Exposure to perfluoroalkyl and polyfluoroalkyl substances and risk of stroke in adults: a meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Evidence of the adverse metabolic health effects of perfluoroalkyl and polyfluoroalkyl substances (PFAS) is increasing. However, the impact of PFAS on cardiovascular diseases remains controversial. This meta-analysis aimed to analyze the impact of PFAS on the stroke risk. CONTENT: Databases were searched for studies published up to November 1, 2022, which report the association between stroke and exposure to at least one of four main PFAS (perfluorooctanoic acid [PFOA], perfluorooctanesulfonic acid [PFOS], perfluorononanoic acid [PFNA], and perfluorohexane sulfonic acid [PFHxS]). Data extraction and quality assessment were performed according to the Newcastle-Ottawa scale. SUMMARY AND OUTLOOK: Four studies were included in this systematic review. Multivariate adjusted odds ratios (ORs) for incident stroke per 1-log unit increment in each serum PFAS were combined in the meta-analysis. The risk of development of stroke was not significantly associated with PFOA, PFOS, or PFNA exposure (PFOA: pooled odds ratio [OR]=1.001, 95 % confidence interval [CI]=0.975-1.028, p=0.934; PFOS: pooled OR=0.994, 95 % CI=0.972-1.017, p=0.601; PFNA: pooled OR=1.016, 95 % CI=0.920-1.123, p=0.752), whereas a moderately lower risk was associated with PFHxS exposure without statistical significance (pooled OR=0.953, 95 % CI=0.908-1.001, p=0.054). PFOA, PFOS, and PFNA exposure showed a neutral association, while PFHxS showed a possible inverse association with the risk of stroke. Therefore, this finding should be interpreted with caution. Further prospective observational studies with PFAS mixture analyses are warranted.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it