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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.
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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