Gender-Based Differences in Abdominal Aortic Aneurysm Rupture: A Retrospective Study
Bibliographic record
Abstract
BACKGROUND: Annually, 5% of sudden deaths are due to abdominal aortic aneurysm (AAA) rupture. There is evidence suggesting that AAA ruptures have worse outcomes in females than males and the aneurysms rupture at a smaller size in females than in males. The United States Preventive Services Task Force (USPSTF) recommends a one-time ultrasound screening for males aged 65 - 75 years who ever smoked. There is insufficient evidence to screen females aged 65 - 75 years who ever smoked though there is evidence suggesting that AAAs rupture at a smaller size and have worse outcomes in females. The objective of this study is to compare the characteristics, mortality and morbidity of ruptured AAAs in females and males. METHODS: This is a retrospective review of 117 patients from two teaching institutions over a period of 6 years. A total of 39 parameters were compared between males and females including demographic variables, comorbidities like hypertension, dyslipidemia, cardiovascular diseases; previous history of AAA; medications, characteristics of aneurysm, type of surgery and its outcome; postoperative complications and long-term survival. RESULTS: The overall incidence of AAA rupture was higher in males (68%) than in females (32%). Females die from AAA rupture at a later age. There was a significant difference in the size of AAA rupture between females (mean = 7.4 cm, standard deviation (SD) = 2.0) and males (mean = 8.2 cm, SD = 1.8; P = 0.04). The probability to undergo surgery for ruptured AAA was significantly lower for females as compared to males (P = 0.03). Females had higher overall mortality (P = 0.001), postoperative mortality (P = 0.02), higher length of intensive care unit (ICU) stay, incidence of postoperative complications, use of vasopressors and use of ventilator. CONCLUSIONS: Using a similar threshold of size of AAA for elective surgery for both males and females might not be appropriate. Further population-based studies are needed to warrant AAA screening for high-risk females owing to the higher morbidity and mortality.
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 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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".