Tracking the Uptake of Evidence
Bibliographic record
Abstract
BACKGROUND: Advances in clinical research methods have led to prospective randomized controlled (level 1) clinical studies evaluating diagnostic modalities resulting in a paradigm shift in the literature for diagnosing deep vein thrombosis (DVT) and pulmonary embolism (PE). To assess whether these advances correlate with clinical practice, we analyzed 21-year trends in diagnostic testing for patients with venous thromboembolism. METHODS: We used discharge data from the National Hospital Discharge Survey (1979-1999) to determine DVT and PE cases annually. Procedure fields were screened to determine patients who had DVT or PE or who underwent venography, arteriography of the pulmonary arteries, pulmonary scintigraphy, or DVT ultrasonic scanning. Searching EMBASE, MEDLINE, and the American Thoracic Society guidelines, a literature-based time line of level 1 studies was derived and juxtaposed against trends and procedure use. RESULTS: Improved diagnostic tests resulted in diagnostic changes in patients with suspected venous thromboembolism. These observed changes correlated over time in subsequent years with level 1 studies. Diagnostic DVT approaches showed an initial marked increased use of venography followed by a rapid decline that coincided with increased use of Doppler ultrasonography. Diagnostic approaches to PE were characterized by initial marked increases in lung scanning followed by a rapid decline as use of ultrasonography considerably increased and pulmonary angiography modestly increased. CONCLUSIONS: Diagnostic approaches to DVT and PE have changed markedly during the past 2 decades, in temporal harmony with the evolving literature. Change in clinical practice occurs over years, and long-term follow-up is required to capture this change.
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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 | 0.210 | 0.635 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.053 | 0.034 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.025 | 0.016 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".