The GUIDE-HF trial of pulmonary artery pressure monitoring in heart failure: impact of the COVID-19 pandemic
Bibliographic record
Abstract
AIMS: During the coronavirus disease 2019 (COVID-19) pandemic, important changes in heart failure (HF) event rates have been widely reported, but few data address potential causes for these changes; several possibilities were examined in the GUIDE-HF study. METHODS AND RESULTS: From 15 March 2018 to 20 December 2019, patients were randomized to haemodynamic-guided management (treatment) vs. control for 12 months, with a primary endpoint of all-cause mortality plus HF events. Pre-COVID-19, the primary endpoint rate was 0.553 vs. 0.682 events/patient-year in the treatment vs. control group [hazard ratio (HR) 0.81, P = 0.049]. Treatment difference was no longer evident during COVID-19 (HR 1.11, P = 0.526), with a 21% decrease in the control group (0.536 events/patient-year) and no change in the treatment group (0.597 events/patient-year). Data reflecting provider-, disease-, and patient-dependent factors that might change the primary endpoint rate during COVID-19 were examined. Subject contact frequency was similar in the treatment vs. control group before and during COVID-19. During COVID-19, the monthly rate of medication changes fell 19.2% in the treatment vs. 10.7% in the control group to levels not different between groups (P = 0.362). COVID-19 was infrequent and not different between groups. Pulmonary artery pressure area under the curve decreased -98 mmHg-days in the treatment group vs. -100 mmHg-days in the controls (P = 0.867). Patient compliance with the study protocol was maintained during COVID-19 in both groups. CONCLUSION: During COVID-19, the primary event rate decreased in the controls and remained low in the treatment group, resulting in an effacement of group differences that were present pre-COVID-19. These outcomes did not result from changes in provider- or disease-dependent factors; pulmonary artery pressure decreased despite fewer medication changes, suggesting that patient-dependent factors played an important role in these outcomes. Clinical Trials.gov: NCT03387813.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".