Epidemiologic insights on the role of fibroblast growth factor 23 in cardiovascular disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: Fibroblast growth factor 23 (FGF23) regulates phosphate and vitamin D homeostasis and rises as kidney function declines. Animal studies have demonstrated direct and indirect effects of FGF23 that may promote heart disease. Herein, we review the recent epidemiologic literature evaluating the relationship between FGF23 and cardiovascular disease. RECENT FINDINGS: In observational prospective studies, higher FGF23 associates with a greater risk of incident cardiovascular disease including ischemic heart disease, stroke, heart failure, and atrial fibrillation. These studies establish a temporal sequence of events over long-term follow-up that suggest a possible role of FGF23 in cardiovascular disease pathogenesis. In most studies, risk is generally graded; however, in the largest study to date, higher FGF23 within the low-normal range was not associated with higher risk. In several recent studies higher FGF23 associated more strongly with the risk of congestive heart failure compared with atherosclerotic events, a finding consistent with surrogate endpoints and animal experiments. Currently, the utility of FGF23 as a predictive biomarker of cardiovascular risk is not established, and interventions to reduce FGF23 need to be studied to confirm its possible pathophysiologic role. SUMMARY: Higher FGF23 is associated with the subsequent development of cardiovascular disease, and perhaps most notably heart failure, in a growing number of studies. These findings bolster ongoing efforts to lower FGF23 using strategies to reduce phosphate intake and absorption.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".