Cigarette smoking and risk of intracranial aneurysms in middle-aged women
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We previously reported a single-centre study demonstrating that smoking confers a six-fold increased risk for having an unruptured intracranial aneurysm (UIA) in women aged between 30 and 60 years and this risk was higher if the patient had chronic hypertension. There are no data with greater generalisability evaluating this association. We aimed to validate our previous findings in women from a multicentre study. METHODS: A multicentre case-control study on women aged between 30 and 60 years, that had magnetic resonance angiography (MRA) during the period 2016-2018. Cases were those with an incidental UIA, and these were matched to controls based on age and ethnicity. A multivariable conditional logistic regression was conducted to evaluate smoking status and hypertension differences between cases and controls. RESULTS: From 545 eligible patients, 113 aneurysm patients were matched to 113 controls. The most common reason for imaging was due to chronic headaches in 62.5% of cases and 44.3% of controls. A positive smoking history was encountered in 57.5% of cases and in 37.2% of controls. A multivariable analysis demonstrated a significant association between positive smoking history (OR 3.7, 95%CI 1.61 to 8.50), hypertension (OR 3.16, 95% CI 1.17 to 8.52) and both factors combined with a diagnosis of an incidental UIA (OR 6.9, 95% CI 2.49 to 19.24). CONCLUSIONS: Women aged between 30 and 60 years with a positive smoking history have a four-fold increased risk for having an UIA, and a seven-fold increased risk if they have underlying chronic hypertension. These findings indicate that women aged between 30 and 60 years with a positive smoking history might benefit from a screening recommendation.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".