The Heart and Kidney: Abnormal Phosphate Homeostasis Is Associated With Atherosclerosis
Bibliographic record
Abstract
CONTEXT: Phosphate has gained recognition as a risk factor for adverse cardiovascular outcomes, potentially due to accelerated vascular calcification. Fibroblast growth factor-23 (FGF-23) is a counter-regulatory hormone that increases renal phosphate excretion to maintain normal levels. OBJECTIVE: The purpose of the study was to determine the association of phosphate and FGF-23 to atherosclerosis. DESIGN AND SETTING: A prospective cohort study (n = 204) of outpatients referred for coronary angiography over of a 1-year recruitment period at the Kingston General Hospital. INTERVENTION: Blood was collected, and a focused carotid ultrasound was performed. MAIN OUTCOME MEASURE: Degree of angiographic coronary artery disease was scored. Carotid maximum plaque height, total area, grayscale median, and tissue pixel distribution were measured. Plasma phosphate was assessed by mineral assay and FGF-23 by ELISA. RESULTS: < 0.01). FGF-23 was associated with increased plaque % calcium-like tissue. Participants with no coronary artery disease had significantly lower phosphate levels. Phosphate was associated with higher grayscale median (GSM) in male subjects but with lower GSM in female subjects. FGF-23 was associated with increased plaque % fat in male subjects but increased plaque % calcium in female subjects. CONCLUSIONS: Phosphate was independently associated with the severity of atherosclerosis in terms of plaque burden and composition. FGF-23 was associated with plaque calcification. These findings suggest that abnormal phosphate homeostasis may play an under-recognized but potentially modifiable role in cardiovascular disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".