SP495IMPACT OF FGF-23 ON THE EVOLUTION OF LEFT VENTRICULAR HYPERTROPHY IN INCIDENT DIALYSIS PATIENTS: A PROSPECTIVE STUDY
Bibliographic record
Abstract
Introduction and Aims:Background: Patients undergoing haemodialysis (HD) are well known to suffer from high rates of cardiovascular mortality. Amongst the structural and functional cardiac abnormalities common in this population is a high incidence of left ventricular hypertrophy (LVH). FGF-23 is one of a family of proteins regulating cell proliferation and has been implicated in the development of LVH in chronic kidney disease. We performed a prospective study to investigate the relationship between FGF-23 levels, left ventricular mass and their progression over 12 months in incident HD patients. Methods: 41 incident HD patients were recruited for a prospective study. Patients had FGF-23 levels taken prior to dialysis at baseline and after 12 months and tested by ELISA according to manufacturers instructions (Kainos Laboratories, Tokyo). All patients underwent tagged cardiac MRI scanning at baseline and 12 months to determine cardiac structure and function using the gold standard investigation. Results: Mean age of the cohort was 60.1years±15.1, 66% were male and mean dialysis vintage at baseline was 128 days±69. At baseline the median serum phosphate level was 4.8mg/dl (2) with a mean serum calcium level of 9.2mg/dl±0.6. There was a wide variation in FGF-23 levels across the cohort with a mean serum FGF-23 level was grossly elevated at 3528pg/ml±8784. At 12 months this had increased further to mean serum levels of 5048pg/ml±9307 (p=0.46). Left Ventricular Mass Index (LVMI) at baseline was 79.6g/m2±21.4 and stayed relatively constant at 79.2g/m2±21.6 at 12 months. Mean change in FGF-23 at 12 months was 1025pg/ml±3682 with a mean change in LVMI of -0.43g/m2±13.4. There was no correlation between FGF-23 levels and LVMI either at baseline (r=-0.11 p=0.95) or 12 months (r=0.17 p=0.39), nor was there any correlation between the change in FGF-23 and the change in LVMI over 1 year (r=-0.02 p=0.90).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".