目的 探讨新诊断早发T2DM患者发生DKD的危险因素.方法 选取 2018 年 1 月至 2021 年 6 月于我院内分泌代谢科住院治疗的新诊断早发T2DM患者 500 例.根据是否合并DKD分为单纯T2DM组(n=402)和DKD组(n=98),Logistic回归分析DKD的危险因素.结果 DKD组合并高血压比例、FPG、FC-P、TG及TG-葡萄糖(TyG)指数高于T2DM组(P<0.05).Spearman相关分析显示,DKD与高血压分级、FC-P、TG及TyG指数呈正相关(P<0.05).Logistic回归分析显示,高血压 2 级、3 级及TyG指数是新诊断早发T2DM患者发生DKD的危险因素.结论 高血压和TyG指数是新诊断早发T2DM患者DKD的危险因素.

ObjectivesTo systematically evaluate the risk prediction models for postoperative delirium in older adult hip fracture patients.MethodsRisk prediction models for postoperative delirium in older adult hip fracture patients were collected from the Cochrane Library, PubMed, Web of Science, and Ovid via the internet, covering studies from the establishment of the databases to March 15, 2023. Two researchers independently screened the literature, extracted data, and used Stata 13.0 for meta-analysis of predictive factors and the Prediction Model Risk of Bias Assessment Tool (PROBAST) to evaluate the risk prediction models for postoperative delirium in older adult hip fracture patients, evaluated the predictive performance.ResultsThis analysis included eight studies. Six studies used internal validation to assess the predictive models, while one combined both internal and external validation. The Area Under Curve (AUC) for the models ranged from 0.67 to 0.79. The most common predictors were preoperative dementia or dementia history (OR = 3.123, 95% CI 2.108–4.626, p < 0.001), American Society of Anesthesiologists (ASA) classification (OR = 2.343, 95% CI 1.146–4.789, p < 0.05), and age (OR = 1.615, 95% CI 1.387–1.880, p < 0.001). This meta-analysis shows that these were independent risk factors for postoperative delirium in older adult patients with hip fracture.ConclusionResearch on the risk prediction models for postoperative delirium in older adult hip fracture patients is still in the developmental stage. The predictive performance of some of the established models achieve expectation and the applicable risk of all models is low, but there are also problems such as high risk of bias and lack of external validation. Medical professionals should select existing models and validate and optimize them with large samples from multiple centers according to their actual situation. It is more recommended to carry out a large sample of prospective studies to build prediction models.Systematic review registrationThe protocol for this systematic review was published in the International Prospective Register of Systematic Reviews (PROSPERO) under the registered number CRD42022365258.

Background: We established a nomogram for ketosis-prone type 2 diabetes mellitus (KP-T2DM) in the Chinese adult population in order to identify high-risk groups early and intervene in the disease progression in a timely manner.Methods: We reviewed the medical records of 924 adults with newly diagnosed T2DM from January 2018 to June 2021. All patients were randomly divided into the training and validation sets at a ratio of 7:3. The least absolute shrinkage and selection operator regression analysis method was used to screen the predictors of the training set, and the multivariable logistic regression analysis was used to establish the nomogram prediction model. We verified the prediction model using the receiver operating characteristic (ROC) curve, judged the model's goodness-of-fit using the Hosmer-Lemeshow goodness-of-fit test, and predicted the risk of ketosis using the decision curve analysis.Results: A total of 21 variables were analyzed, and four predictors-hemoglobin A1C, 2-hour postprandial blood glucose, 2-hour postprandial C-peptide, and age-were established. The area under the ROC curve for the training and validation sets were 0.8172 and 0.8084, respectively. The Hosmer-Lemeshow test showed that the prediction model and validation set have a high degree of fit. The decision curve analysis curve showed that the nomogram had better clinical applicability when the threshold probability of the patients was 0.03-0.79.Conclusion: The nomogram based on hemoglobin A1C, 2-hour postprandial blood glucose, 2-hour postprandial C-peptide, and age has good performance and can serve as a favorable tool for clinicians to predict KP-T2DM.

OBJECTIVETo evaluate the effect of neuromuscular electrical stimulation (NMES) on muscle strength and duration of mechanical ventilation through cumulative Meta-analysis and sequential trial analysis (TSA).METHODSRandomized controlled trial (RCT) of NMES intervention in intensive care unit (ICU) patients with mechanical ventilation were searched from PubMed database of US National Library of Medicine, EMbase database of Netherlands Medical Abstract, Web of Science, SinoMed database of China, CNKI, Wanfang data, VIP and other Chinese and English databases from database construction to July 15, 2021. The control group received ICU routine nursing or rehabilitation exercise; the experimental group received NMES (low frequency electric current through electrode stimulation to make muscle groups twitch or contract) based on routine care in ICU. Relevant data were screened, evaluated and extracted by two researchers independently. After extracting data, STATA 15.0 and TSA software were used to analyze the data and evaluate the research results.RESULTSA total of 9 studies were enrolled, including 619 subjects. Among the 9 articles included, 2 were grade A and 7 were grade B, indicating good overall quality. Cumulative Meta-analysis showed that compared with ICU routine care, NMES improved muscle strength of patients undergoing mechanical ventilation [standardized mean difference (SMD) = 0.64, 95% confidence interval (95%CI) was 0.07 to 1.21] and shortened the duration of mechanical ventilation (SMD = -1.84, 95%CI was -2.58 to -1.10). TSA analysis of the two outcomes showed that the sample size of muscle strength outcome index (n = 518) and mechanical ventilation outcome index (n = 419) did not meet the expected information (RIS; n values of 618 and 685); the cumulative Z-value line of the muscle strength outcome index crossed the traditional boundary line and TSA boundary line, indicating that more tests were not needed to verify this result. In the outcome index of mechanical ventilation duration, it was found that the cumulative Z-value line only crossed the traditional boundary line, but did not cross the TSA boundary line, indicating that further studies in this area should be carried out in the future to demonstrate this result.CONCLUSIONNMES can improve ICU patients' muscle strength and reduce the duration of mechanical ventilation.

Background: Type 2 diabetes is an emergent worldwide health crisis, and rates are growing globally. Aerobic exercise is an essential measure for patients with diabetes, which has the advantages of flexible time and low cost. Aerobic exercise is a popular method to reduce blood glucose. Due to the lack of randomized trials to compare the effects of various aerobic exercises, it is difficult to judge the relative efficacy. Therefore, we intend to conduct a network meta-analysis to evaluate these aerobic exercises. Methods: According to the retrieval strategies, randomized controlled trials on different aerobic exercise training will be obtained from China National Knowledge Infrastructure, WanFang, SinoMed, PubMed, Web of Science, EMBASE, and Cochrane Library, regardless of publication date or language. Studies were screened based on inclusion and exclusion criteria, and the Cochrane risk bias assessment tool will be used to evaluate the quality of the literature. The network meta-analysis will be performed in Markov Chain Monte Carlo method and carried out with Stata14 and OpenBUGS software. Ultimately, the evidentiary grade for the results will be evaluated. Results: Eighteen literatures with a total of 1134 patients were included for the meta-analysis. In glycemia assessment, Tennis (standard mean difference = 3.59, credible interval 1.52, 5.65), had significantly better effects than the named control group. Tennis (standard mean difference = 3.50, credible interval 1.05, 5.59), had significantly better effects than the named Taiji group. Conclusion: All together, these results suggest that tennis may be the best way to improve blood glucose in patients with type 2 diabetes. This study may provide an excellent resource for future control glycemia and may also serve as a springboard for creative undertakings as yet unknown.

ICU获得性衰弱(ICU-AW)的危险因素包括患者个体因素、临床辅助治疗、各类生化代谢指标、药物治疗情况、相关并发症及医护人员对ICU-AW的认识情况等.早期发现、早期进行治疗和护理干预是治疗ICU-AW的关键.今后ICU-AW危险因素的研究应关注患者住院期间心理社会状态,并提高医护人员对该病的知信行,可尽早预防该病的发生.

Abstract Background: Type 2 diabetes is an emergent worldwide health crisis, and rates are growing globally. Aerobic exercise is an essential measure for patients with diabetes, which has the advantages of flexible time and low cost. Aerobic exercise is a popular method to reduce blood glucose. Due to the lack of randomized trials to compare the effects of various aerobic exercises, it is difficult to judge the relative efficacy. Therefore, we intend to conduct a network meta-analysis to evaluate these aerobic exercises. Methods: According to the retrieval strategies, randomized controlled trials on different aerobic exercise training will be obtained from China National Knowledge Infrastructure, WanFang, SinoMed, PubMed, Web of Science, EMBASE, and Cochrane Library, regardless of publication date or language. Studies were screened based on inclusion and exclusion criteria, and the Cochrane risk bias assessment tool will be used to evaluate the quality of the literature. The network meta-analysis will be performed in Markov Chain Monte Carlo method and carried out with Stata14 and OpenBUGS software. Ultimately, the evidentiary grade for the results will be evaluated. Results: Eighteen literatures with a total of 1134 patients were included for the meta-analysis. In glycemia assessment, Tennis (standard mean difference = 3.59, credible interval 1.52, 5.65), had significantly better effects than the named control group. Tennis (standard mean difference = 3.50, credible interval 1.05, 5.59), had significantly better effects than the named Taiji group. Conclusion: All together, these results suggest that tennis may be the best way to improve blood glucose in patients with type 2 diabetes. This study may provide an excellent resource for future control glycemia and may also serve as a springboard for creative undertakings as yet unknown.