The diagnosis of heart failure can be difficult, even for heart failure specialists. Artificial Intelligence-Clinical Decision Support System (AI-CDSS) has the potential to assist physicians in heart failure diagnosis. The aim of this work was to evaluate the diagnostic accuracy of an AI-CDSS for heart failure. AI-CDSS for cardiology was developed with a hybrid (expert-driven and machine-learning-driven) approach of knowledge acquisition to evolve the knowledge base with heart failure diagnosis. A retrospective cohort of 1198 patients with and without heart failure was used for the development of AI-CDSS (training dataset, n = 600) and to test the performance (test dataset, n = 598). A prospective clinical pilot study of 97 patients with dyspnea was used to assess the diagnostic accuracy of AI-CDSS compared with that of non-heart failure specialists. The concordance rate between AI-CDSS and heart failure specialists was evaluated. In retrospective cohort, the concordance rate was 98.3% in the test dataset. The concordance rate for patients with heart failure with reduced ejection fraction, heart failure with mid-range ejection fraction, heart failure with preserved ejection fraction, and no heart failure was 100%, 100%, 99.6%, and 91.7%, respectively. In a prospective pilot study of 97 patients presenting with dyspnea to the outpatient clinic, 44% had heart failure. The concordance rate between AI-CDSS and heart failure specialists was 98%, whereas that between non-heart failure specialists and heart failure specialists was 76%. In conclusion, AI-CDSS showed a high diagnostic accuracy for heart failure. Therefore, AI-CDSS may be useful for the diagnosis of heart failure, especially when heart failure specialists are not available.

Background: Shift work has been hypothesized as a risk factor for obesity. In this study, we investigated the association between current shift work and body mass index (BMI) among female nurses in Korea. The relationship between duration of shift work and BMI of the participants was also evaluated. Methods: This cross-sectional survey evaluated participants in the Korean Nurses’ Survey, conducted from October to December 2011, using web-based self-administered questionnaires. A total of 9,989 nurses were included among 10,000 who registered on the survey web site (5,287 shift workers and 4,702 non-shift workers). Current shift workers were divided into tertiles of shift work duration (0.08–3.00 years, n = 1,732; 3.08–6.75 years, n = 1,731; and 6.83–38.00 years, n = 1,686). The BMI thresholds of overweight and obesity were ≥23 kg/m² and ≥25 kg/m², respectively. Data were analyzed using SPSS software. Results: Mean participant age was 33.2 ± 8.6 years and the mean BMI was 20.9 ± 2.5 kg/m². There were statistically significant differences in current smoking status, regular drinking habit, dietary habits, regular exercise, sleep problems and self-perceived health status according to duration of shift work. The overall prevalence of overweight/obesity (18.6%) and obesity (7.4%) increased significantly as shift work duration increased from the lowest to highest tertile (P for trend <0.001). Multivariate logistic regression analysis revealed no association between current shift work and BMI. However, after adjusting for potential confounders, the participants with the longest duration of shift work were 1.63 (95% CI, 1.22–2.17) times more likely to be overweight or obese than those with the shortest duration. There was a significant positive association between obesity and shift work duration in the unadjusted analysis; however, it was attenuated and no longer significant in the multivariate model. Conclusions: The duration of shift work was positively associated with prevalence of overweight/obesity in nurses in Korea. Although these findings need to be confirmed in prospective studies, they suggest that special attention should be paid to female nurses with a long duration of shift work.

Background: Many patients with heart failure ( HF ) with reduced ejection fraction ( HF r EF ) experience improvement or recovery of left ventricular ejection fraction ( LVEF ). Data on clinical characteristics, outcomes, and medical therapy in patients with HF with improved ejection fraction (HFiEF) are scarce. Methods and Results: Of 5625 consecutive patients hospitalized for acute HF in the KorAHF (Registry [Prospective Cohort] for Heart Failure in Korea) study, 5103 patients had baseline echocardiography and 2302 patients had follow‐up echocardiography at 12 months. HF phenotypes were defined as persistent HF r EF ( LVEF ≤40% at baseline and at 1‐year follow‐up), HF i EF ( LVEF ≤40% at baseline and improved up to 40% at 1‐year follow‐up), HF with midrange ejection fraction (LVEF between 40% and <50%), and HF with preserved ejection fraction ( LVEF ≥50%). The primary outcome was 4‐year all‐cause mortality from the time of HF i EF diagnosis. Among 1509 HF r EF patients who had echocardiography 1 year after index hospitalization, 720 (31.3%) were diagnosed as having HF i EF . Younger age, female sex, de novo HF , hypertension, atrial fibrillation, and β‐blocker use were positive predictors and diabetes mellitus and ischemic heart disease were negative predictors of HF i EF . During 4‐year follow‐up, patients with HF i EF showed lower mortality than those with persistent HF r EF in univariate, multivariate, and propensity‐score–matched analyses. β‐Blockers, but not renin–angiotensin system inhibitors or mineralocorticoid receptor antagonists, were associated with a reduced all‐cause mortality risk (hazard ratio: 0.59; 95% CI , 0.40–0.87; P =0.007). Benefits for outcome seemed similar among patients receiving low‐ or high‐dose β‐blockers (log‐rank, P =0.304). Conclusions: HF i EF is a distinct HF phenotype with better clinical outcomes than other phenotypes. The use of β‐blockers may be beneficial for these patients. Clinical Trial Registration: URL : https://www.clinicaltrials.gov . Unique identifier: NCT01389843.

Park JJ, et al. Int J Heart Fail. 2021 Oct;3(4):224-236. https://doi.org/10.36628/ijhf.2021.0023

The application of a simple blood test to predict prognosis in acute heart failure (AHF) patients is not well established. Neutrophil-lymphocyte ratio (NLR) is inexpensive and easy to obtain in hospitalized patients using a routine blood test. We evaluate the prognostic implications of NLR as an independent predictor of in-hospital and long-term mortality in AHF patients. Among 5625 patients enrolled in the Korean Acute Heart Failure registry, 5580 patients were classified into quartiles by their NLR level, and analyzed for in-hospital and post-discharge three-year mortality. Patients in the highest NLR quartile had the highest in-hospital and post-discharge three-year mortality. The same results were seen by dividing the aggravating factor into the infection or ischemia group and the non-infection or non-ischemia group. For patients aggravated from infection or ischemia, a cut-off NLR value was 7.0 that increase the risk of in-hospital and post-discharge three-year mortality. In subgroups of patients not aggravated from infection or ischemia, a cut-off NLR value was 5.0 that increase the risk of in-hospital and post discharge three-year mortality. Elevated NLR in AHF patients at the index hospitalization is an independent predictor for in-hospital and post-discharge three-year mortality. Taken together, NLR is a marker for risk assessment of AHF patients.

Objective To determine the prognostic value of atrial fibrillation (AF) in patients with heart failure (HF) and preserved, mid-range or reduced ejection fraction (EF). Methods Patients hospitalised for acute HF were enrolled in the Korean Acute Heart Failure registry, a prospective, observational, multicentre cohort study, between March 2011 and February 2014. HF types were defined as reduced EF (HFrEF, LVEF <40%), mid-range EF (HFmrEF, LVEF 40%–49%) or preserved EF (HFpEF, LVEF ≥50%). Results Of 5414 patients enrolled, HFrEF, HFmrEF and HFpEF were seen in 3182 (58.8%), 875 (16.2%) and 1357 (25.1%) patients, respectively. The prevalence of AF significantly increased with increasing EF (HFrEF 28.9%, HFmrEF 39.8%, HFpEF 45.2%; p for trend <0.001). During follow-up (median, 4.03 years; IQR, 1.39–5.58 years), 2806 (51.8%) patients died. The adjusted HR of AF for all-cause death was 1.06 (0.93–1.21) in the HFrEF, 1.10 (0.87–1.39) in the HFmrEF and 1.22 (1.02–1.46) in the HFpEF groups. The HR for the composite of all-cause death or readmission was 0.97 (0.87–1.07), 1.14 (0.93–1.38) and 1.03 (0.88–1.19) in the HFrEF, HFmrEF and HFpEF groups, respectively, and the HR for stroke was 1.53 (1.03–2.29), 1.04 (0.57–1.91) and 1.90 (1.13–3.20), respectively. Similar results were observed after propensity score matching analysis. Conclusions AF was more common with increasing EF. AF was seen to be associated with increased mortality only in patients with HFpEF and was associated with an increased risk of stroke in patients with HFrEF or HFpEF. Trial registration number NCT01389843