Assessing myocardial indices and inflammatory factors to determine anxiety and depression severity in patients with chronic heart failure

评估心肌指标和炎症因子以确定慢性心力衰竭患者的焦虑和抑郁严重程度

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Abstract

BACKGROUND: Patients with chronic heart failure (CHF) have a progressive disease that is associated with poor quality of life and high mortality. Many patients experience anxiety and depression (A&D) symptoms, which can further accelerate disease progression. We hypothesized that indicators of myocardial function and inflammatory stress may reflect the severity of A&D symptoms in patients with CHF. Changes in these biomarkers could potentially predict whether A&D symptoms will deteriorate further in these individuals. AIM: To measure changes in cardiac and inflammatory markers in patients with CHF to determine A&D severity and predict outcomes. METHODS: We retrospectively analyzed 233 patients with CHF treated at the Jingzhou Hospital, Yangtze University between 2018-2022 and grouped them according to Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) scores. We compared clinical data in the no-A&D, mild-A&D, moderate-A&D, and severe-A&D groups, the SAS and SDS scores with the New York Heart Association (NYHA) functional classification, and cardiac markers and inflammatory factors between the no/mild-A&D and moderate/severe-A&D groups. Regression analysis was performed on the markers with P < 0.05 to determine their ability to predict A&D severity in patients and the area under the receiver operating characteristic curve (AUROC) was used to evaluate their accuracy. RESULTS: In the inter-group comparison, the following variables had an effect on A&D severity in patients with CHF: NYHA class, left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter, N-terminal pro-brain natriuretic peptide (NT-proBNP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (P < 0.05). Other variables did not differ significantly between the A&D groups (P > 0.05). In addition, we found that higher NYHA classes were associated with higher the SAS and SDS scores (P < 0.05). Regression analysis showed that LVEF, NT-proBNP, and IL-6 were independent risk factors for A&D severity (P < 0.05). Among them, NT-proBNP had the best predictive ability as a single indicator (AUROC = 0.781). Furthermore, the combination of these three indicators exhibited a good predictive effect toward discriminating the extent of A&D severity among patients (AUROC = 0.875). CONCLUSION: Cardiac and inflammatory biomarkers, such as LVEF, NT-proBNP, and IL-6, are correlated with A&D severity in patients with CHF and have predictive value.

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