OBJECTIVE: As the incidence of heart failure (HF) increases, the need for practical tools to evaluate the long-term prognosis in these patients remains critical. Our study aimed to develop a 48 month prediction model for all-cause mortality in decompensated HF patients using available clinical indicators.
METHODS: HF patients (n = 503), 60 years or older, were divided into a training cohort (n = 402) and a validation cohort (n = 101). Data on demographics, comorbidities, laboratory results and medications were gathered. Prediction models were developed using the Prognostic Nutritional Index (PNI), cholinesterase (ChE) and a multifactorial nomogram incorporating clinical variables. These models were constructed using the least absolute shrinkage and selection operator algorithm and multivariate logistic regression analysis. The performance of the model was assessed in terms of calibration, discrimination and clinical utility.
RESULTS: The mean age was 77.11 ± 8.85 years, and 216 (42.9%) were female. The multifactorial nomogram included variables of ChE, lymphocyte count, albumin, serum creatinine and N-terminal pro-brain natriuretic peptide (all P < 0.05). In the training cohort, the nomogram\'s C-index was 0.926 [95% confidence interval (CI) 0.896-0.950], outperforming the PNI indices at 0.883 and ChE at 0.804 (Z-tests, P < 0.05). The C-index in the validation cohort was 0.913 (Z-tests, P < 0.05). Calibration and decision curve analysis confirmed model reliability, indicating a more significant net benefit than PNI and ChE alone.
CONCLUSIONS: Both the ChE- and PNI-based prediction models effectively predict the long-term prognosis in patients over 60 years of age with decompensated HF. The multifactorial nomogram model shows superior performance, improving clinical decision-making and patient outcomes.

UNASSIGNED: To investigate the relationship between red blood cell (RBC) folate and congestive heart failure (CHF).
UNASSIGNED: We extracted the concentrations of RBC folate and collated CHF information from the National Health and Nutrition Examination Survey (NHANES) survey (12820 individuals). Weighted univariate logistic regression, weighted multivariate logistic regression, and restrictive cubic spline (RCS) were used to assess the relationship between RBC folate concentrations and CHF.
UNASSIGNED: The unadjusted model showed that the highest tertile group of RBC folate concentration was significantly associated with a higher risk of CHF compared to the lowest tertile group of RBC folate levels (odds ratio [OR] = 3.09; 95% confidence interval [CI], 2.14-4.46). Similar trends were seen in the multivariate-adjusted analysis (OR = 1.98; 95% CI: 1.27-3.09). The OR was > 1.0 when the predicted RBC folate exceeded 2757 nmol/L in the RCS model, indicating that the risk of CHF was low and relatively stable up to a predicted RBC folate level of 2757 nmol/L, but began to increase rapidly thereafter (p = 0.001).
UNASSIGNED: The risk of CHF may be increased either by high RBC folate concentrations (highest tertile of RBC folate or > 2637 nmol/L) or by folate deficiency. Considering the two sides of the association between RBC folate and CHF, there is a need for large-scale clinical research to better investigate if the association between RBC folate and CHF is a cause-effect relationship, what are the underlying pathophysiological basis, as well as to identify optimal dietary folate equivalent (DFE) and RBC folate concentration intervals.

OBJECTIVE: Iron deficiency is a major public health concern. We aimed to assess the predictive capability of 4 iron metabolism biomarkers for all-cause and cardiovascular disease-specific mortality in U.S. patients with congestive heart failure (CHF).
RESULTS: 1904 CHF patients aged ≥20 years were enrolled from NHANES, 1999-2000 to 2017-2018. All analyses were weighted to provide nationally representative estimates. Among 1905 CHF patients, mean age was 71 years, and 1024 (53.8%), 459 (24.1%), 206 (10.8%), and 216 (11.3%) were Non-Hispanic Black, Non-Hispanic White, Hispanic-Mexican American, and Hispanic-Other Hispanic, respectively. During follow-ups, 1080 deaths occurred. Median follow-up time was 5.08 years. Per-unit increase in natural-logarithmic-transformed iron and transferrin saturation decreased all-cause mortality risk separately by 33.0% (adjusted hazard ratio: 0.670, 95% confidence interval: 0.563 to 0.797, P < 0.001) and 32.6% (0.674, 0.495 to 0.917, 0.013), and per-unit increase in transferrin receptor increased mortality risk by 33.7% (1.337, 1.104 to 1.618, 0.004). Two derivates from 3 significant iron biomarkers were generated - transferrin receptor to natural-logarithmic-transformed iron ratio (TRI) and transferrin receptor to natural-logarithmic-transformed transferrin saturation ratio (TRTS), which were significantly associated with all-cause mortality, with per-unit increase corresponding to 2.692- and 1.655-fold increased all-cause mortality risk (P: 0.003 and 0.023). Only iron and TRTS were associated with the significant risk of cardiovascular disease-specific mortality (P: 0.004 and 0.017).
CONCLUSIONS: Our findings identified 3 iron metabolism biomarkers that were individually, significantly, and independently associated with all-cause mortality in patients with CHF, and importantly 2 derivates generated exhibited stronger predictive capability.

BACKGROUND: While previous population studies have shown that higher triglyceride-glucose (TyG) index values are associated with an increased risk of congestive heart failure (CHF), the relationship between TyG and CHF in patients with abnormal glucose metabolism remains understudied. This study aimed to evaluate the association between TyG and CHF in individuals with diabetes and prediabetes.
METHODS: The study population was derived from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018. The exposure variable, TyG, was calculated based on triglyceride and fasting blood glucose levels, while the outcome of interest was CHF. A multivariate logistic regression analysis was employed to assess the association between TyG and CHF.
RESULTS: A total of 13,644 patients with diabetes and prediabetes were included in this study. The results from the fitting curve analysis demonstrated a non-linear U-shaped correlation between TyG and CHF. Additionally, linear logistic regression analysis showed that each additional unit of TyG was associated with a non-significant odds ratio (OR) of 1.03 (95%CI: 0.88-1.22, P = 0.697) for the prevalence of CHF. A two-piecewise logistic regression model was used to calculate the threshold effect of the TyG. The log likelihood ratio test (p < 0.05) indicated that the two-piecewise logistic regression model was superior to the single-line logistic regression model. The TyG tangent point was observed at 8.60, and on the left side of this point, there existed a negative correlation between TyG and CHF (OR: 0.54, 95%CI: 0.36-0.81). Conversely, on the right side of the inflection point, a significant 28% increase in the prevalence of CHF was observed per unit increment in TyG (OR: 1.28, 95%CI: 1.04-1.56).
CONCLUSIONS: The findings from this study suggest a U-shaped correlation between TyG and CHF, indicating that both elevated and reduced levels of TyG are associated with an increased prevalence of CHF.

UNASSIGNED: There hasn\'t been research done on the connection between serum anion gap (AG) levels and long-, medium-, and short-term all-cause mortality in congestive heart failure (CHF) patients. This study aims to investigate the association between serum anion gap levels and all-cause mortality in CHF patients after adjusting for other covariates.
UNASSIGNED: For each patient, we gather demographic information, comorbidities, laboratory results, vital signs, and scoring data using the ICU (Intensive Care Unit) Admission Scoring System from the MIMIC-III database. The connection between baseline AG and long-, medium-, and short-term all-cause mortality in critically ill congestive heart failure patients was investigated using Kaplan-Meier survival curves, subgroup analysis, restricted cubic spline, and Cox proportional risk analysis.
UNASSIGNED: 4840 patients with congestive heart failure in total were included in this study. With a mean age of 72.5 years, these patients had a gender split of 2567 males and 2273 females. After adjusting for other covariates, a multiple regression analysis revealed that, in critically ill patients with congestive heart failure, all-cause mortality increased significantly with rising AG levels. In the fully adjusted model, we discovered that AG levels were strongly correlated with 4-year, 365-day, 90-day, and 30-day all-cause mortality in congestive heart failure patients with HRs (95% CI) of 1.06 (1.04, 1.08); 1.08 (1.05, 1.10); and 1.08 (1.05, 1.11) (p-value < 0.05). Our subgroup analysis\'s findings demonstrated a high level of consistency and reliability. K-M survival curves demonstrate that high serum AG levels are associated with a lower survival probability.
UNASSIGNED: Our research showed the association between CHF patients\' all-cause mortality and anion gap levels was non-linear. Elevated anion gap levels are associated with an increased risk of long-, medium-, and short-term all-cause death in patients with congestive heart failure. Continuous monitoring of changes in AG levels may have a clinical predictive role.

UNASSIGNED: Congestive heart failure (CHF) demonstrates a heightened prevalence in individuals with diabetes mellitus within Intensive Care Units. The occurrence of abnormal chloride levels is frequently observed in critically ill patients, yet its clinical significance remains subject to debate. This study endeavors to explore the relationship between serum chloride levels and in-hospital mortality among patients affected by both congestive heart failure and diabetes.
UNASSIGNED: A retrospective cohort study was conducted, utilizing data from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database, focusing on adult patients in the United States. The impact of serum chloride levels upon ICU admission on in-hospital mortality was analyzed using multivariable logistic regression models, generalized additive models and subgroup analysis.
UNASSIGNED: The study encompassed 7,063 patients with coexisting diabetes and congestive heart failure. The fully adjusted model revealed an inverse association between serum chloride levels and in-hospital mortality. As a tertile variable (Q3 vs Q1), the odds ratio (OR) was 0.73 with a 95% confidence interval (CI) of 0.54-0.98 (p = 0.039). As a continuous variable, per 1 mmol/L increment, the OR (95% CI) was 0.97 (0.96-0.99, p = 0.01). The relationship between serum chloride and in-hospital mortality demonstrated linearity (non-linear p = 0.958). Stratified analyses further validated the robustness of this correlation.
UNASSIGNED: Serum chloride levels exhibited a negative association with in-hospital mortality in patients with both congestive heart failure and diabetes. Nevertheless, prospective, randomized, controlled studies are warranted to corroborate and validate the findings presented in this investigation.

UNASSIGNED: Frailty correlates with adverse outcomes in many cardiovascular diseases and is prevalent in individuals with heart failure (HF). The Hospital Frailty Risk Score (HFRS) offers an integrated, validated solution for frailty assessment in acute care settings, but its application in critically ill patients with congestive HF lacks exploration. This study aimed to identify the association between frailty assessed by the HFRS and in-hospital mortality in critically ill patients with congestive HF.
UNASSIGNED: This observational study retrospectively enrolled 12,179 critically ill patients with congestive HF. Data from the Medical Information Mart for Intensive Care IV database was used. The HFRS was calculated to assess frailty. Patients were categorized into three groups: non-frailty (HFRS < 5, n = 7,961), pre-frailty (5 ≤ HFRS < 15, n = 3,684), and frailty (HFRS ≥ 15, n = 534). Outcomes included in-hospital mortality, length of intensive care unit stay, and length of hospital stay. Multiple logistic regression and Locally Weighted Scatterplot Smoothing (LOWESS) smoother were used to investigate the association between frailty and outcomes. Subgroup analysis was employed to elucidate the correlation between frailty levels and in-hospital mortality across diverse subgroups.
UNASSIGNED: 12,179 patients were enrolled, 6,679 (54.8%) were male, and the average age was 71.05 ± 13.94 years. The overall in-hospital mortality was 11.7%. In-hospital mortality increased with the escalation of frailty levels (non-frailty vs. pre-frailty vs. frailty: 9.7% vs. 14.8% vs. 20.2%, P < 0.001). The LOWESS curve demonstrated that the HFRS was monotonically positively correlated with in-hospital mortality. Upon controlling for potential confounders, both pre-frailty and frailty statuses were found to be independently linked to a heightened risk of mortality during hospitalization (odds ratio [95% confidence interval]: pre-frailty vs. non-frailty: 1.27 [1.10-1.47], P = 0.001; frailty vs. non-frailty: 1.40 [1.07-1.83], P = 0.015; P for trend < 0.001). Significant interactions between frailty levels and in-hospital mortality were observed in the following subgroups: race, heart rate, creatinine, antiplatelet drug, diabetes, cerebrovascular disease, chronic renal disease, and sepsis.
UNASSIGNED: In critically ill patients with congestive HF, frailty as assessed by the HFRS emerged as an independent predictor for the risk of in-hospital mortality. Prospective, randomized studies are required to determine whether improvement of frailty levels could improve clinical prognosis.

UNASSIGNED: α-Klotho is a potential biological marker of aging with satisfactory clinical applicability. However, its prognostic significance in age-related diseases has largely been undermined. Therefore, we aimed to report the prognostic value of serum α-klotho levels in age-related diseases.
UNASSIGNED: Participants with available serum α-klotho data from the National Health and Nutrition Examination Survey (2007-2016) were included. Their survival status was collected at 7.62 ± 2.99 years after serum α-klotho data was collected, and the endpoint was all-cause and cardiovascular mortality. A Cox regression model was established to examine the association between serum α-klotho levels and all-cause and cardiovascular mortality.
UNASSIGNED: The present study included 13,746 U.S. adults with a survey-weighted mean age of 56.19 ± 10.42 years old. Of these, 52.2 % were female and 72.9 % were non-Hispanic whites. The optimal cutoff value of serum α-klotho for predicting all-cause mortality risk in the general population was 603.5 pg/ml. Individuals with low serum α-klotho (<603.5 pg/ml) had a significantly higher risk of all-cause (adjusted HR: 1.34(1.18-1.52), P < 0.001) and cardiovascular mortality (adjusted HR: 1.63(1.27-2.10), P < 0.001). Subgroup analysis showed that low serum α-klotho level was an independent risk factor for all-cause and cardiovascular mortality in people with hypertension, congestive heart failure, diabetes mellitus, and emphysema, while it was an independent risk factor for all-cause mortality in patients with renal insufficiency.
UNASSIGNED: A low serum α-klotho concentration (<603.5 pg/ml) could serve as a marker of all-cause and cardiovascular mortality in the general population and in people with age-related diseases, including hypertension, congestive heart failure, diabetes mellitus, and emphysema.

UNASSIGNED: As of 30 April 2023, the COVID-19 pandemic has resulted in over 6.9 million deaths worldwide. The virus continues to spread and mutate, leading to continuously evolving pathological and physiological processes. It is imperative to reevaluate predictive factors for identifying the risk of early disease progression.
UNASSIGNED: A retrospective study was conducted on a cohort of 1379 COVID-19 patients who were discharged from Xin Hua Hospital affiliated with Shanghai Jiao Tong University School of Medicine between 15 December 2022 and 15 February 2023. Patient symptoms, comorbidities, demographics, vital signs, and laboratory test results were systematically documented. The dataset was split into testing and training sets, and 15 different machine learning algorithms were employed to construct prediction models. These models were assessed for accuracy and area under the receiver operating characteristic curve (AUROC), and the best-performing model was selected for further analysis.
UNASSIGNED: AUROC for models generated by 15 machine learning algorithms all exceeded 90%, and the accuracy of 10 of them also surpassed 90%. Light Gradient Boosting model emerged as the optimal choice, with accuracy of 0.928 ± 0.0006 and an AUROC of 0.976 ± 0.0028. Notably, the factors with the greatest impact on in-hospital mortality were growth stimulation expressed gene 2 (ST2,19.3%), interleukin-8 (IL-8,17.2%), interleukin-6 (IL-6,6.4%), age (6.1%), NT-proBNP (5.1%), interleukin-2 receptor (IL-2R, 5%), troponin I (TNI,4.6%), congestive heart failure (3.3%) in Light Gradient Boosting model.
UNASSIGNED: ST-2, IL-8, IL-6, NT-proBNP, IL-2R, TNI, age and congestive heart failure were significant predictors of in-hospital mortality among COVID-19 patients.

Congestive heart failure (CHF) is a multifaceted cardiovascular condition that imposes significant economic and social burdens on society, while also presenting a dearth of efficacious treatment modalities. Long non-coding RNAs (lncRNAs) possess the ability to influence the pathophysiological mechanisms underlying cardiac disease through their regulation of gene transcription, translation, and post-translational modifications. Additionally, certain lncRNAs can be encoded by the mitochondrial genome, hence impacting mitochondrial function. The heart relies heavily on mitochondrial oxidative phosphorylation for approximately 95 % of its ATP production. Consequently, the primary determinant linking mitochondrial dysfunction to heart failure is the impairment of cardiac energy supply resulting from mitochondrial injury. Cardiac dysfunction can arise as a result of various factors, including metabolic disease, disturbances in calcium homeostasis, oxidative stress, apoptosis, and mitochondrial phagocytosis, all of which are facilitated by mitochondrial damage. Currently, an increasing body of research indicates that lncRNA plays a significant role in the regulation of mitochondrial activity, hence impacting heart failure. As a result, the goal of this paper is to propose new ideas and targets for clinical research and therapy of heart failure by reviewing recent research on the regulatory mechanism of mitochondrial function by novel lncRNAs.