Trends of self-reported non-adherence among type 2 diabetes medication users in the United States across three years using the self-reported Medication Adherence Reasons Scale

Background & aimsTo determine the trends of self-reported non-adherence rates among adults taking Type 2 medicines (T2D) medicines between 2017 and 2019 and to identify the patterns for the frequently reported reasons for non-adherence in the United States.Methods & resultsData from the National Health and Wellness Survey, a self-administered, internet-based cross-sectional survey of US adults from 2017 to 2019 was used. Non-adherence was measured using the self-reported Medication Adherence Reasons Scale (MAR-Scale). Frequencies were used to identify the reasons for non-adherence for insulin and non-insulin therapies for T2D.Data were obtained from 2983 respondents in 2017, 5416 in 2018, and 5268 in 2019. Based on the MAR-Scale, the self-reported medication non-adherence rate was 25% in 2017, 21% in 2018, and 27% in 2019. The most common reason for non-adherence across all the three years was simple forgetfulness, yet patients reported the lowest mean number of days missing medication for that reason. Though less frequently reported, non-adherence lasted longer when patient did not know how to take their medicines, cost was a reason, or had concerns about the long term effects of the medicines.ConclusionsWith no significant improvement in adherence with T2D medicines over time, regardless of better awareness and extensive diabetes education, focus should be on individualized non-adherence reasons-based interventions.     

Analyses of rare predisposing variants of lung cancer in 6,004 whole genomes in Chinese

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Bone Metastases: From Mechanisms to Treatment

ObjectivesBone metastases are of high clinical relevance because they are a frequent complication of most types of common cancers, such as breast and prostate. The metastatic process is complex, requiring the completion of several different steps to allow successful dissemination and homing. In addition, preparation of the metastatic niche changes the constant cycle of bone matrix formation and degradation, leading to the clinical phenotypes of lytic and sclerotic lesions. We review our current knowledge on this topic and briefly explain the current treatment landscape of bone metastasis.Data SourcesThese include PubMed, international guidelines, and clinician experience.ConclusionBone metastases remain a clinical challenge that negatively impacts patients prognosis and quality of life. A comprehensive understanding of the complex molecular mechanisms that results in bone metastasis is the basis for successful treatment of affected patients. The disruption of bone matrix metabolism is already recognized as the prerequisite for metastasis formation, but many open questions remain that need to be addressed in future research to establish individually tailored treatment approaches.Implications for Nursing PracticePatient-centered therapy of bone metastases requires suitable pharmacological options, and importantly a holistic approach in care delivery across the multidisciplinary team. Nurses provide the cornerstone of the multidisciplinary team and provide the closest and the most frequent contact to the patient and their families to provide timely intervention. Nurses require a basic understanding of the complex physiology of metastasis to inform practice.     

Prediction of all-cause mortality with malnutrition assessed by nutritional screening and assessment tools in patients with heart failure：a systematic review

Background and aimsIn the absence of a gold standard or scientific consensus regarding the nutritional evaluation of heart failure (HF) patients, this study aimed to summarize and systematically evaluate the prognostic value of nutritional screening and assessment tools used for all-cause mortality in HF patients.Methods and resultsRelevant studies were retrieved from major databases (PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), WanFang Data, and China Biology Medicine disc (CMB)) and searched from the earliest available date until July 2021. If three or more studies used the same tool, meta-analysis using RevMan 5.3 was performed. This systematic review was registered at PROSPERO (number CRD42021275575). A total of 36 articles involving 25,141 HF patients were included for qualitative analysis and 31 studies for quantitative analysis. Meta-analysis of these studies indicated, poor nutritional status evaluated by using 5 nutritional screening tools (Prognostic Nutritional Index (PNI), Geriatric Nutritional Risk Index (GNRI), Controlling Nutritional Status Score (CONUT), Nutritional Risk Index (NRI), and Short Form Mini Nutritional Assessment (MNA-SF)) or 2 nutritional assessment tools (the Mini Nutritional Assessment (MNA) and Generated Subjective Global Assessment (SGA)) predicted all-cause mortality in HF patients. Of all tools analyzed, MNA had the maximum HR for mortality [HR = 2.62, 95%CI 1.11–6.20, P = 0.03] and MNA-SF [HR = 1.94, 95%CI 1.40–2.70, P＜0.001] was the best nutritional screening tools.ConclusionPoor nutritional status predicted all-cause mortality in HF patients. MNA may be the best nutritional assessment tool, and MNA-SF is most recommended for HF patient nutritional screening. The application value of MNA, especially in patients with reduced left ventricular ejection fraction (LVEF), needs to be further confirmed. The clinical application value of Mini-Nutrition Assessment Special for Heart Failure (MNA-HF) and Global Leadership Initiative on Malnutrition (GLIM) in HF patients needs to be confirmed.     

SARIMA模型在苏州市肺结核发病预测中的应用

目的 建立苏州市肺结核发病的SARIMA模型并预测发病,为苏州市肺结核防控提供参考。方法 收集结核病信息管理系统（新）中苏州市2010年1月—2018年12月肺结核月发病数,通过时间序列分析建立SARIMA模型并预测苏州市2019年肺结核的发病情况。结果 苏州市肺结核发病数具有明显的季节周期性,每年的发病最高峰为5月,发病最低谷为2月。苏州市肺结核发病数的最佳拟合模型为SARIMA (0,1,1)×(0,1,1)₁₂,AIC=9.590,SBC=9.644,模型参数均具有统计学意义,模型残差为白噪声序列,模型的预测值与实际值平均绝对百分比误差MAPE=7.943%,模型预测精度较高。预测苏州市2019年肺结核发病数为3 467例,月发病数平均值为289例,发病水平较2018年略有下降。结论 SARIMA(0,1,1)×(0,1,1)₁₂模型能较好拟合出苏州市肺结核发病数的时间变化趋势,可应用于苏州市肺结核月发病数的短期预测。     

Genomic epidemiological investigation of a Streptococcus suis outbreak in Guangxi,China, 2016

In June 2016, a Streptococcus suis outbreak occurred in Guangxi, China. We determined the genetic characteristics of six clinically isolated strains by serotyping, PCR, and whole-genome sequencing, performing genome epidemiology analysis on these and 961 public available S. suis genomes. We also classified the first sequence type ST665 human case. Sporadic and outbreak cases were distinguished by whole-genome sequencing and phylogenomics. This approach could help to prevent and control S. suis epidemics in Guangxi and the wider region.     

苏州市初治菌阴肺结核患者就诊延迟现况及临床特征

目的 分析初治菌阴肺结核患者就诊延迟现况及临床特征,为制定有效措施提供科学依据。方法 应用横断面研究,收集苏州市5家结核病定点医院初治菌阴肺结核患者人口学、经济来源、生活方式、结核病知识、主要病史及进入结核病定点医院前发病和就诊等临床资料,采用Logistic回归方法进行统计分析。结果 379例初治菌阴肺结核患者就诊延迟186例,就诊延迟率为49.08%。老年人(OR=1.898,95% CI=1.157~3.112,P=0.011)、日工作时间大于8 h(OR=1.774,95% CI=1.014~3.102, P=0.044)、流动人口(OR=3.252; 95% CI=1.807~5.855, P<0.001)和发热(OR= 2.061,95% CI=1.021~4.160,P=0.043)是初治菌阴肺结核患者发生就诊延迟的危险特征,而咯血(OR= 0.356, 95% CI= 0.164~0.773,P=0.009)是就诊延迟的保护特征。结论 初治菌阴肺结核患者就诊延迟现象较严重,需对不同临床特征的患者采取综合干预措施,减少就诊延迟发生。