Effect of long‐term use of unfractionated or low‐molecular‐weight heparin on bone mineral density in maintenance hemodialysis patients
Bibliographic record
Abstract
ABSTRACT Introduction Long‐term use of unfractionated heparin (UFH) or low‐molecular‐weight heparin (LMWH) causes bone loss and osteoporosis in patients not receiving hemodialysis. This study aimed to investigate the effect of UFH and LMWH on bone mineral density (BMD) in patients undergoing maintenance hemodialysis (MHD). Methods Patients undergoing MHD using UFH or LMWH as anticoagulants were enrolled. BMD (in g/cm2), T‐score and Z‐score (BMDs) were measured at the lumbar spine and femur neck using dual‐energy X‐ray absorptiometry (DXA) at baseline and 2 years later. Patient demographics and clinical indices were collected. Correlation analysis was used to identify significant predictors of bone loss. Multiple linear regression was used to explore the relationship between heparin type and bone loss progression. Findings A total of 104 patients were enrolled and completed the baseline BMD test; 72 completed the test again 2 years later. Six patients were excluded because they used both UFH and LMWH. Although BMD decreased in some patients in the UFH group, a slight increase in the BMD was observed on an average in the LMWH group after 2 years. The mean change in BMD (in g/cm2) [0(−0.03,0.04) vs. 0.04(0,0.06), P = 0.023], T‐score [0(−0.40,0.30) vs. 0.35(−0.03,0.53), P = 0.038], and Z‐score [0.10(−0.30,0.40) vs. 0.45(0.08,0.63), P = 0.031] in the lumbar spine in the UFH group was lower than those in the LMWH group. Femur neck BMD did not change significantly. In a linear regression model, after adjusting for diabetes mellitus, parathyroid hormone, and serum phosphate, we did not find an association between heparin substances and BMD. Discussion UFH might be associated with loss of lumbar spine BMD in patients undergoing MHD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".