Non Invasive Cardiac Output Evaluation with CO2 Rebreathing Method for CRT Patients
Bibliographic record
Abstract
Background: Cardiac resynchronization therapy with ICD (CRT-D) or pacemaker (CRT-P) is useful to reverse the deleterious effects of ventricular dyssynchronia in heart failure (HF) patients. To determinate the responders patients, hemodynamic parameters are difficult to evaluate during follow-up, due to the invasivity of the procedures. We compare hemodynamic response to CRT with cardiac output, not invasively detected (CO2 rebreathing method, Innocor system), with conventional clinical, functional and echocardiographic parameters. Methods: We enrolled 29 patients affected by end-stage dilated cardiomyopathy treated with CRT-P/CRT-D according to the latest guidelines (NYHA class II-IV, left ventricular ejection fraction [LVEF] ≤ 35%, QRS ≥ 120 ms, sinus rhythm, optimal medical therapy). Patients were evaluated before and after CRT (3 months), considering: NYHA class, Quality of Life score (Minnesota Living with Heart Failure questionnaire), QRS width, echocardiographic parameters (diastolic and systolic left ventricular volumes and related LVEF), six minutes walking test (6MWT) and cardiac output (detected with Innocor system). Results: Our data showed a significant improvement in Innocor cardiac output 3 months after CRT implant compared to baseline (4.01±0.72 vs 4.48±0.59 l/min, p=0.001). The percentage improvement in cardiac output correlates with the percentage increase in LVEF (25±6% vs 30±7%; r=0.541). The correlation is not statistically significant with NYHA class (from 2.52±0.73 to 1.78±0.60; r=0.098), QoL (from 22.57±15.37 to 9.91±9.14 score; r=0.231) and exercise tolerance (from 390±50 to 437±54 meters; r=0.144). Conclusions: The Innocor system is a promising non-invasive method to assess the cardiac output at baseline and during follow up in HF patients treated with CRT.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".