Abstract 265: Plasma Lactate and Incident Hypertension in the Atherosclerosis Risk in Communities (ARIC) Study
Bibliographic record
Abstract
Insufficient oxidative capacity, or mitochondrial dysfunction, may contribute to the development of high blood pressure by stimulating increased blood flow. To test this hypothesis, we examined the prospective association of lactate, a product of glycolysis and marker of oxidative capacity, with incident hypertension in 5,554 participants from the Atherosclerosis Risk in Communities (ARIC) Study. Participants had no diagnosed hypertension and blood pressures <140/<90 mm Hg at baseline (1996-1998). Incident hypertension was assessed during annual telephone calls and defined as a self-reported physician diagnosis of hypertension or hypertension medication use. Analyses were performed with Cox proportional hazards models. The mean age was 61.9 years, and the mean lactate was 0.08 mmol/L. The population was 45.1% male and 12.8% black. During a median follow-up period of 11.9 years (range: 26.9 days to 13.4 years), there were 3,849 new cases of hypertension. The unadjusted 10-yr cumulative incidences across quartiles 1-4 of lactate were 14.6, 18.3, 21.5, and 32.3%. After adjustment for traditional hypertension risk factors, including baseline systolic and diastolic blood pressure, the highest quartile of baseline lactate was associated with 1.18 times the hazard of the lowest quartile (95% CI: 1.07, 1.31; P-trend = 0.001) (Figure). This association was stronger (HR 1.42; 95% CI: 1.23, 1.63) in participants with blood pressures <120/<80 mm Hg. Mild elevations in lactate precede hypertension even in a normotensive population. These findings have important implications for early detection of hypertension risk in healthy adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".