Myocardial fibrosis and inflammation are predictors of heart failure outcomes in people living with HIV
Bibliographic record
Abstract
Abstract Background People living with HIV (PLWH) have higher prevalence of heart failure (HF), which cannot be fully related to traditional cardiovascular disease (CVD) risk factor< or coronary artery disease. Tissue characterisation by cardiac magnetic resonance (CMR), such as with T1 and T2 mapping, is a unique diagnostic approach to provide non-invasive insights into the underlying myocardial pathophysiology. Purpose To examine prognostic associations of CMR measures, conventional and modified CVD risk scores with HF outcome in PLWH on long-term highly active antiretroviral therapy (HAART). Methods Consecutive PLWH underwent prospectively standardized evaluation of HF using CMR, risk scores and blood markers. CMR protocol included T1 and T2 mapping, perfusion and scar imaging. MAGGIC, Framingham and D:A:D risk scores were collected. Primary HF endpoint was defined as hospitalization or mortality due to HF, and time-to-even analysis from the index CMR to the first event per patient was performed. Results 141 PLWH (61% males, 48.0 [40.1–54.6] years, CD4 count 655 [411–909] cells/μl) were included. 16 HF events were observed (12 hospitalizations and 4 deaths) during a median follow-up of 13 [9–16] months. Baseline myocardial native T1, T2, left ventricular volumes and troponin were significant univariate predictors of the HF endpoint. The only signifcant (p<0.001) independent predictor in the multivariate analysis was myocardial native T1 (T1 ≥4 SD, HR (95% CI): 5.0 [1.8–13.4]). Conventional and modified CVD risk scores showed no prognostic association with HF outcomes. Conclusions Our results show that presence and severity of myocardial inflammation and predominantly diffuse fibrosis detected by T2 and T1 mapping strongly relates to HF events in contrast to conventional and traditional CVD risk scores. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): The German Centre for Cardiovascular Research (DZHK)
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".