Impaired health status is independently associated with persistently elevated NT-proBNP levels despite medical therapy for heart failure with reduced ejection fraction
Bibliographic record
Abstract
Abstract Background Impaired health status as measured by standardized tools such as Kansas City Cardiomyopathy Questionnaire (KCCQ), Duke Activity Status Index (DASI) and six-minute walk test (6MWT) has been shown to predict hospitalization and mortality in patients with chronic heart failure. However, prognostic implications of these measurements in response to guideline-directed medical therapy for heart failure with reduced ejection fraction (HFrEF) remained to be elucidated. Purpose We hypothesized that impaired health status were predictive of persistently elevated N-terminal pro-B-type natriuretic peptide (NT-proBNP) after 6 and 12 months of therapeutic optimization in HFrEF. Methods Data on the GUIDE-IT trial that included protocolized HFrEF drug titration were analyzed. Patients who did not have NT-proBNP at 12 months were excluded. KCCQ overall and clinical summary scores, and DASI scores at baseline and 6 months were calculated. Six-minute walk test (6MWT) distance at baseline were also available. Response to medical therapy was defined as having NT-proBNP at 12 months of less than 1,000 pg/mL. Median value of each measurement was used as a cutoff. Multivariate logistic regression analysis was used to determine independent associations between different QOL scores and NT-proBNP response after adjustment for age, comorbidities, baseline EF, NYHA functional class, and NT-proBNP. Results There were 193 (43%) responders. Compared with those who responded to the medical therapy, non-responders were older, and more likely to have comorbidities including coronary artery disease, stroke, PAD, AF, hypertension, COPD, DM, CKD, and dyslipidemia, as well as lower EF, NHYA functional class and higher baseline NT-proBNP. After adjustment for baseline characteristics, lower KCCQ (either overall or summary) scores at baseline and 6 months, and lower DASI scores at 6 months (but not baseline) were independently associated with lower likelihood of response to GDMT (Table). In contrast, baseline 6MWT distance did not predict non-response to GDMT after adjustments. Conclusions Only impaired baseline KCCQ scores were predictive of persistently elevated NT-proBNP, while lower KCCQ and DASI scores at 6 month were predictive of persistently elevated NT-proBNP. Funding Acknowledgement Type of funding sources: None. Health Status Score below Median and ORs
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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) | 0.002 | 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".