SD of participants’ age was 58.6 (±11.63) years and mean ± SD for duration of HD was 45.69 (± 43.76) months. Osteoporosis was found in 48% (n=96) and low bone density in 36% (n=76) of our patients. General osteoporosis was more frequent in those undergoing HD for more than 3 years, although not significantly (P=0.093, odds ratio [OR]=0.37). However, regional osteoporosis in hip and femoral neck, but not spine vertebrae, were significantly higher after three years of HD (P=0.036, OR=0.27; P=0.042, OR=0.27; and P=0.344, OR=0.56, respectively). Increased body mass index (BMI) correlated negatively with osteoporosis (P=0.050). Conclusion: With increasing age and duration of HD, BMD decreases. Higher BMI was associated with higher bone mass density. Bone density assessment seems to be necessary in patients undergoing HD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".