TY - JOUR
T1 - Validation of a Computational Phenotype to Identify Acute Brain Dysfunction in Pediatric Sepsis
AU - Alcamo, Alicia M.
AU - Barren, Gregory J.
AU - Becker, Andrew E.
AU - Hayes, Katie
AU - Fitzgerald, Julie C.
AU - Balamuth, Fran
AU - Pennington, Jeffrey W.
AU - Curley, Martha A.Q.
AU - Tasker, Robert C.
AU - Topjian, Alexis A.
AU - Weiss, Scott L.
N1 - Publisher Copyright:
© 2022 by the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - OBJECTIVES: To validate a computational phenotype that identifies acute brain dysfunction (ABD) based on clinician concern for neurologic or behavioral changes in pediatric sepsis. DESIGN: Retrospective observational study. SETTING: Single academic children's hospital. PATIENTS: Four thousand two hundred eighty-nine index sepsis episodes. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: An existing computational phenotype of ABD was optimized to include routinely collected variables indicative of clinician concern for acute neurologic or behavioral change (completion of CT or MRI, electroencephalogram, or new antipsychotic administration). First, the computational phenotype was compared with an ABD reference standard established from chart review of 527 random sepsis episodes to determine criterion validity. Next, the computational phenotype was compared with a separate validation cohort of 3,762 index sepsis episodes to determine content and construct validity. Criterion validity for the final phenotype had sensitivity 83% (95% CI, 76-89%), specificity 93% (90-95%), positive predictive value 84% (77-89%), and negative predictive value 93% (90-96%). In the validation cohort, the computational phenotype identified ABD in 35% (95% CI 33-36%). Content validity was demonstrated as those with the ABD computational phenotype were more likely to have characteristics of neurologic dysfunction and severe illness than those without the ABD phenotype, including nonreactive pupils (15% vs 1%; p < 0.001), Glasgow Coma Scale less than 5 (44% vs 12%; p < 0.001), greater than or equal to two nonneurologic organ dysfunctions (50% vs 25%; p < 0.001), and need for intensive care (81% vs 65%; p < 0.001). Construct validity was demonstrated by higher odds for mortality (odds ratio [OR], 6.9; 95% CI, 5.3-9.1) and discharge to rehabilitation (OR, 11.4; 95% CI 7.4-17.5) in patients with, versus without, the ABD computational phenotype. CONCLUSIONS: A computational phenotype of ABD indicative of clinician concern for new neurologic or behavioral change offers a valid retrospective measure to identify episodes of sepsis that involved ABD. This computational phenotype provides a feasible and efficient way to study risk factors for and outcomes from ABD using routinely collected clinical data.
AB - OBJECTIVES: To validate a computational phenotype that identifies acute brain dysfunction (ABD) based on clinician concern for neurologic or behavioral changes in pediatric sepsis. DESIGN: Retrospective observational study. SETTING: Single academic children's hospital. PATIENTS: Four thousand two hundred eighty-nine index sepsis episodes. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: An existing computational phenotype of ABD was optimized to include routinely collected variables indicative of clinician concern for acute neurologic or behavioral change (completion of CT or MRI, electroencephalogram, or new antipsychotic administration). First, the computational phenotype was compared with an ABD reference standard established from chart review of 527 random sepsis episodes to determine criterion validity. Next, the computational phenotype was compared with a separate validation cohort of 3,762 index sepsis episodes to determine content and construct validity. Criterion validity for the final phenotype had sensitivity 83% (95% CI, 76-89%), specificity 93% (90-95%), positive predictive value 84% (77-89%), and negative predictive value 93% (90-96%). In the validation cohort, the computational phenotype identified ABD in 35% (95% CI 33-36%). Content validity was demonstrated as those with the ABD computational phenotype were more likely to have characteristics of neurologic dysfunction and severe illness than those without the ABD phenotype, including nonreactive pupils (15% vs 1%; p < 0.001), Glasgow Coma Scale less than 5 (44% vs 12%; p < 0.001), greater than or equal to two nonneurologic organ dysfunctions (50% vs 25%; p < 0.001), and need for intensive care (81% vs 65%; p < 0.001). Construct validity was demonstrated by higher odds for mortality (odds ratio [OR], 6.9; 95% CI, 5.3-9.1) and discharge to rehabilitation (OR, 11.4; 95% CI 7.4-17.5) in patients with, versus without, the ABD computational phenotype. CONCLUSIONS: A computational phenotype of ABD indicative of clinician concern for new neurologic or behavioral change offers a valid retrospective measure to identify episodes of sepsis that involved ABD. This computational phenotype provides a feasible and efficient way to study risk factors for and outcomes from ABD using routinely collected clinical data.
KW - acute brain dysfunction
KW - computational phenotype
KW - neurologic dysfunction; pediatric
KW - sepsis
UR - https://www.scopus.com/pages/publications/85143198971
U2 - 10.1097/PCC.0000000000003086
DO - 10.1097/PCC.0000000000003086
M3 - Article
C2 - 36214585
AN - SCOPUS:85143198971
SN - 1529-7535
VL - 23
SP - 1027
EP - 1036
JO - Pediatric Critical Care Medicine
JF - Pediatric Critical Care Medicine
IS - 12
ER -