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Clinical risk factors for increased respiratory drive in intubated hypoxemic patients



There is very limited evidence identifying factors that increase respiratory drive in hypoxemic intubated patients. Most physiological determinants of respiratory drive cannot be directly assessed at the bedside (e.g., neural inputs from chemo- or mechano-receptors), but clinical risk factors commonly measured in intubated patients could be correlated with increased drive. We aimed to identify clinical risk factors independently associated with increased respiratory drive in intubated hypoxemic patients.


We analyzed the physiological dataset from a multicenter trial on intubated hypoxemic patients on pressure support (PS). Patients with simultaneous assessment of the inspiratory drop in airway pressure at 0.1-s during an occlusion (P0.1) and risk factors for increased respiratory drive on day 1 were included. We evaluated the independent correlation of the following clinical risk factors for increased drive with P0.1: severity of lung injury (unilateral vs. bilateral pulmonary infiltrates, PaO2/FiO2, ventilatory ratio); arterial blood gases (PaO2, PaCO2 and pHa); sedation (RASS score and drug type); SOFA score; arterial lactate; ventilation settings (PEEP, level of PS, addition of sigh breaths).


Two-hundred seventeen patients were included. Clinical risk factors independently correlated with higher P0.1 were bilateral infiltrates (increase ratio [IR] 1.233, 95%CI 1.047–1.451, p = 0.012); lower PaO2/FiO2 (IR 0.998, 95%CI 0.997–0.999, p = 0.004); higher ventilatory ratio (IR 1.538, 95%CI 1.267–1.867, p < 0.001); lower pHa (IR 0.104, 95%CI 0.024–0.464, p = 0.003). Higher PEEP was correlated with lower P0.1 (IR 0.951, 95%CI 0.921–0.982, p = 0.002), while sedation depth and drugs were not associated with P0.1.


Independent clinical risk factors for higher respiratory drive in intubated hypoxemic patients include the extent of lung edema and of ventilation-perfusion mismatch, lower pHa, and lower PEEP, while sedation strategy does not affect drive. These data underline the multifactorial nature of increased respiratory drive.


Respiratory drive is the source signal for a descending cascade which ultimately generates the inspiratory effort and breathing pattern [1]. The neural output from the brainstem centers determines the frequency, velocity, and magnitude of respiratory muscle contraction and thus the rate, flow, and magnitude of tidal ventilation [2].

Biochemical inputs from central [3] and peripheral [4] chemoreceptors (sensing alterations of pCO2, pH and oxygen) and various inputs from lung mechanoreceptors and chemoreceptors (affected by changes in lung mechanics, edema and inflammation) [5], together with “behavioral” factors (agitation, anxiety) modulate the activity of the respiratory centers. All these alterations represent hallmark physiological derangements of patients with acute hypoxemic respiratory failure (AHRF), potentially increasing activation of respiratory drive [6]. However, both respiratory drive and most of its physiological determinants (apart from arterial gas analysis) cannot be directly measured at the bedside.

The airway occlusion pressure at 100 ms (P0.1) [7] is an accurate surrogate for respiratory drive output in mechanically ventilated patients [8]. Moreover, clinical risk factors correlated with determinants of respiratory drive such as the severity of lung injury (e.g., extent of radiologic pulmonary infiltrates), inflammation, the development of organ dysfunction (e.g., the SOFA score) and the brain cortical activity (e.g., RASS score) can be assessed at the bedside. A few small clinical studies have explored the association between clinical risk factors and respiratory drive, and a lack of correlation between deep sedation and lower P0.1 has recently been described [9].

In terms of clinical interventions, adjustment of ventilation settings is one of the most implemented strategies to modulate respiratory drive and achieve physiological targets [10, 11]. Previous small physiological studies showed that the level of pressure support and addition of sigh breaths affect the P0.1, tidal volume and respiratory rate of intubated patients [12]. It has also been suggested that higher positive end-expiratory pressure (PEEP) might reduce effort and improve lung protection in animal models during assisted ventilation [13,14,15], but its effect on respiratory drive and effort seems more variable [11, 16]. Thus, lower PS and PEEP, and a lack of sigh breaths could be considered clinical risk factors for increased drive.

We recently conducted a large pilot randomized controlled trial on the feasibility and safety of addition of intermittent sigh breaths to pressure support in intubated hypoxemic patients [17]. In the present study, we analyzed potential independent correlations between clinical risk factors for increased respiratory drive and P0.1 on the first day of enrolment.


Patients, study design and setting

We analyzed the dataset obtained from an international, multicentered, randomized controlled trial (NCT03201263) [17] in order to explore respiratory physiology, as pre-planned in the original study protocol [18]. The trial included mechanically ventilated patients with acute hypoxemic respiratory failure (PaO2/FiO2 ≤ 300) who had been intubated for 7 days or less and who had been switched to pressure support ventilation within the prior 24 h. After enrollment and randomization, physiological measurements including P0.1 were collected daily. From the original database, in the present study we included all patients with a measurement of P0.1 on day 1.

The study was approved by the Ethics Committee of Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan, Italy (ref. 318/2017). The institutional review boards of all participating centers approved the study. Informed consent was obtained for each patient following local regulations. Additional details regarding exclusion criteria and methods of the original study have been described previously [18].

Variables and measurements

We analyzed measurements of P0.1 and clinical risk factors for increased respiratory drive collected in each patient at the same time on day 1. Measurements of P0.1 were performed by the built-in software of each ventilator (see Additional file 1 for brands and models) and recorded in the online form by clinicians. We collected different variables for each category of clinical risk factors, as outlined by our previous work [6] and further defined below, in the statistical analysis section: severity of lung injury, arterial blood gases, sedation, and systemic activation of inflammation. The following mechanical ventilation settings were also collected: PS level, external set PEEP and addition of sigh. Note that PS level and set PEEP has been titrated as follow, according to the original study protocol: at least every 8 h, the PSV level was adjusted to maintain a tidal volume of 6–8 mL/kg PBW and respiratory rate of 20–35 bpm, while PEEP and FiO2 were managed to keep the SpO2 at 90–96%.

Demographic characteristics (age, sex, body mass index), etiology of AHRF and clinical severity at enrollment were also included in the analysis. Additional details about data collection can be found in Additional file 1.

Statistical analyses

Normally distributed data are described with mean and standard deviation (SD), whereas non-normally distributed data are described using median and quartiles [Q1Q3]. Descriptive statistics are used to characterize the study population. A two-tailed p-value below 0.05 was considered as statistically significant.

The bivariate relationship between P0.1 values and clinical risk factors was assessed using a generalized linear model based on a gamma distribution with a log link function, because P0.1 was a continuous variable with no zero values and a right skewed distribution. The following candidate clinical risk factors were assessed in the bivariate analyses: severity of lung injury (diagnosis of ARDS [categorical], PaO2/FiO2 and ventilatory ratio); arterial blood gases (PaO2, PaCO2 and pHa); sedation depth measured by the Richmond Agitation-Sedation Scale (RASS) [19] [categorical], and sedative drugs defined according to the type and number of different classes of drugs administered for sedation (sedative/anesthetics, opioids, both sedative and opioids, none; see Additional file 1) [categorical]; activation of systemic inflammation (SOFA score [categorical] and lactate); ventilation settings (pressure support, set PEEP and addition of sigh breaths). Then, we constructed a multivariate model with a stepwise approach to identify independent clinical risk factors for P0.1.

Physiologically sound clinical risk factors were included in the stepwise multivariate approach, while baseline characteristics (age, sex, and SAPS II at admission) and PaCO2 were considered adjusting factors, so as fixed effects of the multivariate model. PaCO2 was considered only as an adjusting factor and not as a clinical risk factor due to its inverse bivariate association with P0.1, suggesting that it represents a consequence of increased drive. Multicollinearity was tested to exclude high intercorrelation among the determinants included in the final multivariate regression model.

Results of bivariate regression models were reported as β coefficient and p-value, while for the multivariate model we also reported increase ratio (IR) estimates as exp(β) with 95% confidence intervals (95%CI). IR is the relative increase of P0.1 at one unit increase of the clinical risk factor.

Statistical analyses were performed with SAS 9.4 TS Levek 1M7 (2020 SAS Institute Inc., Cary, NC, USA) and R Studio 2002.07.1 (2009-2002Rstudio PBC).


Two-hundred-seventeen patients with measurements of P0.1 and its potential clinical risk factors simultaneously recorded on study day 1 were included in the analysis. The median P0.1 was 1.5 cmH2O with a range of 0.1–8.5 cmH2O. These values are in line with those described in previous smaller series [7,8,9] and indicate a wide range of respiratory drive activation.

The main characteristics of the study population are reported in Table 1: 71% patients were male, and median time from intubation was 3 days. The admitting diagnosis was infectious pneumonia in 58% of patients and 47% fulfilled diagnostic criteria for ARDS, with the remaining having AHRF with unilateral infiltrates on chest x-ray.

Table 1 Baseline demographics and clinical characteristics

Association between potential clinical risk factors for increased respiratory drive and P 0.1

As expected, several candidate factors were correlated with P0.1 at bivariate analysis, indicating the overlapping interconnections between clinical risk factors and physiological determinants of respiratory drive. We report here the main findings, while additional figures can be found in Additional file 1.

Severity of lung injury

Diagnosis of ARDS versus presence of unilateral infiltrates was associated with higher P0.1 (β = 0.22, p = 0.014) (Additional file 1: Fig. E1). PaO2/FiO2 was inversely associated with P0.1 (β =  − 0.002, p = 0.001) while the ventilatory ratio was directly associated (β = 0.382, p < 0.001) (Fig. 1). To further investigate the role of ventilatory ratio, we explored the correlation between P0.1 and minute ventilation (β = 0.096, p < 0.001), respiratory rate (β = 0.047, p < 0.001) and tidal volume (β =  − 0.0002, p = 0.582) (Additional file 1: Fig. E2).

Fig. 1
figure 1

Association between severity of lung injury (ventilation/perfusion mismatch) and P0.1. Results of bivariate analyses show that P0.1 was inversely associated to PaO2/FiO2 and directly associated with ventilatory ratio, indicating that impairment in oxygenation and CO2 clearance are clinical risk factors for increased respiratory drive

Fig. 2
figure 2

Association between arterial blood gases and P0.1. Results of bivariate analyses show that P0.1 was inversely associated with both PaO2 and PaCO2, while the association with arterial pH was not statistically significant

Arterial blood gases

There was a significant association between lower PaO2 (β =  − 0.004, p = 0.041) and, counterintuitively, lower PaCO2 (β =  − 0 to 013, p = 0.017) with higher P0.1. The correlation between pHa and P0.1 did not reach statistical significance (β =  − 1.578, p = 0.067) (Fig. 2).


The correlation between higher RASS category and higher P0.1 did not reach statistical significance (β = 0.072, p = 0.063) (Fig. 3); moreover, the type of drug used for sedation did not appear to influence P0.1 (Additional file 1: Fig. E3).

Fig. 3
figure 3

Impact of sedation depth on P0.1. No significant association was found between P0.1 and RASS category at bivariate analysis

Activation of systemic inflammation

Neither SOFA score (β = 0.006, p = 0.664) nor arterial lactates (β = 0.005, p = 0.846) were associated with P0.1 (Additional file 1: Fig. E4).

Fig. 4
figure 4

Impact of PEEP on P0.1. Clinically set PEEP was inversely associated with P0.1, indicating that lower PEEP is a risk factor for increased respiratory drive in these patients

Ventilation settings

Clinically set PEEP was inversely correlated with P0.1 (β =  − 0.04, p = 0.036) (Fig. 4), while the level of pressure support was not associated with respiratory drive (β =  − 0.008, p = 0.526). Application of sigh breaths had no impact on P0.1 (β = 0.055, p = 0.542) (Additional file 1: Fig. E5).

Independent clinical risk factors correlated with increased respiratory drive

Results from the multivariate analysis investigating the independent impact of clinical risk factors on higher P0.1 are presented in Table 2. Based on previous physiological data and reasoning, the following factors were included as predictors in the model, adjusted for age, sex, SAPS II score and PaCO2: diagnosis of ARDS vs. unilateral lung injury, PaO2/FiO2 ratio, ventilatory ratio, PaO2, pHa, RASS, SOFA, sedative drugs, PS level, PEEP and addition of sigh breaths.

Table 2 Multivariate regression model describing independent clinical risk factors for increased P0.1

We identified the following the following clinical parameters independently associated with increased risk of higher P0.1: diagnosis of ARDS (increase ratio: 1.233 [95%CI 1.047–1.451]), lower PaO2/FiO2 ratio (IR 0.998 [0.997–0.999], higher ventilatory ratio (1.538 [1.267–1.867], lower pH (IR 0.104 [0.024–0.464]) and lower set PEEP (0.951 [0.921–0.982]) (Table 2).

RASS, SOFA, sedative drugs, PS level and addition of Sigh were not significantly associated with P0.1.


This study investigated clinical risk factors for increased P0.1 in a large population of intubated patients with AHRF undergoing pressure support ventilation. Independent factors predicting higher respiratory drive measured by P0.1 were diagnosis of ARDS, lower PaO2/FiO2, higher ventilatory ratio, lower arterial pH, and lower clinically set PEEP. Sedation strategy (target RASS and drugs type), instead, was not associated with modulation of respiratory drive.

In patients intubated for AHRF, high respiratory drive may hinder safe spontaneous breathing during assisted ventilation by inducing high lung stress and occult pendelluft [20,21,22], dyssynchronies [23] and dyspnea [24]. Stimuli related to the severity of lung injury, including impairment of gas exchange and altered respiratory mechanics, but also activation of peripheral lung receptors by edema or inflammation, may lead to increased drive [6]. In addition, extra-pulmonary factors such as agitation, systemic inflammation and metabolic acidosis may contribute. In clinical practice, most of the determinants stimulating the respiratory centers are impossible to measure. However, several clinical risk factors measured at the bedside could reflect these inputs and thus be associated with P0.1. Understanding the impact and the independent contribution of these factors in determining the value of P0.1 could be useful to guide safe initiation and management of assisted ventilation in patients with AHRF [10]. On the other hand, lack of association between a candidate clinical risk factor and P0.1 could be interpreted in two ways: either the clinical risk factor is not an accurate surrogate for the physiological determinant, or the clinical factor has limited relevance in patients.

The present study describes that in patients with AHRF, the severity of lung injury, as assessed by larger extent of pulmonary infiltrates, lower oxygenation, and higher ventilatory ratio, is a clinical risk factor for increased P0.1. More specifically, the extent of lung edema and of ventilation/perfusion mismatch could represent global markers of structural and functional impairment of the lung [25], associated with higher P0.1.

In healthy subjects, respiratory drive mainly depends on the chemoreflex control of arterial CO2. On the contrary, assisted ventilation limits the spontaneous modulation of tidal volume in response to the chemical feedback from CO2 [26, 27]. Indeed, PaCO2 seems to be a consequence more than a determinant of drive and effort in our patients [20, 28], given the correlation between higher P0.1 and both higher minute ventilation and lower PaCO2. In this perspective, since the minute ventilation enters in the calculation of ventilatory ratio, the positive association between ventilatory ratio and P0.1 could have been driven by the effect of higher minute ventilation.

The correlation between PaO2 and P0.1 at bivariate analysis likely reflects patient severity, but PaO2 was not confirmed as an independent risk factor for elevated P0.1. This finding might also depend on the protocol adopted for titration of SpO2 in this study, resulting in a limited range of values for PaO2. Although it has been demonstrated that moderate decreases in PaO2 could increase respiratory drive in some patients [29], it is known that the effect of PaO2 becomes much stronger below 60 mmHg [30].

Similar to a recent study [9], we could not find an independent correlation between sedation depth and sedative drug type on P0.1, suggesting a limited effect of sedatives and opioids in the modulation of respiratory drive in patients with AHRF, as compared to pulmonary and systemic disease severity. However, the lack of correlation between sedation depth and drive might also be due to the limited ability of the RASS score to evaluate descending cortical input to the respiratory centers.

Arterial lactate was not a clinical risk factor for increased drive in this study, in contrast with our previous finding in septic patients without acute respiratory failure [31]. The lack of correlation between P0.1 and both lactate and SOFA score could suggest that the role of extra-pulmonary organ failure and distal hypoperfusion may have less of an impact on respiratory drive when lung injury is present.

Adjustment of ventilation settings is probably the most common clinical intervention used to modulate respiratory drive and effort when attempting to achieve lung and diaphragm protective ventilation [10]. Early studies showed that changing the level of support and PEEP can influence the breathing pattern [32]. Indeed, increasing the level of inspiratory assist decreases respiratory drive and effort [33] by unloading the respiratory muscles in patients recovering from AHRF [34,35,36,37]. However, it is now recognized that a significant number of patients with AHRF may not exhibit such a response [38], suggesting the presence of high respiratory drive due to stimuli other than arterial pH and PaCO2 [21, 39]. Indeed, we could not find a correlation between the level of support and P0.1. Interestingly, our results show that higher PEEP is associated with lower P0.1. This finding reinforces the accumulating experimental [15] and clinical [40] evidence of the beneficial effects of higher PEEP during spontaneous breathing, likely due to the modulation of respiratory drive and effort induced by stabilizing alveolar recruitment [11, 16].

The strengths of the present analysis are the large multicenter sample of patients with AHRF, the early timing of assessment after switching to assisted ventilation and the accurate collection of physiological and clinical data from a randomized controlled trial. Our study also has limitations. First, automated P0.1 measurements overall underestimate absolute P0.1 values with differences between different ventilators [8, 41]. This can also be seen as a strength as our data coincide with those available in clinical practice, which rely on P0.1 displayed by different ventilators. Second, we lack measurements of respiratory system compliance or recruitment and thus we can only hypothesize about the mechanisms by which PEEP modulates drive. Third, we could only analyze some of the potential clinical risk factors for increased respiratory drive, while other factors like pulmonary and systemic inflammatory cytokines were not collected.


In a large population of intubated hypoxemic patients, clinical risk factors independently associated with higher P0.1 included the extent of pulmonary infiltrates, the degree of ventilation/perfusion mismatch and lower arterial pH. Higher set PEEP was independently associated with lower P0.1. Sedation strategy, including actual RASS score and sedative drug type, despite being extensively used in clinical practice to control drive, seems to have no impact on P0.1. These results confirm the multifactorial nature of the activation of respiratory drive and highlight the key role of severity of lung injury in increasing drive.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.



Acute hypoxemic respiratory failure


Acute respiratory distress syndrome


Confidence interval


Increase ratio


Inspiratory drop in airway pressure at 0.1-s during an occlusion

PaCO2 :

Partial pressure of arterial CO2

PaO2/FiO2 :

Partial pressure of arterial O2/fraction of inspired O2


Positive end expiratory pressure


Pressure support


Richmond Agitation Sedation Scale


Simplified Acute Physiology Score


Standard deviation


Sequential Organ Failure Assessment score


  1. Del Negro CA, Funk GD, Feldman JL. Breathing matters. Nat Rev Neurosci. 2018;19:351–67.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Clark FJ, von Euler C. On the regulation of depth and rate of breathing. J Physiol. 1972;222:267–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Bruce EN, Cherniack NS. Central chemoreceptors. J Appl Physiol. 1985;1987(62):389–402.

    Google Scholar 

  4. Forster HV, Pan LG, Lowry TF, Serra A, Wenninger J, Martino P. Important role of carotid chemoreceptor afferents in control of breathing of adult and neonatal mammals. Respir Physiol. 2000;119:199–208.

    Article  CAS  PubMed  Google Scholar 

  5. Sant’Ambrogio G. Nervous receptors of the tracheobronchial tree. Annu Rev Physiol. 1987;49:611–27.

    Article  CAS  PubMed  Google Scholar 

  6. Spinelli E, Mauri T, Beitler JR, Pesenti A, Brodie D. Respiratory drive in the acute respiratory distress syndrome: pathophysiology, monitoring, and therapeutic interventions. Intensive Care Med. 2020;46:606–18.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Whitelaw WA, Derenne JP, Milic-Emili J. Occlusion pressure as a measure of respiratory center output in conscious man. Respir Physiol. 1975;23:181–99.

    Article  CAS  PubMed  Google Scholar 

  8. Telias I, Junhasavasdikul D, Rittayamai N, Piquilloud L, Chen L, Ferguson ND, Goligher EC, Brochard L. Airway occlusion pressure as an estimate of respiratory drive and inspiratory effort during assisted ventilation. Am J Respir Crit Care Med. 2020;201:1086–98.

    Article  PubMed  Google Scholar 

  9. Dzierba AL, Khalil AM, Derry KL, Madahar P, Beitler JR. Discordance between respiratory drive and sedation depth in critically Ill patients receiving mechanical ventilation. Crit Care Med. 2021;49:2090–101.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Goligher EC, Dres M, Patel BK, Sahetya SK, Beitler JR, Telias I, Yoshida T, Vaporidi K, Grieco DL, Schepens T, Grasselli G, Spadaro S, Dianti J, Amato M, Bellani G, Demoule A, Fan E, Ferguson ND, Georgopoulos D, Guerin C, Khemani RG, Laghi F, Mercat A, Mojoli F, Ottenheijm CAC, Jaber S, Heunks L, Mancebo J, Mauri T, Pesenti A, Brochard L. Lung- and diaphragm-protective ventilation. Am J Respir Crit Care Med. 2020;202:950–61.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Dianti J, Fard S, Wong J, Chan TCY, Del Sorbo L, Fan E, Amato MBP, Granton J, Burry L, Reid WD, Zhang B, Ratano D, Keshavjee S, Slutsky AS, Brochard LJ, Ferguson ND, Goligher EC. Strategies for lung- and diaphragm-protective ventilation in acute hypoxemic respiratory failure: a physiological trial. Crit Care. 2022;26:259.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Berger KI, Sorkin IB, Norman RG, Rapoport DM, Goldring RM. Mechanism of relief of tachypnea during pressure support ventilation. Chest. 1996;109:1320–7.

    Article  CAS  PubMed  Google Scholar 

  13. Morais CCA, Koyama Y, Yoshida T, Plens GM, Gomes S, Lima CAS, Ramos OPS, Pereira SM, Kawaguchi N, Yamamoto H, Uchiyama A, Borges JB, Vidal Melo MF, Tucci MR, Amato MBP, Kavanagh BP, Costa ELV, Fujino Y. High positive end-expiratory pressure renders spontaneous effort noninjurious. Am J Respir Crit Care Med. 2018;197:1285–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Pellegrini M, Hedenstierna G, Roneus A, Segelsjo M, Larsson A, Perchiazzi G. The diaphragm acts as a brake during expiration to prevent lung collapse. Am J Respir Crit Care Med. 2017;195:1608–16.

    Article  CAS  PubMed  Google Scholar 

  15. Magalhaes PAF, Padilha GA, Moraes L, Santos CL, Maia LA, Braga CL, Duarte M, Andrade LB, Schanaider A, Capellozzi VL, Huhle R, de Abreu MG, Pelosi P, Rocco PRM, Silva PL. Effects of pressure support ventilation on ventilator-induced lung injury in mild acute respiratory distress syndrome depend on level of positive end-expiratory pressure: A randomised animal study. Eur J Anaesthesiol. 2018;35:298–306.

    Article  PubMed  Google Scholar 

  16. Perez J, Dorado JH, Navarro E, Morais CCA, Accoce M. Mechanisms of lung and diaphragmatic protection by high PEEP in obese COVID-19 ARDS: role of the body mass index. Crit Care. 2022;26:182.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Mauri T, Foti G, Fornari C, Grasselli G, Pinciroli R, Lovisari F, Tubiolo D, Volta CA, Spadaro S, Rona R, Rondelli E, Navalesi P, Garofalo E, Knafelj R, Gorjup V, Colombo R, Cortegiani A, Zhou JX, D’Andrea R, Calamai I, Vidal Gonzalez A, Roca O, Grieco DL, Jovaisa T, Bampalis D, Becher T, Battaglini D, Ge H, Luz M, Constantin JM, Ranieri M, Guerin C, Mancebo J, Pelosi P, Fumagalli R, Brochard L, Pesenti A, Collaborators PT. Sigh in patients with acute hypoxemic respiratory failure and ARDS: the PROTECTION pilot randomized clinical trial. Chest. 2021;159:1426–36.

    Article  CAS  PubMed  Google Scholar 

  18. Mauri T, Foti G, Fornari C, Constantin JM, Guerin C, Pelosi P, Ranieri M, Conti S, Tubiolo D, Rondelli E, Lovisari F, Fossali T, Spadaro S, Grieco DL, Navalesi P, Calamai I, Becher T, Roca O, Wang YM, Knafelj R, Cortegiani A, Mancebo J, Brochard L, Pesenti A, Protection Study G. Pressure support ventilation + sigh in acute hypoxemic respiratory failure patients: study protocol for a pilot randomized controlled trial, the PROTECTION trial. Trials 2018; 19: 460

  19. Sessler CN, Gosnell MS, Grap MJ, Brophy GM, O’Neal PV, Keane KA, Tesoro EP, Elswick RK. The Richmond Agitation-Sedation Scale: validity and reliability in adult intensive care unit patients. Am J Respir Crit Care Med. 2002;166:1338–44.

    Article  PubMed  Google Scholar 

  20. Bertoni M, Telias I, Urner M, Long M, Del Sorbo L, Fan E, Sinderby C, Beck J, Liu L, Qiu H, Wong J, Slutsky AS, Ferguson ND, Brochard LJ, Goligher EC. A novel non-invasive method to detect excessively high respiratory effort and dynamic transpulmonary driving pressure during mechanical ventilation. Crit Care. 2019;23:346.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Mauri T, Langer T, Zanella A, Grasselli G, Pesenti A. Extremely high transpulmonary pressure in a spontaneously breathing patient with early severe ARDS on ECMO. Intensive Care Med. 2016;42:2101–3.

    Article  PubMed  Google Scholar 

  22. Yoshida T, Uchiyama A, Matsuura N, Mashimo T, Fujino Y. Spontaneous breathing during lung-protective ventilation in an experimental acute lung injury model: high transpulmonary pressure associated with strong spontaneous breathing effort may worsen lung injury. Crit Care Med. 2012;40:1578–85.

    Article  PubMed  Google Scholar 

  23. Beitler JR, Sands SA, Loring SH, Owens RL, Malhotra A, Spragg RG, Matthay MA, Thompson BT, Talmor D. Quantifying unintended exposure to high tidal volumes from breath stacking dyssynchrony in ARDS: the BREATHE criteria. Intensive Care Med. 2016;42:1427–36.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Schmidt M, Demoule A, Polito A, Porchet R, Aboab J, Siami S, Morelot-Panzini C, Similowski T, Sharshar T. Dyspnea in mechanically ventilated critically ill patients. Crit Care Med. 2011;39:2059–65.

    Article  PubMed  Google Scholar 

  25. Spinelli E, Kircher M, Stender B, Ottaviani I, Basile MC, Marongiu I, Colussi G, Grasselli G, Pesenti A, Mauri T. Unmatched ventilation and perfusion measured by electrical impedance tomography predicts the outcome of ARDS. Crit Care. 2021;25:192.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Morrell MJ, Shea SA, Adams L, Guz A. Effects of inspiratory support upon breathing in humans during wakefulness and sleep. Respir Physiol. 1993;93:57–70.

    Article  CAS  PubMed  Google Scholar 

  27. Georgopoulos DB, Anastasaki M, Katsanoulas K. Effects of mechanical ventilation on control of breathing. Monaldi Arch Chest Dis. 1997;52:253–62.

    CAS  PubMed  Google Scholar 

  28. Vicka V, Januskeviciute E, Krauklyte J, Aleknaviciene A, Ringaitiene D, Jancoriene L, Sipylaite J. Determinants of increased effort of breathing in non-intubated critical COVID-19 patients. Medicina (Kaunas). 2022;58:1133.

    Article  PubMed  Google Scholar 

  29. Pesenti A, Rossi N, Calori A, Foti G, Rossi GP. Effects of short-term oxygenation changes on acute lung injury patients undergoing pressure support ventilation. Chest. 1993;103:1185–9.

    Article  CAS  PubMed  Google Scholar 

  30. Gonzalez C, Almaraz L, Obeso A, Rigual R. Oxygen and acid chemoreception in the carotid body chemoreceptors. Trends Neurosci. 1992;15:146–53.

    Article  CAS  PubMed  Google Scholar 

  31. Mauri T, Spinelli E, Pavlovsky B, Grieco DL, Ottaviani I, Basile MC, Dalla Corte F, Pintaudi G, Garofalo E, Rundo A, Volta CA, Pesenti A, Spadaro S. Respiratory drive in patients with sepsis and septic shock: modulation by high-flow nasal cannula. Anesthesiology. 2021;135:1066–75.

    Article  CAS  PubMed  Google Scholar 

  32. Vitacca M, Bianchi L, Zanotti E, Vianello A, Barbano L, Porta R, Clini E. Assessment of physiologic variables and subjective comfort under different levels of pressure support ventilation. Chest. 2004;126:851–9.

    Article  PubMed  Google Scholar 

  33. Alberti A, Gallo F, Fongaro A, Valenti S, Rossi A. P0.1 is a useful parameter in setting the level of pressure support ventilation. Intensive Care Med. 1995;21:547–53.

    Article  CAS  PubMed  Google Scholar 

  34. MacIntyre NR, Leatherman NE. Ventilatory muscle loads and the frequency-tidal volume pattern during inspiratory pressure-assisted (pressure-supported) ventilation. Am Rev Respir Dis. 1990;141:327–31.

    Article  CAS  PubMed  Google Scholar 

  35. Perrigault PF, Pouzeratte YH, Jaber S, Capdevila XJ, Hayot M, Boccara G, Ramonatxo M, Colson P. Changes in occlusion pressure (P0.1) and breathing pattern during pressure support ventilation. Thorax. 1999;54:119–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Carteaux G, Cordoba-Izquierdo A, Lyazidi A, Heunks L, Thille AW, Brochard L. Comparison between neurally adjusted ventilatory assist and pressure support ventilation levels in terms of respiratory effort. Crit Care Med. 2016;44:503–11.

    Article  PubMed  Google Scholar 

  37. Doorduin J, Sinderby CA, Beck J, van der Hoeven JG, Heunks LM. Assisted ventilation in patients with acute respiratory distress syndrome: lung-distending pressure and patient-ventilator interaction. Anesthesiology. 2015;123:181–90.

    Article  PubMed  Google Scholar 

  38. Doorduin J, Nollet JL, Roesthuis LH, van Hees HW, Brochard LJ, Sinderby CA, van der Hoeven JG, Heunks LM. Partial neuromuscular blockade during partial ventilatory support in sedated patients with high tidal volumes. Am J Respir Crit Care Med. 2017;195:1033–42.

    Article  PubMed  Google Scholar 

  39. Spinelli E, Mauri T, Lissoni A, Crotti S, Langer T, Albanese M, Volta CA, Fornari C, Tagliabue P, Grasselli G, Pesenti A. Spontaneous breathing patterns during maximum extracorporeal CO2 removal in subjects with early severe ARDS. Respir Care. 2020;65:911–9.

    Article  PubMed  Google Scholar 

  40. Patel BK, Wolfe KS, Pohlman AS, Hall JB, Kress JP. Effect of noninvasive ventilation delivered by helmet vs face mask on the rate of endotracheal intubation in patients with acute respiratory distress syndrome: a randomized clinical trial. JAMA. 2016;315:2435–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Beloncle F, Piquilloud L, Olivier PY, Vuillermoz A, Yvin E, Mercat A, Richard JC. Accuracy of P0.1 measurements performed by ICU ventilators: a bench study. Ann Intensive Care. 2019;9:104.

    Article  PubMed  PubMed Central  Google Scholar 

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Study collaborators: Plug Working Group (; Daniela Tubiolo (Ospedale Maggiore Policlinico, Milan, Italy); Emanuele Rezoagli (Ospedale san Gerardo, Monza, Italy); Riccardo Pinciroli (Ospedale Niguarda, Milan, Italy); Lorenzo Ball, MD (San Martino Policlinico Hospital, IRCCS for Oncology and Neurosciences, Genoa, Italy); Italo Calamai (AUSL Toscana Centro, Empoli, Italy); Domenico Luca Grieco (IRCCS Fondazione Policlinico A. Gemelli, Rome, Italy); Riccardo Colombo (ASST Fatebenefratelli Sacco, Milan, Italy); Savino Spadaro (Anesthesia and Intensive Care Unit, University of Ferrara, Ferrara, Italy); Manel Santafè (Vall d’Hebron University Hospital, Barcelona, Spain); Tobias Becher (Universitätsklinikum Schleswig-Holstein, Kiel, Germany); Anxela Vidal (Hospital Universitario Fundación Jiménez Díaz de Madrid, Spain); Dimitrios Bampalis (Larissa General Hospital, Larissa, Greece), Jian Xin Zhou (Tiantan Hospital, Beijing, China); Eugenio Garofalo (Magna Graecia University, Catanzaro, Italy); Andrea Cortegiani (Policlinico Paolo Giaccone, Palermo, Italy); Rocco D’Andrea (Hospital St. Orsola-Malpighi, Bologna, Italy); Urša Mikuž (University Medical Center Ljubljana, Slovenia), Tomas Jovaisa (Barking Havering and Redbridge University Hospitals NHS Trust, London, UK); Huiqing Ge (Zhejiang University School of Medicine, Hangzhou, China); Mariana Luz (Hospital Universitário Professor Edgard Santos, Salvador, Bahia, Brazil).


Open access funding provided by Università degli Studi di Milano within the CRUI-CARE Agreement. The study was supported, in part, by the ESICM Clinical Research Award 2016 (TM) and, in part, by Italian Ministry of Health—Current research IRCCS, Rome, Italy (AP, GG, TM).

Author information

Authors and Affiliations



ES, AP, DS, JM, LB, TM and CF (statistical advisors) contributed to the concept; ES, AP, DS, JM, LB and TM contributed to the design; ES, AP, RF, GG, CAV, GF, PN, RK and PP acquired the data; ES, DS, CF and TM analyzed the data; ES, DS, CF, LB and TM interpreted the data; ES, DS and TM drafted the manuscript; all authors and contributors revised the manuscript for intellectual content and final approval. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Tommaso Mauri.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Ethics Committee of Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan, Italy (ref. 318/2017). The institutional review boards of all participating centers approved the study. Informed consent was obtained for each patient following local regulations.

Consent for publication

Not applicable.

Competing interests

PN received personal fees for lectures from Fisher and Paykel, Mindray, Hamilton, outside of the submitted work. TM received personal fees for lectures from Drager, Mindray and Fisher and Paykel, outside of the submitted work. All other authors declare that they have no competing interests.

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Jordi Mancebo deceased before publication of this work was completed.

Supplementary Information

Additional file 1.

Clinical risk factors for increased respiratory drive in intubated hypoxemic patients: additional methods and results.

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Spinelli, E., Pesenti, A., Slobod, D. et al. Clinical risk factors for increased respiratory drive in intubated hypoxemic patients. Crit Care 27, 138 (2023).

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  • Risk factors
  • Respiratory drive
  • Acute respiratory failure
  • Positive end-expiratory pressure