Maternal exposure to the production of fireworks and reduced rate of new onset hypertension in pregnancy
Bibliographic record
Abstract
BACKGROUND: Carbon monoxide (CO) is one of the main substances contained in fireworks. Previous studies suggested that CO may have protective effect on the development of hypertension of pregnancy. METHOD: The authors conducted a prospective cohort study in Liuyang, Hunan, China between January 2010 and December 2011. Demographic and life-style variables of the participating pregnant women were obtained through structured interview with the women and clinical data were retrieved from antenatal medical records. Density of fireworks factories was defined as the number of fireworks factories per 1000 residents in the township where the mothers resided during pregnancy. Multiple logistic regression analysis was used to analyze the independent association between maternal exposure to the production of fireworks and new onset hypertension in pregnancy. RESULTS: A total of 5976 pregnant women were included in the final analysis. Density of fireworks factories was inversely correlated with incidence of new onset hypertension in pregnancy (Pearson correlation coefficient = -0.29, p < 0.001). Multiple logistic regression analysis showed that, compared with women who resided during pregnancy in a township with 0-0.25 fireworks factories per 1000 residents, the rates of new onset hypertension in pregnancy in women who resided in a township with 0.26-1.00 fireworks factories per 1000 residents (Odds Ratio = 0.66, 95% confidence interval: 0.46, 0.96) and >1.5 fireworks factories per 1000 residents (Odds Ratio = 0.65, 95% confidence interval: 0.44, 0.97) were reduced by more than 30%. CONCLUSION: Maternal exposure to the high density of fireworks factories is associated with reduced risk of developing new onset hypertension in pregnancy.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".