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Severity Trajectories of Pediatric Inpatients Using the Criticality Index
Eduardo A Trujillo Rivera1, Anita K Patel2, Qing Zeng-Treitler1
1George Washington University School of Medicine and Health Sciences, Washington, DC.
Insights
The Criticality Index accurately reflects pediatric patient illness severity, showing distinct trajectories for survivors and deaths across ICU and non-ICU care settings. This tool validates clinical expectations for patient care pathways.
Area of Science:
- Pediatric critical care medicine
- Biomedical data science
- Health informatics
Background:
- Assessing illness severity in pediatric patients is crucial for predicting outcomes.
- Existing methods may not fully capture dynamic changes in patient condition.
- Understanding illness trajectories in Intensive Care Units (ICUs) and non-ICU settings is vital.
Purpose of the Study:
- To evaluate the Criticality Index's ability to describe illness severity trajectories.
- To compare severity trajectories between survivors and deaths in pediatric patients.
- To analyze trajectories across different care pathways (ICU vs. non-ICU).
Main Methods:
- Utilized the Criticality Index, a deep neural network-based measure of illness severity.
- Analyzed sequential 6-hour Criticality Index values for pediatric patients.
- Compared Criticality Index trajectories for five groups based on ICU and non-ICU care sequences.
Main Results:
- Criticality Index values were significantly higher in the ICU compared to non-ICU settings (80-fold).
- Patients transferred to the ICU had higher non-ICU Criticality Index values than those never transferred (40-fold).
- ICU deaths exhibited higher Criticality Index values than ICU survivors, with distinct trajectory patterns.
Conclusions:
- The Criticality Index demonstrated strong validity in reflecting expected clinical courses for pediatric patients.
- Severity trajectories accurately differentiated between survivors and deaths across various care settings.
- The Criticality Index provides a reliable measure for assessing illness severity dynamics in pediatric care.
Objectives:
To assess severity of illness trajectories described by the Criticality Index for survivors and deaths in five patient groups defined by the sequence of patient care in ICU and routine patient care locations.
Design:
The Criticality Index developed using a calibrated, deep neural network, measures severity of illness using physiology, therapies, and therapeutic intensity. Criticality Index values in sequential 6-hour time periods described severity trajectories.
Setting:
Hospitals with pediatric inpatient and ICU care.
Patients:
Pediatric patients never cared for in an ICU (n = 20,091), patients only cared for in the ICU (n = 2,096) and patients cared for in both ICU and non-ICU care locations (n = 17,023) from 2009 to 2016 Health Facts database (Cerner Corporation, Kansas City, MO).
Interventions:
None.
Measurements And Main Results:
Criticality Index values were consistent with clinical experience. The median (25-75th percentile) ICU Criticality Index values (0.878 [0.696-0.966]) were more than 80-fold higher than the non-ICU values (0.010 [0.002-0.099]). Non-ICU Criticality Index values for patients transferred to the ICU were 40-fold higher than those never transferred to the ICU (0.164 vs 0.004). The median for ICU deaths was higher than ICU survivors (0.983 vs 0.875) (p < 0.001). The severity trajectories for the five groups met expectations based on clinical experience. Survivors had increasing Criticality Index values in non-ICU locations prior to ICU admission, decreasing Criticality Index values in the ICU, and decreasing Criticality Index values until hospital discharge. Deaths had higher Criticality Index values than survivors, steeper increases prior to the ICU, and worsening values in the ICU. Deaths had a variable course, especially those who died in non-ICU care locations, consistent with deaths associated with both active therapies and withdrawals/limitations of care.
Conclusions:
Severity trajectories measured by the Criticality Index showed strong validity, reflecting the expected clinical course for five diverse patient groups.
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