The value of cardiovascular hospitalization as an endpoint for clinical atrial fibrillation research
Bibliographic record
Abstract
This editorial refers to ‘Cardiovascular hospitalization as a surrogate endpoint for mortality in studies of atrial fibrillation: report from the Stockholm Cohort Study of Atrial Fibrillation’ by L. Friberg and M. Rosenqvist, on page 626. Cardiovascular (CV) hospitalization has been used as a primary endpoint in clinical studies on atrial fibrillation (AF), but its value remains controversial. Cardiovascular hospitalization is associated with a decreased quality of life, 1 increased costs of care, 2 and increased risk of mortality. 3,4 However, it is also composed of a multiplicity of different clinical conditions ranging from heart failure to angina, and rates may vary among geographical regions and clinical settings. The operational definition and value of CV hospitalization as an endpoint should be well understood to draw valid conclusions in AF research. Mortality is a relevant outcome to assess the effect of therapies in AF patients. However, because death rates are low and existing therapies are effective, mortality trials are challenging to conduct. From the feasibility and cost perspective it is useful to employ surrogate and combined endpoints, but these should be well understood and validated. 5,6 Cardiovascular hospitalization is a potentially useful outcome of clinical importance. The Atrial Fibrillation Follow up Investigation of Rhythm Management (AFFIRM) investigators have shown that CV hospitalization could be a valid outcome in AF trials since it occurs prior to and more often than the true endpoint (mortality), can be objectively measured, and accurately predicted mortality independent of the application of rate or rhythm control. 3 The first time CV hospitalization or death was used as a primary outcome in a major AF trial was in the ATHENA (A placebo controlled, double blind Trial to assess the efficacy of dronedarone for the prevention of cardiovascular Hospitalization or death from any cause in patiENts with Atrial fibrillation and flutter) study, which was also the first study to demonstrate a reduction in important clinical CV outcomes with an antiarrhythmic drug (dronedarone). 7 With the Stockholm Cohort Study of Atrial Fibrillation (SCAF) analysis, Friberg and Rosenqvist 4 demonstrate an association between CV hospitalization and all-cause mortality among 2912 AF patients during a 6.5-year follow-up using a prospective observational cohort with detailed patient information. The SCAF analysis confirms the original findings of the AFFIRM analysis regarding the significant association of CV hospitalization with mortality. The strength of the association did not differ greatly from that in AFFIRM, although it depends on which SCAF analysis you look at. The AFFIRM reported a hazard ratio of 2.15 in the rhythm control group and 1.71 in the rate control group. 3 The SCAF hazard ratio for mortality during the first 3 months following hospitalization was 1.69, but decreased to 1.43 when taking into account deaths during 1 year and even to 1.35 when using a propensity score to correct for unmeasured differences between groups and improve comparability in this observational study. When adding medication use to the model of the final 2.5 years of the follow-up, the hazard ratios for mortality during 3 and 12 months were 2.08 and 1.63 respectively, which compared favourably with those observed in AFFIRM. All analyses of the SCAF verified the significance of the association of CV hospitalization and mortality, but also indicated the importance of the nature of the analysis to assess the strength of the association. Using hospitalization as an endpoint is not a new concept since hospitalization for heart failure has been widely used in heart failure research. Although any CV hospitalization is less of a disease-specific endpoint in AF research, its use as a mortality substitute seems justified considering that a two-fold increased risk for mortality associated with AF mainly relates to the presence of concomitant CV disease and risk factors. 8 The exact definition of CV hospitalization therefore needs some thought. The SCAF analysis showed that hospitalization primarily for AF was associated with lower mortality than hospitalization for other CV diagnoses. Considering that AF hospitalization was the main driver for CV hospitalization, with 44% of all hospitalizations, a treatment specifically targeting AF might lower the overall CV hospitalization rate without significantly affecting mortality. In the ATHENA study
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".