Pericardial fluid troponin in cardiac surgery
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Pericardial Fluid (PF) is a rich reservoir of biologically active factors. Due to its proximity to the heart, the biochemical structure of PF may reflect the pathological changes in the cardiac interstitial environment. This manuscript aimed to determine whether the PF level of cardiac troponins changes in patients undergoing cardiac surgery. METHODS: This scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Medline, EMBASE, Cochrane, ClinicalTrials.gov, and Google Scholar databases were electronically searched for primary studies using the keywords "pericardial fluid," "troponin," and "cardiac surgery." The primary outcome of interest was changes in troponin levels within the PF preoperatively and postoperatively. Secondary outcomes of interest included comparisons between troponin level changes in the PF compared to plasma. RESULTS: A total of 2901 manuscripts were screened through a title and abstract stage by two independent blinded reviewers. Of those, 2894 studies were excluded, and the remaining seven studies underwent a full-text review. Studies were excluded if they did not provide data or failed to meet inclusion criteria. Ultimately, six articles were included that discussed cardiac troponin levels within the PF in patients who had undergone cardiac surgery. Pericardial troponin concentration increased over time after surgery, and levels were significantly higher in PF compared to serum. All studies found that the type of operation did not affect these overall observations. CONCLUSION: Our review of the literature suggest that the PF level of cardiac troponins increases in patients undergoing cardiac surgery, irrespective of the procedure type. However, these changes' exact pattern and clinical significance remain undefined.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".