Integrating the 6-Minute Walk Test Into New York Heart Association Functional Classification
Bibliographic record
Abstract
The New York Heart Association (NYHA) Functional Classification System is integral to guiding management of patients with heart failure. However, reproducibility remains a challenge due to subjective assessment of patient functional capacity based on self-reported symptoms and clinical interpretations. The 6-minute walk test (6MWT), involving walking as far as possible in 6 minutes, represents a simple, objective functional assessment tool. The objective of this study was to determine the clinical utility of the 6MWT in improving reproducibility of cardiologist-assigned NYHA classification. This was a prospective observational study. After performing a 6MWT, adults with hypertrophic cardiomyopathy, heart failure, or pulmonary hypertension were reassessed for NYHA classification. Of 56 participants, 25 were classified as NYHA Class I, 21 as NYHA Class II, 9 as NYHA Class III, and 1 as NYHA Class IV at baseline. The 6MWT resulted in redistribution of 15 participants in NYHA Class I, 21 participants in NYHA Class II, 16 participants in NYHA Class III, and 4 participants in NYHA Class IV. Participants were predominantly reclassified to higher NYHA classes (25/56 (45%)) while 4/56 (7%) received a lower NYHA Class. 6-minute walk distance was negatively correlated with NYHA Class, particularly between NYHA Classes I and II which are often difficult to differentiate. Traditional cardiac risk factors (age, sex, dyslipidemia, diabetes, hypertension, and smoking) or history of invasive procedures (pacemakers, stents, valve replacements) were not associated with effect on the 6MWT. In conclusion, the 6MWT reveals more severe functional impairment than expected by relying solely on patient-reported symptoms and clinical judgment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".