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Objective:To investigate the application value of aortic dissection detection risk score (ADD-RS) combined with D-dimer (DD) in the early diagnosis of acute aortic dissection (AAD).Methods:The clinical data of 70 patients with suspected aortic dissection detection admitted to The Second Hospital of Jiaxing from August 2019 to April 2020 were collected. All patients were scored using the ADD-RS, and grouped according to the scoring results. The sensitivity and specificity of ADD-RS plus DD in the early diagnosis of AAD were calculated. The areas under the receiver operating characteristic (ROC) curves that were plotted for drADD-RS plus DD versus DD alone to screen AAD were compared to evaluate efficacy. Results:CT angiography results showed that among 70 patients with suspected AAD, 29 patients had AAD and 41 patients had no AAD. A total of 21 patients were scored 0, 41 patients were scored > 1, and 8 patients were scored > 0. ADD-RS > 0 had an overall sensitivity of 79.31% and a specificity of 36.59% for AAD diagnosis. DD test results had an overall sensitivity of 86.20% and a specificity of 36.50% for AAD diagnosis. The area under the ROC curve of ADD-RS = 0 plus DD-negative result and the area under the ROC curve of DD-negative result alone in ruling out AAD were 0.885 with 95% CI (0.786-0.949) and 0.787 with 95% CI (0.673-0.876), respectively. The difference between the two groups was statistically significant ( P = 0.024). Conclusion:Compared with DD-negative result alone, the ADD-RS = 0 plus DD-negative result strategy offers greater specificity to rule out AAD. The combined strategy has a greater efficacy in ruling out AAD. However, a multi-center study involving a large sample is required for in-depth evaluation.
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Objective:To investigate the clinical value of modified acute aortic dissection risk score in the early diagnosis of acute aortic dissection (AAD).Methods:The general, clinical, and imaging data of 162 patients who complained of chest and back pain who received treatment between January 2019 and January 2021 in the Department of Emergency, The Second Hospital of Jiaxing, China were collected for this study. The included patients were divided into control (non-AAD, n = 120) and observation (AAD, n = 42) groups according to whether they were diagnosed with AAD. The indexes with statistical significance between the two groups were analyzed using multivariate logistic regression analysis. A score table was established according to the size of OR value. The modified AAD risk score was predicted using the receiver operating curve. Results:Multivariate logistic regression analysis showed that male sex, family history, sudden severe chest and back pain, bilateral blood pressure asymmetry, hypertension, abnormal ultrasound, and D-dimer level were independent risk factors for the diagnosis of AAD (statistical values = 7.84, 6.96, 7.04, 11.38, 7.12, 8.15, 15.07, 9.11, all P < 0.05). Taking the total score of 5 as the prediction standard, the specificity and sensitivity in the prediction of the occurrence of AAD were 84.94% and 95.43%, respectively. The area under the receiver operating curve regarding the modified AAD risk score was 0.909. Conclusion:The modified AAD risk score can be used to conveniently and quickly predict the occurrence of AAD and has a high predictive value. This study is highly innovative and scientific.
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Anxiety is usually generated because of the threatened feeling. The data of electrocardio, respiration, blood volume pulse and skin conductance signals were collected. The arithmetic of Relief were used for the feature selection and combined with k-Nearest Neighbor (kNN) arithmetic and Support Vector Machine (SVM) arithmetic for classification. The results show that the combination of Relief-SVM is better than combination of Relief-kNN on the recognition of anxiety state. The emotion recognition based on multi-physiological signals is superior to that based on one single signal.