A Near Real-Time Risk Analytics Algorithm Predicts Elevated Lactate Levels in Pediatric Cardiac Critical Care Patients

Ahmed Asfari, Department of Pediatric Cardiology, Section of Cardiac Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL.
Joshua Wolovits, Division of Critical Care, Department of Pediatrics, UT Southwestern Medical Center, Dallas, TX.
Avihu Z. Gazit, Divisions of Critical Care and Cardiology, Department of Pediatrics, Washington University, St. Louis, MO.
Qalab Abbas, Department of Pediatrics and Child Health, Section of Pediatric Critical Care Medicine, Aga Khan University Hospital, Karachi, Pakistan.
Andrew J. Macfadyen, Division of Critical Care, Department of Pediatrics, University of Nebraska Medical Center, Omaha, NE.
David S. Cooper, Division of Cardiology, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH.
Craig Futterman, Division of Critical Care, Department of Pediatrics, George Washington University, Washington, DC.
Jamie S. Penk, Division of Cardiology, Department of Pediatrics, Northwestern University, Chicago, IL.
Robert B. Kelly, Division of Critical Care, Children's Hospital of Orange County, Orange, CA.
Joshua W. Salvin, Division of Cardiology, Department of Pediatrics, Harvard Medical School, Boston, MA.
Santiago Borasino, Department of Pediatric Cardiology, Section of Cardiac Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL.
Hayden J. Zaccagni, Department of Pediatric Cardiology, Section of Cardiac Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL.

Document Type

Journal Article

Publication Date

12-1-2023

Journal

Critical care explorations

Volume

5

Issue

12

DOI

10.1097/CCE.0000000000001013

Keywords

analytic algorithms; inadequate delivery of oxygen; low-cardiac output state; pediatric cardiac surgery; risk estimation; serum lactate

Abstract

BACKGROUND: Postoperative pediatric congenital heart patients are predisposed to develop low-cardiac output syndrome. Serum lactate (lactic acid [LA]) is a well-defined marker of inadequate systemic oxygen delivery. OBJECTIVES: We hypothesized that a near real-time risk index calculated by a noninvasive predictive analytics algorithm predicts elevated LA in pediatric patients admitted to a cardiac ICU (CICU). DERIVATION COHORT: Ten tertiary CICUs in the United States and Pakistan. VALIDATION COHORT: Retrospective observational study performed to validate a hyperlactatemia (HLA) index using T3 platform data (Etiometry, Boston, MA) from pediatric patients less than or equal to 12 years of age admitted to CICU ( = 3,496) from January 1, 2018, to December 31, 2020. Patients lacking required data for module or LA measurements were excluded. PREDICTION MODEL: Physiologic algorithm used to calculate an HLA index that incorporates physiologic data from patients in a CICU. The algorithm uses Bayes' theorem to interpret newly acquired data in a near real-time manner given its own previous assessment of the physiologic state of the patient. RESULTS: A total of 58,168 LA measurements were obtained from 3,496 patients included in a validation dataset. HLA was defined as LA level greater than 4 mmol/L. Using receiver operating characteristic analysis and a complete dataset, the HLA index predicted HLA with high sensitivity and specificity (area under the curve 0.95). As the index value increased, the likelihood of having higher LA increased ( < 0.01). In the validation dataset, the relative risk of having LA greater than 4 mmol/L when the HLA index is less than 1 is 0.07 (95% CI: 0.06-0.08), and the relative risk of having LA less than 4 mmol/L when the HLA index greater than 99 is 0.13 (95% CI, 0.12-0.14). CONCLUSIONS: These results validate the capacity of the HLA index. This novel index can provide a noninvasive prediction of elevated LA. The HLA index showed strong positive association with elevated LA levels, potentially providing bedside clinicians with an early, noninvasive warning of impaired cardiac output and oxygen delivery. Prospective studies are required to analyze the effect of this index on clinical decision-making and outcomes in pediatric population.

Department

Pediatrics

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