Inflammatory cardiomyopathies: short- and long-term outcomes after heart transplantation—a protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Heart transplantation (HTx) for patients with "giant cell myocarditis" (GCM) or "cardiac sarcoidosis" (CS) is still controversial. However, no single center has accumulated enough experience to investigate post-HTx outcome. The primary aim of this systematic review is to identify, appraise, and synthesize existing literature investigating whether patients who have undergone HTx because of GCM or CS have worse outcomes as compared with patients transplanted because of other etiologies. A systematic and comprehensive search will be performed using PubMed, Scopus, Web of Science, EMBASE, and Google Scholar, for studies published up to December 2019. Observational and interventional population-based studies will be eligible for inclusion. The quality of observational studies will be assessed using the Newcastle-Ottawa scale, while the interventional studies will be assessed using the Cochrane Effective Practice Organization of Care tool. The collected evidence will be narratively synthesized; in addition, we will perform a meta-analysis to pool estimates from studies considered to be homogenous. Reporting of the systematic review and meta-analysis will be in accordance with the Meta-analysis of Observational Studies in Epidemiology Preferred Reporting Items for Systematic reviews and Meta-Analysis guidelines. To our knowledge, this will be the first synthesis of outcomes, including survival, acute cellular rejection, and disease recurrence, in patients with either GCM or CS treated with HTx. Reviewing the suitability of HTx in this population and highlighting areas for further research will benefit both patients and healthcare providers. Trial registration: CRD42019140574.
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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 | 0.064 | 0.088 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.021 | 0.038 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.036 | 0.004 |
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".