PMC:2652658 / 6466-7677 JSONTXT

{"project":"0_colil","denotations":[{"id":"18635400-2868337-8531","span":{"begin":575,"end":576},"obj":"2868337"},{"id":"18635400-15350232-8532","span":{"begin":908,"end":910},"obj":"15350232"}],"text":"2.3 Statistical analysis\nThe distribution of all time periods (total pre-hospital delay, decision time and home-to-hospital delay) was skewed, so analyses were based on binary divisions of each interval. The factors associated with total pre-hospital delay were analyzed by comparing the characteristics of patients with delays longer or shorter than the median of 120 min. Decision time was analyzed by comparing individuals with decision times ≤ 60 or \u003e 60 min. This criterion was selected because reperfusion therapy is most effective if initiated within the first hour [2]. Home-to-hospital delay was also analyzed by comparing individuals with delays ≤ 60 or \u003e 60 min since the target set by the UK National Service Framework for administration of thrombolysis to eligible patients is within 1 h of calling for help [18]. Other studies investigating pre-hospital delay have used similar time cut offs [11]. Groups were compared using χ2 tests, and significant effects were subsequently entered into multivariate analyses using logistic regression with age and gender as covariates. Results are presented as percentages and odds ratios (OR) adjusted for age and gender with 95% confidence intervals (C.I.)."}

{"project":"2_test","denotations":[{"id":"18635400-2868337-28906403","span":{"begin":575,"end":576},"obj":"2868337"},{"id":"18635400-15350232-28906404","span":{"begin":908,"end":910},"obj":"15350232"}],"text":"2.3 Statistical analysis\nThe distribution of all time periods (total pre-hospital delay, decision time and home-to-hospital delay) was skewed, so analyses were based on binary divisions of each interval. The factors associated with total pre-hospital delay were analyzed by comparing the characteristics of patients with delays longer or shorter than the median of 120 min. Decision time was analyzed by comparing individuals with decision times ≤ 60 or \u003e 60 min. This criterion was selected because reperfusion therapy is most effective if initiated within the first hour [2]. Home-to-hospital delay was also analyzed by comparing individuals with delays ≤ 60 or \u003e 60 min since the target set by the UK National Service Framework for administration of thrombolysis to eligible patients is within 1 h of calling for help [18]. Other studies investigating pre-hospital delay have used similar time cut offs [11]. Groups were compared using χ2 tests, and significant effects were subsequently entered into multivariate analyses using logistic regression with age and gender as covariates. Results are presented as percentages and odds ratios (OR) adjusted for age and gender with 95% confidence intervals (C.I.)."}

{"project":"MyTest","denotations":[{"id":"18635400-2868337-28906403","span":{"begin":575,"end":576},"obj":"2868337"},{"id":"18635400-15350232-28906404","span":{"begin":908,"end":910},"obj":"15350232"}],"namespaces":[{"prefix":"_base","uri":"https://www.uniprot.org/uniprot/testbase"},{"prefix":"UniProtKB","uri":"https://www.uniprot.org/uniprot/"},{"prefix":"uniprot","uri":"https://www.uniprot.org/uniprotkb/"}],"text":"2.3 Statistical analysis\nThe distribution of all time periods (total pre-hospital delay, decision time and home-to-hospital delay) was skewed, so analyses were based on binary divisions of each interval. The factors associated with total pre-hospital delay were analyzed by comparing the characteristics of patients with delays longer or shorter than the median of 120 min. Decision time was analyzed by comparing individuals with decision times ≤ 60 or \u003e 60 min. This criterion was selected because reperfusion therapy is most effective if initiated within the first hour [2]. Home-to-hospital delay was also analyzed by comparing individuals with delays ≤ 60 or \u003e 60 min since the target set by the UK National Service Framework for administration of thrombolysis to eligible patients is within 1 h of calling for help [18]. Other studies investigating pre-hospital delay have used similar time cut offs [11]. Groups were compared using χ2 tests, and significant effects were subsequently entered into multivariate analyses using logistic regression with age and gender as covariates. Results are presented as percentages and odds ratios (OR) adjusted for age and gender with 95% confidence intervals (C.I.)."}

{"project":"testtesttest","denotations":[{"id":"T16","span":{"begin":943,"end":948},"obj":"Body_part"}],"attributes":[{"id":"A16","pred":"uberon_id","subj":"T16","obj":"http://purl.obolibrary.org/obo/UBERON_0000473"}],"text":"2.3 Statistical analysis\nThe distribution of all time periods (total pre-hospital delay, decision time and home-to-hospital delay) was skewed, so analyses were based on binary divisions of each interval. The factors associated with total pre-hospital delay were analyzed by comparing the characteristics of patients with delays longer or shorter than the median of 120 min. Decision time was analyzed by comparing individuals with decision times ≤ 60 or \u003e 60 min. This criterion was selected because reperfusion therapy is most effective if initiated within the first hour [2]. Home-to-hospital delay was also analyzed by comparing individuals with delays ≤ 60 or \u003e 60 min since the target set by the UK National Service Framework for administration of thrombolysis to eligible patients is within 1 h of calling for help [18]. Other studies investigating pre-hospital delay have used similar time cut offs [11]. Groups were compared using χ2 tests, and significant effects were subsequently entered into multivariate analyses using logistic regression with age and gender as covariates. Results are presented as percentages and odds ratios (OR) adjusted for age and gender with 95% confidence intervals (C.I.)."}