The prevalence, determinants, natural history and impact of atrial fibrillation and atrial flutter in patients with tuberculosis pericarditis - insights from the IMPI trial
Bibliographic record
Abstract
Tuberculosis is the most common cause of pericarditis in Africa. The dual human immunodeficiency virus (HIV)-tuberculosis epidemics are major contributors to the burden of extra-pulmonary tuberculosis, including tuberculous pericarditis. Mortality rates remain unacceptably high. Atrial fibrillation (AF) is the most common sustained arrhythmia encountered in clinical practice. It is associated with increased cardiovascular mortality and morbidity, as well as complications related to thromboembolic disease and haemodynamic instability. Similarly, atrial flutter (AFL) is a common macro-reentry arrhythmia, often associated with AF and its complications. While there is a recognized association between atrial fibrillation and / or atrial flutter (AF/AFL) and tuberculous pericarditis, there are limited data regarding the prevalence, determinants, natural history, and outcomes of AF/AFL in tuberculous pericarditis. Hypothesis: In patients with tuberculous pericarditis, AF/AFL is common, and when compared to tuberculous pericarditis patients that are in sinus rhythm, is associated with increased morbidity and mortality. Aims In participants with tuberculous pericarditis enrolled into the Investigation of the Management of Pericarditis (IMPI) trial, we intend to: 1. Estimate the prevalence of AF/AFL 2. Describe the natural history of AF/AFL 3. Identify clinical, biochemical and, echocardiographic predictors of AF/AFL 4. Determine the clinical impact of AF/AFL.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".