A Systematic Review of the Prognostic Value of Cardiopulmonary Exercise Testing in Patients with Ischemic and Nonischemic Cardiomyopathy
Bibliographic record
Abstract
Background The prognostic utility of cardiopulmonary exercise testing (CPET) in heart failure (HF) is well established; however, whether optimal CPET parameter thresholds differ across HF etiologies remains unclear. This systematic review aimed to determine how CPET-derived parameters and their prognostic threshold values differ and associate with adverse outcomes in patients with ischemic and non-ischemic cardiomyopathy. Methods Eligible studies assessed adult HF patients and reported outcomes of all-cause mortality, left ventricular assist device implantation, heart transplantation, or hospitalization. CPET parameters and associated threshold values were extracted, and risk of bias was assessed using the Joanna Briggs Institute checklist for cohort studies. Results Four studies comprising 491 ischemic and 218 non-ischemic HF patients were included. Peak oxygen consumption (p V ˙ O 2 ) was the only CPET parameter unanimously reported. In ischemic HF, the optimal p V ˙ O 2 thresholds in ml/kg/min were ≤ 14.10 (HR 3.3; CI:1.9–5.8), ≤ 10.0 (HR 0.76; CI:0.59–0.98), ≤ 15.20, and ≤ 14.0 (used in one study as a guideline comparator), yielding a mean threshold of ≤ 13.33 (± 2.28) ml/kg/min. In non-ischemic HF, optimal thresholds in ml/kg/min were ≤ 14.60 (HR 4.30 [2.10–8.90]) and ≤ 14.0, yielding a mean of ≤ 14.30 (± 0.42) ml/kg/min. Conclusions There was significant heterogeneity in study design, patient populations, and CPET Variables assessed. The few consistently assessed prognostic thresholds were similar across HF etiologies. Peak oxygen consumption (p V ˙ O 2 ) remains a robust prognostic marker in both ischemic and non-ischemic cardiomyopathy. While patients with ischemic cardiomyopathy generally have worse clinical profiles, this review suggests that there are no meaningful differences in a few key CPET prognostic thresholds, namely p V ˙ O 2 across etiologies. These findings support continued use of established guideline-recommended thresholds for risk stratification, irrespective of HF subtype, but require further confirmation.
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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 | 0.009 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".