External validation of a deep learning detection system for glaucomatous optic neuropathy: a real-world multicentre study.

OBJECTIVES: To conduct an external validation of an automated artificial intelligence (AI) diagnostic system using fundus photographs from a real-life multicentre cohort. METHODS: We designed external validation in multiple scenarios, consisting of 3049 images from Qilu Hospital of Shandong University in China (QHSDU, validation dataset 1), 7495 images from three other hospitals in China (validation dataset 2), and 516 images from high myopia (HM) population of QHSDU (validation dataset 3). The corresponding sensitivity, specificity and accuracy of this AI diagnostic system to identify glaucomatous optic neuropathy (GON) were calculated. RESULTS: In validation datasets 1 and 2, the algorithm yielded accuracy of 93.18% and 91.40%, area under the receiver operating curves (AUC) of 95.17% and 96.64%, and significantly higher sensitivity of 91.75% and 91.41%, respectively, compared to manual graders. On the subsets complicated with retinal comorbidities, such as diabetic retinopathy or age-related macular degeneration, in validation datasets 1 and 2, the algorithm achieved accuracy of 87.54% and 93.81%, and AUC of 97.02% and 97.46%, respectively. In validation dataset 3, the algorithm achieved comparable accuracy of 81.98% and AUC of 87.49%, with a sensitivity of 83.61% and specificity of 81.76% on GON recognition specifically in the HM population. CONCLUSIONS: With acceptable generalization capability across varying levels of image quality, different clinical centres, or certain retinal comorbidities, such as HM, the automatic AI diagnostic system had the potential to provide expert-level glaucoma detection.

Effects of Combination of Baoxinkang and Conventional Medicine Intervention on Cardiac Function and Adenylate Metabolism of Heart Failure Rats / 广州中医药大学学报

Objective To evaluate the synergistic effect of Baoxinkang on chronic heart failure ( CHF) rats by observing the effect of the combination of Baoxinkang and conventional medicine intervention on cardiac function and adenylate metabolism. Methods Sixty Sprague-Dawley rats were randomly divided into 6 groups, namely sham-operation group, model group, Baoxinkang group ( Baoxinkang 1 020 mg/kg) , conventional medicine intervention group (metoprolol 10 mg/kg, captopril 5 mg/kg, and digoxin 0.022 5 mg/kg), combination group 1 ( conventional medicine intervention + Baoxinkang 1 020 mg/kg) , and combination group 2 ( conventional medicine intervention + trimetazidine 10 mg/kg) . Abdominal aora was constricted to establish CHF rat model. The rats except for the sham-operation group and model group were given the corresponding medicine according to the experimental design for 6 weeks. Echocardiography ( ECHO) was performed to evaluate the cardiac function of rats. High performance liquid chromatography was utilized to investigate the contents of myocardiac adenylate of adenosine triphosphate ( ATP) , adenosine diphosphate ( ADP) , adenosine monophosphate (AMP) . Total adenylate nucleotide pool (TAN) was equal to ATP+ADP+AMP, energy charge (EC) was equal to ( ATP+0.5 ×ADP) /TAN. Results The results of ECHO showed that the heart size was reduced, left ejection fraction and cardiac output were increased in the combination group 1 compared with the model group and conventional medicine intervention group. The levels of ATP, TAN, and EC were significantly increased, whereas the levels of ADP and AMP were decreased in the combination group 1 (P0.05) . Conclusion Baoxinkang may have some synergistic effect on the improvement of CHF rat cardiac energy metabolism disorder treated by conventional medicine.