Comparison of calcium phosphate product values using measurement of plasma total calcium and serum ionized calcium
Bibliographic record
Abstract
Calcium phosphate product (Ca x Pi) is a clinically relevant tool to estimate the cardiovascular risk of patients with renal failure. In reports, mostly total serum calcium has been used. As measurement of serum ionized calcium has some benefits and is being used increasingly, we estimated the respective levels of calcium phosphate product using both total (t-Ca x Pi) and ionized calcium (ion-Ca x Pi). Fifty-eight healthy individuals and 180 hemodialysis (HD) patients from 2 centers were studied. Diagnostic accuracies for corresponding values of the t-Ca x Pi and ion-Ca x Pi were calculated using a GraphROC program. Of HD patients, 64% had t-Ca x Pi <4.4 mmol(2)/L(2) regarded as a desirable goal, and 10% had values over 5.6 mmol(2)/L(2) associated with a high cardiovascular risk. Based on GraphROC analysis, t-Ca x Pi of 4.4 mmol(2)/L(2) corresponded to a value of 2.2 mmol(2)/L(2) of ion-Ca x Pi and, respectively, t-Ca x Pi of 5.6 mmol(2)/L(2) corresponded 2.8 mmol(2)/L(2) of ion-Ca x Pi. Owing to the good agreement between the results in the 2 centers, these values for risk levels can be used in both centers. When measurement of ionized calcium is used, Ca x Pi values of 2.2 and 2.8 mmol(2)/L(2) can be used instead of generally used values of 4.4 and 5.6 mmol(2)/L(2) with total calcium.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".