Markers of Inflammation in Recipients of Continuous-Flow Left Ventricular Assist Devices
Bibliographic record
Abstract
Although the newer continuous-flow left ventricular assist devices (CF-LVADs) provide clinical advantages over the pulsatile pumps, the effects of low pulsatility on inflammation are incompletely understood. The objective of our study was to examine the levels of inflammatory mediators in CF-LVAD recipients compared with both healthy control subjects and heart failure patients who were candidates for CF-LVAD support. Plasma levels of chemokines, cytokines, and inflammatory markers were measured in 18 CF-LVAD recipients and compared with those of 14 healthy control subjects and 14 heart failure patients who were candidates for CF-LVADs. The levels of granulocyte macrophage-colony stimulating factor, macrophage inflammatory proteins-1β, and macrophage-derived chemokine were significantly higher in the CF-LVAD group compared with both the heart failure and the healthy control groups, whereas no significant differences were observed between the healthy control subjects and the heart failure groups. Compared with the healthy controls, C-reactive protein, interferon gamma-induced protein-10, monocyte chemotactic protein-1, and interleukin-8 levels were significantly higher in both the CF-LVAD and heart failure groups, but no significant differences were observed between the CF-LVAD recipients and the heart failure patients. Inflammatory markers were elevated in CF-LVAD recipients compared with healthy control subjects and the heart failure patients. Further studies should investigate the clinical implications of elevated levels of inflammation in CF-LVAD recipients.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".