Diastolic dysfunction: assessment and implications on the single ventricle circulation
Bibliographic record
Abstract
PURPOSE OF REVIEW: Patients with a functionally single ventricle (SV) are palliated with a series of procedures leading to a Fontan circulation. Over the life span, a substantial proportion of SV patients develop heart failure that can arise from circulatory or ventricular failure. Diastolic dysfunction (DD) is an important determinant of adverse outcomes in SV patients. However, assessment and categorization of DD in the SV remains elusive. We review recent literature and developments in assessment of DD in the SV and its relation to clinical outcomes. RECENT FINDINGS: DD is prevalent in the SV and associated with worse outcomes. Occult DD can be exposed with provocative testing by exercise or preload challenge during catheterization. Likewise, sensitivity to detect DD may be increased via assessment of atrial function and strain imaging. Recent studies revisiting previous concepts such as incoordinate diastolic wall motion show that these are associated with SV end-diastolic pressures and post-Fontan recovery, yielding accessible DD assessment. Emerging technologies such as ultrafast ultrasound (UFUS) can provide noninvasive assessment of myocardial stiffness, inefficient diastolic flow patterns and intraventricular pressure gradients, thereby yielding new tools and insights into diastolic myocardial and hemodynamic properties. SUMMARY: Characterizing DD in the SV continues to have substantial limitations, necessitating synthesis of multiple parameters into an overall assessment, accounting for their change over time, and in the context of the patient's clinical status. New and emerging techniques may help advance DD assessment and the ability to track response to treatment of new targets.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".