B-type peptides to predict post–liver transplant mortality: systematic review and meta-analysis
Bibliographic record
Abstract
Background: Cirrhotic patients undergoing liver transplantation are at risk of cardiac complications. Brain natriuretic peptide (BNP) and amino terminal brain natriuretic peptide (NT-BNP) are used in cardiac risk stratification. Their significance in predicting mortality risk in cirrhotic patients during or after liver transplantation is unknown. We conducted a systematic review and meta-analysis to answer this question. Methods: An electronic search of EMBASE, MEDLINE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews (2005-September 2016), Google Scholar, and study bibliographies was conducted. Study quality was determined, and demographic and outcome data were gathered. Random effects meta-analyses of mortality-based BNP and NT-BNP level or presence of post-transplant heart failure were conducted. Results: Seven studies including 2,010 patients were identified. Demographics were similar between patients with high or low BNP or NT-BNP levels. Hepatitis C was the most prevalent etiology of cirrhosis (38%). Meta-analysis revealed a pooled relative risk of 3.1 (95% CI 1.9% to 5.0%) for post-transplant mortality based on elevated BNP or NT-BNP level. Meta-analysis also revealed a pooled relative risk of 1.6 (95% CI 1.3% to 2.1%) for post-transplant mortality if patients had demonstrated post-transplant heart failure. Conclusions: Our analysis suggests that BNP or NT-BNP measurement may help in risk stratification and provides data on post-operative mortality in cirrhotic patients undergoing liver transplantation. Discriminatory thresholds are higher in cirrhotic patients relative to prior studies with non-cirrhotic patients. However, the number of analyzed studies is limited, and our findings should be validated further through larger, prospective studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".