Implications of Perceived Dyspnea and Global Well-Being Measured by Visual Assessment Scales During Treatment for Acute Decompensated Heart Failure

An Individual Patient-Level Meta-Analysis of Ischemic Versus Nonischemic Cardiomyopathy and Trajectory of Decongestion in Patients With Acute Decompensated Heart Failure

Data are limited regarding the impact of ischemic cardiomyopathy (ICM) or non-ICM (NICM) on the trajectory of in-hospital decongestion among patients with acute decompensated heart failure (ADHF). Therefore, we aimed to assess the course of decongestion among patients admitted for ADHF by history of ICM and NICM. Patients included in the DOSE (Diuretic strategies in patients with acute decompensated heart failure), ROSE (ROSE acute heart failure randomized trial), and Ultrafiltration in decompensated heart failure with cardiorenal syndrome (CARRESS-HF) trials of patients with ADHF were categorized into ICM and NICM based on history. Among 762 patients included in our meta-analysis, 433 (56.8%) had a history of ICM. Patients with ICM were older (70.8 vs 63.9 years; p ≤0.001) and had higher rates of co-morbidities. After covariate adjustment, there was no significant differences between NICM and ICM regarding net fluid loss (4,952 vs 4,384 ml, p = 0.81) or mean change in serum N-terminal pro-brain natriuretic peptide (-2,162 vs -1,809 pg/ml, p = 0.092). Mean change in weight showed modest improvement in favor of patients with NICM, but this did not meet statistical significance (-8.24 vs -7.70 pounds, p = 0.068). After adjustment, there was no significant difference in the risk of 60-day composite all-cause mortality or hospitalization for HF among those with ICM versus NICM. Among patients with left ventricular ejection fraction <40%, NICM was associated with higher scoring on global sense of well-being (global visual analog scale; +25.5 vs +19.1, p = 0.023) and improvement in serum creatinine (-0.031 mg/100 ml vs +0.042 mg/100 ml, p = 0.009) at 72 hours. Among patients with left ventricular ejection fraction >40%, NICM was associated with decreased scoring on global visual analog scale at 72 hours (+15.7 vs +21.2, p = 0.049). In conclusion, more than half of the patients admitted for ADHF had ICM. History of ICM was not independently associated with a difference in course of decongestion, self-assessment of well-being and dyspnea, or short-term clinical outcomes.

Lack of correlation between different congestion markers in acute decompensated heart failure

BACKGROUND

Hospitalizations for acute decompensated heart failure (ADHF) are commonly associated with congestion-related signs and symptoms. Objective and quantitative markers of congestion have been identified, but there is limited knowledge regarding the correlation between these markers.

METHODS

Patients hospitalized for ADHF irrespective of left ventricular ejection fraction were included in a prospective registry. Assessment of congestion markers (e.g., NT-proBNP, maximum inferior vena cava diameter, dyspnea using visual analogue scale, and a clinical congestion score) was performed systematically on admission and at discharge. Telephone interviews were performed to assess clinical events, i.e., all-cause death or readmission for cardiovascular cause, after discharge. Missing values were handled by multiple imputation.

RESULTS

In total, 130 patients were prospectively enrolled. Median length of hospitalization was 9 days (interquartile range 6 to 16). All congestion markers declined from admission to discharge (p < 0.001). No correlation between the congestion markers could be identified, neither on admission nor at discharge. The composite endpoint of all-cause death or readmission for cardiovascular cause occurred in 46.2% of patients. Only NT-proBNP at discharge was predictive for this outcome (hazard ratio 1.48, 95% confidence interval 1.15 to 1.90, p = 0.002).

CONCLUSION

No correlation between quantitative congestion markers was observed. Only NT-proBNP at discharge was significantly associated with the composite endpoint of all-cause death or readmission for cardiovascular cause. Findings indicate that the studied congestion markers reflect different aspects of congestion.

Estimating Respiratory Rate From Breath Audio Obtained Through Wearable Microphones

Respiratory rate (RR) is a clinical metric used to assess overall health and physical fitness. An individual's RR can change from their baseline due to chronic illness symptoms (e.g., asthma, congestive heart failure), acute illness (e.g., breathlessness due to infection), and over the course of the day due to physical exhaustion during heightened exertion. Remote estimation of RR can offer a cost-effective method to track disease progression and cardio-respiratory fitness over time. This work investigates a model-driven approach to estimate RR from short audio segments obtained after physical exertion in healthy adults. Data was collected from 21 individuals using microphone-enabled, near-field headphones before, during, and after strenuous exercise. RR was manually annotated by counting perceived inhalations and exhalations. A multi-task Long-Short Term Memory (LSTM) network with convolutional layers was implemented to process mel-filterbank energies, estimate RR in varying background noise conditions, and predict heavy breathing, indicated by an RR of more than 25 breaths per minute. The multi-task model performs both classification and regression tasks and leverages a mixture of loss functions. It was observed that RR can be estimated with a concordance correlation coefficient (CCC) of 0.76 and a mean squared error (MSE) of 0.2, demonstrating that audio can be a viable signal for approximating RR.Clinical relevance-The subject technology facilitates the use of accessible, aesthetically acceptable wearable headphones to provide a technologically efficient and cost-effective method to estimate respiratory rate and track cardio-respiratory fitness over time.