Relation Between Alkaline Phosphatase, Serum Phosphate, and All-Cause or Cardiovascular Mortality
Bibliographic record
Abstract
BACKGROUND: Higher levels of serum alkaline phosphatase (AlkP) are associated with excess mortality in dialysis patients, but whether AlkP is associated with adverse outcomes among people without kidney failure is unknown. METHODS AND RESULTS: We first analyzed the association between AlkP and cardiovascular outcomes among 4115 participants with a previous myocardial infarction (the Cholesterol And Recurrent Events [CARE] study). Results were validated by analyzing the association between AlkP and mortality in an independent sample of 14,716 adults from the general US population (the Third National Health and Nutrition Examination Survey). A graded, independent association was noted between baseline tertile of AlkP and the adjusted hazard ratio of all-cause mortality in CARE participants (P(trend)=0.02). After adjustment for serum phosphate, hepatic enzymes, and other potential confounders, participants with AlkP in the highest tertile had an adjusted hazard ratio of 1.43 (95% confidence interval 1.08 to 1.89) compared with those in the lowest tertile. Multivariable-adjusted associations between higher AlkP and all-cause and cardiovascular mortality were present in the Third National Health and Nutrition Examination Survey (P(trend) across tertiles of AlkP=0.006 and 0.038, respectively). Findings from both CARE and the Third National Health and Nutrition Examination Survey were similar among individuals with and without evidence of kidney disease, defined by estimated glomerular filtration rate <60 mL min(-1) 1.73 m(-2). CONCLUSIONS: We found an independent relation between higher levels of AlkP and adverse outcomes among survivors of myocardial infarction and in a general population sample. The excess risk of death was present in people without evidence of kidney disease and was particularly high among people with higher levels of both AlkP and serum phosphate.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".