基于主成分分析下慢性阻塞性肺疾病急性加重频率的判别分析

目的 对慢性阻塞性肺疾病患者（COPD)）一般资料及临床资料进行主成分分析和判别分析,研究影响疾病急性加重频率的因素,以预测患者后续发病频率。 方法 选取我院2016年1月～2017年10月收治的350例COPD患者为研究对象,收集患者例入院时一般资料、24h内动脉血气分析,首次降钙素原（PCT）含量、C反应蛋白（CRP）含量及血常规,及入院结束治疗时的抗生素治疗时间、住院时间。对入选患者随访1年,并明确1年内慢性阻塞性肺疾病急性加重（AECOPD）次数,根据疾病加重次数将患者分为三组（A组：≤1次;B组：＜3次;C组：≥3次）。比较三组一般资料及临床资料的差异,利用因子分析提取上述临床指标及一般资料主成分,并利用主成分对AECOPD患者急性加重频数行判别分析,比较提取主成分前后判别分析率差异。结果 共纳入患者321例,其中A组105例、B组105例、C组111例,三组一般资料及临床资料除吸烟年无明显差异,其余指标组间比较,差异有统计学意义（P＜0.05）。从临床指标及一般资料中共提取5个主成分,综合信息提取率833%。一般资料及临床指标判别分析提示,总体判别正确率为748%,A、B、C组三组正确判别率分别为88.6%、65.7%、70.3%;利用提取的主成分进行判别分析提示,总体判别正确率72.0%,A、B、C组三组正确判别率分别为971%、60%、595%。结论 利用常见一般资料及临床资料进行判别分析,可预测患者发病频数,主成分分析的判别正确率与综合资料判别正确率间无明显差异。     

20856例急诊患者疾病谱及就诊特点

目的 分析达州市中西医结合医院急诊科就诊患者的疾病谱构成及就诊特点,为进一步明确救治重点、优化急诊流程、优化及合理使用急诊资源提供数据支撑。方法 通过调取达州市中西医结合医院HIS系统2017年1月1日0:00～2017年12月31 日23:59急诊就诊共计20856例患者的基本信息及诊断资料,分析患者的性别、年龄、就诊时间、疾病种类、是否住院等情况,采用描述性统计方法进行分析,SPSS 25.0软件进行统计学处理,率的比较采用X2检验。结果 20856例患者中,男性比例高于女性;年龄组以青年组（45.97%）急诊就诊率最高;一年四季中夏季（26.63%）就诊量最多,春季（23.46%）最低;8月（9.58%）为急诊就诊月高峰,4月（7.49%）为低谷期;急诊就诊量星期时间点波动（14.02%～14.59%）不明显,周末效应不明显;急诊全天1小时高峰时段为20:00～21:00时,4小时高峰时段为18:00～22:00时;疾病谱中以外伤（2330%）、消化系统（21.25%）、其他类（1429%）为前三位病种。全年急诊就诊患者住院率明显高于同期门诊患者住院率。结论 该医院急诊患者就诊有一定的规律性,医院可考虑根据该规律提前增排加强班。急诊科医护人员应加强对排名前位系统疾病的诊治流程进行优化及学习,并加强急诊外科建设。     

Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: A sociotechnical analysis

Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making.     

Trends in adolescent alcohol use in the Netherlands, 1992–2015: Differences across sociodemographic groups and links with strict parental rule-setting

BackgroundFrom an international perspective, studying trends in adolescent alcohol use in the Netherlands is an important case study. Whereas Dutch adolescents topped the international rankings of alcohol consumption in the beginning of this century, they are nowadays found more toward the bottom of these rankings. This study examines time trends in adolescent alcohol use between 1992 and 2015, and tests whether these trends differ according to gender, age group, and educational track. Moreover, it examines to what extent the strictness of parental rule-setting can explain the identified trends.MethodsUsing data from ten waves of two nationally representative studies with a repeated cross-sectional design, trends were examined for eight different alcohol measures. Interaction analyses were conducted to test for subgroup differences. All analyses were controlled for educational track, family structure, and ethnicity. For the period 2007–2015, trends in parental alcohol-specific rule-setting were included as a predictor of the trends in adolescent alcohol use.ResultsAdolescent alcohol use increased substantially between 1992 and 2003, and decreased sharply thereafter. Trends were stronger for 12- to 15-year olds, compared to the 16-year olds, and for adolescents attending higher educational tracks, compared to adolescents attending lower educational tracks. Overall, gender differences remained constant over time. Between 2007 and 2015, strict parental alcohol-specific rule-setting increased substantially, and this (partly) explained the strong decline in adolescent alcohol use during this period.ConclusionThis study shows clear time trend changes in alcohol use among Dutch adolescents. The phenomenal decrease in adolescent alcohol use since 2003 appears to be closely related to a radical change in parenting behaviours surrounding the alcohol use of their children. While national prevention programs may have encouraged stricter parenting behaviours, the decline in alcohol use should be interpreted in a broader context of internationally changing sociocultural norms regarding adolescent alcohol use.     

Study of autosomal STR loci with IBS method in full sibling identification

Objective: We investigated the application of 51 autosomal short tandem repeat (STR) loci with the identity by state (IBS) method and a discriminant function algorithm in full-sib identification. Methods: A total of 342 pairs of full sibs (FSs) and 3900 pairs of unrelated individuals (UIs) were genotyped for 51 STR loci. Groups were formed in accordance with discrimination power (DP) values and the number of loci, and IBS scores of FSs and UIs were analyzed and compared. The discriminant functions of FS-UI were determined by using the Fisher discriminant with SPSS software. Results: All IBS in FSs and UIs groups showed normal distributions and there were significant differences between FS-UI. Receiver operating characteristic curves revealed that the detection efficiency of full-sib identification was affected by both the locus polymorphism and the number of loci detected. Comparing the rate of false positive and false negative of discriminant function between groups, a higher average DP value and larger number of loci detected were associated with a lower rate of miscarriage of justice and were more helpful for full-sib identification. Conclusion: STRs with higher DP values should be selected when additional autosomal markers are required for FS identification. Discriminant analysis with the IBS method is highly applicable for the FS-UI test.     

Effect of change in coding rules on recording diabetes in hospital administrative datasets

AimDuring 2008–2011 Australian Coding Standards mandated a causal relationship between diabetes and inpatient care as a criterion for recording diabetes as a comorbidity in hospital administrative datasets. We aim to measure the effect of the causality mandate on recorded diabetes and associated inter-hospital variations.MethodFor patients with diabetes, all admissions between 2004 and 2013 to all New South Wales acute public hospitals were investigated. Poisson mixed models were employed to derive adjusted rates and variations.ResultsThe non-recorded diabetes incidence rate was 20.7%. The causality mandate increased the incidence rate four fold during the change period, 2008–2011, compared to the pre- or post-change periods (32.5% vs 8.4% and 6.9%). The inter-hospital variation was also higher, with twice the difference in the non-recorded rate between hospitals with the highest and lowest rates (50% vs 24% and 27% risk gap). The variation decreased during the change period (29%), while the rate continued to rise (53%). Admission characteristics accounted for over 44% of the variation compared with at most two per cent attributable to patient or hospital characteristics. Contributing characteristics explained less of the variation within the change period compared to pre- or post-change (46% vs 58% and 53%). Hospital relative performance was not constant over time.ConclusionThe causality mandate substantially increased the non-recorded diabetes rate and associated inter-hospital variation. Longitudinal accumulation of clinical information at the patient level, and the development of appropriate adoption protocols to achieve comprehensive and timely implementation of coding changes are essential to supporting the integrity of hospital administrative datasets.     

Health Warnings,Smoking Rules,and Smoking Status: A Cross-National Comparison of Turkey and the United States

Objectives: This study aimed to compare the prevalence of smoking status (i.e., current, former and never) between the United States and Turkey in terms of age and gender, and examine how smoking rules and health warnings are associated with smoking status within and between the two countries. Methods: The study used data from the 2012–2013 National Adult Tobacco Survey (U.S. sample, N = 60,196) and the 2012 Global Adult Tobacco Survey (Turkey sample, N = 9,581). SAS PROC SURVEYLOGISTIC with a weighted variable was used to examine the associations between demographics (age, gender and education), smoking rules, health warnings, and smoking status within and between the two countries. Results: There was an 18% current smoking prevalence among U.S. sample, compared to 27% of the Turkey sample. The U.S. sample had a higher rate of former smoking compared to the Turkey sample (25% vs. 22%). In both countries, being older and male gender predicted former smoking while being younger and female gender predicted never smoking. Having seen a health warning, and not allowing smoking in the vehicle and home positively predicted former and never smoking status. Higher education predicted both smoking statuses in the U.S. only. Conclusions: It is important to work with partners particularly in low- and middle-income countries (e.g., Turkey) to combat the global tobacco epidemic. In both counties, cessation endeavors should emphasize a comprehensive understanding of smoking status in terms of smoking rules in personal spaces and health warnings.     

Exploratory Analysis

Abstract

QEEG variables (5 activation, 2 relationship variables, 19 locations and 5 bands up to 64 Hertz) were collected under three activation conditions (auditory attention, visual attention and listening to paragraphs) on 84 subjects, consisting of 32 mild head-injured subjects (no loss of consciousness) and 52 normals over the age of 14. Additional variables collected included years of education, time since accident, sex, handedness and Shipley Institute of Living measures of IQ, verbal and abstraction scores.

The results were encouraging for future development of a discriminant employing activation conditions, as the results varied from 88% to 100% correct classification. Very few of the variables, which distinguished the groups under the three conditions or were used in the discriminant analysis, were shown to increase as the time since accident increased. This result, tentatively, indicates little effect of time on the improvement in the electrophysiological functioning of the brain. Time (spontaneous improvement) does not appear to heal the brain in any significant manner.     

Integrating multiple-domain rules for disease classification

In psychiatry, clinicians use criteria sets from the Diagnostic and Statistical Manual of Mental Disorders to diagnose mental disorders. Most criteria sets have several symptom domains, and in order to be diagnosed, an individual must meet the minimum number of symptoms required by each domain. Some efforts are now focused on adding biomarkers to these symptom domains to facilitate the detection of and highlight the neurobiological basis of psychiatric disorders. Thus, a new criteria set may consist of both clinical symptom counts in several domains and continuous biomarkers. In this paper, we propose a method to integrate classification rules from multiple data sources to estimate an optimal criteria set. Each domain-specific rule can be counts of symptoms, a linear function of symptoms, or even nonparametric. The overall classification rule is the intersection of these domain-specific rules. Based on examining the expected population loss function, we propose two iterative algorithms using either support vector machines or logistic regression to fit intersection rules consistent with the Diagnostic and Statistical Manual of Mental Disorders. In simulation studies, these proposed methods are comparable with the true decision rule. The methods are applied to the motivating study to construct a criteria set for complicated grief. The developed criteria set shows a substantial improvement in sensitivity and specificity compared to the current standards on an independent validation study.