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Agreement Between Automated and Equation-Derived Mechanical Power in Pediatric Mechanical Ventilation
Farhan A Rashid Shaikh1, Monesh Kethineni Bhaskaran1, Vikas Muppa1
1Drs. Shaikh, Bhaskaran, Muppa, Jogu, Sachane, Yerra, and Chirla are affiliated with the Department of Pediatric Intensive Care, Rainbow Children's Hospital, Hyderabad, India.
Background:
Newer ventilators provide automated real-time mechanical power (MPauto) measurements, but their accuracy in children across ventilation modes remains uncertain. We aimed to evaluate the agreement between the MPauto measured on the Mindray SV-600 ventilator and the equation-derived MP (MPcalc) across two tidal volume (VT) settings, ventilation modes, and predefined age groups in ventilated children.
Method:
In this prospective observational physiology study, consecutive mechanically ventilated children aged 1 month to 18 years were enrolled between August 2024 and May 2025 in a 30-bed pediatric ICU. MPauto was compared with MPcalc, using comprehensive and surrogate equations during continuous mandatory volume-control (VC-CMV) and pressure-control (PC-CMV) modes at VT of 6 and 8 mL/kg body weight. Subgroup analyses considered age and pediatric ARDS. In VC-CMV mode, MP was calculated with Gattinoni's equation (MPVCcomprehensive) and Giosa's equation (MPVCsurrogate). In PC-CMV mode, Van der Meijden's equation (MPPCcomprehensive) and Becher's equation (MPPCsurrogate) were used. Bland-Altman analyses evaluated agreement.
Results:
We included 147 children, with a median (interquartile range [IQR]) age of 49 (16-92) months, of whom 34 (23%) had pediatric ARDS. MPauto showed strong agreement with MPcalc across ventilation modes and VT settings. The agreement was highest in VC-CMV, with minimal bias (-0.12 to +0.011 J/min; intra-class correlation [ICC] ≥0.95) and >88% of observations within clinical limits of agreement. In PC-CMV, MPauto demonstrated a systematic negative bias relative to MPcalc (minimal bias -1.23 to -0.62 J/min; ICC ≥0.92), with similar findings in subjects with pediatric ARDS. Age influenced agreement between MPauto and MPcalc (slope -0.008 to -0.005), especially in PC-CMV mode (R2 = 0.226-0.27). Pediatric ARDS status affected this relationship only in PC-CMV mode (P = .02 for MPPCcomprehensive and P = .006 for MPPCsurrogate).
Conclusion:
MPauto demonstrated strong agreement with equation-derived MP during VC-CMV mode across different age groups. However, MPauto showed a systematic negative bias relative to equation-derived MP in PC-CMV mode, particularly among younger children and those with pediatric ARDS.
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