TY - JOUR
T1 - The effects of respiratory rate and tidal volume on pulse pressure variation in healthy lungs-a generalized additive model approach may help overcome limitations
AU - Enevoldsen, Johannes
AU - Brandsborg, Birgitte
AU - Juhl-Olsen, Peter
AU - Rees, Stephen Edward
AU - Thaysen, Henriette Vind
AU - Scheeren, Thomas W L
AU - Vistisen, Simon Tilma
N1 - © 2023. The Author(s).
PY - 2024/2
Y1 - 2024/2
N2 - Pulse pressure variation (PPV) is a well-established method for predicting fluid responsiveness in mechanically ventilated patients. The predictive accuracy is, however, disputed for ventilation with low tidal volume (VT) or low heart-rate-to-respiratory-rate ratio (HR/RR). We investigated the effects of VT and RR on PPV and on PPV's ability to predict fluid responsiveness. We included patients scheduled for open abdominal surgery. Prior to a 250 ml fluid bolus, we ventilated patients with combinations of VT from 4 to 10 ml kg-1 and RR from 10 to 31 min-1. For each of 10 RR-VT combinations, PPV was derived using both a classic approach and a generalized additive model (GAM) approach. The stroke volume (SV) response to fluid was evaluated using uncalibrated pulse contour analysis. An SV increase > 10% defined fluid responsiveness. Fifty of 52 included patients received a fluid bolus. Ten were fluid responders. For all ventilator settings, fluid responsiveness prediction with PPV was inconclusive with point estimates for the area under the receiver operating characteristics curve between 0.62 and 0.82. Both PPV measures were nearly proportional to VT. Higher RR was associated with lower PPV. Classically derived PPV was affected more by RR than GAM-derived PPV. Correcting PPV for VT could improve PPV's predictive utility. Low HR/RR has limited effect on GAM-derived PPV, indicating that the low HR/RR limitation is related to how PPV is calculated. We did not demonstrate any benefit of GAM-derived PPV in predicting fluid responsiveness.Trial registration: ClinicalTrials.gov, reg. March 6, 2020, NCT04298931.
AB - Pulse pressure variation (PPV) is a well-established method for predicting fluid responsiveness in mechanically ventilated patients. The predictive accuracy is, however, disputed for ventilation with low tidal volume (VT) or low heart-rate-to-respiratory-rate ratio (HR/RR). We investigated the effects of VT and RR on PPV and on PPV's ability to predict fluid responsiveness. We included patients scheduled for open abdominal surgery. Prior to a 250 ml fluid bolus, we ventilated patients with combinations of VT from 4 to 10 ml kg-1 and RR from 10 to 31 min-1. For each of 10 RR-VT combinations, PPV was derived using both a classic approach and a generalized additive model (GAM) approach. The stroke volume (SV) response to fluid was evaluated using uncalibrated pulse contour analysis. An SV increase > 10% defined fluid responsiveness. Fifty of 52 included patients received a fluid bolus. Ten were fluid responders. For all ventilator settings, fluid responsiveness prediction with PPV was inconclusive with point estimates for the area under the receiver operating characteristics curve between 0.62 and 0.82. Both PPV measures were nearly proportional to VT. Higher RR was associated with lower PPV. Classically derived PPV was affected more by RR than GAM-derived PPV. Correcting PPV for VT could improve PPV's predictive utility. Low HR/RR has limited effect on GAM-derived PPV, indicating that the low HR/RR limitation is related to how PPV is calculated. We did not demonstrate any benefit of GAM-derived PPV in predicting fluid responsiveness.Trial registration: ClinicalTrials.gov, reg. March 6, 2020, NCT04298931.
KW - Dynamic filling variable
KW - Fluid responsiveness
KW - Heart–lung interaction
KW - Hemodynamic monitoring
KW - Mechanical ventilation
KW - Pulse pressure variation
UR - http://www.scopus.com/inward/record.url?scp=85176746334&partnerID=8YFLogxK
U2 - 10.1007/s10877-023-01090-6
DO - 10.1007/s10877-023-01090-6
M3 - Journal article
C2 - 37968547
SN - 1387-1307
VL - 38
SP - 57
EP - 67
JO - Journal of Clinical Monitoring and Computing
JF - Journal of Clinical Monitoring and Computing
IS - 1
ER -