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Original Article • Crit. Care Sci. 37 • 2025 • https://doi.org/10.62675/2965-2774.20250403 linkcopy

Open-access Effects of secular changes in tidal volume and respiratory rate on the mechanical power of ventilation: a retrospective single-center study of invasively ventilated patients

AuthorshipSCIMAGO INSTITUTIONS RANKINGS

    ABSTRACT

    Objective:  To evaluate how secular changes in tidal volume and respiratory rate influence the mechanical power of ventilation during the first 24 hours in critically ill patients over two decades and to compare their effects in patients with high and low respiratory system compliance.

    Methods:  This secondary analysis of the Amsterdam University Medical Center database included two time periods: 2003 to 2009 and 2010 to 2016. The primary endpoint was mechanical power. Analyses also assessed secular changes in mechanical power in patients with respiratory system compliance groups.

    Results:  Among 4,877 patients (2,536 patients in 2003 - 2009, and 2,341 in 2010 - 2016), median tidal volume decreased (mean difference of −0.6 [-0.4 to −0.7] mL/kg predicted body weight; p < 0.01), median respiratory rate increased (mean difference of +1.0 [+0.75 to +1.25] breath/minute; p < 0.01), and median mechanical power fell from 12.1 (8.7 - 16.7) J/minute to 10.4 (7.6 - 14.6) J/minute (mean difference of −1.7 [-1.2 to −2.0] J/minute; p < 0.01). In patients with low respiratory system compliance, median mechanical power decreased more significantly (13.4 J/minute to 11.7 J/minute, mean difference of −1.7 J/minute; p < 0.01) compared to those with high respiratory system compliance (10.5 J/minute to 9.7 J/minute, mean difference of −0.8 J/minute; p < 0.01) despite comparable respiratory rate changes

    Conclusion:  In this single-center cohort, secular changes in tidal volume and respiratory rate were associated with lower mechanical power, particularly in patients with low respiratory system compliance.

    Keywords:
    Intensive care; Ventilation; Tidal volume; Respiratory rate; Intensity of ventilation; Mechanical power

    INTRODUCTION

    Ventilation with a low tidal volume (VT) has been shown to improve outcomes of patients with acute respiratory distress syndrome (ARDS) compared to ventilation with a high VT.(1) Consequently, clinical practices have shifted towards ‘low VT ventilation’ (LTVV), not only in patients with ARDS but also in patients not having this severe form of acute hypoxemic respiratory failure.(2-6) We may want to refine the concept that VT should invariably be low. Firstly, we have gained insights into the significance of a low driving pressure (ΔP), which may be equally critical.(7) Secondly, adopting LTVV can lead to a compensatory increase in respiratory rate (RR) to maintain minute ventilation with potential consequences.(8,9) Last but not least, the interplay between these key ventilator settings could be crucial, as a combination of low VT with high RR could be beneficial in a patient with a lower respiratory system compliance (CRS), but harmful in patients with higher CRS.(10,11)

    Rather than focusing solely on VT, mechanical power (MP) of ventilation integrates VT, airway pressures, and RR to quantify the total energy delivered to the respiratory system.(12,13) Although MP equations assume a direct relationship between VT and MP, the physiological interplay is more complex. Changes in RR may compensate for reductions in VT to maintain minute ventilation, while both VT and RR can affect airway pressures in different ways.(14) Despite its physiological relevance, MP remains underutilized in clinical practice, as LTVV is simpler to implement and does not require complex calculations.(13) However, whether reducing VT alone reliably minimizes mechanical energy exposure in clinical settings remains uncertain.

    Our objective was to evaluate how secular changes in VT and RR influence the mechanical power of ventilation during the first 24 hours in critically ill patients over two decades and to compare their effects in patients with high and low respiratory system compliance. We assessed how secular changes in VT and RR affect MP in invasively ventilated patients in a large single-center cohort spanning from 2003 to 2016. We hypothesized that a more intense use of LTVV would decrease MP. Additionally, we compared the effects of secular changes in VT and RR on MP in patients with high versus low CRS.

    METHODS

    Design and setting

    This is a secondary analysis of the Amsterdam University Medical Center database (the AmsterdamUMCdb; version 1.0.2, released March 2020). AmsterdamUMCdb is a publicly freely accessible database, comprising anonymized health data from intensive care unit (ICU) patients between 2003 and 2016. The creation of this database was endorsed by the European Society of Intensive Care Medicine (ESICM) and its Data Science Section. An external privacy expert audited the process, and the Ethics Section of the ESICM provided external ethics review and appraisal. Need for individual patient consent was waived as this database collected data captured as part of routine care, and data were deidentified to protect patient privacy. Compliance with General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA) was ensured through detailed legal reviews and robust privacy safeguards, overcoming legal and ethical hurdles.(15)

    Inclusion and exclusion criteria

    Patients were eligible for this secondary analysis if they were aged over 16 years and they had received invasive ventilation for at least 24 hours. Patients were excluded in case their datasets were incomplete about ventilator variables and parameters necessary for the calculation of MP. In case a patient was admitted more than once, only the data of the first admission were used.

    Data collected

    Baseline demographics and patients’ characteristics were captured at baseline. The severity of patients was evaluated based on the Acute Physiology and Chronic Health Evaluation (APACHE II) and the Sequential Organ Failure Assessment (SOFA) score. Ventilatory variables, including VT, airway pressures, and RR, were recorded at a frequency of up to one value per minute following patient intubation. To create a manageable dataset, we calculated the average value of each variable for blocks of 60 minutes, thereby reducing the dataset to a single averaged value per variable for each time block.

    Calculations

    Tidal volume was expressed in mL/kg predicted body weight (PBW), and ΔP, CRS, and MP were calculated using the following equations:(1)

    [Eq. 1] PBW = 45.5 + 0.91 ∗ ( centimeters of height − 152.4 ) (for females)

    and

    [Eq. 2] PBW = 50 + 0.91 * (centimeters of height − 152.4 ) (for males)

    The dynamic MP was calculated using the following equation:

    [Eq. 3](12,16,17) MP ( J / minute ) = 0.098 ∗ V T ( L ) ∗ RR ∗ ( Pmax − 1 2 ∗ ΔP )

    Driving pressure and CRS were calculated using the following equations:

    [Eq. 4] ΔP ( cmH 2 O ) = Pmax-positive end-expiratory pressure (PEEP)

    and

    [Eq. 5] C RS ( mL / cm H 2 O ) = V T ( mL ) / ΔP ( cmH 2 O )

    Definitions

    Low VT ventilation was defined as ventilation with VT < 8mL/kg PBW.(6) Low-intensity was defined pragmatically as ventilation with ΔP < 15cmH2O(7) and MP < 17J/minute,(17) while high-intensity ventilation was defined as ΔP ≥ 15cmH2O or MP ≥ 17J/minute. Accordingly, groups were labeled as follows: ventilation with low VT at low-intensity (LV-L), ventilation with high VT at low-intensity (HV-L), ventilation with low VT at high-intensity (LV-H), and ventilation with high VT at high-intensity (HV-H). We used the median split method to create the two subgroups, low CRS and high CRS.(18)

    Study endpoints

    Mechanical power, calculated 24 hours after the initiation of invasive ventilation, was the primary endpoint of this analysis. Secondary exploratory endpoints included ICU-, 28-, and 90-day mortality, ICU length of stay, and ventilator-free days in ICU survivors at day 28 (VFD-28).

    Sample size

    We did not perform a formal sample size calculation; instead, the number of eligible patients in the database served as the sample size.

    Statistical analysis

    Demographic, clinical, and outcome variables were presented as percentages for categorical variables and as medians with interquartile ranges (IQR) for continuous variables.

    We anticipated a shift toward lower VT in the second temporal cohort of patients, following a broader implementation to patients without ARDS.(19-21) For analytical purposes, the AmsterdamUMCdb was divided into two cohorts, one lasting from 2003 to 2009 and one from 2010 to 2016. We employed time-weighted averaging for each variable to account for daily fluctuations in the data. The daily value of each variable for the patient was calculated by averaging the medians of four 6-hour intervals over the first 24 hours. To compare variables between patients in the two temporal cohorts, we performed the Wilcoxon signed-rank test for continuous variables and Fisher's exact test for categorical variables.

    We used cumulative distribution plots to visualize ventilator settings and MP differences between the two temporal cohorts. Herein, VT, ΔP, RR, and MP were plotted against cumulative frequencies ranging from 0 to 1. Both temporal cohorts were plotted on the same graph to facilitate comparison, providing a visual representation of differences in ventilator variables and parameters. Tidal volume, ΔP, RR, and MP correlations are visualized using scatter plot diagrams.

    The cumulative incidence of ICU discharge and mortality over time was calculated based on the type of ventilation: LV-L, LV-H, HV-L, and HV-H. Discharge and death were treated as competing events, with prolonged ICU hospitalization serving as the reference. The follow-up period continued until the end of the study, at which point the data were censored. Ventilation-free days up to 28 days were calculated by subtracting the total number of days a patient was on mechanical ventilation within the first 28 days from 28.

    We performed several post hoc analysis. Since we noticed a difference in patient demographics between the two secular cohorts - a 10% higher proportion of medical patients in the 2010 - 2016 cohort - to address this issue, we conducted a post hoc analysis in which we first divided the cohort into medical and surgical patients, and then repeated the analysis within each group separately. In a second post hoc analysis, we employed a simplified mechanical power equation specifically adapted for pressure-controlled ventilation modes (Table 1S - Supplementary Material).(22) In a third post hoc analysis, we calculated MP using alternative equations (Table 1S - Supplementary Material), and we normalized MP to PBW and to CRS as done previously.(9,23,24)

    All analyses were performed in R through the R-studio interface (www.r-project.org, R version 4.3.1). A p-value < 0.05 was considered significant.

    RESULTS

    Patients

    Of the 4,877 included patients, 2,536 were admitted between 2003 and 2009 and 2,341 between 2010 and 2016 (Figure 1S - Supplementary Material). Baseline demographics and patient characteristics were similar for the two temporal cohorts (Table 1). Patients with low CRS had a higher prevalence of females, ICU hospitalizations mostly related to respiratory problems, and lower oxygenation metrics compared to those with high CRS.

    Thumbnail
    Table 1
    Characteristics of patients from 2003 - 2009 and 2010 - 2016, shown for both the total population and subgroups categorized by low and high respiratory system compliance, with a cut-off value of 36mL/cmH2O

    Secular changes in tidal volume, respiratory rate, and mechanical power

    From 2003 to 2009 to 2010 to 2016, median VT decreased (mean difference [MD] of −0.6 [-0.4 to −0.7] mL/kg PBW; p < 0.01) and median RR increased (MD of +1.0 [+0.75 to +1.25] breath/minute; p < 0.01) (Figure 1 and Table 2, and Table 1S and Figure 2S [Supplementary Material]). The percentage of patients who received LTVV increased from 76% to 82%. The temporal changes in VT and RR were associated with a decrease in median MP from 12.1 (8.7 to 16.7) J/minute to 10.4 (7.6 - 14.6) J/minute (MD −1.7 [-2.0 to −1.2] J/minute; p < 0.01). The percentage of patients with MP of < 17 J/minute increased from 76 to 83%.

    thumbnail of Figure 1
    Figure 1
    Cumulative distribution curves for tidal volume, respiratory rate, driving pressure and mechanical ventilation power comparing two study periods, from 2003 to 2009 and from 2010 to 2016.
    Thumbnail
    Table 2
    Ventilation parameters of patients from 2003 - 2009 and 2010 - 2016, shown for both the total population and subgroups categorized by low and high respiratory system compliance, with a cut-off value of 36mL/cmH2O

    Secular changes in high versus low CRS patients

    Whilst there was a clear difference in the decrease in VT between the two CRS groups, with a larger reduction in median VT in patients with low CRS, the changes in median RR were comparable between the two CRS groups (Figure 1 and Table 2, and Table 1S and Figure 2S [Supplementary Material]). The reduction in median MP was less pronounced in patients with high CRS (MD of −0.81 J/minute [-1.31 to −0.44]) compared to patients with low CRS (MD −1.68 J/minute [-2.28 to −1.22]).

    Association of tidal volume and ventilation intensity with intensive care unit mortality in the two temporary cohorts

    Independent of VT, high-intensity ventilation (LV-H, HV-H) was associated with higher mortality compared to low-intensity ventilation (LV-L, HV-L). The combination of ventilation with higher VT at low-intensity ventilation (HV-L) resulted in the lowest mortality rate (Figure 2, and Figure 3S [Supplementary Material]). Also independent of VT, high-intensity ventilation resulted in fewer VFD-28 (Figure 4S - Supplementary Material). The differences in mortality based on ventilation intensity were more pronounced in patients with low CRS than those with high CRS (Figures 5S and 6S - Supplementary Material).

    thumbnail of Figure 2
    Figure 2
    Cumulative incidence of intensive care unit discharge and mortality within 28 days by ventilation intensity and tidal volume per predicted body weight.

    Post hoc analysis

    Results from a post hoc analysis in which we repeated the analysis within medical and surgical patients separately are shown in tables 3S and 4S, and figures 7S and 8S (Supplementary Material). The results were consistent with the primary analysis in both medical and surgical patients. Furthermore, no differing patterns emerged when using the pressure control-oriented MP formula or alternative methods for MP assessment (Table 2, Tables 3S and 4S [Supplementary Material]).

    DISCUSSION

    The main findings of this study can be summarized as follows: most patients received LTVV with median VT declining over the years; despite a modest compensatory rise in RR, this shift resulted in an overall decrease in MP; the impact of lower VT on MP varied with CRS, showing less pronounced effects in patients with high CRS; ventilation intensity was associated with increased mortality in patients ventilated with LTVV or high VT, particularly in patients with low CRS.

    Our study has several strengths. The dataset is extensive, covering more than 13 years, which allows for a robust evaluation of changes in ventilatory practices over time. It includes a diverse patient population with a wide range of pathologies and VT values, enhancing the generalizability of the findings. Additionally, the patients presented a broad spectrum of CRS, enabling a detailed analysis of how adjustments in VT and RR affect MP across different respiratory mechanics subgroups. Furthermore, the study's design, which incorporates time-weighted averaging to account for daily fluctuations in ventilatory variables, provides a robust method of data analysis. This approach minimizes the risk of bias from transient changes and allows for a more accurate assessment of the effects of VT on MP in real-life settings.

    The results of this study align with previous research,(5,6,25-28) consistently demonstrating a trend of decreasing VT in patients receiving invasive ventilation over recent decades. Notably, the majority of patients received VT below 8mL/kg PBW during both study periods, indicating that the LTVV strategy has been adopted early at this medical facility.(25,29,30) The more pronounced decrease in VT in patients with low CRS suggests that clinicians were particularly cautious in managing airway pressures. Clinicians actively lowered VT to the lowest feasible levels when airway pressure-derived parameters, such as plateau or driving pressures, were elevated - indicating increased strain on the lungs. This approach likely reflects an effort to minimize lung injury and reduce mechanical stress in patients with compromised respiratory mechanics, in which small adjustments in ventilation settings could significantly impact lung protection. Therefore, our study corroborates trends in VT utilization in the context of LTVV and demonstrates a consistent effort to employ even smaller VT to improve lung mechanics.

    Previous research in ARDS patients did not show a secular change in RR with decreasing VT over time, as only the highest RR values were considered in that study.(5) In contrast, we reported time-weighted average RR values. Another study using time-weighted average RR also observed a reduction in VT but without a corresponding increase in RR; however, VT often exceeded 8mL/kg PBW in that study.(4) Our findings suggest that in patients receiving LTVV, further reducing VT lowers airway pressures and subsequently reduces MP, even if RR increases.

    Our observations are consistent with findings from an experimental mathematical model in ARDS patients, which showed that reducing VT, even if it leads to a modest increase in RR, is an effective strategy for lowering MP.(31) Indeed, our study suggests that excessively low VT may not be advantageous per se in patients ventilated receiving LTVV. Although minimizing VT increased the number of patients receiving lung protective ventilation, a notable number of patients received LTVV with high intensity, which may worsen outcomes. Therefore, the results of this study support the idea that the primary benefit of low VT is the reduction in ΔP rather than the reduction in VT itself, as indicated in a previous study.(32)

    In patients with elevated CRS, the compensatory increase in RR was disproportionately greater than the decrease in VT, rendering VT reduction less effective in lowering MP than patients with lower CRS. Although the precise rationale behind this discrepancy remains uncertain, it is conceivable that, in patients with reduced compliance, a certain degree of permissive hypercapnia was tolerated, whereas in those with higher compliance, maintaining minute ventilation was prioritized.(9) Regardless of the underlying mechanisms, our findings reinforce the notion that increases in RR substantially amplify MP, aligning with prior observations.(33) Moreover, these results emphasize the necessity of adapting ventilatory strategies to individual respiratory mechanics to optimize MP, thereby supporting modeling-based hypotheses suggesting that the impact of VT reduction on clinical outcomes may differ according to baseline CRS.(9)

    This study has limitations. The retrospective design limits the ability to establish causality between VT, RR, and MP trends with the outcome. Therefore, we cannot prove that changes in VT, RR, or MP directly influenced outcomes as unmeasured confounders may have influenced both ventilatory settings and clinical outcomes. Differences observed between the two secular cohorts may reflect changes in local hospital organization over time. Including all mechanically ventilated patients increases generalizability but introduces diagnostic heterogeneity. The post hoc analysis, in which we first divided the cohort into medical and surgical patients, and then repeated the analysis within each group separately, showed similar trends in VT, RR, and MP in both medical and surgical ICU admissions, indicating consistent practice changes across diagnostic groups. Additionally, as in previous research, MP was calculated based on dynamic variables.(16,17) Although airway ΔP correlates with transpulmonary ΔP, it remains a surrogate that can be affected by factors like resistive airway pressures and chest wall compliance, which were not evaluated here. As a result, transpulmonary pressure could be underestimated, particularly in our population where VT decreased substantially and RR increased, leading to only subtle changes in respiratory system pressure while promoting air trapping and potential auto-PEEP. The relevance of total MP has been challenged with special criticism towards its PEEP component(34) and concerns regarding the ability of the proposed initially formula to accurately measure MP in patients receiving pressure-controlled ventilation.(35) Nevertheless, the additional analyses using alternative equations for calculating MP also confirmed the findings of the primary analysis. Lastly, although our analysis was limited to the first 24 hours after intubation, when spontaneous breathing efforts are minimal, we could not reliably distinguish and exclude such efforts, potentially affecting the accuracy of driving pressure and MP estimates.

    CONCLUSION

    In this single-center cohort of patients receiving invasive ventilation for at least 24 hours, secular changes in tidal volume were associated with a decline in median mechanical power, despite compensatory increases in respiratory rate. This association was less pronounced in patients with high respiratory system compliance, suggesting that the potential benefits of further tidal volume reduction warrant careful consideration within the framework of low tidal volume ventilation.

    • Publisher's note

    Data availability

    The AmsterdamUMCdb dataset that we employed in our research is open-access and available upon request. To gain access to the database, the requester must complete a specific training course focusing on managing deidentified clinical data. Please visit https://amsterdammedicaldatascience.nl for additional information on how to access AmsterdamUMCdb.

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    Edited by

    Publication Dates

    • Publication in this collection
      06 Oct 2025
    • Date of issue
      2025

    History

    • Received
      31 Dec 2024
    • Accepted
      29 May 2025
    Creative Common - by 4.0
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