PMC:7116472 / 16776-17379 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"240","span":{"begin":467,"end":474},"obj":"Species"},{"id":"241","span":{"begin":569,"end":577},"obj":"Species"}],"attributes":[{"id":"A240","pred":"tao:has_database_id","subj":"240","obj":"Tax:9606"},{"id":"A241","pred":"tao:has_database_id","subj":"241","obj":"Tax:9606"}],"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":"We also performed a decision curve analysis.27 Briefly, assessment of the adequacy of clinical prediction models can be extended by determining clinical utility. By using decision curve analysis, we can make a clinical judgment about the relative value of benefits (treating a true positive) and harms (treating a false positive) associated with a clinical prediction tool. The standardised net benefit was plotted against the threshold probability for considering a patient high risk for age alone and for the best discriminating models applicable to more than 50% of patients in the validation cohort."}

{"project":"LitCovid-sentences","denotations":[{"id":"T112","span":{"begin":0,"end":161},"obj":"Sentence"},{"id":"T113","span":{"begin":162,"end":373},"obj":"Sentence"},{"id":"T114","span":{"begin":374,"end":603},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"We also performed a decision curve analysis.27 Briefly, assessment of the adequacy of clinical prediction models can be extended by determining clinical utility. By using decision curve analysis, we can make a clinical judgment about the relative value of benefits (treating a true positive) and harms (treating a false positive) associated with a clinical prediction tool. The standardised net benefit was plotted against the threshold probability for considering a patient high risk for age alone and for the best discriminating models applicable to more than 50% of patients in the validation cohort."}