Biomaterials for direct cardiac repair—A rapid scoping review 2012–2022
Bibliographic record
Abstract
A plethora of biomaterials for heart repair are being tested worldwide for potential clinical application. These therapeutics aim to enhance the quality of life of patients with heart disease using various methods to improve cardiac function. Despite the myriad of therapeutics tested, only a minority of these studied biomaterials have entered clinical trials. This rapid scoping review aims to analyze literature available from 2012 to 2022 with a focus on clinical trials using biomaterials for direct cardiac repair, i.e., where the intended function of the biomaterial is to enhance the repair of the endocardium, myocardium, epicardium or pericardium. This review included neither biomaterials related to stents and valve repair nor biomaterials serving as vehicles for the delivery of drugs. Surprisingly, the literature search revealed that only 8 different biomaterials mentioned in 23 different studies out of 7038 documents (journal articles, conference abstracts or clinical trial entries) have been tested in clinical trials since 2012. All of these, intended to treat various forms of ischaemic heart disease (heart failure, myocardial infarction), were of natural origin and most used direct injections as their delivery method. This review thus reveals notable gaps between groups of biomaterials tested pre-clinically and clinically. STATEMENT OF SIGNIFICANCE: Rapid scoping review of clinical application of biomaterials for cardiac repair. 7038 documents screened; 23 studies mention 8 different biomaterials only. Biomaterials for repair of endocardium, myocardium, epicardium or pericardium. Only 8 different biomaterials entered clinical trials in the past 10 years. All of the clinically translated biomaterials were of natural origin.
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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".