Repeatability and Correlation of Coronary Physiology Indices Measured With Bolus and Continuous Thermodilution
Bibliographic record
Abstract
BACKGROUND: Previous studies have shown weak agreement between coronary physiology indices derived from continuous and bolus thermodilution, and suggested greater variability with bolus thermodilution measurements. This study aimed to evaluate the repeatability and correlation of continuous and bolus thermodilution–derived physiology indices in cardiac transplant recipients. METHODS: Paired fractional flow reserve (FFR), coronary flow reserve (CFR), index of microcirculatory resistance (IMR), absolute hyperemic resistance (R Hyp ), and microvascular resistance reserve (MRR) using continuous and bolus thermodilution were performed in consecutive cardiac transplant recipients. RESULTS: In 20 patients, IMR was more repeatable than CFR and MRR derived from either continuous thermodilution (intraclass correlation coefficient, 0.95 versus 0.70 and 0.59; P =0.004 and P =0.002, respectively) or bolus thermodilution (intraclass correlation coefficient, 0.95 versus 0.20 and 0.33; P <0.001 and P =0.002, respectively), and similarly repeatable compared with R Hyp (intraclass correlation coefficient, 0.95 versus 0.87; P =0.188). FFR by continuous thermodilution correlated with standard FFR measurements ( R =0.89, P <0.001) but were significantly lower in value (0.87±0.05 versus 0.89±0.05; P =0.004). CFR and MRR measurements using continuous thermodilution did not correlate with measurements using bolus thermodilution ( R =0.33, P =0.170; R =0.34, P =0.155, respectively) and were significantly lower in value (2.9±1.0 versus 3.7±0.8, P =0.003; 3.4±1.1 versus 4.8±1.3, P <0.001, respectively). IMR and R Hyp did not correlate ( R =0.28, P =0.226). CONCLUSIONS: In cardiac transplant recipients, IMR had superior repeatability compared with CFR and MRR derived from either bolus or continuous thermodilution, and was equally repeatable compared with R Hyp . FFR, CFR, and MRR values obtained from continuous thermodilution were systematically lower compared with their counterparts obtained from bolus thermodilution.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".