Abstract 13835: Anti-inflammatory Effect of Rosuvastatin in Patients With HIV Infection: A Randomized Controlled FDG-PET Study
Bibliographic record
Abstract
Introduction: Cardiovascular disease (CVD) is a major source of morbidity and mortality in HIV+ patients, which is thought to be in part due to a state of persistent systemic inflammation that results in accelerated atherosclerosis. Hypothesis: We hypothesized that inflammation, as measured by 18F-fluorodeoxyglucose (18F-FDG) uptake measured by 18F-FDG positron emission tomography/computed tomography (18F-FDG-PET/CT) in the bone marrow, spleen and thoracic aorta would improve in HIV+ patients following therapy with rosuvastatin compared to HIV+ patients not receiving a statin. Methods: HIV+ patients with a moderate Framingham risk score were enrolled in the study and randomized to treatment with rosuvastatin or usual treatment for 6 months. Patients were matched for age, sex, smoking status, Framingham risk score, duration of anti-retroviral therapy (ART) and type of ART. Fasting blood was collected and 18F-FDG-PET/CT imaging of bone marrow, spleen, and thoracic aorta was performed at baseline and 6 months. Results: Thirty-five HIV+ patients were enrolled in the study; 17 were randomized to treatment with rosuvastatin and 18 were randomized to the control group. There was a significant drop in the 18F-FDG bone marrow, spleen and thoracic aortic uptake in the statin-treated group compared to the control group (bone marrow: -10.3±16.9% versus 5.0±18.9%, p=0.0262; spleen: -9.8±20.3% versus 11.3±28.8%, p=0.0497; thoracic aorta: -8.6±24.5% versus 12.6±29.5%, p=0.0343). 18F-FDG changes over the study period are shown in Figure 1. Conclusions: The present study observed a significant decrease in 18F-FDG-PET uptake in the bone marrow, spleen, and thoracic aorta following treatment with rosuvastatin for 6 months in HIV+ patients. These data suggest a wide-range anti-inflammatory effect of rosuvastatin in HIV+ individuals with well-controlled infection on ART, ultimately resulting in decreased inflammatory activity in the arterial walls of these patients.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".