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Retrospective Validation of a Computerized Physiologic Equation to Predict Minute Ventilation Needs in Critically Ill
Jonathan H Pelletier1, Jaskaran Rakkar2, Alicia K Au1,2,3,4,5,6,7
1Division of Critical Care, Department of Pediatrics, Akron Children's Hospital, Akron, OH.
Insights
A new computerized equation accurately predicts minute ventilation needs in critically ill children on mechanical ventilation. This tool outperformed clinician adjustments in 75% of cases, offering a promising advancement in pediatric critical care.
Area of Science:
- Pediatric Critical Care Medicine
- Respiratory Physiology
- Medical Informatics
Background:
- Mechanical ventilation (MV) is a cornerstone therapy for critically ill children.
- Accurate titration of MV is crucial for optimizing patient outcomes and minimizing ventilator-induced lung injury.
- Existing methods for adjusting MV settings often rely on clinician judgment, which can be variable.
Purpose of the Study:
- To validate a computerized physiologic equation for predicting minute ventilation requirements in pediatric patients.
- To compare the performance of this equation against clinician-driven ventilator adjustments in an in silico trial.
- To assess the accuracy of the equation in predicting arterial blood gas (ABG) values.
Main Methods:
- Retrospective cohort study utilizing electronic medical records from a quaternary pediatric intensive care unit (PICU).
- Inclusion criteria: children on invasive MV with serial ABG analysis and pharmacologic neuromuscular blockade (NMB).
- A computerized equation was used to predict PaCO2 and pH based on ABG and minute ventilation data; its recommendations were compared to clinician actions in an in silico trial.
Main Results:
- The study analyzed 15,121 ABGs from 484 patients. The median PaCO2 prediction error was 0.00 mm Hg.
- In the in silico trial involving 1,499 ABGs, the computerized equation's recommendations were more favorable than clinician actions in 75.0% of cases.
- Sensitivity analyses confirmed the favorable performance of the equation across various clinical scenarios.
Conclusions:
- A computerized equation for predicting minute ventilation requirements demonstrated superior performance compared to clinician adjustments in 75% of analyzed ABGs in critically ill children.
- This predictive tool shows potential for improving the management of mechanical ventilation in pediatric intensive care.
- Further prospective validation studies are warranted to confirm these findings in real-world clinical practice.
Objectives:
Mechanical ventilation (MV) is pervasive among critically ill children. We sought to validate a computerized physiologic equation to predict minute ventilation requirements in children and test its performance against clinician actions in an in silico trial.
Design:
Retrospective, electronic medical record linkage, cohort study.
Setting:
Quaternary PICU.
Patients:
Patients undergoing invasive MV, serial arterial blood gas (ABG) analysis within 1-6 hours, and pharmacologic neuromuscular blockade (NMB).
Measurements And Main Results:
ABG values were filtered to those occurring during periods of NMB. Simultaneous ABG and minute ventilation data were linked to predict serial Pa co2 and pH values using previously published physiologic equations. There were 15,121 included ABGs across 500 encounters among 484 patients, with a median (interquartile range [IQR]) of 20 (10-43) ABGs per encounter at a duration of 3.6 (2.1-4.2) hours. The median (IQR) Pa co2 prediction error was 0.00 (-3.07 to 3.00) mm Hg. In Bland-Altman analysis, the mean error was -0.10 mm Hg (95% CI, -0.21 to 0.01 mm Hg). A nested, in silico trial of ABGs meeting criteria for weaning (respiratory alkalosis) or escalation (respiratory acidosis), compared the performance of recommended ventilator changes versus clinician decisions. There were 1,499 of 15,121 ABGs (9.9%) among 278 of 644 (43.2%) encounters included in the trial. Calculated predictions were favorable to clinician actions in 1124 of 1499 ABGs (75.0%), equivalent to clinician choices in 26 of 1499 ABGs (1.7%), and worse than clinician decisions in 349 of 1499 ABGs (23.3%). Calculated recommendations were favorable to clinician decisions in sensitivity analyses limiting respiratory rate, analyzing only when clinicians made changes, excluding asthma, and excluding acute respiratory distress syndrome.
Conclusions:
A computerized equation to predict minute ventilation requirements outperformed clinicians' ventilator adjustments in 75% of ABGs from critically ill children in this retrospective analysis. Prospective validation studies are needed.
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