Long-term Outcomes of the Western Australian Trial of Screening for Abdominal Aortic Aneurysms
Bibliographic record
Abstract
IMPORTANCE: Mortality from ruptured abdominal aortic aneurysms (AAAs) remains high. The benefit of screening older men for AAAs needs to be assessed in a range of health care settings. OBJECTIVE: To assess the influence of screening for AAAs in men aged 64 to 83 years on mortality from AAAs. DESIGN, SETTING, AND PARTICIPANTS: This randomized clinical trial performed from April 1, 1996, through March 31, 1999, with a mean of 12.8 years of follow-up (range, 11.6-14.2 years) included a population-based sample from a single metropolitan region in Western Australia identified via the electoral roll. Data analysis was performed from June 1, 2015, to June 1, 2016. INTERVENTIONS: Randomization to an invitation to undergo ultrasonography of the abdominal aorta or a control group without invitation. MAIN OUTCOMES AND MEASURES: Surgery for and mortality from AAA. RESULTS: A total of 49 801 men aged 64 to 83 years were identified for the study. Men living too far from screening centers (n = 8671) or who died before invitation (n = 2650) were excluded, resulting in 19 249 men in the invited group and 19 231 controls (mean [SD] age, 72.5 [4.6] years; 95% white). Of 19 249 men invited for screening, 12 203 (63.4%) attended. There were more elective operations (536 vs 414, P < .001) and fewer ruptured AAAs (72 vs 99, P = .04) in the invited group compared with the control group. Overall, there were 90 deaths from AAAs in the invited group (mortality rate, 47.86 per 100 000 person-years; 95% CI, 38.93-58.84) and 98 in the control group (52.53 per 100 000 person-years; 95% CI, 43.09-64.03) for a rate ratio of 0.91 (95% CI, 0.68-1.21). For men aged 65 to 74 years, the AAA mortality rate in the invited group was 34.52 per 100 000 person-years (95% CI, 26.02-45.81) compared with 37.67 per 100 000 person-years (95% CI, 28.71-49.44) in the control group for a rate ratio of 0.92 (95% CI, 0.62-1.36). The number needed to invite for screening to prevent 1 death from an AAA in 5 years was 4784 for men aged 64 to 83 years and 3290 for men aged 65 to 74 years. There were no meaningful differences in all-cause, cardiovascular, and other mortality risks. CONCLUSIONS AND RELEVANCE: Use of the electoral roll to identify and invite men aged 64 to 83 years for screening for AAAs had no significant effect on the overall mortality from AAAs. TRIAL REGISTRATION: isrctn.org Identifier: ISRCTN16171472.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".