Additional file 1 of The effect of inspiratory rise time on mechanical power calculations in pressure control ventilation: dynamic approach
Creators: name: Acicbe, Özlem
name: Özgür, Canan Yazıcı
name: Rahimi, Payam
name: Canan, Emral
name: Aşar, Sinan
name: Çukurova, Zafer
Publisher: name: figshare
Year: 2024
Subjects: subject: Biophysics
subject: Physical Sciences not elsewhere classified
subject: Medicine
subject: Cell Biology
subject: Physiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: Mathematical Sciences not elsewhere classified
subject: Statistics
subject: FOS: Mathematics
subject: Hematology

description: Additional file 1: Table S1. Mechanical power equations in PCV,VCV, and PCV: Pressure Control Ventilation; MPpcv: alternative pressure control power equation, MPpcv(m-simpl): modified pressure control simplified power equation, MPpcv(simpl): simplified pressure control power equation, MPpcv(slope): comprehensive pressure control simplified power equation, VCV: Volume Control Ventilation; MPstd: standart volume control power equation MPvcv-simpl: Gattinoni simplified equation MPvcv-surr: volume control surrogate power equation, MPdyn: dynamic power equation, MPpmean: mean airway pressure (Pmean) derived power equation, CF: conversion factor. Figure S1. Flow chart C-ARDS, Covid-19 related acute respiratory distress syndrome; CHF, congestive heart failure; COPD, Chronic obstructive pulmonary disease; IMV, invasive mechanical ventilation; ECMO, extracorporeal membrane oxygenation; ICU, intensive care unit; LOS, length of stay. Figure S2. Dynamic pressure–volume loop (P–V), pressure—time, flow—time and volume—time graphs of IE 1:1 and Tslope 5%, 10%, 15% and 20% times of the patient ventilated in passive pressure control mode (obtained with screen shots of the Servo-U mechanical ventilator). Figure S3. In univariable logistic regression analyses on mechanical power of all patients average. For IE 1:2 and T-slope 5%: A. MPLM (y-axis) is plotted as function of the MPdyn equation (x-axis). For IE 1:2 and T-slope 10%: B. MPLM (y-axis) is plotted as function of the MPdyn equation (x-axis). For IE 1:2 and Tslope 15%: C. MPLM (y-axis) is plotted as function of the MPdyn equation (x-axis). For IE 1:2 and Tslope 20%: D. MPLM (y-axis) is plotted as function of the MPdyn equation (x-axis). Figure S4. In univariable logistic regression analyses on mechanical power of all patients average. For IE 1:1 and T-slope 5%: A. MPLM (y-axis) is plotted as function of the MPdyn equation (x-axis). For IE 1:1 and Tslope 10%: B. MPLM (y-axis) is plotted as function of the MPdyn equation (x-axis). For IE 1:1 and Tslope 15%: C. MPLM (y-axis) is plotted as function of the MPdyn equation (x-axis). For IE 1:1 and T-slope 20%: D. MPLM (y-axis) is plotted as function of the MPdyn equation (x-axis). Table S2. The patient averages of mechanical power values calculated with MPLM and MPdyn equations at I:E 1:2 and 1:1 ratios at Tslope 5%, 10%, 15%, 20% times were compared with the repeated measures MANOVA method. Tukey's multiple comparisons test was used to detect significant difference between groups. Table S3. The patient averages of Tslope 5%, 10%, 15%, and 20% Pinsp, PEEP, MVe and WOBv parameters were compared with the repeated MANOVA method. Tukey's multiple comparisons test was used to detect significant difference between groups. Table S4. The patient averages of Tslope 5%, 10%, 15%, and 20% RR, TVe, Tinsp, Vee, FiO2, SpO2 and etCO2 parameters were compared with the repeated MANOVA method. Tukey's multiple comparisons test was used to detect significant difference between groups.