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BREVOC Study: Exhaled VOCs for High-Risk Chest Pain in the ED

Qilu Hospital of Shandong University · 2026
ClinicalTrials.gov · Datasets · License: Public Domain · 2026
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acute-coronary-syndromeaortic-dissectionpulmonary-embolismvolatile-organic-compounds
Study Objectives 1. Screening and identification of diagnostic biomarkers: To establish the exhaled volatile organic compound (VOC) profile of patients with acute high-risk chest pain and to differentiate high-risk chest pain patients. 2. Exploration of aldehyde detection: To investigate the role of exhaled aldehyde detection in high-risk chest pain patients; to establish and validate an early differential diagnostic model of exhaled VOCs for high-risk chest pain, thereby optimizing emergency triage procedures. 3. Prognostic evaluation: To assess the predictive value of VOC concentration changes for in-hospital mortality and major adverse cardiovascular events (MACE) in high-risk chest pain patients. 4. Novel diagnostic markers: To explore new biomarker combinations superior to conventional diagnostic indicators. Study Hypotheses 1. High-risk chest pain patients present a VOC profile distinct from that of healthy individuals and patients with other causes of chest pain. 2. Baseline levels and early changes of exhaled VOCs can achieve both rapid diagnosis and risk stratification. 3. Exhaled VOCs can predict the prognosis of high-risk chest pain patients. Sample Size Calculation This is an exploratory study, aiming to enroll all patients presenting with acute chest pain to the emergency department of our hospital between May 2025 and June 2026. Based on prior studies, the primary endpoint is assessed using area under the receiver operating characteristic curve (AUC-ROC) analysis, with α = 0.05 and 1-β = 0.90. The expected model AUC is 0.75, compared to a minimum acceptable AUC of 0.65. Assuming a group ratio of 1:2 (high-risk: non-high-risk), Power Analysis and Sample Size (PASS) software estimates a minimum sample size of approximately 1,320 patients. To enable subgroup analyses (e.g., acute coronary syndrome \[ACS\], pulmonary embolism \[PE\], aortic dissection \[AD\]) and the construction of multivariable predictive models, at least 150-300 patients per subgrou
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