ESC Heart Failure最新文献

Aims: Sodium-glucose co-transporter inhibitors (SGLTis) have cardiovascular protective effects. We aimed to assess the effects of SGLTis on individual hard clinical endpoints and quality of life (QoL) in patients with cardiovascular risk factors.

Methods and results: Data was searched in PubMed, Embase, Cochrane Library and clinicaltrials.gov databases up to February 2024. Randomized controlled trials (RCTs) comparing SGLTis with placebo were included. The primary outcomes were individual hard clinical endpoints (Subset A) and QoL (Subset B). For Subset A, 13 RCTs including 90 413 patients were enrolled (age 66 ± 10.1 years, 35.7% female, follow-up 2.4 ± 0.3 years); as compared with placebo, SGLTis were associated with significantly lower risk of all-cause mortality [risk ratio (RR): 0.90, 95% confidence interval (CI): 0.86-0.94, P < 0.01], cardiovascular mortality (RR: 0.87, 95% CI: 0.82-0.92, P < 0.01), hospitalization for heart failure (HF) (RR: 0.72, 95% CI: 0.68-0.76, P < 0.01), HF events (RR: 0.72, 95% CI: 0.68-0.75, P < 0.01), hospitalization for any cause (RR: 0.91, 95% CI: 0.88-0.93, P < 0.01) and myocardial infarction (MI) (RR: 0.92, 95% CI: 0.85-0.99, P = 0.03). Notably, the favourable effect of SGLTis on all-cause mortality was more pronounced in younger (<65 years) patients (RR: 0.86, 95% CI: 0.81-0.92) and in studies with less female (RR: 0.84, 95% CI: 0.79-0.90). The favourable effect of SGLTis on MI was only observed in patients who received sotagliflozin (RR: 0.47, 95% CI: 0.31-0.73). For Subset B, nine RCTs including 2552 HF patients were enrolled (age 67.8 ± 12.4 years, 36.4% female, follow-up 3.4 ± 1.9 months); SGLTis were associated with significant improvement in QoL as compared with placebo.

Conclusions: In patients with a broad spectrum of cardiovascular risk factors, SGLTis substantially improve individual hard clinical outcomes and QoL.

Aims: Natriuretic peptide-based pre-heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre-heart failure, has not been well established. This study evaluated the performance of machine learning prediction models for predicting elevated N terminal pro brain natriuretic peptide (NT-proBNP) levels in the US general population.

Methods and results: Individuals aged 20-79 years without cardiovascular disease from the nationally representative National Health and Nutrition Examination Survey 1999-2004 were included. Six prediction models (two conventional regression models and four machine learning models) were trained with the 1999-2002 cohort to predict elevated NT-proBNP levels (>125 pg/mL) using demographic, lifestyle, and commonly measured biochemical data. The model performance was tested using the 2003-2004 cohort. Of the 10 237 individuals, 1510 (14.8%) had NT-proBNP levels >125 pg/mL. The highest area under the receiver operating characteristic curve (AUC) was observed in SuperLearner (AUC [95% CI] = 0.862 [0.847-0.878], P < 0.001 compared with the logistic regression model). The logistic regression model with splines showed a comparable performance (AUC [95% CI] = 0.857 [0.841-0.874], P = 0.08). Age, albumin level, haemoglobin level, sex, estimated glomerular filtration rate, and systolic blood pressure were the most important predictors. We found a similar prediction performance even after excluding socio-economic information (marital status, family income, and education status) from the prediction models. When we used different thresholds for elevated NT-proBNP, the AUC (95% CI) in the SuperLearner models 0.846 (0.830-0.861) for NT-proBNP > 100 pg/mL and 0.866 (0.849-0.884) for NT-proBNP > 150 pg/mL.

Conclusions: Using nationally representative data from the United States, both logistic regression and machine learning models well predicted elevated NT-proBNP. The predictive performance remained consistent even when the models incorporated only commonly available variables in daily clinical practice. Prediction models using regularly measured information would serve as a potentially useful tools for clinicians to effectively identify targets of natriuretic-peptide screening.

Background and aims: Patients with heart failure with preserved ejection fraction (HFpEF) tend to have low resting and exercise heart rates. Phosphodiesterase-3 (PDE-3) inhibitors improve heart rates, haemodynamics and symptoms in patients with HFpEF. Cilostazol is an oral PDE-3 inhibitor used in peripheral artery disease. This study thought to evaluate the short-term effects of cilostazol on health status, N-terminal brain natriuretic peptide (NT-proBNP) levels and mechanisms of action.

Methods: The effect of cilostazol was evaluated in 23 patients with HFpEF in a randomized placebo controlled multiple crossover trial (CLIP-HFpEF). Participants received placebo or cilostazol for 1 week followed by three crossovers to the alternate assignment at weeks 2, 3 and 4. The primary endpoint was the Kansas City Cardiomyopathy Questionnaire (KCCQ-12) overall summary score obtained at the end of each treatment period. NT-proBNP was the secondary endpoint. In an exploratory mechanistic analysis, pulmonary artery (PA) pressures and heart rates were followed amongst the five participants with implanted pressure monitors.

Results: Cilostazol improved the KCCQ score by 4.8 points (95% confidence interval, 2.0-7.7, P = 0.003). NT-proBNP levels were 448 (154-1056) pg/mL on placebo and 375 (68-974) pg/mL on cilostazol (P = 0.006). In patients with PA pressure monitors, diastolic pressure was 20.5 (18.7-23.0) mmHg on placebo and 18.0 (17.0-20.0) mmHg on cilostazol, an effect linked to higher heart rates (P < 0.001).

Conclusions: Amongst patients with HFpEF, short-term treatment with cilostazol leads to improvements in health status and NT-proBNP when compared with placebo. These effects are likely conveyed by a heart rate-dependent reduction in cardiac filling pressures.

Trial registration: ClinicalTrials.gov Identifier: NCT05126836.

Background: Seasonal variations have been observed in heart failure (HF) hospitalization. Numerous explanatory mechanisms have been proposed, but no prior studies have examined potential contributors directly. Our objective was to identify specific factors that could contribute to seasonal variability using a large longitudinal dataset of HF hospitalizations.

Methods: Hospital discharge data were obtained for all hospitals in the state of New York from 1994 to 2007. Records with a primary diagnosis of HF by the International Classification of Diseases-9 Clinical Modification (ICD-9-CM) code (428.xx and 425.xx) were included. Year and month of admission were used as predictors to evaluate outcomes of in-hospital mortality, population-adjusted daily rate of hospital admissions and length of stay (LOS) using univariable regression including a sinusoidal model to assess the seasonality of HF outcomes. Observations were then adjusted for multiple medical covariables as well as the average local monthly temperature and humidity at each hospital using data from the Global Historical Climate Network to identify potential modifiers of seasonal variability.

Results: Among 949 907 records, the median age was 76 [inter-quartile range (IQR) 65-84 years old], and the cohort was 54% female (510 945 records). The population-adjusted rate of HF admissions per day increased by 1.1 admissions/day/year between 1994 and 2007, whereas in-hospital mortality and LOS decreased by -0.3%/year and -0.3 days/year, respectively (P < 0.001 for all). Seasonal trends were identified for daily HF admissions (February peak, P < 0.0001), mortality (January peak, P < 0.001) and LOS (January peak, P < 0.01). Cosinor analysis revealed significant periodicity for HF admission rate (amplitude = ±0.9 admissions/day/100 000 people, P < 0.001), in-hospital mortality (amplitude = ±0.47%, P < 0.001) and LOS (amplitude = ±0.23 days, P < 0.01). No other patient characteristics were significant modifiers of seasonality. Odds of mortality were highest in July rather than January when adjusted for average local temperature but not humidity.

Conclusions: Adverse outcomes in patients hospitalized with HF were significantly worse in the winter months even when adjusted for patient characteristics and concurrent acute diagnoses such as pneumonia. Local ambient temperature was the strongest modifier of the observed seasonality. Given the increasing frequency of extreme weather events, additional work to determine the mechanisms of this and other environmental risk factors is urgently needed.

Aim: Heart failure (HF) is a highly prevalent condition managed in both primary care (PC) and hospital care (HC)-based settings. HF patients managed in these two settings may differ in their demography, comorbidities and outcomes, so we aimed to compare the patient management in PC and HC in the Västra Götaland Region (VGR) in Sweden.

Methods: The VEGA database is an administrative database that includes all patients living in VGR. Patients with a first principal or contributory diagnosis of HF (I50) ≥18 years old between 2008 and 2017 were included. One-year mortality was used as the outcome.

Results: In total, 35 375 new-onset HF cases were included with 18 722 identified only in PC and 16 651 in HC. HF patients in PC were older (80.7 ± 10.9 vs. 76.1 ± 13.6), more women (57.1% vs. 44.9%), with more hypertension, musculoskeletal and mental disorders, but less myocardial infarction. Patients in HC had almost 4 times higher all-cause 1 year mortality [3.92 (3.77-4.08), P < 0.0001] compared with PC after adjustment for age and sex. Over a 10 year period, despite decreasing mortality in both settings, hazard ratios for HC versus PC were significantly increased for all patients (P for interaction 0.0004), which was more marked in female and for 70-80 years old patients.

Conclusion: Over a 10 year period, we demonstrated the differences in demography, comorbidities and outcomes between heart failure patients managed in hospital care versus primary care.

Background: There are limited data on the efficacy of smartphone-based personal health records (PHRs) in patients with cardiovascular disease. This study aimed to examine the processes, outcomes and challenges associated with the implementation of integrated PHRs in patients with heart failure (HF) or coronary artery disease (CAD).

Methods: This prospective single-group study evaluated the effects of a PHR system with the capability to capture electronic health records and vital signs in patients with HF or CAD. The outcomes measured were the 6 -month changes in blood pressure (BP), body weight (BW), brain natriuretic peptide (BNP) levels, lipid profiles and haemoglobin (Hb) A1c levels.

Results: Between June 2021 and March 2022, we enrolled 111 patients (median age: 61 years and 47% women) with CAD and/or HF. Over 6 months, the PHR review count distribution was skewed: median 749 times (lowest 2, highest 5724)/180 days, suggesting both low and excessive PHR users. After 3 days, 23% of the patients discontinued inputting their vital signs and medication status. At 6 months, compared with patients who discontinued, those who continued to input their vital signs (N = 86) showed a significant decrease in their systolic BP and LDL-C levels but not in the diastolic BP, BW, BNP, HDL-C, triglyceride or HbA1c levels.

Conclusions: The implementation of smartphone-based PHRs in daily practice is challenging for patients with HF or CAD. However, we observed positive indications of the benefits of PHR in these patients.

Trial registration number: UMIN000044369.