Biomarker-enhanced Artificial Intelligence Based Pediatric Sepsis Screening Tool

Официальное название

Biomarker-enhanced Artificial Intelligence Based Pediatric Sepsis Screening Tool Towards Early Recognition and Personalized Therapeutics

Обзор

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.

Подробное описание

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.).

Вмешательства

• Диагностический тест Pediatric sepsis screening tool (either algorithmic or manual)
  All participating institutions employ either an algorithmic, manual, or combined algorithmic/manual pediatric sepsis screening protocol for patients that present with fever and/or a concern for infection. While the specific parameters tested in screening tools differ, they generally consist of tests for a systemic inflammatory response (e.g. SIRS) and/or organ dysfunction (e.g. SOFA) and/or high susceptibility (e.g. immunocompromised) factors.

Первичные конечные точки

• Effective Expert System-based Pediatric Sepsis Screening Tool (PSCT) [Срок оценки: Final 3 months of study period.]
• High performance Expert System-based Pediatric Sepsis Screening Tool (PSCT) [Срок оценки: Using "early data" following presentation to ED, e.g., upon receipt of biomarker data within 1st 3 hours of presentation)]

Вторичные конечные точки (1)

• Effective sepsis phenotyping for personalized treatment [Срок оценки: Features based on 1st 6 hours following presentation in patients diagnosed with sepsis and treatment protocol initiated.]

Критерии участия

Критерии включения

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.

Критерии исключения

• 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

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Случай-контроль

Центры проведения

США · 1 центр

• Children's National Hospital — Washington D.C.

Публикации

• Goldstein B, Giroir B, Randolph A; International Consensus Conference on Pediatric Sepsis. International pediatric sepsis consensus conference: definitions for sepsis and organ dysfunction in pediatrics. Pediatr Crit Care Med. 2005 Jan;6(1):2-8. doi: 10.1097/01.PCC.0000149131.72248.E6. PMID 15636651
• Eisenberg M, Madden K, Christianson JR, Melendez E, Harper MB. Performance of an Automated Screening Algorithm for Early Detection of Pediatric Severe Sepsis. Pediatr Crit Care Med. 2019 Dec;20(12):e516-e523. doi: 10.1097/PCC.0000000000002101. PMID 31567896
• Eisenberg MA, Freiman E, Capraro A, Madden K, Monuteaux MC, Hudgins J, Harper M. Outcomes of Patients with Sepsis in a Pediatric Emergency Department after Automated Sepsis Screening. J Pediatr. 2021 Aug;235:239-245.e4. doi: 10.1016/j.jpeds.2021.03.053. Epub 2021 Mar 30. PMID 33798508
• Iwashyna TJ, Odden A, Rohde J, Bonham C, Kuhn L, Malani P, Chen L, Flanders S. Identifying patients with severe sepsis using administrative claims: patient-level validation of the angus implementation of the international consensus conference definition of severe sepsis. Med Care. 2014 Jun;52(6):e39-43. doi: 10.1097/MLR.0b013e318268ac86. PMID 23001437
• Mathias B, Mira JC, Larson SD. Pediatric sepsis. Curr Opin Pediatr. 2016 Jun;28(3):380-7. doi: 10.1097/MOP.0000000000000337. PMID 26983000
• Weiss SL, Parker B, Bullock ME, Swartz S, Price C, Wainwright MS, Goodman DM. Defining pediatric sepsis by different criteria: discrepancies in populations and implications for clinical practice. Pediatr Crit Care Med. 2012 Jul;13(4):e219-26. doi: 10.1097/PCC.0b013e31823c98da. PMID 22460773
• Scott HF, Brilli RJ, Paul R, Macias CG, Niedner M, Depinet H, Richardson T, Riggs R, Gruhler H, Larsen GY, Huskins WC, Balamuth F; Improving Pediatric Sepsis Outcomes (IPSO) Collaborative Investigators.. Evaluating Pediatric Sepsis Definitions Designed for Electronic Health Record Extraction and Multicenter Quality Improvement. Crit Care Med. 2020 Oct;48(10):e916-e926. doi: 10.1097/CCM.00000000000 PMID 32931197
• Lippi G. Sepsis biomarkers: past, present and future. Clin Chem Lab Med. 2019 Aug 27;57(9):1281-1283. doi: 10.1515/cclm-2018-1347. No abstract available. PMID 30710482

Идентификаторы

NCT: NCT05311046 · NIAID 1R41AI167224-01

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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