Correlation of new bone metabolic markers with conventional biomarkers in hemodialysis patients
Bibliographic record
Abstract
BACKGROUND: New bone metabolic markers have become available clinically for evaluating chronic kidney disease mineral and bone disorders (CKD-MBD). The aim of this study was to correlate these new bone metabolic markers with conventional markers in regular hemodialysis (HD) patients. METHODS: One hundred forty three HD patients underwent cross-sectional assessment. Two bone formation markers, bone-specific alkaline phosphatase (BAP) and osteocalcin (OC), and one bone resorption marker, amino-terminal telopeptides of type 1 collagen (NTx), were selected for study. RESULTS: Both circulating OC and NTx levels showed positive correlations with serum intact parathyroid hormone (iPTH) levels. The levels of NTx and OC showed a strongly positive correlation, although they are known to be markers of different aspects of bone metabolism: bone formation and resorption. Patients with high iPTH (≥300pg/mL) had significantly higher levels of all the three bone markers compared with patients with low or normal iPTH . CONCLUSION: Serum OC and NTx levels may be useful markers of serum iPTH levels for evaluating bone turnover in HD patients and may eventually prove useful in the management of patients with CKD-MBD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".