ArticleJournal of thoracic disease2024
The value of anxiety and depression in predicting physical function and major adverse cardiovascular events in patients with acute coronary syndrome.
Article in Journal of thoracic disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- The Hidden Burden of Depression in STEMI: Effects on Early Complications and 12-Month MACCE.Diagnostics (Basel, Switzerland) · 2026Article
- Therapeutic efficacy and safety of Shexiang Baoxin Pill in relation to anxiety and depression in patients with coronary heart disease.Medicine · 2026Article
- Post-percutaneous coronary intervention psychological disorders predict poor adherence and cardiovascular events in elderly heart failure patients.World journal of psychiatry · 2025Article
- Ambient ammonium exposure is associated with physical dysfunction in older adults in China.Scientific reports · 2025Article
- Correlation of blood lipids, glucose, and inflammatory indices with the occurrence and prognosis of lesion complexity in unstable angina, a retrospective cohort study.Journal of thoracic disease · 2025Article
- Development and Validation of a Machine Learning Model for Predicting Long-Term Depression Risk in ACS Patients After PCI: A Retrospective Cohort Study.International journal of general medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Psychological distress, including anxiety and depression, is not only prevalent in patients with coronary heart disease (CHD) but can actually predict adverse clinical events. Therefore, the necessity of addressing psychological problems among patients with CHD to improve their treatment results is increasingly acknowledged. This study's objective was to examine the prognostic impact of anxiety and depression on major adverse cardiovascular events (MACEs) and physical function among patients with acute coronary syndrome (ACS). Methods: A total of 978 patients admitted to our hospital from September 2021 to September 2022 and diagnosed with severe vascular lesions using coronary angiography were enrolled. According to their scores on the Hospital Anxiety and Depression Scale (HADS) and the Center for Epidemiologic Studies Depression Scale at admission, they were divided into two groups and four subgroups: an anxiety group, a non-anxiety group, a depression group, and a non-depression group. The participants' baseline information, clinical characteristics, coronary angiography findings, MACEs, and changes in physical functionality were compared. Results: There were statistically significant differences between the anxiety and depression groups in marital status, education level, history of diabetes, clinical diagnosis, cardiac troponin T (cTnI), B-type natriuretic peptide (BNP), coronary angiography, and synergy between percutaneous coronary intervention with taxus and cardiac surgery (SYNTAX) score. Logistic regression analysis showed that gender, education level, diabetes history, cTnI, and SYNTAX score were risk factors for anxiety, while education level, diabetes, and SYNTAX score were risk factors for depression. A Kaplan-Meier survival curve model was used to analyze survival rates in the anxiety and depression groups. Hierarchical regression analyses of anxiety and depression at baseline predicted significant declines in physical functionality. Conclusions: Social support improved physical functionality and reduced the impact of psychological distress. Psychological state had the greatest long-term prognostic value in patients with CHD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.