Regional, sex, and age differences in diagnostic testing among participants in the NAVIGATE-ESUS trial
Bibliographic record
Abstract
BACKGROUND AND AIM: The diagnosis of embolic stroke of undetermined source (ESUS) is based on excluding other more likely stroke etiologies, and therefore diagnostic testing plays an especially crucial role. Our objective was to compare the diagnostic testing by region, sex, and age among the participants of NAVIGATE-ESUS trial. METHODS: Participants were grouped according to five global regions (North America, Latin America, Western Europe, Eastern Europe and East Asia), age (<60, 60-74, and >75 years), and sex. Frequencies of each diagnostic test within areas of echocardiography, cardiac rhythm monitoring, and arterial imaging were described and compared across groups. A multivariable logistic regression model for each diagnostic test was fit to assess the independent influence of each of region, age, and sex and likelihood of testing. RESULTS: We included 6985 patients in the analysis (918 from North America; 746 from Latin America; 2853 from Western Europe; 1118 from Eastern Europe; 1350 from East Asia). Average age (highest in Western Europe (69 years), lowest in Eastern Europe (65 years)), % females (highest in Latin America (44%) and lowest in East Asia (31%)), and use of each diagnostic test varied significantly across regions. Region, but not sex, was independently associated with use of each diagnostic test examined. Transesophageal echocardiography and either CT or MR angiogram were more often used in younger patients. CONCLUSION: Diagnostic testing differed by region, and less frequently by age, but not by sex. Our findings reflect the existing variations in global practice in diagnostic testing in ESUS patients.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".