Clinical Features of Aortic Dissection in the Emergency Department: A Single-center Experience from South China

Li, Xiangmin; Huang, Guoqing; Wang, Aimin; Zhou, Liping; Mo, Xiaoye; Zhang, Fang‐Jie

doi:10.5811/westjem.2021.7.52525

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…Activated partial thromboplastin time (APTT) is also involved in the coagulation pathway, it is often used to reflect the activity of coagulation factors in the endogenous coagulation pathway. One study demonstrated that higher values of APTT were found in the deceased group of patients with type A aortic dissection [ 20 ]. Therefore, we also collected the preoperative blood APTT levels of the patients and finally concluded that the patients who died during hospitalization had higher APTT levels.…”

Section: Discussionmentioning

confidence: 99%

A novel nomogram model to predict in-hospital mortality in patients with acute type A aortic dissection after surgery

Zhou,

Fan,

Jiang

et al. 2024

J Cardiothorac Surg

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Background Acute type A aortic dissection is a dangerous disease that threatens public health. In recent years, with the progress of medical technology, the mortality rate of patients after surgery has been gradually reduced, leading that previous prediction models may not be suitable for nowadays. Therefore, the present study aims to find new independent risk factors for predicting in-hospital mortality and construct a nomogram prediction model. Methods: The clinical data of 341 consecutive patients in our center from 2019 to 2023 were collected, and they were divided into two groups according to the death during hospitalization. The independent risk factors were analyzed by univariate and multivariate logistic regression, and the nomogram was constructed and verified based on these factors. Results: age, preoperative lower limb ischemia, preoperative activated partial thromboplastin time (APTT), preoperative platelet count, Cardiopulmonary bypass (CPB) time and postoperative acute kidney injury (AKI) independently predicted in-hospital mortality of patients with acute type A aortic dissection after surgery. The area under the receiver operating characteristic curve (AUC) for the nomogram was 0.844. The calibration curve and decision curve analysis verified that the model had good quality. Conclusion: The new nomogram model has a good ability to predict the in-hospital mortality of patients with acute type A aortic dissection after surgery.

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Section: Discussionmentioning

confidence: 99%

A novel nomogram model to predict in-hospital mortality in patients with acute type A aortic dissection after surgery

Zhou,

Fan,

Jiang

et al. 2024

J Cardiothorac Surg

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“…Fan et al discovered that preoperatively elevated SCr is associated with death in patients with ATAAD following surgical treatment ( 34 ). In patients with type A aortic dissection, Li et al revealed that increased blood urea nitrogen levels might be a death risk factor ( 35 ). Our study enhanced the impact of preoperative renal impairment on postoperative hospital death among patients with ATAAD using the two variables, SCr and BUN, as the conventional reference index for evaluating renal function.…”

Section: Discussionmentioning

confidence: 99%

Prediction of in-hospital death following acute type A aortic dissection

Chen

Bai

Liu

et al. 2023

Front. Public Health

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BackgroundOur goal was to create a prediction model for in-hospital death in Chinese patients with acute type A aortic dissection (ATAAD).MethodsA retrospective derivation cohort was made up of 340 patients with ATAAD from Tianjin, and the retrospective validation cohort was made up of 153 patients with ATAAD from Nanjing. For variable selection, we used least absolute shrinkage and selection operator analysis, and for risk scoring, we used logistic regression coefficients. We categorized the patients into low-, middle-, and high-risk groups and looked into the correlation with in-hospital fatalities. We established a risk classifier based on independent baseline data using a multivariable logistic model. The prediction performance was determined based on the receiver operating characteristic curve (ROC). Individualized clinical decision-making was conducted by weighing the net benefit in each patient by decision curve analysis (DCA).ResultsWe created a risk prediction model using risk scores weighted by five preoperatively chosen variables [AUC: 0.7039 (95% CI, 0.643–0.765)]: serum creatinine (Scr), D-dimer, white blood cell (WBC) count, coronary heart disease (CHD), and blood urea nitrogen (BUN). Following that, we categorized the cohort's patients as low-, intermediate-, and high-risk groups. The intermediate- and high-risk groups significantly increased hospital death rates compared to the low-risk group [adjusted OR: 3.973 (95% CI, 1.496–10.552), P < 0.01; 8.280 (95% CI, 3.054–22.448), P < 0.01, respectively). The risk score classifier exhibited better prediction ability than the triple-risk categories classifier [AUC: 0.7039 (95% CI, 0.6425–0.7652) vs. 0.6605 (95% CI, 0.6013–0.7197); P = 0.0022]. The DCA showed relatively good performance for the model in terms of clinical application if the threshold probability in the clinical decision was more than 10%.ConclusionA risk classifier is an effective strategy for predicting in-hospital death in patients with ATAAD, but it might be affected by the small number of participants.

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“…AD may also be clinically silent in many cases. A broad range of symptoms may be related to AD, including acute chest or back pain, cough, shortness of breath, abdominal pain or discomfort, a feeling of fullness, stroke, transient ischemic attack, hoarseness, limb ischemia, and so on [ 1 , 3 ]. Such varied symptoms can easily be missed and misdiagnosed.…”

Section: Introductionmentioning

confidence: 99%

Cerebral Infarction as the Primary Presentation of Acute Aortic Dissection

Zhou¹,

Li²,

Huang³

et al. 2023

Rev. Cardiovasc. Med.

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Background:The aim of this study was to determine the clinical characteristics and outcome of patients with aortic dissection (AD) who present with an initial manifestation of cerebral infarction. Methods: We retrospectively analyzed patients who were diagnosed with AD and admitted to the emergency department from May 1, 2017 to May 1, 2022. Data was collected for variables including age, sex, clinical manifestation, past medical history, and laboratory test results. Results: Twenty-five patients (2.61%, 22 type A and 3 type B) showed cerebral infarction as the primary presentation for acute AD, while another 933 AD patients (471 type A and 462 type B) who presented with other symptoms served as the control group. Eighteen of the 25 patients (72%) were initially diagnosed with stroke, and the diagnosis of AD was missed. However, patients with a missed diagnosis of AD did not have significantly different mortality to those in whom AD was diagnosed (chi-square test, p > 0.9999). Patients with cerebral infarction as the first presentation had a higher incidence of type A AD than the control patients (p = 0.0002), while their mortality rate was also higher than the control group of AD patients (p < 0.0001). Furthermore, patients with cerebral infarction as the first presentation were more likely to have multiple organ dysfunction. Conclusions: AD with an initial presentation of cerebral infarction is a rare condition with high mortality. However, the initial failure to diagnose AD does not further increase patient mortality.

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Clinical Features of Aortic Dissection in the Emergency Department: A Single-center Experience from South China

Cited by 3 publications

References 22 publications

A novel nomogram model to predict in-hospital mortality in patients with acute type A aortic dissection after surgery

A novel nomogram model to predict in-hospital mortality in patients with acute type A aortic dissection after surgery

Prediction of in-hospital death following acute type A aortic dissection

Cerebral Infarction as the Primary Presentation of Acute Aortic Dissection

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