S178 A Systematic Review of the Gut Microbiota Profile in Patients With Heart Failure
Bibliographic record
Abstract
Introduction: The “gut-heart axis” could explain the role of the human gut microbiota in the pathogenesis of heart failure (HF) by activation of host inflammation induced by a state of gut dysbiosis. This systematic review characterized the gut microbiota profile in HF patients compared to healthy subjects. Methods: Peer-reviewed human studies published in Ovid MEDLINE, Ovid EMBASE, SCOPUS, and the Cochrane Library up to April 18, 2022, were searched. Studies comparing the gut microbiota profile in adult HF patients and healthy controls (HCs) were eligible for inclusion. The alpha diversity (microbial richness and diversity), beta diversity (dissimilarity in microbiota composition between two groups), and the relative abundance of gut microbiota taxa were compared in adult HF patients and HCs. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of included studies. Results: A total of nine studies, including 317 HF patients and 510 HCs, were included in this systematic review. Decreased gut microbiota richness and similar microbial diversity and significantly different gut microbiota composition were observed between HF patients and HCs. HF patients had a greater abundance of Actinobacteria, Proteobacteria, and Synergistetes phyla; Enterococcus, Escherichia, Klebsiella, Lactobacillus, Ruminococcus, Streptococcus, and Veilonella genera; and Ruminococcus gnavus, Streptococcus sp., and Veilonella sp. Species compared to HCs. Decreased abundance of Firmicutes phylum; Blautia, Eubacterium, Faecalibacterium, Lachnospiraceae FCS020, and Sutterella genera; and Dorea longicatena, Eubacterium rectale, Faecalibacterium prausnitzii, Oscillibacter sp., and Sutterella wadsworthensis species were noted in HF patients. Conclusion: The gut microbiota diversity, richness, and composition in HF patients are significantly different from HCs. Overall, short-chain fatty acids-producing gut microbiota was depleted in HF patients.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".