The Utility of Dobutamine Stress Echocardiography for the Diagnosis of Coronary Artery Disease in the HIV Population
Bibliographic record
Abstract
BACKGROUND: The introduction of highly active antiretroviral therapy (HAART) has increased human immunodeficiency virus (HIV) patient longevity by 10-15 years. This increased longevity has habituated new cardiovascular complications, in particular, accelerated coronary artery disease (CAD). Although dobutamine stress echocardiography (DSE) is a highly sensitive and specific test for the noninvasive detection of underlying CAD in the general population, its utility in the HIV population remains unknown. OBJECTIVE: The objective of the current study was to assess the validity of DSE for the noninvasive detection of underlying symptomatic CAD in the HIV population using cardiac catheterization as the gold standard. METHODS AND RESULTS: A total of 40 HIV positive patients (mean 49 ± 8 years; 31 males) between 2006 and 2009 inclusively underwent routine DSE and coronary angiography. A positive stress echo with new wall motion abnormalities was detected in 9 (23%) individuals. Coronary angiography, following DSE, detected obstructive CAD in 12 (30%) individuals. For the diagnosis of obstructive CAD, DSE has a sensitivity of 67%, specificity of 97%, positive predictive value (PPV) of 89%, and negative predictive value (NPV) of 87%. CONCLUSION: In this select HIV population, DSE was highly specific for the noninvasive detection of obstructive CAD.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".