MEMS Technology in Cardiology: Advancements and Applications in Heart Failure Management Focusing on the CardioMEMS Device.

Heart failure (HF) is a complex clinical syndrome associated with significant morbidity, mortality, and healthcare costs. It is characterized by various structural and/or functional abnormalities of the heart, resulting in elevated intracardiac pressure and/or inadequate cardiac output at rest and/or during exercise. These dysfunctions can originate from a variety of conditions, including coronary artery disease, hypertension, cardiomyopathies, heart valve disorders, arrhythmias, and other lifestyle or systemic factors. Identifying the underlying cause is crucial for detecting reversible or treatable forms of HF. Recent epidemiological studies indicate that there has not been an increase in the incidence of the disease. Instead, patients seem to experience a chronic trajectory marked by frequent hospitalizations and stagnant mortality rates. Managing these patients requires a multidisciplinary approach that focuses on preventing disease progression, controlling symptoms, and preventing acute decompensations. In the outpatient setting, patient self-care plays a vital role in achieving these goals. This involves implementing necessary lifestyle changes and promptly recognizing symptoms/signs such as dyspnea, lower limb edema, or unexpected weight gain over a few days, to alert the healthcare team for evaluation of medication adjustments. Traditional methods of HF monitoring, such as symptom assessment and periodic clinic visits, may not capture subtle changes in hemodynamics. Sensor-based technologies offer a promising solution for remote monitoring of HF patients, enabling early detection of fluid overload and optimization of medical therapy. In this review, we provide an overview of the CardioMEMS device, a novel sensor-based system for pulmonary artery pressure monitoring in HF patients. We discuss the technical aspects, clinical evidence, and future directions of CardioMEMS in HF management.

Impact of Sex in the Incidence of Heart Failure in Patients with Chronic Coronary Syndrome.

PURPOSE OF REVIEW: This review examines the available evidence concerning the incidence of heart failure in patients with chronic coronary syndrome, with a focus on gender differences. RECENT FINDINGS: The incidence of heart failure in the context of chronic coronary syndrome presents conflicting data. Most of the available information stems from studies involving stable patients' post-acute coronary syndrome, revealing a wide range of incidence rates, from less than 3% to over 20%, observed over 5 years of follow-up. Regarding the gender differences in heart failure incidence, there is no consensus about whether women exhibit a higher incidence, particularly in the presence of evidence of obstructive coronary artery disease. However, in cases where obstructive coronary artery disease is absent, women may face a more unfavourable prognosis due to a higher prevalence of microvascular disease and heart failure with preserved ventricular function. The different profile of ischaemic heart disease in women difficult to establish differences in prognosis independently associated with female sex. Targeted investigations are essential to discern the incidence of heart failure in chronic coronary syndrome and explore potential gender-specific associations.

An Integrated Machine Learning Approach for Congestive Heart Failure Prediction.

Congestive heart failure (CHF) is one of the primary sources of mortality and morbidity among the global population. Over 26 million individuals globally are affected by heart disease, and its prevalence is rising by 2% yearly. With advances in healthcare technologies, if we predict CHF in the early stages, one of the leading global mortality factors can be reduced. Therefore, the main objective of this study is to use machine learning applications to enhance the diagnosis of CHF and to reduce the cost of diagnosis by employing minimum features to forecast the possibility of a CHF occurring. We employ a deep neural network (DNN) classifier for CHF classification and compare the performance of DNN with various machine learning classifiers. In this research, we use a very challenging dataset, called the Cardiovascular Health Study (CHS) dataset, and a unique pre-processing technique by integrating C4.5 and K-nearest neighbor (KNN). While the C4.5 technique is used to find significant features and remove the outlier data from the dataset, the KNN algorithm is employed for missing data imputation. For classification, we compare six state-of-the-art machine learning (ML) algorithms (KNN, logistic regression (LR), naive Bayes (NB), random forest (RF), support vector machine (SVM), and decision tree (DT)) with DNN. To evaluate the performance, we use seven statistical measurements (i.e., accuracy, specificity, sensitivity, F1-score, precision, Matthew's correlation coefficient, and false positive rate). Overall, our results reflect our proposed integrated approach, which outperformed other machine learning algorithms in terms of CHF prediction, reducing patient expenses by reducing the number of medical tests. The proposed model obtained 97.03% F1-score, 95.30% accuracy, 96.49% sensitivity, and 97.58% precision.

CardioMEMS monitoring device migration: A rare complication.

We present a rare case of CardioMEMS device migration six years post-implantation. Much is still being learned about endothelization of pulmonary vasculature and this case highlights the importance of device surveillance and device-related complications.

Study of CHF3/CH2F2 Adsorption Separation in TIFSIX-2-Cu-i.

Hydrofluorocarbons (HFCs) have important applications in different industries; however, they are environmentally unfriendly due to their high global warming potential (GWP). Hence, reclamation of used hydrofluorocarbons via energy-efficient adsorption-based separation will greatly contribute to reducing their impact on the environment. In particular, the separation of azeotropic refrigerants remains challenging, such as typical mixtures of CH2F2 (HFC-23) and CHF3 (HFC-32), due to a lack of adsorptive mechanisms. Metal-organic frameworks (MOFs) can provide a promising solution for the separation of CHF3-CH2F2 mixtures. In this study, the adsorption mechanism of CHF3-CH2F2 mixtures in TIFSIX-2-Cu-i was revealed at the microscopic level by combining static pure-component adsorption experiments, molecular simulations, and density-functional theory (DFT) calculations. The adsorption separation selectivity of CH2F2/CHF3 in TIFSIX-2-Cu-i is 3.17 at 3 bar under 308 K. The existence of similar TiF62- binding sites for CH2F2 or CHF3 was revealed in TIFSIX-2-Cu-i. Interactions between the fluorine atom of the framework and the hydrogen atom of the guest molecule were found to be responsible for determining the high adsorption separation selectivity of CH2F2/CHF3. This exploration is important for the design of highly selective adsorbents for the separation of azeotropic refrigerants.

The Synthetic Surfactant CHF5633 Restores Lung Function and Lung Architecture in Severe Acute Respiratory Distress Syndrome in Adult Rabbits.

PURPOSE: Acute respiratory distress syndrome (ARDS) is a major cause of hypoxemic respiratory failure in adults. In ARDS extensive inflammation and leakage of fluid into the alveoli lead to dysregulation of pulmonary surfactant metabolism and function. Altered surfactant synthesis, secretion, and breakdown contribute to the clinical features of decreased lung compliance and alveolar collapse. Lung function in ARDS could potentially be restored with surfactant replacement therapy, and synthetic surfactants with modified peptide analogues may better withstand inactivation in ARDS alveoli than natural surfactants. METHODS: This study aimed to investigate the activity in vitro and the bolus effect (200 mg phospholipids/kg) of synthetic surfactant CHF5633 with analogues of SP-B and SP-C, or natural surfactant Poractant alfa (Curosurf®, both preparations Chiesi Farmaceutici S.p.A.) in a severe ARDS model (the ratio of partial pressure arterial oxygen and fraction of inspired oxygen, P/F ratio ≤ 13.3 kPa) induced by hydrochloric acid instillation followed by injurious ventilation in adult New Zealand rabbits. The animals were ventilated for 4 h after surfactant treatment and the respiratory parameters, histological appearance of lung parenchyma and levels of inflammation, oxidative stress, surfactant dysfunction, and endothelial damage were evaluated. RESULTS: Both surfactant preparations yielded comparable improvements in lung function parameters, reductions in lung injury score, pro-inflammatory cytokines levels, and lung edema formation compared to untreated controls. CONCLUSIONS: This study indicates that surfactant replacement therapy with CHF5633 improves lung function and lung architecture, and attenuates inflammation in severe ARDS in adult rabbits similarly to Poractant alfa. Clinical trials have so far not yielded conclusive results, but exogenous surfactant may be a valid supportive treatment for patients with ARDS given its anti-inflammatory and lung-protective effects.

Physical activity changes and related factors in chronic heart failure patients during the postdischarge transition period: a longitudinal study.

BACKGROUND: Physical activity (PA) is essential and effective for chronic heart failure (CHF) patients. A greater understanding of the longitudinal change in PA and its influencing factors during the postdischarge transition period may help create interventions for improving PA. The aims of this study were (1) to compare the change in PA, (2) to examine the influencing factors of PA change, and (3) to verify the mediating pathways between influencing factors and PA during the postdischarge transition period in CHF patients. METHODS: A total of 209 CHF patients were recruited using a longitudinal study design. The Chinese version of the International Physical Activity Questionnaire (IPAQ), Patient-reported Outcome Measure for CHF (CHF-PRO), and the Chinese version of the Tampa Scale for Kinesiophobia Heart (TSK-Heart) were used to assess PA, CHF-related symptoms, and kinesiophobia. The IPAQ score was calculated (1) at admission, (2) two weeks after discharge, (3) two months after discharge, and (4) three months after discharge. Two additional questionnaires were collected during admission. Generalized estimating equation (GEE) models were fitted to identify variables associated with PA over time. We followed the STROBE checklist for reporting the study. RESULTS: The PA scores at the four follow-up visits were 1039.50 (346.50-1953.00) (baseline/T1), 630.00 (1.00-1260.00) (T2), 693.00 (1-1323.00) (T3) and 693.00 (160.88-1386.00) (T4). The PA of CHF patients decreased unevenly, with the lowest level occurring two weeks after discharge, and gradually improving at two and three months after discharge. CHF-related symptoms and kinesiophobia were significantly associated with changes in PA over time. Compared with before hospitalization, an increase in CHF-related symptoms at two weeks and two months after discharge was significantly associated with decreased PA. According to our path analysis, CHF-related symptoms were positively and directly associated with kinesiophobia, and kinesiophobia was negatively and directly related to PA. Moreover, CHF-related symptoms are indirectly related to PA through kinesiophobia. CONCLUSION: PA changed during the postdischarge transition period and was associated with CHF-related symptoms and kinesiophobia in CHF patients. Reducing CHF-related symptoms helps improve kinesiophobia in CHF patients. In addition, the reduction in CHF-related symptoms led to an increase in PA through the improvement of kinesiophobia. TRIAL REGISTRATION: The study was registered in the Chinese Clinical Trial Registry (11/10/2022 ChiCTR2200064561 retrospectively registered).

Warming Yang Promoting Blood Circulation and Diuresis Alleviates Myocardial Damage by Inhibiting Collagen Fiber and Myocardial Fibrosis and Attenuating Mitochondria Signaling Pathway Mediated Apoptosis in Chronic Heart Failure Rats.

Warming Yang promoting blood circulation and diuresis (WYPBD) has been proven effective in treating some diseases. This study aimed to evaluate therapeutic effect of WYPBD in treating chronic heart failure (CHF). CHF rats were established by intraperitoneally injecting doxorubicin (DOX). Therapeutic effects of WYPBD on cardiac function and hemodynamic parameters of myocardial tissues were analyzed. Collagen fiber production and myocardial fibrosis were evaluated. Transcriptions of COL1A1 gene, COL3A1 gene, and TGFB1 gene were evaluated with RT-PCR. Expression of BNP, AVP, PARP, caspase-3, and Bcl-2 in myocardial tissues were evaluated. TUNEL assay was used to identify apoptosis of cardiomyocytes. WYPBD alleviated degree of myocardial hypertrophy in CHF rats compared to the rats in CHF model group (P < 0.05). WYPBD significantly improved cardiac hemodynamics (increased LVEF and LVSF) of CHF rats compared to rats in the CHF model group (P < 0.05). WYPBD protected myocardial structure and inhibited collagen fiber production in myocardial tissues of CHF rats. WYPBD markedly decreased myocardial fibrosis mediators (Col1α, Col3α, TGF-ß1) transcription in myocardial tissues of CHF rats compared to rats in CHF model group (P < 0.05). WYPBD significantly reduced BNP and AVP expression in myocardial tissues of CHF rats compared to rats in the CHF model group (P < 0.05). WYPBD markedly reduced the expression of PRAP and caspase-3, and increased Bcl-2 expression in myocardial tissues of CHF rats compared to rats in the CHF model group (P < 0.05). In conclusion, WYPBD alleviated CHF myocardial damage by inhibiting collagen fiber and myocardial fibrosis, attenuating apoptosis associated with the mitochondria signaling pathway of cardiomyocytes.

Estimate Gaps of Montreal Protocol-Regulated Potent Greenhouse Gas HFC-152a Emissions in China Have Been Explained.

1,1-Difluoroethane (HFC-152a) is a hydrofluorocarbon regulated by the Montreal Protocol, and its emissions in China are of concern as China will regulate HFC-152a in 2024. However, no observation-inferred top-down estimates were undertaken after 2017, and substantial gaps existed among previous estimates of China's HFC-152a emissions. Using the atmospheric observations and inverse modeling, this study reveals China's HFC-152a emissions of 9.4 ± 1.7 Gg/yr (gigagrams per year), 10.6 ± 1.8 Gg/yr, and 9.7 ± 1.5 Gg/yr in 2018, 2019, and 2020, respectively. In addition, we display an overall increasing trend during 2011-2020, which is in contrast to the decreasing and steady trend reported by the Emission Database for Global Atmospheric Research (EDGAR) and the Chinese government, respectively. Subsequently, we establish a comprehensive bottom-up emission inventory matching with top-down estimates and thus succeed in explaining the gaps among previous estimates. Furthermore, the contribution of China's emissions to global HFC-152a emission growth increased from 15% during 2001-2010 to >100% during 2011-2020. An emission projection based on our improved inventory shows that the Kigali Amendment (KA) would assist in avoiding 1535.6-4710.6 Gg (251.8-772.5 Tg CO2-eq) HFC-152a emissions during 2024-2100. Our findings indicate relatively accurate China's HFC-152a emissions and provide scientific support for addressing climate change and implementing the KA.

Cardiac related pleural effusions: a narrative review.

Background and Objective: Pleural effusions (PEs) are commonly seen in various pathologies and have a significant impact on patient health and quality of life. Unlike for malignant PEs, non-malignant PEs (NMPEs) do not have well-established guidelines. Much of the evidence base in this field is from a handful of randomised controlled trials (RCTs) and the majority are from retrospective cohort analyses and cases series. Cardiac related PEs fall within the entity of NMPEs and the aim of this narrative review is to gather the existing evidence in the field of congestive heart failure (CHF), pericarditis and post-cardiac injury syndrome (PCIS). This narrative review investigates the pathophysiology, diagnostic criteria and treatment options for the various cause of cardiac related PEs. Methods: This narrative review is based on a comprehensive literature search analysing RCTs, prospective and retrospective cohort analyses and published case series. Key Content and Findings: CHF related PEs have a substantial mortality rate and carry a worse prognosis if the PEs are bilateral and transudative in nature. Light's criteria have often shown to misclassify transudative effusions in CHF (pseudo-exudates) and hence measuring serum-pleural albumin gradient is an invaluable tool to accurately identify transudates. Elevated serum and pleural N-terminal pro-B type natriuretic peptide (NT-proBNP) has shown increasing evidence of correctly identifying PEs secondary to CHF. However, they should be considered with the pre-test probability of CHF. Therapeutic thoracentesis and indwelling pleural catheter (IPC) placement may be necessary if medical management has failed. PEs can also occur secondary to pericarditis and are often small, bilateral and exudative. PCIS also results in PEs and are commonly seen in post-coronary artery bypass graft (CABG) surgery. Both entities need management of the underlying cause first, but in cases where PEs are refractory, individualised pleural interventions may be necessary. Conclusions: This comprehensive narrative review provides valuable insights into the aetiology, diagnosis and management of PEs secondary to CHF, pericarditis and PCIS. The aim is to enhance the clinicians' knowledge of this complex and controversial topic to improve patient care of cardiac-related PEs. Ongoing trials in this field will be able to provide valuable insights.

Machine Learning Model for Readmission Prediction of Patients With Heart Failure Based on Electronic Health Records: Protocol for a Quasi-Experimental Study for Impact Assessment.

BACKGROUND: Care for patients with heart failure (HF) causes a substantial load on health care systems where a prominent challenge is the elevated rate of readmissions within 30 days following initial discharge. Clinical professionals face high levels of uncertainty and subjectivity in the decision-making process on the optimal timing of discharge. Unwanted hospital stays generate costs and cause stress to patients and potentially have an impact on care outcomes. Recent studies have aimed to mitigate the uncertainty by developing and testing risk assessment tools and predictive models to identify patients at risk of readmission, often using novel methods such as machine learning (ML). OBJECTIVE: This study aims to investigate how a developed clinical decision support (CDS) tool alters the decision-making processes of health care professionals in the specific context of discharging patients with HF, and if so, in which ways. Additionally, the aim is to capture the experiences of health care practitioners as they engage with the system's outputs to analyze usability aspects and obtain insights related to future implementation. METHODS: A quasi-experimental design with randomized crossover assessment will be conducted with health care professionals on HF patients' scenarios in a region located in the South of Sweden. In total, 12 physicians and nurses will be randomized into control and test groups. The groups shall be provided with 20 scenarios of purposefully sampled patients. The clinicians will be asked to take decisions on the next action regarding a patient. The test group will be provided with the 10 scenarios containing patient data from electronic health records and an outcome from an ML-based CDS model on the risk level for readmission of the same patients. The control group will have 10 other scenarios without the CDS model output and containing only the patients' data from electronic medical records. The groups will switch roles for the next 10 scenarios. This study will collect data through interviews and observations. The key outcome measures are decision consistency, decision quality, work efficiency, perceived benefits of using the CDS model, reliability, validity, and confidence in the CDS model outcome, integrability in the routine workflow, ease of use, and intention to use. This study will be carried out in collaboration with Cambio Healthcare Systems. RESULTS: The project is part of the Center for Applied Intelligent Systems Research Health research profile, funded by the Knowledge Foundation (2021-2028). Ethical approval for this study was granted by the Swedish ethical review authority (2022-07287-02). The recruitment process of the clinicians and the patient scenario selection will start in September 2023 and last till March 2024. CONCLUSIONS: This study protocol will contribute to the development of future formative evaluation studies to test ML models with clinical professionals. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/52744.

A new approach for heart disease detection using Motif transform-based CWT's time-frequency images with DenseNet deep transfer learning methods.

OBJECTIVES: Electrocardiogram (ECG) signals are extensively utilized in the identification and assessment of diverse cardiac conditions, including congestive heart failure (CHF) and cardiac arrhythmias (ARR), which present potential hazards to human health. With the aim of facilitating disease diagnosis and assessment, advanced computer-aided systems are being developed to analyze ECG signals. METHODS: This study proposes a state-of-the-art ECG data pattern recognition algorithm based on Continuous Wavelet Transform (CWT) as a novel signal preprocessing model. The Motif Transformation (MT) method was devised to diminish the drawbacks and limitations inherent in the CWT, such as the issue of boundary effects, limited localization in time and frequency, and overfitting conditions. This transformation technique facilitates the formation of diverse patterns (motifs) within the signals. The patterns (motifs) are constructed by comparing the amplitudes of each individual sample value in the ECG signals in terms of their largeness and smallness. In the subsequent stage, the obtained one-dimensional signals from the MT transformation were subjected to CWT to obtain scalogram images. In the last stage, the obtained scalogram images were subjected to classification using DenseNET deep transfer learning techniques. RESULTS AND CONCLUSIONS: The combined approach of MT + CWT + DenseNET yielded an impressive success rate of 99.31 %.

The Clinical Impact and Good Practices of Remote Patient Monitoring for Chronic Heart Failure: A French Case Report.

Purpose: Remote patient monitoring (RPM) can improve the management of chronic diseases. Since 2019, RPM in chronic heart failure (CHF) management has been internationally supported. However, evidence on the clinical impact and good practices of RPM is scarce. We present a case of a patient with CHF that used RPM in France. Patients and Methods: A 74-year-old male was diagnosed with CHF (NYHA I) at the AP-HP Cochin Hospital in January 2020. He faced repetitive hospitalizations for acute heart failure and acute kidney injury. The causes of these acute episodes were unknown. Three therapeutic interventions were implemented (diuretic treatment, RPM and therapeutic education sessions). The patient answered questionnaires regularly and directly through the RPM web application named Satelia®Cardio. Therapeutic education was provided to instruct the patient about his symptoms and treatment management. Results: Since November 11, 2020, the patient had seven hospitalizations representing a total length of stay of 76 days over a period of 15 months and 2 weeks. Pericarditis was diagnosed as a potential cause and a pre-operative checkup was performed. No tangible benefits were found with diuretic treatment and therapeutic education since they had no effect on stopping the acute episodes leading to hospitalization. RPM did not trigger any clinical alerts until his last hospitalization. During this stay, a clinical telehealth nurse reviewed the patient's clinical setup and found that his initial baseline weight was incorrectly inputted. Since amending this, there were no new episodes. A high-risk, complex and costly heart surgery for pericardial decortication was avoided, and patient satisfaction has increased. Conclusion: To respect good practices, inclusion not only involves adding or registering a patient to a telehealth activity and database but involves redesigning the management and pathway of patients in order to conduct periodic and personalized clinical care via integrated technology into routine care.

Sound Touch Elastography for Noninvasive Assessment of Liver Stiffness in Patients With Chronic Heart Failure.

Heart failure (HF) can damage various organs, including the liver, a phenomenon known as "cardiohepatic syndrome." The latter is characterized by liver congestion and hepatic artery hypoperfusion, which can lead to liver damage. In this study, we aimed to assess liver damage quantitatively in chronic HF (CHF) with sound touch elastography (STE). A total of 150 subjects were enrolled, including HF with reduced ejection fraction (HFrEF) groups (left ventricular ejection fraction ≤40%, n = 45), HF with mildly reduced ejection fraction (HFmrEF) groups (left ventricular ejection fraction between 41% and 49%, n = 40), and right-sided HF (RHF) groups (n = 25); normal groups (n = 40). Liver stiffness measurement (LSM) was performed in all subjects by STE. The other hepatic parameters were also measured. The LSM was 5.4 ± 1.1 kPa in normal subjects and increased slightly to 5.9 ± 0.7 kPa in patients with HFmrEF. However, the HFrEF and RHF groups had significantly higher LSMs of 8.4 ± 2.0 kPa and 10.3 ± 2.7 kPa, respectively. The LSM of HFrEF was significantly higher than that of HFmrEF, whereas the increase in LSM in patients with RHF was significant relative to HFmrEF and HFrEF. In addition, the other parameters showed abnormal values in only RHF and HFrEF. In conclusion, STE is a useful clinical technique for the noninvasive evaluation of liver stiffness associated with CHF, which could help patients with CHF manage their treatment regimens.

Influenza Vaccine Effectiveness Pre-pandemic Among Adults Hospitalized With Congestive Heart Failure or Chronic Obstructive Pulmonary Disease and Older Adults.

BACKGROUND: Data are limited on influenza vaccine effectiveness (VE) in the prevention of influenza-related hospitalizations in older adults and those with underlying high-risk comorbidities. METHODS: We conducted a prospective, test-negative, case-control study at 2 US hospitals from October 2018-March 2020 among adults aged ≥50 years hospitalized with acute respiratory illnesses (ARIs) and adults ≥18 years admitted with congestive heart failure (CHF) or chronic obstructive pulmonary disease (COPD) exacerbations. Adults were eligible if they resided in 1 of 8 counties in metropolitan Atlanta, Georgia. Nasopharyngeal and oropharyngeal swabs were tested using BioFire FilmArray (bioMérieux, Inc.) respiratory panel, and standard-of-care molecular results were included when available. Influenza vaccination history was determined from the Georgia vaccine registry and medical records. We used multivariable logistic regression to control for potential confounders and to determine 95% confidence intervals (CIs). RESULTS: Among 3090 eligible adults, 1562 (50.6%) were enrolled. Of the 1515 with influenza vaccination history available, 701 (46.2%) had received vaccination during that season. Influenza was identified in 37 (5.3%) vaccinated versus 78 (9.6%) unvaccinated participants. After adjustment for age, race/ethnicity, immunosuppression, month, and season, pooled VE for any influenza-related hospitalization in the eligible study population was 63.1% (95% CI, 43.8-75.8%). Adjusted VE against influenza-related hospitalization for ARI in adults ≥50 years was 55.9% (29.9-72.3%) and adjusted VE against influenza-related CHF/COPD exacerbation in adults ≥18 years was 80.3% (36.3-93.9%). CONCLUSIONS: Influenza vaccination was effective in preventing influenza-related hospitalizations in adults aged ≥50 years and those with CHF/COPD exacerbations during the 2018-2020 seasons.

Increased expression of protein tyrosine phosphatase nonreceptor type 22 alters early T-cell receptor signaling and differentiation of CD4+ T cells in chronic heart failure.

CD4+ T-cell counts are increased and activated in patients with chronic heart failure (CHF), whereas regulatory T-cell (Treg) expansion is inhibited, probably due to aberrant T-cell receptor (TCR) signaling. TCR signaling is affected by protein tyrosine phosphatase nonreceptor type 22 (PTPN22) in autoimmune disorders, but whether PTPN22 influences TCR signaling in CHF remains unclear. This observational case-control study included 45 patients with CHF [18 patients with ischemic heart failure versus 27 patients with nonischemic heart failure (NIHF)] and 16 non-CHF controls. We used flow cytometry to detect PTPN22 expression, tyrosine phosphorylation levels, zeta-chain-associated protein kinase, 70 kDa (ZAP-70) inhibitory residue tyrosine 292 and 319 phosphorylation levels, and CD4+ T cell and Treg proportions. We conducted lentivirus-mediated PTPN22 RNA silencing in isolated CD4+ T cells. PTPN22 expression increased in the CD4+ T cells of patients with CHF compared with that in controls. PTPN22 expression was positively correlated with left ventricular end-diastolic diameter and type B natriuretic peptide but negatively correlated with left ventricular ejection fraction in the NIHF group. ZAP-70 tyrosine 292 phosphorylation was decreased, which correlated positively with PTPN22 overexpression in patients with NIHF and promoted early TCR signaling. PTPN22 silencing induced Treg differentiation in CD4+ T cells from patients with CHF, which might account for the reduced frequency of peripheral Tregs in these patients. PTPN22 is a potent immunomodulator in CHF and might play an essential role in the development of CHF by promoting early TCR signaling and impairing Treg differentiation from CD4+ T cells.

Effectiveness of Heart Failure Checklist Management in Patients with Chronic Heart Failure: An Open-Label, Single-Center Controlled Study During 18 Months of Follow-Up.

Background: The efficacy of chronic heart failure (CHF) checklist management in reducing adverse outcomes of heart failure patients is still uncertain. This study explores whether CHF checklist management is more useful than usual care in reducing adverse health outcomes in the medium- and long-term among CHF patients. Methods: In our prospective study, 132 patients with CHF were randomly assigned to CHF management group and usual care group by random number method. Patients in CHF management group were conducted through CHF checklist by cardiologists and general practitioner. Patients assigned to usual care were treated by non-stationary medical group without checklist. All groups were followed up for 18 months. Results: There was no significant difference in overall mortality rate between management group and control group during 18 months (12.3% [8/65] vs. 11.7% [7/60], P = 0. 912]). The re-hospitalization rate of heart failure in management group (18.5% [12/65]) was significantly lower than that in usual care group (38.3% [23/60]) after 18 months of follow-up (P = 0.013). Median NT-proBNP level (632.3 ng/l vs. 1678 ng/l, p = 0.004) was lower in management group than that in usual care group. Cardiac ultrasonography was performed at 18 months between the management and usual care group. LVEDD (55.88±7.11 mm vs. 60.92±8.06 mm) and LVESD (43.25±8.42mm vs. 48.41± 9.02mm) were decreased (P<0.01). LVEF was increased (45.36±10.64% vs. 39.96 ±10.15%, P<0.01). The utilization rate of ACEI/ARB/ARNI, ß-blocker were high in management group. Conclusion: CHF checklist management by cardiologists and general practitioners can significantly reduce the re-hospitalization and improve cardiac function. CHF management through heart failure checklist may improve prognosis in patients with CHF in the medium- and long-term.

[Ways for reducing mortality from cardiovascular diseases: A review].

Ways for reducing mortality from cardiovascular diseases The article analyzes the possible ways to further reduce cardiovascular disease mortality in the Russian Federation by eliminating shortcomings and pitfalls, introducing known but not used opportunities, and new organizational and medical technologies based on the accumulated experience of "best practice".

Mineralocorticoid receptor antagonists for chronic heart failure: a meta-analysis focusing on the number needed to treat.

Aims: Recent studies have shown that mineralocorticoid receptor antagonists (MRAs) can decrease mortality in patients with heart failure; however, the application of MRAs in current clinical practice is limited because of adverse effects such as hyperkalemia that occur with treatment. Therefore, this meta-analysis used the number needed to treat (NNT) to assess the efficacy and safety of MRAs in patients with chronic heart failure. Methods: We meta-analysed randomized controlled trials (RCTs) which contrasted the impacts of MRAs with placebo. As of March 2023, all articles are published in English. The primary outcome was major adverse cardiovascular events (MACE), and secondary outcomes included all-cause mortality, cardiovascular death, myocardial infarction (MI), stroke, and adverse events. Results: We incorporated seven studies with a total of 9,056 patients, 4,512 of whom received MRAs and 4,544 of whom received a placebo, with a mean follow-up period of 2.1 years. MACE, all-cause mortality, and cardiovascular mortality were all reduced by MRAs, with corresponding numbers needed to treat for benefit (NNTB) of 37, 28, and 34; as well as no impact on MI or stroke. MRAs increased the incidence of hyperkalemia and gynecomastia, with the corresponding mean number needed to treat for harm (NNTH) of 18 and 52. Conclusions: This study showed that enabling one patient with HF to avoid MACE required treating 37 patients with MRAs for 2.1 years. MRAs reduce MACE, all-cause mortality, and cardiovascular death; however, they increase the risk of hyperkalemia and gynecomastia.