First-trimester smoking cessation in pregnancy did not increase the risk of preeclampsia/eclampsia: A Murmansk County Birth Registry study
Bibliographic record
Abstract
BACKGROUND: Although prior studies have shown that smoking reduces preeclampsia/eclampsia risk, the consequence of giving up this habit during pregnancy should be assessed. The aims of the current study were threefold: (i) describe maternal characteristics of women with preeclampsia/eclampsia; (ii) examine a possible association between the number of cigarettes smoked daily during pregnancy and the development of this affliction; and (iii) determine if first-trimester discontinuation of smoking during pregnancy influences the risk. METHODS: A registry-based study was conducted using data from the Murmansk County Birth Registry (MCBR). It included women without pre-existing hypertension, who delivered a singleton infant during 2006-2011 and had attended the first antenatal visit before 12 week of gestation. We adjusted for potential confounders using logistic regression. RESULTS: The prevalence of preeclampsia/eclampsia was 8.3% (95%CI: 8.0-8.6). Preeclampsia/eclampsia associated with maternal age, education, marital status, parity, excessive weight gain and body mass index at the first antenatal visit. There was a dose-response relationship between the number of smoked cigarettes per day during pregnancy and the risk of preeclampsia/eclampsia (adjusted OR1-5 cig/day = 0.69 with 95%CI: 0.56-0.87; OR6-10 cig/day = 0.65 with 95%CI: 0.51-0.82; and OR≥11 cig/day = 0.49 with 95%CI: 0.30-0.81). There was no difference in this risk among women who smoked before and during pregnancy and those who did so before but not during pregnancy (adjusted OR = 1.10 with 95%CI: 0.91-1.32). CONCLUSIONS: Preeclampsia/eclampsia was associated with maternal age, education, marital status, parity, excessive weight gain, and body mass index at the first antenatal visit. There was a negative dose-response relationship between the number of smoked cigarettes per day during pregnancy and the odds of preeclampsia/eclampsia. However, women who gave up smoking during the first trimester of gestation had the same risk of preeclampsia/eclampsia as those who smoked while pregnant. Consequently, antenatal clinic specialists are advised to take these various observations into account when counselling women on smoking cessation during pregnancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".