Objective:To retrieve and analyze the evidence related to perioperative blood glucose management in patients with coronary heart disease (CHD) complicated by diabetes undergoing percutaneous coronary intervention (PCI) , and provide clinical guidance for glucose management.Methods:Systematic searches were conducted on domestic and international guideline websites, evidence-based databases, primary research databases, and related association websites for evidence concerning perioperative blood glucose management for this patient group. The search included clinical decisions, guidelines, expert consensus, evidence summaries, and systematic reviews, covering the time span from database inception to February 2022. Two evidence-trained researchers independently conducted literature quality assessments and evidence extraction, with disputes resolved by a third party.Results:Eighteen articles were included: one clinical decision, nine guidelines, and eight expert consensuses. The findings were summarized into eight aspects: team formation and training, admission assessment and treatment, blood glucose control targets, preoperative glucose management, intraoperative glucose management, postoperative glucose management, perioperative abnormal glucose management, and discharge management, totaling 35 evidence points.Conclusions:This study consolidates evidence related to perioperative blood glucose management for patients with CHD complicated by diabetes undergoing PCI. However, during the evidence translation and application process, conditions of the application site, medical resources, and patient preferences should be fully considered. After assessing the feasibility and applicability of the evidence, a personalized blood glucose management plan should be developed for the patient, aiming to improve blood glucose levels and prognosis.

Ultrasound has become the optimal imaging method for prenatal screening,whereas the operator dependence and high imaging variability may affect the accuracy of results and examination efficiency.Applied in segmentation and recognition tasks in images,deep learning(DL)is able to derive higher-level features from lower-level features,accurately characterize the inherent laws or information features of raw data.The research progresses of DL applicated in prenatal ultrasonic section analysis were reviewed in this article.

Objective To investigate the application of Resourcefulness Scale ( RS) and evaluate its reliability and validity. Methods By five steps of translation, back-translation, comprehension, group discussion and expert discussion, the RS was translated into Chinese and went on cultural debugging. Totals of 330 patients with breast cancer were randomly selected to evaluate the reliability and validity. Results After translation and cultural debugging, the content reliability was 0. 90. The Cronbach′sαof internal consistency of the scale was 0. 825. The retest reliability was 0. 852. The retest reliability within each item was 0. 68-0. 82. The correlation index between the whole scale and each item were 0. 40-0. 66. The correlation index of reflect learning RS and social RS was 0. 432. The Chinese RS exploratory factor extracted two factors, which could explain 80. 22% variables. Conclusions Chinese RS has a high reliability and validity, so it can serve as an evaluation tool for patients with breast cancer.