Exercise stress cardiac magnetic resonance imaging in the assessment of induced cardiovascular responses in cardiac patients: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: This scoping review will describe cardiac magnetic resonance imaging testing protocols used in combination with exercise (Ex-CMR) to assess cardiovascular responses. The review will document the advantages and limitations of these protocols in cardiac patients. INTRODUCTION: Ex-CMR characterizes the heart, differentiating between normal and pathological cardiac remodeling with considerable accuracy. However, there is no review detailing existing Ex-CMR protocols. This is particularly important since not all Ex-CMR protocols seem to induce enough stress to effectively characterize cardiac remodeling, hence the need for a review to report on the current evidence. INCLUSION CRITERIA: This review will consider studies that use Ex-CMR testing protocols to assess cardiovascular responses, revealing cardiac remodeling in patients whose age at the time of the study was ≥ 18 years. METHODS: The review will be conducted in accordance with the JBI methodology for scoping reviews and reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The following databases will be searched: PubMed, Embase, ISI Web of Science, OpenGrey, Grey Matters, and OAlster. Articles in English and French will be included and there will be no limitation set for the date of publication. Data will be extracted from papers included in the scoping review by 2 independent reviewers and will be classified in summary tables. REVIEW REGISTRATION: Open Science Framework https://osf.io/hvn75/?view_only=f6cf8fc2112e498d89c39639dbce70d1 .
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 | 0.094 | 0.111 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.014 |
| Bibliometrics | 0.019 | 0.013 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.073 | 0.017 |
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".