Abstract 16803: Relationships Between Invasive and Non-invasive Measures of Cardiac Function During Exercise in Heart Failure With Preserved or Reduced Ejection Fraction
Bibliographic record
Abstract
Introduction: Assessment of cardiac function during exercise is critical in the clinical evaluation of patients with heart failure with preserved (HFpEF) or reduced (HFrEF) ejection fraction. Direct invasive measurement of cardiac power (CP) and stroke work (SW) are robust measures of cardiac function. Non-invasive gas exchange based surrogates may provide practical means of assessing cardiac function in clinical and research settings; however, the relationship between invasive and non-invasive measurement of CP or SW during exercise is unclear in HFpEF and HFrEF. We aimed to assess relationships between invasive and non-invasive measures of CP and SW during exercise in HFpEF and HFrEF. Methods: HFpEF (n=47) and HFrEF (n=29) (age 71±10 vs 55±10 yrs; EF% 62±8 vs 21±6%; BSA 2.1±0.3 vs 2.1±0.2 m 2 ; weight 99±22 vs 87±15 kg; peak work 36±14 vs 37±13 watts (W), respectively; all p<0.05, except peak work) underwent peak exercise testing during right heart catheterization. Invasive measurement of cardiac pressures, hemodynamics, and arterial pressures were recorded at rest, 20 W, and peak work. Continuous measurement of HR and VO 2 occurred from rest to peak work via 12-lead ECG and metabolic measurement system, respectively. Invasive measurements were calculated as, CP=(MAP–RAP) x Q x 2.22х10 -3 ; SW=(MAP–PCWP) x SV I x 0.133; and non-invasive as, CP=VO 2 x MAP; SW=VO 2 /HR x MAP. All indices adjusted for body surface area. Results: At rest, there were moderate relationships between invasive and non-invasive measures of CP and SW in HFpEF (r=0.56 and 0.48) and HFrEF (0.57 and 0.73), respectively (all p<0.05). At 20 W, relationships between invasive and non-invasive measures of CP and SW strengthened in HFpEF (r=0.74 and 0.69) and HFrEF (0.74 and 0.72), respectively (all p<0.05). The relationships noted between invasive and non-invasive measures of CP and SW at 20 W persisted at peak work in HFpEF (r=0.74 and 0.67) and HFrEF (0.78 and 0.69), respectively (all p<0.05). Conclusion: These data suggest that non-invasive estimates of CP and SW correlate closely with invasive measures and may be reasonable surrogates for these indices during peak exercise testing in both HFpEF and HFrEF patients.
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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 | 0.002 |
| 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) | 0.005 | 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".