Correlates of parathyroid hormone concentration in hemodialysis patients
Bibliographic record
Abstract
BACKGROUND: The implications of chemical hyperparathyroidism on bone and mineral metabolism measures in maintenance hemodialysis (MHD) are not well known. We hypothesized that a higher serum intact parathyroid hormone (iPTH) level is associated with the higher likelihood of hyperphosphatemia, hyperphosphatasemia [high serum alkaline phosphatase (ALP) levels] and hypercalcemia. METHODS: Over an 8-year period (July 2001-June 2009), we identified 106 760 MHD patients with iPTH and calcium (Ca), phosphorous (P) and ALP data from a large dialysis clinic. Logistic regression models were examined to assess the association between serum iPTH increments and the likelihood of hyperphosphatemia (P ≥5.5 mg/dL), hypercalcemia (Ca ≥10.2 mg/dL) and hyperphosphatasemia (ALP ≥120 U/L). RESULTS: Patients were 61 ± 16 years old and included 45% women, 59% diabetics and 33% Blacks. Compared with an iPTH level of 100 to <200 pg/mL, patients with an iPTH level of 600-700, 700 to <800 and ≥800 pg/mL had 122% (OR: 2.22, 95% CI: 2.04-2.41), 153% (OR: 2.53, 95% CI: 2.29-2.80) and 243% (OR: 3.43, 95% CI: 3.22-3.66) higher risk of hyperphosphatemia, respectively, and had 109% (OR: 2.09, 95% CI: 1.93-2.26), 130% (OR: 2.30, 95% CI: 2.10-2.52) and 376% (OR: 4.76, 95% CI: 4.50-5.04) higher risk of hyperphosphatasemia, respectively. Compared with an iPTH level of 100 to <200 pg/mL, both the low iPTH (<100 pg/mL, OR: 2.45, 95% CI: 2.27-2.64) and the high iPTH (≥800 pg/mL: OR: 2.13, 95% CI: 1.95-2.33) levels were associated with hypercalcemia. CONCLUSIONS: Higher levels of iPTH are incremental correlates of hyperphosphatemia and hyperphosphatasemia, whereas both very low and high PTH levels are linked to hypercalcemia. If these associations are causal, correction of hyperparathyroidism may have overarching implications on bone and mineral disorders in MHD patients.
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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 | 0.000 |
| 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) | 0.000 | 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".