Comparison of New York Heart Association Class and Patient-Reported Outcomes for Heart Failure With Reduced Ejection Fraction
Bibliographic record
Abstract
Importance: It is unclear how New York Heart Association (NYHA) functional class compares with patient-reported outcomes among patients with heart failure (HF) in contemporary US clinical practice. Objective: To characterize longitudinal changes and concordance between NYHA class and the Kansas City Cardiomyopathy Questionnaire Overall Summary Score (KCCQ-OS), and their associations with clinical outcomes. Design, Setting, and Participants: This cohort study included 2872 US outpatients with chronic HF with reduced ejection fraction across 145 practices enrolled in the CHAMP-HF registry between December 2015 and October 2017. All patients had complete NYHA class and KCCQ-OS data at baseline and 12 months. Longitudinal changes and correlations between the 2 measure were examined. Multivariable models landmarked at 12 months evaluated associations between improvement in NYHA and KCCQ-OS from baseline to 12 months with clinical outcomes occurring from months 12 through 24. Statistical analyses were performed from March to August 2020. Exposure: Change in health status, as defined by 12-month change in NYHA class or KCCQ-OS. Main Outcomes and Measures: All-cause mortality, HF hospitalization, and mortality or HF hospitalization. Results: In total, 2872 patients were included in this analysis (median [interquartile range] age, 68 [59-75] years; 872 [30.4%] were women; and 2156 [75.1%] were of White race). At baseline, 312 patients (10.9%) were NYHA class I, 1710 patients (59.5%) were class II, 804 patients (28.0%) were class III, and 46 patients (1.6%) were class IV. For KCCQ-OS, 1131 patients (39.4%) scored 75 to 100 (best health status), 967 patients (33.7%) scored 50 to 74, 612 patients (21.3%) scored 25 to 49, and 162 patients (5.6%) scored 0 to 24 (worst health status). At 12 months, 1002 patients (34.9%) had a change in NYHA class (599 [20.9%] with improvement; 403 [14.0%] with worsening) and 2158 patients (75.1%) had a change of 5 or more points in KCCQ-OS (1388 [48.3%] with improvement; 770 [26.8%] with worsening). The most common trajectory for NYHA class was no change (1870 [65.1%]), and the most common trajectory for KCCQ-OS was an improvement of at least 10 points (1047 [36.5%]). After adjustment, improvement in NYHA class was not associated with subsequent clinical outcomes, whereas an improvement of 5 or more points in KCCQ-OS was independently associated with decreased mortality (hazard ratio, 0.59; 95% CI, 0.44-0.80; P < .001) and mortality or HF hospitalization (hazard ratio, 0.73; 95% CI, 0.59-0.89; P = .002). Conclusions and Relevance: Findings of this cohort study suggest that, in contemporary US clinical practice, compared with NYHA class, KCCQ-OS is more sensitive to clinically meaningful changes in health status over time. Changes in KCCQ-OS may have more prognostic value than changes in NYHA class.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".