Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data.

ABSTRACT:

Background

Rapid antibiotic administration is known to improve sepsis outcomes, however early diagnosis remains challenging due to complex presentation. Our objective was to develop a model using readily available electronic health record (EHR) data capable of recognizing infant sepsis at least 4 hours prior to clinical recognition.

Methods and findings

We performed a retrospective case control study of infants hospitalized ≥48 hours in the Neonatal Intensive Care Unit (NICU) at the Children's Hospital of Philadelphia between September 2014 and November 2017 who received at least one sepsis evaluation before 12 months of age. We considered two evaluation outcomes as cases: culture positive-positive blood culture for a known pathogen (110 evaluations); and clinically positive

SUBMITTER: Masino AJ 

PROVIDER: S-EPMC6386402 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature