Implementation of MADIT and MUSTT in Clinical Practice: <i>Results of an International Survey</i>
Bibliographic record
Abstract
BACKGROUND: The long-awaited dramatically positive outcome of the Multicenter Automatic Defibrillator Implantation Trial (MADIT II), just published by Moss et al.,(14) has generated cardiologists' interest on the implementation into clinical practice of that trial. Important lessons may be learned by examining the clinical implementation of two preceding randomized, prospective, prophylactic ICD trials: the original MADIT trial, published late 1996, and the Multicenter Unsustained Tachycardia Trial (MUSTT), published late 1999. Both demonstrated that implantable cardioverter defibrillators reduce all-cause mortality by over 50% in high risk patients without previous sustained arrhythmias. METHODS: In early 2000, we surveyed 133 active electrophysiology centers (47 American, 81 European, 5 Canadian) to determine the extent to which these practices have been implemented in clinical practice during 1999, and the responses were compared to a similar survey for the year 1998. RESULTS: ICDs implanted for MADIT or MUSTT criteria accounted for 18% of new ICD implants in 1999, 65% greater than in 1998, increasing from 6% to 11% in Europe, and from 15% to 24% in America. During 1999, 53% of patients receiving ICDs for these indications were inpatients identified during hospitalization, 27% were outpatients referred specifically for MADIT/MUSTT indications, and 20% were identified by routine screening. Per the survey, in 1999 68% of responders were "somewhat (10-20%)" and 14% were "considerably (>20%)" more likely to implant ICDs for all indications. CONCLUSIONS: Extrapolating the results of this survey to all initial ICD implants for 1999, we estimate that 8500 implants for MADIT/MUSTT criteria took place in 1999, with the overall number of such implants substantially increased over the previous year, irrespective of geographic location, and influenced significantly by the publication of MUSTT. However, screening and implant practices between centers continue to vary over a broad spectrum. It will be interesting to observe whether similar patterns will follow with MADIT II.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".