Cardiac index in adults with repaired tetralogy of Fallot: Are we missing the forest for the trees?
Bibliographic record
Abstract
Many cardiac parameters have been associated with poor outcomes in patients with repaired tetralogy of Fallot (TOF) and significant residual pulmonary regurgitation (PR). However, the utility of cardiac index (CI) in these patients has never been studied. Our study aimed to assess if a low CI is associated with the development of adverse cardiac events in this population and compare it to other established cardiac parameters. All patients with repaired TOF and significant PR who had a cardiac magnetic resonance imaging (CMR) at our institution were enrolled. CI was measured by CMR and their charts were reviewed for the development of the following outcomes: worsening NYHA class, admission for heart failure, arrhythmias, and sudden cardiac death. Fifty-five patients were included in the study. Median age was 28 years and mean follow-up was 9.5 years. Eighteen patients (32.7%) developed one or more of the predefined outcomes. Their CI was significantly lower compared to patients without adverse events (CI 2.3 vs. 2.8 L/min/m2; p-value = 0.0045). CI alone had a better yield in predicting adverse events when compared to the other combined CMR parameters (AUC 0.78 vs 0.61). Patients with a CI < 2.4 had a 74.3% cumulative probability of developing adverse cardiac events at 10 years compared to 22.4% in patients with a CI ≥ 2.4 (p-value<0.0001). In adults with repaired TOF and significant residual PR, CI appears to be the best predictor of midterm adverse cardiac events. Whether it can be used for timing of pulmonary valve replacement remains to be studied.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".