Predictive Value of the Serum Cystatin C/Prealbumin Ratio in Combination With NT-proBNP Levels for Long-Term Prognosis in Chronic Heart Failure Patients: A Retrospective Cohort Study

Differences in the Evaluation of Malnutrition and Body Composition Using Bioelectrical Impedance Analysis, Nutritional Ultrasound, and Dual-Energy X-ray Absorptiometry in Patients with Heart Failure

BACKGROUND

Although malnutrition is frequently observed in patients with heart failure (HF), this diagnosis should be performed carefully since HF itself is associated with increased inflammatory activity, which affects body weight, functionality, and some nutritional parameters; thus, its isolated interpretation can erroneously identify surrogate markers of severity as markers of malnutrition. In this context, we aimed to evaluate the prevalence of malnutrition using different classification systems and perform a comprehensive nutritional evaluation to determine the reliability of different diagnostic techniques.

PATIENTS AND METHODS

Eighty-three patients with a recent hospital admission due to HF were evaluated. GLIM diagnosis criteria and subjective global assessment (SGA) were performed; a comprehensive anthropometric, functional, and biochemical nutritional evaluation was performed, in which bioelectrical impedance analysis (BIA), nutritional ultrasound, and dual-energy X-ray absorptiometry (DXA) were performed. Additionally, mortality and additional admissions due to HF were determined after a mean follow up of 18 months.

RESULTS

Malnutrition according to the GLIM criteria (54%) accurately distinguished patients with impaired functionality, lower lean mass, skeletal mass index, and appendicular muscle mass (BIA), as well as lower trunk fat mass, trunk lean mass, fat-free mass (DXA), and decreased albumin and increased C-reactive protein serum levels. According to SGA, there were significant changes in body composition parameters determined by BIA, muscle ultrasound, and functional tests between well-nourished patients and patients with risk of malnutrition (53.7%) or who had malnutrition (7.1%), but not when the last two groups were compared. BIA and DXA showed strong correlations when evaluating muscle and fat mass in HF patients, but correlations with nutritional ultrasound were limited, as well as functional tests. A multivariate analysis showed that no significant association was observed between body composition and mortality, but preperitoneal fat was associated with an increased risk of new hospital admissions (OR: 0.73).

CONCLUSIONS

GLIM criteria identified a lower percentage of patients with HF and malnutrition compared with SGA; thus, SGA could have a role in preventing malnutrition in HF patients. Nutritional evaluation with BIA and DXA in patients with HF showed reliable results of body composition parameters in HF, and both help with the diagnosis of malnutrition according to the GLIM or SGA criteria and could provide complementary information in some specific cases.

Harmony in Chaos: Deciphering the Influence of Ischemic Cardiomyopathy and Non-Cardiac Comorbidities on Holter ECG Parameters in Chronic Heart Failure Patients: A Pilot Study

Background and Objective: In the landscape of heart failure, non-cardiac comorbidities represent a formidable challenge, imparting adverse prognostic implications. Holter ECG monitoring assumes a supplementary role in delineating myocardial susceptibility and autonomic nervous system dynamics. This study aims to explore the potential correlation between Holter ECG parameters and comorbidities in individuals with ischemic cardiomyopathy experiencing heart failure (HF), with a particular focus on the primary utility of these parameters as prognostic indicators. Materials and Methods: In this prospective inquiry, a cohort of 60 individuals diagnosed with heart failure underwent stratification into subgroups based on the presence of comorbidities, including diabetes, chronic kidney disease, obesity, or hyperuricemia. Upon admission, a thorough evaluation of all participants encompassed echocardiography, laboratory panel analysis, and 24 h Holter monitoring. Results: Significant associations were uncovered between diabetes and unconventional physiological indicators, specifically the Triangular index (p = 0.035) and deceleration capacity (p = 0.002). Pertaining to creatinine clearance, notable correlations surfaced with RMSSD (p = 0.026), PNN50 (p = 0.013), and high-frequency power (p = 0.026). An examination of uric acid levels and distinctive Holter ECG patterns unveiled statistical significance, particularly regarding the deceleration capacity (p = 0.045). Nevertheless, in the evaluation of the Body Mass Index, no statistically significant findings emerged concerning Holter ECG parameters. Conclusions: The identified statistical correlations between non-cardiac comorbidities and patterns elucidated in Holter ECG recordings underscore the heightened diagnostic utility of this investigative modality in the comprehensive evaluation of individuals grappling with HF. Furthermore, we underscore the critical importance of the thorough analysis of Holter ECG recordings, particularly with regard to subtle and emerging parameters that may be overlooked or insufficiently acknowledged.

The role of serial cardiac biomarkers in prognostication and risk prediction of chronic heart failure: additional scientific insights with hemodynamic feedback

INTRODUCTION

Heart failure (HF) is considered as a chronic long-term and lethal disease and will continue to be a major public health problem. Studying (circulating) biomarkers is a promising field of research and could be the first step toward HF tailored prognostic strategies as well as understanding the response to HF drugs in CHF patients.

AREAS COVERED

In literature, there has been considerable research on elevated biomarker levels that are related to a poor prognosis for HF. Since biomarker levels change over time, it is important to study serial (repeated) biomarker measurements which may help us better understand the dynamic course of HF illness. However, the majority of research focuses predominantly on baseline values of biomarkers. Additionally, remote monitoring devices, like sensors, can be used to link hemodynamic information to freshen biomarker data in order to further ameliorate the management of HF.

EXPERT OPINION

Novel biomarkers and additional scientific insights with hemodynamic feedback strongly aid in the prognostication and risk prediction of chronic HF.

Serum N-terminal pro-B-type natriuretic peptide and cystatin C for acute kidney injury detection in critically ill adults in China: a prospective, observational study

OBJECTIVE

Serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) and cystatin C (sCysC) are available clinically and beneficial in diagnosing acute kidney injury (AKI). Our purpose is to identify the performance of their combined diagnosis for AKI in critically ill patients.

DESIGN

A prospectively recruited, observational study was performed.

SETTING

Adults admitted to the intensive care unit of a tertiary hospital in China.

PARTICIPANTS

A total of 1222 critically ill patients were enrolled in the study.

MAIN OUTCOME MEASURES

To identify the performance of the combined diagnosis of serum NT-proBNP and sCysC for AKI in critically ill patients. The area under the receiver operating characteristic curve (AUC-ROC), category-free net reclassification index (NRI) and incremental discrimination improvement (IDI) were utilised for comparing the discriminative powers of a combined and single biomarker adjusted model of clinical variables enriched with NT-proBNP and sCysC for AKI.

RESULTS

AKI was detected in 256 out of 1222 included patients (20.9%). AUC-ROC for NT-proBNP and sCysC to detect AKI had a significantly higher accuracy than any individual biomarker (p<0.05). After multivariate adjustment, a level of serum NT-proBNP ≥204 pg/mL was associated with 3.5-fold higher odds for AKI compared with those below the cut-off value. Similar results were obtained for sCysC levels (p<0.001). To detect AKI, adding NT-proBNP and sCysC to a clinical model further increased the AUC-ROC to 0.859 beyond that of the clinical model with or without sCysC (p<0.05). Moreover, the addition of these two to the clinical model significantly improved risk reclassification of AKI beyond that of the clinical model alone or with single biomarker (p<0.05), as measured by NRI and IDI.

CONCLUSIONS

In critically ill individuals, serum NT-proBNP, sCysC and clinical risk factors combination improve the discriminative power for diagnosing AKI.

Value of FT3/FT4 Ratio in Prognosis of Patients With Heart Failure: A Propensity-Matched Study

Aims

Abnormal thyroid hormone secretions can alter the manifestation and prognosis of cardiovascular disease. To assess the effect of the free triiodothyronine (FT3)/free thyroxine (FT4) ratio on the prognosis of patients with heart failure (HF), we performed a propensity-matched study on patients with well-balanced baseline characteristics.

Methods

Overall, 8,887 patients with HF were divided into two groups according to the FT3/FT4 ratio. Propensity scores were calculated from each patient. A cohort comprising 2,164 pairs with high or low ratios and with 34 well-balanced baseline characteristics was then assembled. The endpoints were Cardiovascular (CV) mortality and all-cause mortality. The correlation between FT3/FT4 ratio and prognosis was assessed using matched Cox regression analyses. The mean follow-up was 3.3 years.

Results

In the full pre-match cohort, 3,710 (41.7%) patients died, with 2,581 (29.0%) cases of CV mortality. In the matched-pair cohort, all-cause mortality occurred in 923 (1,238/10,000 person-years of follow-up) patients with a high ratio and 1,036 (1,484/10,000 person-years) patients with a low ratio, resulting in a matched HR of 0.841 (95% CI: 0.769-0.919; P < 0.001). For CV mortality, the result was 638 (856/10,000 person-years) and 714 (1,023/10,000 person-years) patients, respectively, resulting in a matched HR of 0.844 (95% CI: 0.759-0.940; P < 0.001). Subgroup analysis revealed that a low FT3/FT4 ratio had a greater predictive value for all-cause and CV mortality in elderly or male patients and in patients with coronary artery disease (CAD), hypertension, diabetes mellitus, HFmrEF, or HFpEF.

Conclusions

A low FT3/FT4 ratio is valuable for predicting CV mortality and all-cause mortality in patients with HF.