OBJECTIVES: From the point of view of clinical data representation, this study attempted to identify obstacles in translating clinical narrative guidelines into computer interpretable format and integrating the guidelines with data in Electronic Health Records in China. METHODS: Based on SAGE and K4CARE formulism, a Chinese clinical practice guideline for hypertension was modeled in Protege by building an ontology that had three components: flowchart, node, and vMR. Meanwhile, data items imperative in Electronic Health Records for patients with hypertension were reviewed and compared with those from the ontology so as to identify conflicts and gaps between. RESULTS: A set of flowcharts was built. A flowchart comprises three kinds of node: State, Decision, and Act, each has a set of attributes, including data input/output that exports data items, which then were specified following ClinicalStatement of HL7 vMR. A total of 140 data items were extracted from the ontology. In modeling the guideline, some narratives were found too inexplicit to formulate, and encoding data was quite difficult. Additionally, it was found in the healthcare records that there were 8 data items left out, and 10 data items defined differently compared to the extracted data items. CONCLUSIONS: The obstacles in modeling a clinical guideline and integrating with data in Electronic Health Records include narrative ambiguity of the guideline, gaps and inconsistencies in representing some data items between the guideline and the patient' records, and unavailability of a unified medical coding system. Therefore, collaborations among various participants in developing guidelines and Electronic Health Record specifications is needed in China.
Asian Continental Ancestry Group ; China* ; Clinical Coding ; Cooperative Behavior ; Decision Support Systems, Clinical ; Delivery of Health Care ; Electronic Health Records ; Humans ; Hypertension ; Methods* ; Practice Guidelines as Topic ; Software Design ; Translating

Cryptosporidium spp., ubiquitous enteric parasitic protozoa of vertebrates, recently emerged as an important cause of economic loss and zoonosis. The present study aimed to determine the distribution and species of Cryptosporidium in post-weaned and adult pigs in Shaanxi province, northwestern China. A total of 1,337 fresh fecal samples of post-weaned and adult pigs were collected by sterile disposable gloves from 8 areas of Shaanxi province. The samples were examined by Sheather's sugar flotation technique and microscopy atx400 magnification for Cryptosporidium infection, and the species in positive samples was further identified by PCR amplification of the small subunit (SSU) rRNA gene. A total of 44 fecal samples were successfully amplified by the nested PCR of the partial SSU rRNA, with overall prevalence of 3.3%. The average prevalence of Cryptosporidium infection in each pig farms ranged from 0 to 14.4%. Species identification by sequencing of SSU rRNA gene revealed that 42 (3.1%) samples were Cryptosporidium suis and 2 (0.15%) were Cryptosporidium scrofarum. C. suis had the highest prevalence (7.5%) in growers and the lowest in breeding pigs (0.97%). C. suis was the predominant species in pre-weaned and adult pigs, while C. scrofarum infected pigs older than 3 months only. A season-related difference of C. suis was observed in this study, with the highest prevalence in autumn (5.5%) and the lowest (1.7%) in winter. The present study provided basic information for control of Cryptosporidium infection in pigs and assessment of zoonotic transmission of pigs in Shaanxi province, China.
Animals ; China/epidemiology ; Cluster Analysis ; Cryptosporidiosis/*epidemiology/*parasitology ; Cryptosporidium/classification/genetics/*isolation & purification ; DNA, Protozoan/chemistry/genetics ; DNA, Ribosomal/chemistry/genetics ; Feces/parasitology ; Molecular Sequence Data ; Phylogeny ; Polymerase Chain Reaction ; Prevalence ; RNA, Ribosomal, 18S/genetics ; Seasons ; Sequence Analysis, DNA ; Swine ; Swine Diseases/*epidemiology/*parasitology

Cryptosporidium spp., ubiquitous enteric parasitic protozoa of vertebrates, recently emerged as an important cause of economic loss and zoonosis. The present study aimed to determine the distribution and species of Cryptosporidium in post-weaned and adult pigs in Shaanxi province, northwestern China. A total of 1,337 fresh fecal samples of post-weaned and adult pigs were collected by sterile disposable gloves from 8 areas of Shaanxi province. The samples were examined by Sheather's sugar flotation technique and microscopy atx400 magnification for Cryptosporidium infection, and the species in positive samples was further identified by PCR amplification of the small subunit (SSU) rRNA gene. A total of 44 fecal samples were successfully amplified by the nested PCR of the partial SSU rRNA, with overall prevalence of 3.3%. The average prevalence of Cryptosporidium infection in each pig farms ranged from 0 to 14.4%. Species identification by sequencing of SSU rRNA gene revealed that 42 (3.1%) samples were Cryptosporidium suis and 2 (0.15%) were Cryptosporidium scrofarum. C. suis had the highest prevalence (7.5%) in growers and the lowest in breeding pigs (0.97%). C. suis was the predominant species in pre-weaned and adult pigs, while C. scrofarum infected pigs older than 3 months only. A season-related difference of C. suis was observed in this study, with the highest prevalence in autumn (5.5%) and the lowest (1.7%) in winter. The present study provided basic information for control of Cryptosporidium infection in pigs and assessment of zoonotic transmission of pigs in Shaanxi province, China.
Animals ; China/epidemiology ; Cluster Analysis ; Cryptosporidiosis/*epidemiology/*parasitology ; Cryptosporidium/classification/genetics/*isolation & purification ; DNA, Protozoan/chemistry/genetics ; DNA, Ribosomal/chemistry/genetics ; Feces/parasitology ; Molecular Sequence Data ; Phylogeny ; Polymerase Chain Reaction ; Prevalence ; RNA, Ribosomal, 18S/genetics ; Seasons ; Sequence Analysis, DNA ; Swine ; Swine Diseases/*epidemiology/*parasitology

No abstract available.
Aged, 80 and over ; Anti-Bacterial Agents/pharmacology ; Bacterial Proteins/*genetics ; China ; Drug Resistance, Multiple, Bacterial ; Humans ; Male ; Methyltransferases/*genetics ; Microbial Sensitivity Tests ; RNA, Ribosomal, 16S/genetics/metabolism ; Serratia marcescens/drug effects/*enzymology/*genetics/isolation & purification ; Urinary Tract Infections/diagnosis/microbiology

To investigate the possible risk factors related to macrosomia. Pregnant women and their newborns (n = 1041) were recruited from a cohort study in Maternal and Child Care Center of Hefei from January 2011 to July 2012. Questionnaires were applied to collect the demographic data besides the medical records. Detailed health records of the entire pregnancy were obtained using retrospective study. Meanwhile the data of neonatal outcomes was prospectively tracked. Associations between exposure risk factors and macrosomia were analyzed using Pearson's chi squared test. Logistic regression models were used to assess the independent association between these potential predictors and macrosomia. The incidence of macrosomia of this cohort was 11.24% of which male: female = 2.55:1. Male incidence (8.07%)of macrosomia was higher than female (3.17%), p < 0.001. Body mass index (BMI) before pregnancy (pre-BMI), maternal height, parity were not independently associated with macrosomia; Multiple logistic regression analysis indicated that macrosomia was mainly independently associated with weight gain in pregnancy (OR=1.14, 95% CI [1.10-1.19]), maternal age (OR = 1.09, 95% CI [1.03-1.15]) and gestational age (OR = 1.62, 95% CI [1.31-1.99]), respectively. Our findings indicate that weight gain in pregnancy, maternal age and gestational age should be considered as independent risk factors for macrosomia.
Body Mass Index ; Child ; Child Care ; Cohort Studies ; Female ; Fetal Macrosomia* ; Gestational Age* ; Humans ; Incidence ; Infant, Newborn ; Logistic Models ; Male ; Maternal Age* ; Medical Records ; Parity ; Pregnancy* ; Pregnant Women ; Prospective Studies ; Retrospective Studies ; Risk Factors ; Weight Gain* ; Surveys and Questionnaires