Biomarker-enhanced Artificial Intelligence Based Pediatric Sepsis Screening Tool

Computer Technology Associates

Status: Begins enrollment in 1 month

Conditions: Sepsis

Treatments: Diagnostic Test: Pediatric sepsis screening tool (either algorithmic or manual)

Study type: Observational

Funder types: Other; Industry

Identifiers

NCT05311046

NIAID 1R41AI167224-01

Details and patient eligibility

About

The overall objective of this proposed research is the derivation of a biomarker-enhanced artificial intelligence (AI)-based pediatric sepsis screening tool (PSCT) (software) that can be used in combination with the hospital's electronic health record (EHR) system to monitor and assess real-time emergency department (ED) electronic health record (EHR) data towards the enhancement of early pediatric sepsis recognition and the initiation of timely, aggressive personalized sepsis therapy known to improve patient outcomes.

It is hypothesized that the screening performance (e.g., positive predictive value) of the envisioned screening tool will be significantly enhanced by the inclusion of a biomarker panel test results (PERSEVERE) that have been shown to be effective in prediction of clinical deterioration in non-critically ill immunocompromised pediatric patients evaluated for infection. It is also hypothesized that enhanced phenotypes can be derived by clustering PERSEVERE biomarkers combined with routinely collected EHR data towards improved personalized medicine.

Full description

Background and Rationale Existing automated pediatric sepsis screening tools (PSCT) based on consensus criteria currently used in emergency departments do not improve early recognition and/or inform personalized therapeutic decisions leading to improved outcomes. The Improving Pediatric Sepsis Outcomes (IPSO) initiative found that by including patients that receive treatment, the extended criteria captured not only patients who developed sepsis with organ dysfunction (OD), but also those in whom early sepsis was treated with OD potentially averted.

The objective of the proposed effort is to derive and retrospectively validate a biomarker-enhanced AI-based pediatric sepsis screening tool that can be used to screen ED EHR data to improve early recognition, severity stratification, and the timely initiation of personalized sepsis therapy. CTA and its 6 institutional partners jointly propose to establish two de-identified patient registries: 1) the "EHR-data only cohort" (N = 2000) and 2) the "EHR + biomarker data cohort" (N = 400) in support of this objective.

Encounter data elements to be abstracted from EHRs for inclusion in these registries include both structured (e.g., time-stamped physiological measurements, treatments, procedures, outcomes) as well as free text notes.

Data Analysis and biases All study data, including physiological data extracted from patient EHR and results of biomarker assays will be analyzed using a variety of machine learning algorithms and techniques towards producing a high precision sepsis screening predictive model. Analytic methods involve standard descriptive statistical analysis of predictive classification performance (e.g., AUC, sensitivity/specificity, PPV, etc.).

Enrollment: 12,961 estimated patients

Sex: All

Ages: 3 months to 45 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

Patients 3 months -45 years of age, inclusive

• Diagnosed with sepsis by a clinician or trigger a sepsis alert and a blood culture is ordered. Controls will be false positive patients.
• For those patients that will be prospectively enrolled for blood sample collection: will require a venipuncture or intravenous line placement.

Exclusion criteria

• Patients participating in an investigational program with interventions outside of routine clinical practice
• Patients with parents or LARs that don't speak English or Spanish
• Pregnancy

Trial design

12,961 participants in 2 patient groups

Retrospective EHR-data only group

Description:

Members of this group are pediatric patients between the ages of 3 months to 45 years inclusive, that presented to one of the six participating institution's emergency department between the years 2016-2021 and screened positive for suspicion of sepsis using the institution's existing pediatric sepsis screening protocol and receive a blood culture order. Current pediatric screening/alerting tools are known to be highly sensitive but poorly specific. "Cases" in this cohort will be comprised of those that are ultimately diagnosed with sepsis and/or receive protocolized sepsis treatment. "Controls" in this cohort will be those with a false positive alert, i.e., are not diagnosed with sepsis and do not receive protocolized sepsis treatment.

Treatment:

Diagnostic Test: Pediatric sepsis screening tool (either algorithmic or manual)

Prospective EHR and Biomarker data group

Description:

Members of this group are pediatric patients between the ages of 3 months to 45 years inclusive, that presented to one of the six participating institution's emergency department during the study enrollment period, screen positive for suspicion of sepsis using the institution's existing pediatric sepsis screening protocol, receive a blood culture order and provide informed consent/assent for the collection of a 1-5 mL blood sample to be used to measure PERSEVERE biomarkers. Members of this cohort will have also consented to the reuse of their medical record data for the research. Current pediatric screening/alerting tools are known to be highly sensitive but poorly specific. "Cases" in this cohort will be comprised of those that are ultimately diagnosed with sepsis and/or receive protocolized sepsis treatment. "Controls" in this cohort will be those with a false positive alert, i.e., are not diagnosed with sepsis and do not receive protocolized sepsis treatment.

Treatment:

Diagnostic Test: Pediatric sepsis screening tool (either algorithmic or manual)