Objective:To explore the risk stratification value of HEART score combined with cardiac troponin (cTn) in emergency patients with chest pain.Methods:A total of 11 583 patients with chest pain who visited the Emergency Department of Zhongshan Hospital Affiliated to Fudan University from January to December 2019 were retrospectively collected. Patients who unfinished 0 h high-sensitivity cardiac troponin T (hs-cTnT) or electrocardiogram diagnosed ST-segment elevation myocardial infarction (STEMI) or lost to follow-up were excluded, and 7 057 patients were finally included. The final diagnosis of chest pain and the occurrence of major adverse cardiovascular events within 6 mon (6 m MACEs) were followed up by telephone and medical history. The HEART score of each patient was calculated by two attending physicians, and the patients were divided into the low-risk group (0-3 points), intermediate-risk group (4-6 points) and high-risk group (7-10 points) according to the final score. The risk stratification performance and safety of HEART score were observed and analyzed. A total of 1 884 patients who completed serial hs-cTnT tests were divided into groups according to HEART score (≤3 as low-risk group) and HEART score combined with serial hs-cTnT pathway (HEART score ≤3 and two hs-cTnT measurements <0.03 ng/mL as the low-risk group). The sensitivity (SE), specificity (SP), positive predictive value (PPV) and negative predictive value (NPV) of each diagnostic method were calculated to compare the diagnostic performance of the two predictive values.Results:The patients were divided into 3 groups by HEART score : 2 765 (39.2%) patients in the low-risk group, 3 438 (48.7%) in the intermediate-risk group, and 854 (12.1%) in the high-risk group. The incidence of 6 m MACEs in each group was 1.2%, 18% and 55.3%, respectively. When the low-risk threshold was 2, 23.1% of patients entered the low-risk group and the incidence of 6 m MACEs was 0.9%. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive performance of the HEART score for 6 m MACEs, and the final AUC was 0.831 ( P=0.006, 95% CI: 0.819-0.843). Regarding the occurrence of NSTEMI at the time of this visit, 4 (0.8%) patients were misdiagnosed by using the HEART score alone. Combined with serial troponin detection, the diagnostic SE and NPV were both 100%; at the same time, the diagnostic SE and NPV of 6 m MACEs in patients increased from 98.1% (95% CI: 96.9%-99.1%), 97.9% (95% CI: 96.2%-99%) to 99.1% (95% CI: 97.9%-99.7%) and 98.9% (95% CI: 97.4%-99.6%), the diagnosis SE and NPV of 6 m myocardial infarction and cardiac death in patients increased from 98% (95% CI: 96%-99.2%), 98.6% (95% CI: 97%-99.4%) to 99.2% (95% CI: 97.6%-99.8%) and 99.3% (95% CI: 98.1%-99.9%). Conclusions:The HEART score can be used for risk assessment in emergency patients with chest pain, and a threshold of 2 is recommended for the low-risk group. The diagnostic performance of HEART score combined with serial cTn is better than that of HEART score alone.

Objective:To investigate the clinical characteristics of patients with acute aortic dissection (AAD) through a retrospective and observational study, and to construct an early warning model of AAD that could be used in the emergency room.Methods:The data of 11 583 patients in the Emergency Chest Pain Center from January to December 2019 were retrospectively collected from the Chest Pain Database of Zhongshan Hospital Affiliated to Fudan University. Inclusion criteria: patients with chest pain who attended the Emergency Chest Pain Center between January and December 2019. Exclusion criteria were 1) younger than 18 years, 2) no chest/back pain, 3) patients with incomplete clinical information, and 4) patients with a previous definite diagnosis of aortic dissection who had or had not undergone surgery. The clinical data of 9668 patients with acute chest/back pain were finally collected, excluding 53 patients with previous definite diagnosis of AAD and/or without surgical aortic dissection. A total of 9 615 patients were enrolled as the modeling cohort for early diagnosis of AAD. The patients were divided into the AAD group and non-AAD group according to whether AAD was diagnosed. Risk factors were screened by univariate and multivariate logistic regression, the best fitting model was selected for inclusion in the study, and the early warning model was constructed and visualized based on the nomogram function in R software. The model performance was evaluated by accuracy, specificity, sensitivity, positive likelihood ratio and negative likelihood ratio. The model was validated by a validation cohort of 4808 patients who met the inclusion/exclusion criteria from January 2020 to June 2020 in the Emergency Chest Pain Center of the hospital. The effect of early diagnosis and early warning model was evaluated by calibration curve.Results:After multivariate analysis, the risk factors for AAD were male sex ( OR=0.241, P<0.001), cutting/tear-like pain ( OR=38.309, P<0.001), hypertension ( OR=1.943, P=0.007), high-risk medical history ( OR=12.773, P<0.001), high-risk signs ( OR=7.383, P=0.007), and the first D-dimer value ( OR=1.165, P<0.001), Protective factors include diabetes( OR=0.329, P=0.027) and coronary heart disease ( OR=0.121, P<0.001). The area under the ROC curve (AUC) of the early diagnosis and warning model constructed by combining the risk factors was 0.939(95 CI:0.909-0.969). Preliminary validation results showed that the AUC of the early diagnosis and warning model was 0.910(95 CI:0.870-0.949). Conclusions:Sex, cutting/tear-like pain, hypertension, high-risk medical history, high-risk signs, and first D-dimer value are independent risk factors for early diagnosis of AAD. The model constructed by these risk factors has a good effect on the early diagnosis and warning of AAD, which is helpful for the early clinical identification of AAD patients.