基于记忆-遗忘规律的健康教育在改善冠心病患者自我管理中的应用研究

目的 探讨基于记忆-遗忘规律的健康教育在改善冠心病患者健康促进生活方式和自我健康管理行为中的影响。方法 选择住院治疗的冠心病患者160例,采用随机数字表法分为观察组(80例)和对照组(80例)。对照组接受常规住院健康教育,观察组接受基于记忆-遗忘曲线规律制定的针对性的健康教育干预。在干预前、干预后使用健康促进生活方式评定量表和冠心病自我管理行为量表,测量两组患者的健康促进生活方式和自我管理行为水平。结果 干预前,两组患者健康促进生活方式和自我健康管理行为水平比较,差异无统计学意义(t=-1.72, 1.88,P值均>0.05)。干预后,观察组健康促进生活方式总分为(83.58±9.54),高于干预前的(63.08±7.11),(t=11.11, P<0.001)。干预前,2组自我管理行为得分比较,差异无统计学意义(t=1.88, P>0.05);干预后,观察组自我管理行为总得分为(118.44±8.42),高于对照组的(99.86±6.49),(t=-15.63, P<0.001)。结论 基于记忆-遗忘规律的健康教育,对冠心病患者健康促进生活方式和自我管理行为有明显改善和提高。     

基于标准化患者法评价四川农村基层医生两种慢性病诊断准确性及其影响因素

目的 运用标准化患者法评估四川农村地区基层医生不稳定型心绞痛和2型糖尿病两种慢性病诊断准确性现状,探讨基层医生两种慢性病诊断准确性的主要影响因素,为提升基层医生两种慢性病诊断准确性提供科学依据。方法 采用多阶段随机整群抽样方法,抽取四川省自贡市5个区/县50个乡镇100个村为研究现场,以调查当日在岗的全科及内科医生作为研究对象。共进行两轮数据采集,第1轮采集样本乡镇卫生院和村卫生室医生的基本信息;第1轮调查完成1个月后,运用标准化患者法开展第2轮调查,收集农村基层医生对不稳定型心绞痛和2型糖尿病诊断结果信息。运用Logistic回归分析农村基层医生不稳定型心绞痛和2型糖尿病诊断准确性的影响因素。结果 共纳入172名农村基层医生,完成186次标准化患者访问,正确诊断率为48.39%。其中不稳定型心绞痛的正确诊断率为18.68%(17/91),2型糖尿病的正确诊断率为76.84%(73/95)。Logistic回归分析显示,具有执业医师资质的农村基层医生更有可能做出正确诊断(OR=4.857,95%CI=1.076~21.933,P=0.040)。农村基层医生在诊断过程中涉及的必要问诊和检查条目越多,做出正确诊断的概率越高(OR=1.627,95%CI=1.065~2.485,P=0.024)。与不稳定型心绞痛相比,农村基层医生对2型糖尿病做出正确诊断的可能性更高(OR=6.306,95%CI=3.611~11.013,P<0.001)。结论 四川农村基层医生不稳定型心绞痛和2型糖尿病诊断准确性整体较差,建议以基层医生慢性病诊断过程质量改善为突破口,提升基层医生执业水平,进而提高慢性病诊断准确性。     

Patient and Procedure-related Characteristics Correlated With Severity of Hemoptysis Following Percutaneous Transthoracic Needle Biopsy: Results of a 10-year Retrospective Review

PurposeA risk of percutaneous transthoracic needle biopsy (PTNB) is hemoptysis, which can range from mild to life-threatening. The reported occurrence of hemoptysis is 1.7% to 14.5%, and the demographic, patient, and procedure characteristics have not been extensively described. The purpose of this study was to assess the associations of demographic, patient, and procedure characteristics with the severity of hemoptysis.Materials and MethodsA single institution, single group, retrospective, electronic medical record (EMR) review was performed on all hemoptysis events occurring between 2008 and 2018. Demographic, clinical, and procedure variables were extracted from EMRs. Outcome of hemoptysis events was graded using Common Terminology Criteria for Adverse Events (CTCAE). Mild-moderate and severe hemoptysis were defined as CTCAE classifications of 1-2 and 3-5, respectively. Associations were generated using logistic regressions and Likelihood Ratio Chi-Square tests.ResultsIn 10 years, 14,665 PTNB resulted in 231 hemoptysis events occurring in 229 patients; 12.7% (n = 29) of those were severe. The strongest and statistically significant variables associated with an increased likelihood of a severe event, if an event occurred, were cigarette pack years (OR = 1.02, 95% C.I. = 1.01-1.04, p = .020); history of chronic obstructive pulmonary disease (COPD) (OR = 3.68, 95% C.I. = 1.53-8.82, p = .003); core biopsy technique (OR = 8.13, 95% CI = 1.07, 61.40, p = .042), and larger diameter needle (20 g vs. 18 g: OR = 2.60, 95% CI 1.09, 6.17, p = .031).ConclusionsPTNB-associated hemoptysis was an uncommon event that was rarely life-threatening. The extent of the patient’s smoking history, the diagnosis of COPD, and core biopsy technique were associated with an increased likelihood of severe hemoptysis.     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

A comparison of two Fendrix hepatitis B vaccination schedules in patients with inflammatory bowel disease

Systemic immunosuppressive therapy (IS) renders patients with inflammatory bowel disease (IBD) vulnerable to fulminant hepatitis B virus (HBV) infection. Seroprotection against HBV through a full vaccination scheme is preferably obtained before IS is initiated, but often conflicts with the clinical need to initiate therapy rapidly. Consequently, the vast majority of patients will use IS during booster vaccinations. In this retrospective cohort study, we examined the serological response after a modified vaccination schedule which includes an initial double dose of Fendrix in patients with IBD and compared the results with the serological responses of patients with IBD who received the standard schedule. Seroprotection rates were 86.2 % and 88.9 % in the modified and standard schedule groups respectively. One-third of patients obtained seroprotection after only one double dose vaccine. A double dose may be considered in patients with IBD at high short-term risk of HBV infection when a rapid protective response is warranted.     

川崎病静脉注射丙种球蛋白无反应预测模型研究现状

川崎病(Kawasaki disease，KD)是一种急性自身免疫性系统性血管炎，是发达国家儿童获得性心脏病的主要病因。KD最严重的后果是冠状动脉病变(coronary artery lesions，CALs)，与KD的预后相关。临床研究证实静脉注射丙种球蛋白(IVIG)耐药是CALs的独立危险因素。近年来，一系列的预测模型已被开发来评估IVIG耐药的风险。然而，目前基于KD儿童人口学特征、临床表现、实验室检查及遗传特性的IVIG耐药性预测评分系统在不同民族和同一民族不同地区的人群中存在显著差异，尚未建立适用普遍人群的预测模型。