Two-Year Follow Up of the LATERAL Clinical Trial
Bibliographic record
Abstract
BACKGROUND: The LATERAL trial validated the safety and efficacy of the thoracotomy approach for implantation of the HeartWare HVAD System, leading to Food and Drug Administration approval. We sought to analyze 24-month adverse event (AE) rates, including a temporal analysis of the risk profile, associated with the thoracotomy approach for the HVAD system. METHODS: AEs from the LATERAL trial were evaluated over 2 years postimplant. Data was obtained from the Interagency Registry for Mechanically Assisted Circulatory Support database for 144 enrolled United States and Canadian patients. Temporal AE profiles were expressed as events per patient year. RESULTS: During 162.5 patient years of support, there were 25 driveline infections (0.15 events per patient year), 50 gastrointestinal bleeds (0.31 events per patient year), and 21 strokes (0.13 events per patient year). Longitudinal AE analysis at follow-up intervals of <30 and 30 to 180 days, and 6 to 12 and 12 to 24 months revealed the highest AE rate at <30 days, with a decrease in total AEs within the first 6 months. After 6 months, most AE rates either stabilized or decreased through 2 years, including a 95% overall freedom from disabling stroke. CONCLUSIONS: Two-year follow-up of the LATERAL trial revealed a favorable morbidity profile in patients supported with the HVAD system, as AE rates were more likely to occur in the first 30 days postimplant, and overall AE rates were significantly reduced after 6 months. Importantly, 2-year freedom from disabling stroke was 95%. These data further support the improving AE profile of patients on long-term HVAD support. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02268942.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".