tetano
Editor, Senior Moderator
NPJ Prim Care Respir Med. 2020 Mar 23;30(1):9. doi: 10.1038/s41533-020-0165-3.
Factors associated with seasonal influenza self-diagnosis: a prospective observational study in Japan.
Maita H[SUP]1,[/SUP][SUP]2[/SUP], Kobayashi T[SUP]3[/SUP], Akimoto T[SUP]3[/SUP], Matsuoka F[SUP]4[/SUP], Osawa H[SUP]3[/SUP], Kato H[SUP]5,[/SUP][SUP]6,[/SUP][SUP]3[/SUP].
Author information
Abstract
This prospective observational study, conducted at a community clinic in Japan during the influenza season, from December 2017 to April 2018 aimed to investigate the accuracy of factors used for influenza self-diagnosis. Data were collected from pre-examination checklists issued to patients with suspected influenza and electronic medical records. Receiver operating characteristic (ROC) curve analysis was performed using a rapid influenza diagnostic test as the reference standard, and 2 ? 2 contingency tables were analysed at each cut-off point. We analysed data from 290 patients (72.8% males, median age: 38 years, interquartile range: 26-50 years). The area under the ROC curve (AUC) for patients who were aware of other patients presumed to have influenza within close proximity was 0.74 (95% confidence interval (CI): 0.66-0.82). The AUCs for patients with a history of influenza, unvaccinated status, cough, or nasal discharge were 0.68 (95% CI: 0.60-0.75), 0.66 (95% CI: 0.59-0.73), 0.67 (95% CI: 0.59-0.75), and 0.70 (95% CI: 0.62-0.78), respectively. The sensitivity, specificity and positive likelihood ratio at a 90% cut-off point was 19.5% (95% CI: 13.5-26.6%), 94.1% (95% CI: 88.7-97.4%) and 3.31 (95% CI: 1.57-6.98). The sensitivity, specificity and negative likelihood ratio at a 10% cut-off point was 95.5% (95% CI: 90.9-98.2%), 9.6% (95% CI: 5.2-15.8%) and 0.48 (95% CI: 0.20-1.16). After multivariate logistic regression analysis, the AUC increased significantly from 0.77 (95% CI: 0.70-0.83) to 0.81 (95% CI: 0.76-0.86) when self-diagnosis-related information was added to basic clinical information. We identified factors that improve the accuracy and validity of influenza self-diagnosis. Appropriate self-diagnosis could contribute to the containment efforts during influenza epidemics and reduce its social and economic burden.
PMID:32251292DOI:10.1038/s41533-020-0165-3
Factors associated with seasonal influenza self-diagnosis: a prospective observational study in Japan.
Maita H[SUP]1,[/SUP][SUP]2[/SUP], Kobayashi T[SUP]3[/SUP], Akimoto T[SUP]3[/SUP], Matsuoka F[SUP]4[/SUP], Osawa H[SUP]3[/SUP], Kato H[SUP]5,[/SUP][SUP]6,[/SUP][SUP]3[/SUP].
Author information
Abstract
This prospective observational study, conducted at a community clinic in Japan during the influenza season, from December 2017 to April 2018 aimed to investigate the accuracy of factors used for influenza self-diagnosis. Data were collected from pre-examination checklists issued to patients with suspected influenza and electronic medical records. Receiver operating characteristic (ROC) curve analysis was performed using a rapid influenza diagnostic test as the reference standard, and 2 ? 2 contingency tables were analysed at each cut-off point. We analysed data from 290 patients (72.8% males, median age: 38 years, interquartile range: 26-50 years). The area under the ROC curve (AUC) for patients who were aware of other patients presumed to have influenza within close proximity was 0.74 (95% confidence interval (CI): 0.66-0.82). The AUCs for patients with a history of influenza, unvaccinated status, cough, or nasal discharge were 0.68 (95% CI: 0.60-0.75), 0.66 (95% CI: 0.59-0.73), 0.67 (95% CI: 0.59-0.75), and 0.70 (95% CI: 0.62-0.78), respectively. The sensitivity, specificity and positive likelihood ratio at a 90% cut-off point was 19.5% (95% CI: 13.5-26.6%), 94.1% (95% CI: 88.7-97.4%) and 3.31 (95% CI: 1.57-6.98). The sensitivity, specificity and negative likelihood ratio at a 10% cut-off point was 95.5% (95% CI: 90.9-98.2%), 9.6% (95% CI: 5.2-15.8%) and 0.48 (95% CI: 0.20-1.16). After multivariate logistic regression analysis, the AUC increased significantly from 0.77 (95% CI: 0.70-0.83) to 0.81 (95% CI: 0.76-0.86) when self-diagnosis-related information was added to basic clinical information. We identified factors that improve the accuracy and validity of influenza self-diagnosis. Appropriate self-diagnosis could contribute to the containment efforts during influenza epidemics and reduce its social and economic burden.
PMID:32251292DOI:10.1038/s41533-020-0165-3