Impact of early surveillance on safety signal identification in the CathPCI DELTA study
Bibliographic record
Abstract
OBJECTIVES: The CathPCI Data Extraction and Longitudinal Trend Analysis study was designed to determine the feasibility of conducting prospective surveillance of a large national registry to perform comparative safety analyses of medical devices. We sought to determine whether the complementary use of retrospective case data could improve safety signal detection time. DESIGN: We performed a simulated surveillance study of the comparative safety of the Mynx vascular closure device (VCD) with propensity score matched alternate VCD recipients, using both retrospective and prospective cohort data. SETTING: Centers within the USA using the National Cardiovascular Data Registry (NCDR) CathPCI Registry. PARTICIPANTS: Percutaneous coronary intervention cases captured within the NCDR CathPCI Registry from July 1, 2009 to September 30, 2013 were included in the analysis. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Absolute and relative risk (RR) of any vascular complication (a composite of bleeding at access site, hematoma at access site, retroperitoneal bleeding, and other vascular complications requiring treatment); time to signal detection. RESULTS: A safety alert was detected for the primary outcome of "any vascular complication" after 15 months of surveillance and was sustained for the study duration (absolute risk of any vascular complication, 1.20% vs 0.73%, RR, 1.63; 95% CI 1.50 to 1.79; p<0.001). The safety signal was identified 12 months earlier with the use of retrospective case data than during the initial study. CONCLUSIONS: Prospective, active surveillance of cardiovascular registries is feasible to perform comparative analyses of medical devices. Retrospective data may complement prospective surveillance to improve time to signal detection, indicating the need for earlier prospective application of safety surveillance for devices new to the market.
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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 | 0.002 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".