A data driven clinical algorithm for differential diagnosis of pertussis and other respiratory infections in infants.

ABSTRACT:

Background

Clinical criteria for pertussis diagnosis and clinical case definitions for surveillance are based on a cough lasting two or more weeks. As several pertussis cases seek care earlier, a clinical tool independent of cough duration may support earlier recognition. We developed a data-driven algorithm aimed at predicting a laboratory confirmed pertussis.

Methods

We enrolled children <12 months of age presenting with apnoea, paroxistic cough, whooping, or post-tussive vomiting, irrespective of the duration of cough. Patients underwent a RT-PCR test for pertussis and other viruses. Through a logistic regression model, we identified symptoms associated with laboratory confirmed pertussis. We then developed a predictive decision tree through Quinlan's C4.5 algorithm to pr

SUBMITTER: Tozzi AE 

PROVIDER: S-EPMC7377414 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature