Integrative review of electrocardiographic characteristics in patients with reduced, mildly reduced, and preserved heart failure

Native QRS duration and outcomes in heart failure with mildly reduced ejection fraction: results from a large-scaled registry

OBJECTIVE

The study investigates the prognostic impact of the native QRS duration in patients with heart failure and mildly reduced ejection fraction (HFmrEF).

BACKGROUND

The prognostic impact of QRS duration in HFmrEF has rarely been investigated.

METHODS

Consecutive patients with HFmrEF and available 12-lead electrocardiogram were retrospectively included at one institution from 2016 to 2022. Patients with QRS duration ≥ 120 ms were compared to patients with QRS duration < 120 ms, further risk stratification was performed comparing patients with left and right bundle branch block (LBBB vs. RBBB). The primary endpoint was all-cause mortality at 30 months, secondary endpoints comprised the risk of HF-related rehospitalization.

RESULTS

In total, 1627 patients with HFmrEF were included with a median QRS duration of 90 ms (i.e., QRS duration ≥ 120 ms: 15%). Although the risk of long-term all-cause mortality was not affected by a prolonged QRS duration (35.1% vs. 28.7%; p = 0.057; HR = 1.254; 95% CI 0.993-1.583), patients with QRS duration ≥ 120 ms had a higher risk of HF-related rehospitalization (18.2% vs. 11.9%; p = 0.008; HR = 1.574; 95% CI 1.124-2.204). A QRS duration ≥ 120 ms was associated with long-term HF-related rehospitalization even after multivariable adjustment (HR 1.420, 95% CI 1.008-2.002, p = 0.045). Finally, the risks of long-term all-cause mortality and HF-related rehospitalization did not differ among patients with LBBB and RBBB.

CONCLUSION

A prolonged native QRS duration is independently associated with a higher risk of HF-related rehospitalization in HFmrEF, but not long-term all-cause mortality.

Estimating very low ejection fraction from the 12 Lead ECG among patients with acute heart failure

BACKGROUND

Identifying patients with low left ventricular ejection fraction (LVEF) in the emergency department using an electrocardiogram (ECG) may optimize acute heart failure (AHF) management. We aimed to assess the efficacy of 527 automated 12‑lead ECG features for estimating LVEF among patients with AHF.

METHOD

Medical records of patients >18 years old and AHF-related ICD codes, demographics, LVEF %, comorbidities, and medication were analyzed. Least Absolute Shrinkage and Selection Operator (LASSO) identified important ECG features and evaluated performance.

RESULTS

Among 851 patients, the mean age was 74 years (IQR:11), male 56 % (n = 478), and the median body mass index was 29 kg/m2 (IQR:1.8). A total of 914 echocardiograms and ECGs were matched; the time between ECG-Echocardiogram was 9 h (IQR of 9 h); ≤30 % LVEF (16.45 %, n = 140). Lasso demonstrated 42 ECG features important for estimating LVEF ≤30 %. The predictive model of LVEF ≤30 % showed an area under the curve (AUC) of 0.86, a 95 % confidence interval (CI) of 0.83 to 0.89, a specificity of 54 % (50 % to 57 %), and a sensitivity of 91 (95 % CI: 88 % to 96 %), accuracy 60 % (95 % CI:60 % to 63 %) and, negative predictive value of 95 %.

CONCLUSIONS

An explainable machine learning model with physiologically feasible predictors may help screen patients with low LVEF in AHF.

Association Between Serum Albumin and the Length of Hospital Stay Among Patients With Acute Heart Failure

Introduction: Albumin plays a vital role in improving osmotic pressure and hemodynamics. A lower serum albumin level may cause pulmonary congestion and edema and contribute to myocardial dysfunction, diuresis resistance, and fluid retention in acute heart failure. Hypothesis: We hypothesized that AHF patients with normal serum albumin have shorter hospital stays. Methods: Using Electronic Medical Records, patients admitted from May 2020 through May 2021 aged >18, ICD-10, and positive Framingham Heart Failure Diagnostic Criteria were included. We excluded patients without albumin records and eGFRs less than 30 mL/min/1.73 m2. Prolonged hospitalization was defined as >8 days of hospitalization. Results: During index emergency department visits, patients were symptomatic (New York Heart Association), aged median of 70 years (Interquartile range (IQR) 18), 59% (n = 103) were male, predominantly White (73%, n = 128), and had a high Charleston Comorbidity index score [5, IQR (4-7)]. Nearly one-fourth (23%, n = 41) of the patients had <3.5 g/dL albumin levels. The median length of hospital stay was eight days (IQR of 11). Comparing differences between lengths of hospital stays (<8 vs. >8 days), there was different serum albumin (3.9 + 0.48 vs. 3.6 + 0.53, p < .001) and left ventricular ejection fraction (45% (range 26-63) versus 30% (range 24-48), p = .004). An increased serum albumin decreased prolonged hospitalization (odds ratio (OR), 0.28; 95% confidence interval (CI), 0.14-0.55, p = <0.001). Patients in the lower albumin group had higher NT-proBNP (median: 8521 (range 2025-9134) versus 5147 (range 2966-14,795) pg/ml, p = .007) and delay in administering intravenous diuretics (391 (167-964) minutes versus 271 (range 157-533) minutes, p = .02). Conclusion: Hypoalbuminemia is strongly associated with prolonged hospitalization. Timely and effective diuretic therapy may reduce hospital stay durations, particularly with albumin supplementation.

Estimating Ejection Fraction from the 12 Lead ECG among Patients with Acute Heart Failure

Background

Identifying patients with low left ventricular ejection fraction (LVEF) in the emergency department using an electrocardiogram (ECG) may optimize acute heart failure (AHF) management. We aimed to assess the efficacy of 527 automated 12-lead ECG features for estimating LVEF among patients with AHF.

Method

Medical records of patients >18 years old and AHF-related ICD codes, demographics, LVEF %, comorbidities, and medication were analyzed. Least Absolute Shrinkage and Selection Operator (LASSO) identified important ECG features and evaluated performance.

Results

Among 851 patients, the mean age was 74 years (IQR:11), male 56% (n=478), and the median body mass index was 29 kg/m2 (IQR:1.8). A total of 914 echocardiograms and ECGs were matched; the time between ECG-Echocardiogram was 9 hours (IQR of 9 hours); ≤30% LVEF (16.45%, n=140). Lasso demonstrated 42 ECG features important for estimating LVEF ≤30%. The predictive model of LVEF ≤30% demonstrated an area under the curve (AUC) of 0.86, a 95% confidence interval (CI) of 0.83 to 0.89, a specificity of 54% (50% to 57%), and a sensitivity of 91 (95% CI: 88% to 96%), accuracy 60% (95% CI:60 % to 63%) and, negative predictive value of 95%.

Conclusions

An explainable machine learning model with physiologically feasible predictors may be useful in screening patients with low LVEF in AHF.