PMC:7780429 / 8448-9978 JSONTXT

{"project":"LitCovid-PD-HP","denotations":[{"id":"T37","span":{"begin":1004,"end":1012},"obj":"Phenotype"}],"attributes":[{"id":"A37","pred":"hp_id","subj":"T37","obj":"http://purl.obolibrary.org/obo/HP_0002315"}],"text":"Statistical analysis\nPrior to the analysis of relationships between variables, descriptive analyses of the different areas that make up the study have been carried out. These descriptive analyses include percentage distributions of the different categories of the analysed variables and, in the case of quantitative variables, average and SD. These same analyses, shown as a cross between variables by means of contingency tables or comparison of averages, have also been elaborated as a preamble to the statistical tests that have been carried out to corroborate if there is a relationship between different variables, thus showing the hypotheses to be contrasted.\nDepending on the nature of the variable and the distribution of the sample, different tests have been used. We used the Χ2 test to contrast whether there is independence between two categorical variables using a contingency table when the data are not paired.\nFor the analysis of the predictive factors with the appearance of a ‘de novo’ headache, we used binary logistic regression methods by steps backwards, to maximise sensitivity; variables with a univariate association of p\u003c0.200 were included as candidates in the multivariate model.\nTo measure the relationship between the different variables in the study, statistical tests with a 95% significance level were used as an acceptance threshold for the hypotheses to be tested, that is, a p value of 0.05. All statistical analyses were performed using the SPSS V.25.0 statistical package program for Windows."}

{"project":"LitCovid-PubTator","denotations":[{"id":"121","span":{"begin":1004,"end":1012},"obj":"Disease"}],"attributes":[{"id":"A121","pred":"tao:has_database_id","subj":"121","obj":"MESH:D006261"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"Statistical analysis\nPrior to the analysis of relationships between variables, descriptive analyses of the different areas that make up the study have been carried out. These descriptive analyses include percentage distributions of the different categories of the analysed variables and, in the case of quantitative variables, average and SD. These same analyses, shown as a cross between variables by means of contingency tables or comparison of averages, have also been elaborated as a preamble to the statistical tests that have been carried out to corroborate if there is a relationship between different variables, thus showing the hypotheses to be contrasted.\nDepending on the nature of the variable and the distribution of the sample, different tests have been used. We used the Χ2 test to contrast whether there is independence between two categorical variables using a contingency table when the data are not paired.\nFor the analysis of the predictive factors with the appearance of a ‘de novo’ headache, we used binary logistic regression methods by steps backwards, to maximise sensitivity; variables with a univariate association of p\u003c0.200 were included as candidates in the multivariate model.\nTo measure the relationship between the different variables in the study, statistical tests with a 95% significance level were used as an acceptance threshold for the hypotheses to be tested, that is, a p value of 0.05. All statistical analyses were performed using the SPSS V.25.0 statistical package program for Windows."}

{"project":"LitCovid-sentences","denotations":[{"id":"T53","span":{"begin":0,"end":20},"obj":"Sentence"},{"id":"T54","span":{"begin":21,"end":168},"obj":"Sentence"},{"id":"T55","span":{"begin":169,"end":342},"obj":"Sentence"},{"id":"T56","span":{"begin":343,"end":665},"obj":"Sentence"},{"id":"T57","span":{"begin":666,"end":773},"obj":"Sentence"},{"id":"T58","span":{"begin":774,"end":925},"obj":"Sentence"},{"id":"T59","span":{"begin":926,"end":1207},"obj":"Sentence"},{"id":"T60","span":{"begin":1208,"end":1427},"obj":"Sentence"},{"id":"T61","span":{"begin":1428,"end":1530},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Statistical analysis\nPrior to the analysis of relationships between variables, descriptive analyses of the different areas that make up the study have been carried out. These descriptive analyses include percentage distributions of the different categories of the analysed variables and, in the case of quantitative variables, average and SD. These same analyses, shown as a cross between variables by means of contingency tables or comparison of averages, have also been elaborated as a preamble to the statistical tests that have been carried out to corroborate if there is a relationship between different variables, thus showing the hypotheses to be contrasted.\nDepending on the nature of the variable and the distribution of the sample, different tests have been used. We used the Χ2 test to contrast whether there is independence between two categorical variables using a contingency table when the data are not paired.\nFor the analysis of the predictive factors with the appearance of a ‘de novo’ headache, we used binary logistic regression methods by steps backwards, to maximise sensitivity; variables with a univariate association of p\u003c0.200 were included as candidates in the multivariate model.\nTo measure the relationship between the different variables in the study, statistical tests with a 95% significance level were used as an acceptance threshold for the hypotheses to be tested, that is, a p value of 0.05. All statistical analyses were performed using the SPSS V.25.0 statistical package program for Windows."}