Ultrafiltration for management of fluid overload in patients with heart failure

Predictive Analysis of the Mortality Rate of Patients with Heart Failure Complicated by Acute Kidney Failure Based on the Fluid Balance: A Retrospective Study Using the MIMIC-IV Database

BACKGROUND

Heart failure (HF) is a global health issue, and its complication with acute kidney failure (AKF) increases the risk of mortality. This study aimed to investigate the predictive value of fluid balance for mortality in patients with HF complicated by AKF. A retrospective analysis was performed using the MIMIC-IV database to evaluate the relationship between fluid balance and mortality in patients with HF complicated by AKF.

MATERIAL AND METHODS

Adult patients with HF and AKF and who were listed in the MIMIC-IV database between 2008 and 2019 were included. The patients were divided into survival and non-survival groups. The primary outcome measure was fluid intake and output in the first three days in the intensive care unit (ICU). The main outcome being in-ICU mortality and the secondary outcome being 28‑day mortality after ICU admission. A multivariable Cox proportional hazards model was used to assess the relationship between fluid balance and the risk of death, after adjusting for potential confounding factors.

RESULTS

A total of 1433 eligible patients were included. The study found that compared to the death group, patients in the survival group maintained lower positive balance on day 1 (453.51 ml vs 1813.66 ml), negative balance on day 2 (-246.75 ml vs 646.00 ml), and negative balance on day 3 (-350.21 ml vs 312.92 ml). Additionally, fluid balance on the first day predicted ICU mortality rate (AUC 0.658, p<0.01), on the second day it predicted ICU mortality rate (AUC 0.654, p<0.01), and on the third day it also predicted ICU mortality rate (AUC 0.634, p<0.01).

CONCLUSION

Positive fluid balance in patients with HF and AKF is independently associated with higher in-hospital mortality. Monitoring and managing fluid balance may provide clinicians with an important tool to improve patient outcomes.

Association between beta-blocker utilization and heart failure mortality in the peritoneal dialysis population: a cohort study

Background

The prognostic significance of beta(β)-blocker therapy in patients at end-stage renal disease, specifically those receiving peritoneal dialysis (PD) and presenting with heart failure, remains inadequately elucidated due to limited research conducted thus far.

Methods

A retrospective analysis was performed on a cohort comprising 608 patients receiving PD between September 2007 and March 2019, with a subsequent follow-up period extending until December 2020. Cox regression and propensity score matching weighted analysis was used to model adjusted hazard ratios for β-blocker use with heart failure-related mortality. Competing risk analysis and subgroup analysis were carried out to further elucidate the correlation.

Results

β-blockers were prescribed for 56.1% of the peritoneal dialysis patients. Heart failure occurred in 43.4% of the total population and 15.5% of deaths were due to heart failure. The prescription of β-blockers was associated with a 43% lower adjusted hazard ratio (HR) for heart failure death within the cohort (95% confidence interval [CI] = 0.36-0.89; P = 0.013). Even after accounting for competing risk events, patients in the group using β-blockers demonstrated a significantly lower cumulative risk of heart failure-related mortality compared to those not using β-blockers (P = 0.007). This protective effect of β-blockers was also observed in subgroup analyses. Conversely, β-blocker use had no statistically significant associations with all-cause mortality.

Conclusion

The use of β-blockers was associated with a reduced risk of heart failure-related mortality in the PD population. Future randomized clinical trials are warranted to confirm the beneficial effect of β-blockers in the context of PD.

Extracorporeal veno-venous ultrafiltration in congestive heart failure: What's the state of the art? A mini-review

Hospitalizations for heart failure exceed 1 million per year in both the United States and Europe and more than 90% are due to symptoms and signs of fluid overload. Rates of rehospitalizations or emergency department visit at 60 days are remarkable regardless of whether loop diuretics were administered at low vs high doses or by bolus injection vs continuous infusion. Ultrafiltration (UF) has been considered a promising alternative to stepped diuretic therapy and it consists in the mechanical, adjustable removal of iso-tonic plasma water across a semipermeable membrane with the application of hydrostatic pressure gradient generated by a pump. Fluid removal with ultrafiltration presents several advantages such as elimination of higher amount of sodium with less neurohormonal activation. However, the conflicting results from UF studies highlight that patient selection and fluid removal targets are not completely understood. The best way to assess fluid status and therefore establish the fluid removal target is also still a matter of debate. Herein, we provide an up-to-date systematic review about the role of ultrafiltration among patients with fluid overload and its gaps in daily practice.

Machine learning predicting mortality in sarcoidosis patients admitted for acute heart failure

Background

Sarcoidosis with cardiac involvement, although rare, has a worse prognosis than sarcoidosis involving other organ systems.

Objective

We used a large dataset to train machine learning models to predict in-hospital mortality among sarcoidosis patients admitted with heart failure (HF).

Method

Utilizing the National Inpatient Sample, we identified 4659 patients hospitalized with a primary diagnosis of HF. In this cohort, we identified patients with a secondary diagnosis of sarcoidosis using International Statistical Classification of Disease, Tenth Revision (ICD-10) codes. Patients were separated into a training group and a testing group in a 7:3 ratio. Least absolute shrinkage and selection operator regression was used to select variables to prevent model overfitting or underfitting. For machine learning models, logistic regression, random forest, and XGBoosting were applied in the training group. Parameters in each of the models were tuned using the GridSearchCV function. After training, all models were further validated in the testing group. Models were then evaluated using the area under curve (AUC) score, sensitivity, and specificity.

Results

A total of 2.3% of sarcoidosis patients died in HF admission. Our machine learning model analysis found the RF model to have the highest AUC score and sensitivity. Feature analysis found that comorbid arrhythmias and fluid electrolyte disorders were the strongest factors in predicting in-hospital mortality.

Conclusion

Machine learning methods can be useful in identifying predictors of in-hospital mortality in a given dataset.

Risk factors and management of pulmonary infection in elderly patients with heart failure: A retrospective analysis

ABSTRACT

Pulmonary infection is common in patients with heart failure, yet the risk factors remain unclear. We aimed to evaluate the clinical characteristics and risk factors of pulmonary infection in elderly patients with heart failure, to provide reference to the prevention of pulmonary infection.This study was a retrospective study design. We included elderly heart failure patient admitted to our hospital from April 1, 2018 to August 31, 2020. The characteristics and clinical data of pulmonary infection and no infection patients were assessed. Logistic regression analyses were conducted to identify the risk factors of pulmonary infections in patients with heart failure.A total of 201 patients were included. The incidence of pulmonary infection in patients with heart failure was 23.88%. There were significant differences in the age, diabetes, New York Heart Association (NYHA) grade, left ventricular ejection fraction (LVEF), C-reactive protein (CRP) between infection and no infection group (all P < .05), and there were not differences in the sex, body mass index, alcohol drinking, smoking, hypertension, hyperlipidemia, length of hospital stay between 2 groups (all P > .05). Logistic regression analyses indicated that age ≥70 years, diabetes, NYHA grade III, LVEF ≤55%, and CRP ≥10 mg/L were the independent risk factors of pulmonary infections in patients with heart failure (all P < .05). Pseudomonas aeruginosa (34.48%), Staphylococcus aureus (19.57%), and Klebsiella pneumoniae (15.22%) were the most common 3 pathogens in patients with pulmonary infection.Heart failure patients with age ≥70 years, diabetes, NYHA grade III, LVEF ≤55%, and CRP ≥10 mg/L have higher risks of pulmonary infections, preventive measures targeted on those risk factors are needed to reduce pulmonary infections.

Comparative effectiveness of furosemide vs torasemide in symptomatic therapy in heart failure patients: A randomized controlled study protocol

BACKGROUND:

We performed this randomized controlled study protocol to investigate the efficacy and adverse effects of furosemide vs torasemide in patients with heart failure (HF).

METHOD:

The present study was authorized by the local research ethics committee of Shanxi Cardiovascular Hospital (no. 48736645) and informed consent was obtained from all patients. Patients were enrolled in a consecutive prospective manner on a voluntary basis. Patients who were aged 18 years and older with HF who were eligible to enroll in this randomized trial. All patients had evidence of left ventricular systolic dysfunction, confirmed by echocardiographic or nuclear imaging. The exclusion criteria were left ventricular diastolic dysfunction only, or receipt of medical or pharmaceutical care in other health systems. The primary efficacy end point was the change in procollagen type I carboxyterminal peptide (PICP) serum levels between baseline and final visit. Secondary efficacy variables included parameters related to the clinical course of HF, such as body weight, presence of edema, signs and symptoms of HF, electrocardiogram and echocardiographic evaluation, amino-terminal pro brain-type natriuretic peptide (NT-proBNP) serum levels measured by ELISA method, systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate, and renal function.

RESULTS:

One hundred patients who met the inclusion criteria were included in our study, Table 1 showed the effects of furosemide and torsemide on measures of clinical outcomes.

DISCUSSION:

Fluid overload is the primary cause of hospitalization among patients with HF. Preventing circulatory congestion requires careful control of dietary sodium and chronic administration of loop diuretics. Torasemide and furosemide are representatives of loop diuretics with an identical diuretic mechanism, but different pharmacokinetic properties and additional effects. There is a need for reliable conclusion regarding the comparison of furosemide and torasemide in patients with HF. Several limitation should be noted: 1. the small number of participants did not enable assessment of the impact of torasemide and furosemide in different clinically relevant subgroups that is, elderly, patients with chronic kidney disease, dilated cardiomyopathy; 2. short-term follow up might lead to underestimation of the complications; 3. methodological weakness in study design may affect the results. Future high quality studies were still required.