No RCT reported on clinically relevant outcome measures - all cause mortality, cardiovascular morbidity and morbidity. There were no significant differences in overall adverse events and withdrawals due to adverse events among the evening versus morning dosing regimens. In terms of BP lowering efficacy, for 24-hour SBP and DBP, the data suggests that better blood pressure control was achieved with bedtime dosing than morning administration of antihypertensive medication, the clinical significance of which is not known.

Stress‐induced hemodynamic and hemostatic responses may acutely trigger atherosclerotic plaque disruption and thrombosis leading to myocardial infarction. This study was designed to evaluate the responses to three stressors and to determine if once‐daily sustained release verapamil (Verelan®) modified these responses. We studied 13 patients with mild to moderate hypertension in a randomized, double‐blind, placebo‐controlled crossover trial. After 4 weeks of therapy, patients were evaluated following assumption of the upright posture, mental stress, and cold pressor test. During placebo, the stressors produced an increase in systolic pressure (144 ± 2 to 167 ± 3 mmHg, p < 0.001), heart rate (70 ± 2 to 77 ± 2 beats/ min, p< 0.001), and platelet aggregability to adenosine diphosphate (threshold concentration fell from 2.8 ± 0.4 to 1.9 ± 0.1 μM, p = 0.05)and epinephrine (3.4±0.9 to 1.6 ±0.6 μM, p < 0.001). Verapamil lowered systolic pressure at baseline (144 ± 2 to 134 ± 2 mmHg, p < 0.001), and after stress (167 ± 3 to 154 < 3 mmHg, p < 0.001), but did not alter the absolute increase with stress. During verapamil, platelet reactivity did not increase with stress, and the post‐stress response to epinephrine was reduced (higher threshold concentration) compared with placebo (3.9 ± 1.3 vs. 1.5 ± 0.3 μM, p = 0.05). Verapamil also reduced the response to collagen (increased lag time) at baseline and after stress (111 ± 9 vs. 91 ± 3 s, p < 0.01). We conclude that verapamil blunted potentially harmful stress‐induced hemodynamic and hemostatic changes. Further studies are required to determine whether these effects translate into a lower incidence of acute cardiovascular events.

Background: Transbronchial cryobiopsy (TBCB) has been widely used to diagnose interstitial lung disease (ILD). Existing reports on TBCB in ILD are mostly single-center prospective or retrospective studies but rarely multicenter prospective real-world studies. We explored the diagnostic efficiency and safety of TBCB in ILD in a real world setting. Methods: A prospective, multicenter, real-world study was conducted to analyze the data of patients with unclarified ILD who underwent TBCB in 20 hospitals in China from October 2018 to October 2019. The results of the pathological and multidisciplinary discussion (MDD) diagnosis and complications related to TBCB were then analyzed.Results: A total of 373 patients were enrolled in this study, including 194 males and 179 females, with an average age of 52.6±12.4 years. None of the patients had severe hemorrhaging, and the incidence of Original Article pneumothorax was 4.8%. The proportions of definitive, possible, and unclassified pathological diagnoses were 62.5%, 5.6%, and 31.9%, respectively. The overall diagnostic yield of MDD was 63.5%. There were 237 patients with a definitive diagnosis of MDD and 136 patients with an unclarified MDD diagnosis.The cooling gas pressure, freezing durations, number of specimens, maximum lengths of specimens, and specimen sizes varied significantly between the definitive and unclarified MDD diagnoses.Conclusions: In China, the application of TBCB in ILD is generally safe, and its diagnostic efficiency is acceptable. Using a 1.9-mm cryoprobe to collect five samples would achieve a better positive diagnostic rate for TBCB in ILD, without a significant increase in complication risk.

This study aimed to analyze the application of the diagnostic model based on deep learning technology in the evaluation of thyroid contrast-enhanced ultrasound images and to provide a reference for the evaluation of benign and malignant thyroid. A diagnosis model of ultrasound images based on long- and short-term memory neural network (LSTM), C-LSTM, was proposed. The diagnostic method was compared with that based on support vector machine (SVM) and manual feature (MF), and it was applied to the diagnosis of thyroid contrast-enhanced ultrasound images. The results showed that the sensitivity, specificity, and accuracy of the C-LSTM model were greatly higher than those of SVM and MF, and the differences were considerable ( P < 0.05 ). The number of parameters and the calculation amount of the C-LSTM model were greatly lower than those of SVM- and MF-based diagnosis methods ( P < 0.05 ). The sensitivity, specificity, and accuracy of the C-LSTM model were greatly greater than those of the C-LSTM-0 model, while the amounts of parameters and calculations were greatly lesser than those of the C-LSTM-0 model ( P < 0.05 ). The numbers of benign tumors with contrast-enhanced ultrasound modes of no enhancement, no enhancement at early stage, and low enhancement were more than those of malignant tumors, while the numbers of high-enhancement tumors were greatly less than those of malignant tumors ( P < 0.05 ). The diagnostic area under the curve (AUC) of rise time (RT) ratio, time to peak (TTP) ratio, and mean transit time (mTT) ratio for malignant masses were large, which were 0.856, 0.794, and 0.761, respectively. RT ratio, TTP ratio, and mTT ratio were of high diagnostic sensitivity and specificity for malignant masses, while RT, TTP, and mTT were of low diagnostic sensitivity and specificity. In summary, the contrast-enhanced ultrasound images based on the deep learning C-LSTM model can effectively improve the diagnostic effect of benign and malignant thyroid masses. The image feature parameters RT ratio, TTP ratio, and mTT ratio were of good efficiency in diagnosing benign and malignant thyroid masses.

Background The current consensus regarding gastric cancer screening in China recommends Li’s Scoring System to assess the risk of gastric cancer. Objectives To compare the predictive capacity of three prediction rules: the ABC method, the Scoring System from the Japan Public Health Center (JPHC), and Li’s Scoring System in Chinese health examination populations. Methods We retrospectively evaluated 1,436 patients undergoing gastroscopy. The patients were classified into three groups (low, medium and high risk) according to each rule. The predictive capacity of three rules to assess the risk of gastric cancer was compared. Results A total of 28 (1.95%) cases with gastric cancer were detected. The Scoring System from JPHC and Li’s Scoring System performed similarly, and the areas under the receiver-operating characteristic (ROC) curves (AUC) were 0.745 (95%CI: 0.722–0.767), and 0.739 (95%CI: 0.715–0.761), respectively. And the AUC for the ABC method was 0.642 (95%CI: 0.617–0.667), significantly lower than that for the Scoring System from JPHC (p < 0.05).Li’s Scoring System had the highest sensitivity, significantly higher than that of the Scoring System from JPHC (85.71% vs 53.57%, p<0.05). Larger proportions of low-risk patients were diagnosed as gastric cancer by the Scoring System from JPHC (1.99%) and ABC method (0.99%) than by Li’s Scoring System (0.55%). Conclusions The Scoring System from JPHC and Li’s Scoring System have a similar performance in assessing the risk of gastric cancer, but Li’s Scoring System is more effective in Chinese health examination populations because of the lowest probability of missed diagnosis.