Bibliographic record
Abstract
Introduction: Prostate-specific antigen (PSA) testing can improve early prostate cancer detection; however, numerous factors can influence patients' willingness and ability to undergo PSA testing.We aimed to assess the association between ischemic heart disease (IHD) diagnosis and PSA testing.Methods: We performed a cross-sectional study investigating the impact of various degrees of IHD on PSA testing.We assessed 3822 male respondents aged 55-75 from the 2018 year of the National Health Interview Survey (NHIS).Men were stratified according to the degree of IHD (none, history of angina pectoris (AP), history of myocardial infarction (MI), or history of neither, but with a diagnosis of IHD.Multivariable logistic regression analysis was used to assess the relationship between IHD and being tested for PSA, adjusting for known cofounders.Results: Multivariable logistic regression demonstrated that males with a history of IHD (no MI or AP) were more likely to have ever been PSA tested than males without IHD (OR 1.630, 95% CI 1.115-2.383,p=0.012) (Table 1).Additionally, older age (p<0.001),having a partner (vs.no partner, p<0.001), homosexual sexual orientation (vs.heterosexual orientation, p=0.007), and a history of cancer (vs.no history, p<0.001) all increased likelihood of being PSA tested.In contrast, Asian race (vs.White, p=0.001), and being a current smoker (vs.no smoking history, p<0.001) decreased the likelihood.Interestingly, males with a history of a symptomatic IHD (MI or AP) were not shown to be more likely to undergo PSA testing.Conclusions: Our results suggest that males with non-symptomatic IHD are more likely to be PSA tested.Males with symptomatic IHD do not seem to undergo more PSA screening, perhaps due to lower suggested life expectancy.Awareness of discrepancies in PSA testing in men with IHD should be raised among healthcare professionals.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.529 | 0.413 |
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".