Novel Oxygenation and Saturation Indices for Mortality Prediction in COVID-19 ARDS Patients: The Impact of Driving Pressure and Mechanical Power.

Background: The oxygenation index (OI) and oxygen saturation index (OSI) are proven mortality predictors in pediatric and adult patients, traditionally using mean airway pressure (Pmean). We introduce novel indices, replacing Pmean with DP (ΔPinsp), MPdyn, and MPtot, assessing their potential for predicting COVID-19 acute respiratory distress syndrome (ARDS) mortality, comparing them to traditional indices. Methods: We studied 361 adult COVID-19 ARDS patients for 7 days, collecting ΔPinsp, MPdyn, and MPtot, OI-ΔPinsp, OI-MPdyn, OI-MPtot, OSI-ΔPinsp, OSI-MPdyn, and OSI-MPtot. We compared these in surviving and non-surviving patients over the first 7 intensive care unit (ICU) days using Mann-Whitney U test. Logistic regression receiver operating characteristic (ROC) analysis assessed AUC and CI values for ICU mortality on day three. We determined cut-off values using Youden's method and conducted multivariate Cox regression on parameter limits. Results: All indices showed significant differences between surviving and non-surviving patients on the third day of ICU care. The AUC values of OI-ΔPinsp were significantly higher than those of P/F and OI-Pmean (P values .0002 and <.0001, respectively). Similarly, AUC and CI values of OSI-ΔPinsp and OSI-MPdyn were significantly higher than those of SpO2/FiO2 and OSI-Pmean values (OSI-ΔPinsp: P < .0001, OSI-MPdyn: P values .047 and .028, respectively). OI-ΔPinsp, OSI-ΔPinsp, OI-MPdyn, OSI-MPdyn, OI-MPtot, and OSI-MPtot had AUC values of 0.72, 0.71, 0.69, 0.68, 0.66, and 0.64, respectively, with cut-off values associated with hazard ratios and P values of 7.06 (HR = 1.84, P = .002), 8.04 (HR = 2.00, P ≤ .0001), 7.12 (HR = 1.68, P = .001), 5.76 (HR = 1.70, P ≤ .0001), 10.43 (HR = 1.52, P = .006), and 10.68 (HR = 1.66, P = .001), respectively. Conclusions: Critical values of all indices were associated to higher ICU mortality rates and extended mechanical ventilation durations. The OI-ΔPinsp, OSI-ΔPinsp, and OSI-MPdyn indices displayed the strongest predictive capabilities for ICU mortality. These novel indices offer valuable insights for intensivists in the clinical management and decision-making process for ARDS patients.

The effect of inspiratory rise time on mechanical power calculations in pressure control ventilation: dynamic approach.

BACKGROUND: Mechanical power may serve as a valuable parameter for predicting ventilation-induced injury in mechanically ventilated patients. Over time, several equations have been developed to calculate power in both volume control ventilation (VCV) and pressure control ventilation (PCV). Among these equations, the linear model mechanical power equation (MPLM) closely approximates the reference method when applied in PCV. The dynamic mechanical power equation (MPdyn) computes power by utilizing the ventilatory work of breathing parameter (WOBv), which is automatically measured by the mechanical ventilator. In our study, conducted in patients with Covid-19 Acute Respiratory Distress Syndrome (C-ARDS), we calculated mechanical power using both the MPLM and MPdyn equations, employing different inspiratory rise times (Tslope) at intervals of 5%, ranging from 5 to 20% and compared the obtained results. RESULTS: In our analysis, we used univariate linear regression at both I:E ratios of 1:2 and 1:1, considering all Tslope values. These analyses revealed that the MPdyn and MPLM equations exhibited strong correlations, with R2 values exceeding 0.96. Furthermore, our Bland-Altman analysis, which compared the power values derived from the MPdyn and MPLM equations for patient averages and all measurements, revealed a mean difference of -0.42 ± 0.41 J/min (equivalent to 2.6% ± 2.3%, p < 0.0001) and -0.39 ± 0.57 J/min (equivalent to 3.6% ± 3.5%, p < 0.0001), respectively. While there was a statistically significant difference between the equations in both absolute value and relative proportion, this difference was not considered clinically relevant. Additionally, we observed that each 5% increase in Tslope time corresponded to a decrease in mechanical power values by approximately 1 J/min. CONCLUSIONS: The differences between mechanical power values calculated using the MPdyn and MPLM equations at various Tslope durations were determined to lack clinical significance. Consequently, for practical and continuous mechanical power estimation in Pressure-Controlled Ventilation (PCV) mode, the MPdyn equation presents itself as a viable option. It is important to note that as Tslope times increased, the calculated mechanical power exhibited a clinically relevant decrease.