Vocal biomarkers explain quality of life trajectories in patients with heart failure: Findings from the AHF-Voice Study

Introduction: Heart failure (HF) is a common reason for recurrent hospitalization. Daily smartphone-based recording of vocal biomarkers appears promising to remotely monitor patient well-being. The connection of self-reported quality of life and vocal biomarkers in patients with HF is unknown.

 

Methods: AHF-Voice is an ongoing monocentric prospective cohort study, focusing on voice alterations in patients hospitalized with acutely decompensated HF. Exclusion criteria are: listed for heart transplantation, high output HF, history of vocal fold disease/surgery, life-expectancy <6 months. Quality of life is assessed by the 23-item Kansas City Cardiomyopathy Questionnaire Overall Summary Score (KCCQ-OSS). Voice recordings (sustained vowels) are sampled iteratively using a specially developed smartphone app. The current analysis focuses on recordings collected at hospital admission and after 6 weeks of follow-up. Feature extraction of voice recordings were performed using python. Vocal biomarkers associated with changes in quality of life were identified using correlation and regression analysis.

 

Results: In this analysis, 72 patients hospitalized with acute HF were included (n=4 withdrew consent; n=6 excluded due to missing data). Hence, 62 patients were analyzed: mean age 76±10 years, 68% men, 81% in NYHA class III/IV, 47% de novo HF, mean LVEF 48±17%, 44% ischemic cause. Between admission and 6 weeks of follow-up, median KCCQ-OSS improved markedly, i.e. by +25 (4; 41) score points. Selected vocal biomarkers also changed materially (Table) and explained to a large degree the observed change in KCCQ over time: the vocal biomarker panel collected during admission explained 33%, whereas the vocal biomarker panel covering changes over time explained 39%, respectively. Overall, the vocal biomarkers explained 61% of the variance observed for change in KCCQ-OSS (Table).

 

Conclusion: In patients with acute HF, vocal biomarkers substantively explain the variation in quality of life. Tracking vocal biomarkers seems to be a promising low-barrier tool to non-invasively assess patient well-being and holds potential to effectively support heart failure management.

Table: Predictive utility of vocal biomarkers to explain changes in KCCQ-OSS.

	At hospital admission n=62	6-week follow-up n=62	Univariable R2 (%) for changes in KCCQ
			Admission	Δ admission to 6 weeks
F1 mean, × 10²	6.8 (5.9, 7.7)	6.8 (6.0, 7.6)	6.5	12.1
F2 mean, × 10²	12.8 (11.2, 15.5)	12.1 (10.9, 14.1)	2.4	3.4
MFCC 2 median	5 (29)	1 (32)	3.2	3.5
MFCC 13 median	-1 (12)	-2 (14)	1.2	6.4
MFCC 13 mean	-1 (12)	-2 (13)	1.4	7.0
ΔMFCC 11 mean, × 103	-7 (-22, 9)	3 (-14, 20)	4.9	6.0
ΔMFCC 15 mean, × 10²	10 (3)	0 (3)	7.0	9.3
ΔMFCC 22 mean, ×103	5 (-18, 18)	2 (-11, 17)	4.9	6.0
ΔΔ MFCC 3 mean, × 103	-23 (-47, 16)	1 (-29, 46)	8.0	11.3
Zero-crossing median, × 10²	11.8 (8.3, 15.8)	13.6 (10.9, 16.6)	1.2	10.2
Zero-crossing mean, × 10²	11.9 (8.7, 15.9)	13.7 (10.8, 16.9)	0.8	3.3
F2 bandwidth mean, × 10²	10.2 (1.7)	9.8 (1.5)	10.7	14.3
Δ T0 mean, × 107	1 (-4, 8)	1 (-4, 4)	4.4	3.3
			33	39
			61

 

KCCQ-OSS was measured and vocal biomarkers were extracted both during hospitalization and after 6 weeks of follow-up. Data are mean (SD) or median (quartiles).
R² = explained variance of vocal biomarker(s) for 6-week change in KCCQ-OSS, using either admission values, or 6-week changes, or the overall information. MFCC = Mel Frequency Cepstral Coefficients; KCCQ-OSS = Kansas City Cardiomyopathy Questionnaire Overall Summary Score.