ObjectiveTo explore the early clinical outcomes of patients with acute type A aortic dissection and intramural hematoma.MethodsThe clinical data of 61 patients with acute type A aortic dissection or intramural hematoma in our hospital from January 23, 2020 to March 10, 2020 were retrospectively analyzed, including 43 males and 18 females, aged 22-81 (52.1±13.0) years. The patient's time of visit, clinical characteristics and early survival were analyzed. Kaplan-Mier survival curve and log-rank test were used for the survival analysis.ResultsThere were 48 (78.7%) patients diagnosed with acute type A aortic dissection and 13 (21.3%) patients with intramural hematoma; 34 patients received operation and 11 were emergent. The 30-day mortality was 2.9% among the patients receiving operation. There were 48 patients alive and 13 patients dead during the study period. The cumulative survival rates for all the patients on postoperative 1 day, 3 days and 7 days were 93.4%, 86.4% and 77.5%, respectively. The cumulative survival rates for the patients with dissection on postoperative 1 day, 3 days and 7 days were 95.7%, 88.7% and 79.4%, respectively. The cumulative survival rates for the patients with hematoma on postoperative 1 day, 3 days and 7 days were 92.3%, 84.6% and 84.6%, respectively. The difference of survival rates between the two groups was not statistically significant (P>0.05). The cumulative survival rate of all the patients on postoperative 14 days was 74.5%. No statistically significant difference in survival rate on postoperative 14 days was found between patients with intramural hematoma and patients with aortic dissection (P>0.05). The proportions of the patients with unstable hemodynamics were found statistically significant between the survival patients and the dead patients (P<0.05).ConclusionPatients with acute aortic dissection and intramural hematoma who survive to the hospital still have the risk of death under active drug therapy, and rupture of the dissection is the leading cause of death in these patients, especially for those with hemodynamic unstability.
ObjectiveTo systematically evaluate the related factors of constipation in patients with stroke. MethodsCochrane Library, PubMed, Web of Science, Embase, CNKI, VIP, Wanfang and China Biomedical Literature Database were searched by computer, and the retrieval time was set to May 2022. Case-control studies, cohort studies and cross-sectional studies on stroke and constipation were selected. Meta-analysis was performed using RevMan 5.3 software. ResultsA total of 13 studies involving 2 834 patients were included. Meta-analysis showed that age [odds ratio (OR) =2.54, 95% confidence interval (CI) (1.36, 3.73), P<0.001], lesion location [OR=1.98, 95%CI (1.27, 3.11), P=0.003], National Institutes of HealthStroke Scale score [OR=0.40, 95%CI (0.10, 0.70), P=0.010], hemiplegia [OR=4.31, 95%CI (2.59, 7.17), P<0.001], dysphagia [OR=2.32, 95%CI (1.27, 4.25), P=0.006], antidepressants [OR=2.33, 95%CI (1.62, 3.34), P<0.001], BI score [OR=−17.08, 95%CI (−33.07, −1.08), P=0.04], eating pattern [OR=4.18, 95%CI (1.16, 15.09), P=0.030], drinking water volume ≥800 mL [OR=0.30, 95%CI (0.19, 0.46), P<0.001] might be the influencing factors of constipation in patients after stroke. The results of sensitivity analysis showed that age, education level, diabetes, smoking, stroke type, lesion location, diuretic and BI score might be the influencing factors of constipation after stroke (P<0.05). The results of bias analysis suggest that publication bias is less likely. Conclusions There are many risk factors for constipation in patients with stroke. Current evidence shows that age, diabetes, smoking and other 11 factors may be risk factors for stroke constipation, while high education level and drinking water ≥800 mL may be protective factors, and the other influencing factors have not been determined and need further study.
Objective To evaluate the risk factors for postoperative in-hospital mortality in elderly patients receiving cardiac valvular surgery, and develop a new prediction models using the least absolute shrinkage and selection operator (LASSO)-logistic regression. Methods The patients≥65 years who underwent cardiac valvular surgery from 2016 to 2018 were collected from the Chinese Cardiac Surgery Registry (CCSR). The patients who received the surgery from January 2016 to June 2018 were allocated to a training set, and the patients who received the surgery from July to December 2018 were allocated to a testing set. The risk factors for postoperative mortality were analyzed and a LASSO-logistic regression prediction model was developed and compared with the EuroSCOREⅡ. Results A total of 7 163 patients were collected in this study, including 3 939 males and 3 224 females, with a mean age of 69.8±4.5 years. There were 5 774 patients in the training set and 1389 patients in the testing set. Overall, the in-hospital mortality was 4.0% (290/7163). The final LASSO-logistic regression model included 7 risk factors: age, preoperative left ventricular ejection fraction, combined coronary artery bypass grafting, creatinine clearance rate, cardiopulmonary bypass time, New York Heart Association cardiac classification. LASSO-logistic regression had a satisfying discrimination and calibration in both training [area under the curve (AUC)=0.785, 0.627] and testing cohorts (AUC=0.739, 0.642), which was superior to EuroSCOREⅡ. Conclusion The mortality rate for elderly patients undergoing cardiac valvular surgery is relatively high. LASSO-logistic regression model can predict the risk of in-hospital mortality in elderly patients receiving cardiac valvular surgery.
Traditional Chinese medicine equipment plays an indispensable role in the prevention, diagnosis, treatment and rehabilitation of traditional Chinese medicine from the needs of people's life and health, and provides technical support for the simple, convenient, cheap and effective clinical practice of traditional Chinese medicine. The traditional Chinese medicine equipment industry has the development advantages of large demand gap, strong policy support and emerging technology empowerment. At the same time, there are also bottlenecks such as lagging standardization construction, weak industrial foundation, insufficient characteristics of traditional Chinese medicine and immature evidence-based evaluation research. The coming of the era of digital intelligence has brought new opportunities for the development and reform of the traditional Chinese medicine equipment industry. This paper provides development ideas for the transformation of traditional Chinese medicine equipment from traditional to modern from the aspects of standardization construction, digital intelligence industry upgrading, improvement of evidence-based evaluation system and in-depth international exchanges and cooperation.
Evidence-based research in traditional Chinese medicine (TCM) has made many important achievements and promoted the modernization and internationalization of TCM. The ability to produce research evidence to guide clinical practice in an emergency treatment situation is a major test of the development of evidence-based Chinese medicine (EBCM) when emerging infectious diseases outbreaks. Along with the development of EBCM, TCM has experienced emerging infectious disease events such as atypical pneumonia (SARS), influenza A (HIN1), and corona virus disease 2019 (COVID-19), and the ability of TCM to conduct clinical research in emergency treatment work has been continuously improved. This article provides an overview of the clinical research conducted in TCM to resist emerging infectious diseases in the past, focusing on the clinical research results obtained in the present time of COVID-19 rescue and treatment, and discusses the role of EBCM development to enhance the clinical research capacity of TCM in emerging infectious diseases.