# Effect of early and later prone positioning on outcomes in invasively ventilated COVID-19 patients with acute respiratory distress syndrome: analysis of the prospective COVID-19 critical care consortium cohort study

Andrew Simpkin, Bairbre Mcnicholas, David Hannon, Robert Bartlett, Davide Chiumello, Heidi Dalton, Kristen Gibbons, Nicole White, Laura Merson, Eddy Fan, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Andrew Simpkin, Bairbre Mcnicholas, David Hannon, Robert Bartlett, Davide Chiumello, et al. Effect of early and later prone positioning on outcomes in invasively ventilated COVID-19 patients with acute respiratory distress syndrome: analysis of the prospective COVID-19 critical care consortium cohort study. Annals of Intensive Care, 2025, 15 (1), pp.22. 10.1186/s13613-025-01422-6. inserm-05005138

HAL Id: inserm-05005138

https://inserm.hal.science/inserm-05005138v1

Submitted on 25 Mar 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>
RESEARCH

Open Access

<figure><img src="image_3.png" /></figure>

Check for
updates

# Effect of early and later prone positioning on outcomes in invasively ventilated COVID-19 patients with acute respiratory distress syndrome: analysis of the prospective COVID-19 critical care consortium cohort study

Andrew J. Simpkin¹ ID, Bairbre A. McNicholas²,³, David Hannon²,³, Robert Bartlett⁴, Davide Chiumello⁵,⁶, Heidi J. Dalton⁷, Kristen Gibbons⁸, Nicole White⁹,²⁵, Laura Merson¹⁰, Eddy Fan¹¹, Mauro Panigada¹², Giacomo Grasselli⁶,¹², Anna Motos¹³,¹⁴,²⁶, Antoni Torres¹³,¹⁴,¹⁵,¹⁶, Ferran Barbé¹³,¹⁷, Pauline Yeung Ng¹⁸, Jonathon P. Fanning²⁰,²²,²³, Alistair Nichol¹⁹, Jacky Y. Suen²⁰,²¹,²², Gianluigi Li Bassi¹³,²⁰,²¹,²³,²⁴, John F. Fraser⁹,²⁰,²¹,²³,²⁴ and John G. Laffey²,³* on behalf of the COVID-19 Critical Care Consortium

**Abstract**

**Background** Prone positioning of patients with COVID-19 undergoing invasive mechanical ventilation (IMV) is widely used, but evidence of efficacy remains sparse. The COVID-19 Critical Care Consortium has generated one of the largest global datasets on the management and outcomes of critically ill COVID-19 patients. This prospective cohort study investigated the association between prone positioning and mortality and in particular focussed on timing of treatment.

**Methods** We investigated the incidence, demographic profile, management and outcomes of prone patients undergoing IMV for COVID-19 in the study. We compared outcomes between patients prone positioned within 48 h of IMV to those (i) never prone, and (ii) prone only after 48 h.

**Results** 3131 patients had data on prone positioning, 1482 (47%) were never prone, 1034 (33%) were prone within 48 h and 615 (20%) were prone only after 48 h of commencement of IMV. 28-day (hazard ratio 0.82, 95% confidence interval [CI] 0.68, 0.98, p = 0.03) and 90-day (hazard ratio 0.81, 95% CI 0.68, 0.96, p = 0.02) mortality risks were lower in those patients prone within 48 h of IMV compared to those never prone. However, there was no evidence for a statistically significant association between prone positioning after 48 h with 28-day (hazard ratio 0.93, 95% CI 0.75, 1.14, p = 0.47) or 90-day mortality (hazard ratio 0.95, 95% CI 0.78, 1.16, p = 0.59).

**Conclusions** Prone positioning is associated with improved outcomes in patients with COVID-19, but timing matters. We found no association between later proning and patient outcome.

**Keywords** COVID-19, Cox proportional hazards models, Invasive mechanical ventilation, Prone positioning, Proning

<figure><img src="image_4.png" /></figure>

<footnote>*Correspondence:
John G. Laffey
jlaffey@universityofgalway.ie
Full list of author information is available at the end of the article</footnote>
**Introduction**

Prone positioning (PP) of patients with severe COVID-19, whether invasively mechanically ventilated or receiving advanced respiratory support (termed 'awake' proning), received considerable attention during the early phases of the COVID-19 pandemic. PP has previously been demonstrated to improve survival for non-COVID patients with moderate-to-severe acute respiratory distress syndrome (ARDS) receiving invasive mechanical ventilation (IMV) [1]. However, there are potentially important differences in the pathophysiology of COVID ARDS compared to 'classic' ARDS. The early stages of COVID-ARDS are characterised by a higher respiratory system compliance [2], with microangiopathy induced alveolar capillary microthrombi leading to higher dead-space fraction and higher V/Q mismatch [3] than in 'classic' ARDS. Given this, it is important not to extrapolate directly from studies of PP in 'classic' ARDS to COVID-19 ARDS.

The effect of prone position in invasively ventilated patients with severe COVID-19 remains unclear. A recent systematic review [4] found nine randomised controlled trials (RCT) and 23 observational studies reporting on the use of prone positioning for patients with COVID-19. The majority of these studies focused on proning of awake patients [5], and both the RCTs and observational studies found that awake proning significantly reduced the intubation rate among such patients. In terms of mortality, two meta-analyses of RCTs found no evidence for a benefit among the awake prone population, but there were no RCTs for patients undergoing IMV [4, 6].

The effect of the timing of PP may also be of importance. In 'classic' ARDS, the PROSEVA study found that early PP was effective, while there is no data demonstrating the efficacy of later or 'rescue' PP [1]. A meta-analysis of two observational studies of patients on IMV, found no evidence for an effect of proning on mortality [7, 8]. However, these studies compared patients prone at any time following commencement of IMV, i.e. both early and later proning, to those who were never prone. Camporota et al. reported patients with COVID-19 ARDS who responded to PP received earlier PP than non-responders, and early PP was associated with improved survival [9]. Conversely, Le Terrier et al. did not demonstrate any survival benefit of early PP (within 24h) compared to later proning in their cohort study [10]. Given this, it is important to determine separately the potential for early proning and for later proning to affect the outcome of COVID-19 induced ARDS.

Since January 2020, the COVID-19 Critical Care Consortium (CCCC), in collaboration with the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) group have generated the largest global

dataset on the demographics, management, and outcomes of critically ill COVID-19 patients. This dataset includes patients who were managed before and after the introduction of disease modifying therapies for COVID-19 including dexamethasone and tocilizumab in 2021 [11]. The CCCC currently includes 354 hospitals across 64 countries [12]. We aimed to examine the incidence, timing, and outcomes of prone positioning for patients with COVID-19 undergoing IMV. Our primary objective was to determine the effect of early (within 48 h of IMV commencement), and later proning (only after 48 h of IMV) compared to patients never prone. Our hypothesis was that the timing of proning is an important factor in its efficacy when treating COVID-19 patients undergoing IMV.

**Methods**

**Study design and setting**

The COVID-19 Critical Care Consortium (CCCC) registry is a global database enrolling COVID-19 patients requiring ICU care (Trial registration ACTRN12620000421932) [12]. Hospitals participating in CCCC obtained approval from their local institutional review board and received waivers of informed consent for all patients. A complete summary of recruiting sites, corresponding ethics/regulatory approvals, contributors, and collaborators is included in online materials. CCCC collaborates with the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC).

**Participants**

Patients enrolled in the CCCC database from 1st January 2020 up to 14th February 2023 with laboratory-confirmed (real-time polymerase chain reaction) SARS-CoV-2 infection and upon first admission to ICU receiving invasive mechanical ventilation (IMV) for any cause were included. Those patients transferred from other ICUs already undergoing IMV were excluded. Patients missing final outcome, with unconfirmed ARDS (no bilateral infiltrates on x-ray) or P/F (PaO2/FiO2) over 300 were excluded.

**Study outcomes, data sources, measurements, and definitions**

As described in the CCCC study protocol [12], data on demographics, comorbidities, clinical symptoms, and laboratory values were collected by clinical/research staff in all participating ICUs and recorded in an electronic case report form up to 28 days from commencement of IMV. Geographical regions were countries grouped into three categories: "Europe", "rest of the world high income", e.g., USA and Japan, and "rest of the world middle income", e.g., Brazil (based on World Bank Gross
National Income Classification). The primary outcome was all-cause mortality within 28 days of commencing IMV, with a secondary outcome of mortality within 90 days of commencing IMV.

## Prone position data definition

Our primary exposure was to assess whether proning within 48 h was beneficial, so we compared those who were prone early (within 48 h of IMV commencement) to those prone only after 48 h and to those never prone in a three-way comparison. We chose 48 h as the cut-off for the early proning group based on the PROSEVA study, which enrolled patients over a similar timeframe.

## Statistical analysis

To investigate the association of prone positioning with mortality we used a Cox proportional hazards model with death within 28 days of commencing IMV as the primary outcome, and repeated this using death within 90 days [13]. For the 28-day ICU mortality outcome, patients were censored if they were discharged from ICU before 28 days or were still alive in ICU on day 28. For the 90-day hospital mortality outcome, patients were censored if they were discharged from hospital before 90 days or were still alive in hospital on day 90. In each model, we adjusted for possible confounders based on previous research on prone positioning and mortality in ICU [6, 14, 15], the complete list of variables is available in online supplement. To account for missing data, we used multiple imputation via chained equations with 20 imputed datasets (full information on missing

data is provided in the online supplement). Cox models performed and hazard ratios (HR) were combined using Rubin's rules [16]. We also present a propensity score matched analyses for the binary exposure of never prone against (a) prone within 48 h and (b) prone only after 48 h, details of which are included in our online supplement. To investigate regional differences, we repeat our Cox regression analysis separately in European countries, non-European high-income countries, and non-European middle-income countries.

A secondary analysis focussed on the effect of prone positioning on PaO2 to FiO2 ratio (P/F) before, during and after prone positioning. Here a linear mixed model with random intercepts and slopes was employed to allow for correlation within and between patients. Time was measured via the day of P/F measurement and a linear spline was added with a knot placed at the day of first prone positioning. The effect of proning on P/F is captured through this linear spline, whose coefficient tells us about the change in P/F trend after proning. As such, this model can only be applied to those who were prone at some stage. All analyses were carried out in R v4.3 and in accordance with STROBE Guidelines [17].

## Results

A total of 3996 patients undergoing IMV were included in the cohort for final analysis (Fig. 1). Among these patients, 3131 patients had data on prone positioning, with 865 missing but included in our statistical analysis via multiple imputation. Of these, 1482 (47%) were never prone and 1649 (53%) were prone at some time, of

<figure><img src="image_5.png" /><figcaption>**Fig. 1** Flow chart for outcome analysis. IMV = invasive mechanical ventilation</figcaption></figure>
whom 1034 (33%) were prone within 48 h of IMV commencement. Among those only prone after 48 h, the median and mean time of first proning were 4 and 5.5 days respectively, with standard deviation 5.7 days and interquartile range 3 days (Figure s1, s2). The P/F ratio on day of first proning was similar between those prone within and after 48 h (Figure s3).

## Demographics of PP use in invasively ventilated COVID-19 patients

We describe the characteristics of 3131 patients with data available on proning. Table 1 compares those who were prone within 48 h of IMV to those never prone and prone after 48 h of IMV. Patients prone within 48 h were more likely to be female, European, with lower prevalence of diabetes, hypertension and chronic cardiac disease than patients who were never prone or prone only after 48 h. Compared to those never prone, patients who were prone within 48 h had higher average PEEP, but lower average S/F (SaO2/FiO2) and P/F ratios, were more likely to receive heparin and corticosteroids, and spent longer undergoing IMV and in ICU on average. Those prone within 48 h were less likely to suffer complications such as heart failure. Among those patients who died, time to death was earlier on average in those never prone compared to those prone within 48 h.

## Patient outcomes

In a three-category comparison, we found a beneficial association of proning within 48 h of IMV on 28-day (HR 0.82, 95% confidence interval [CI] 0.68, 0.98, p=0.029) and 90-day (HR 0.81, 95% CI 0.68, 0.96, p=0.017) mortality compared to never proning. Those prone only after 48 h had no evidence for a reduced risk of 28-day (HR 0.93, 95% CI 0.75, 1.14, p=0.469) and 90-day (HR 0.95, 95% CI 0.78, 1.16, p=0.590) mortality compared to those never prone (Table 2, Fig. 2).

In our propensity score matched analyses, patients who were prone within 48 h had reduced risk of 28-day (HR 0.85, 95% confidence interval [CI] 0.73, 1.00, p=0.045) and 90-day mortality (HR 0.85, 95% CI 0.74, 0.99, p=0.030) mortality compared to matched patients who did not receive early proning (Table 3; Fig. 3).

In a stratified analysis by region (Table 4; Figures s4-s6), the main findings only held in those high-income non-European countries where proning within 48 h was associated with a reduced risk of 28-day (HR 0.80, 95% CI 0.67, 0.96, p=0.015) and 90-day (HR 0.82, 95% CI 0.70, 0.96, p=0.015) mortality compared to no proning.

In our analysis of changes in P/F ratio over time during IMV (Table 5, Fig. 4), we found no significant change in P/F ratio before proning (0.26 change per day, 95% CI -0.60 to 1.13 per day, p=0.551). However, upon proning

this slope change by 2.04 units per day (95% CI 1.14, 2.95, p<0.001) suggesting that P/F ratio changed by 2.3 units per day (i.e. 2.04+0.26) after proning.

## Discussion

In this study, we investigated the patterns of use, and the potential for early and later prone positioning (PP) to impact on outcomes, in patients with COVID-19 induced severe respiratory failure receiving IMV. Our first major finding is that the use of proning was substantially higher than expected, with 53% of patients prone while receiving IMV. We also uncovered discordant results for the efficacy of proning, in that the potential for benefit depended on the timing of a first proning attempt. While proning within 48 h of commencement of IMV was associated with improved outcomes, there was no demonstrable benefit for later proning commencement over usual care. The upward trajectory of improvement in P/F ratio over time was quicker and steeper after prone positioning, as demonstrated via a model of longitudinal P/F ratio during IMV. Here we showed that proning was associated with a greater rate of improvement in P/F over time. Among those prone in the first 48 h 4.7% were co-infected, while in those never prone 5.5% were co-infected (p=0.8).

## Current knowledge regarding PP in COVID-19 patients requiring IMV

PP of patients undergoing IMV has been used frequently in patients with COVID-19. The evidence base for prone positioning of patients with moderate-severe 'classic' ARDS is clear [1]. In addition, the potential for awake prone positioning to reduce the need for IMV [6, 15], and to reduce mortality [5, 18], has been demonstrated in COVID-19 patients receiving advance respiratory support. However, the distinct differences between COVID-19 ARDS and 'classic' ARDS, in terms of lung pathophysiology and treatment responsiveness, and the difference between COVID-19 patients receiving advanced respiratory support versus IMV, raises caution regarding simple extrapolation of therapeutic strategies across these conditions.

The evidence base for PP of invasively ventilated patients with COVID-19 ARDS is surprisingly sparse. Several studies have demonstrated improvements in lung aeration and recruitment and systemic oxygenation [19, 20], reduced shunt [21], and improved haemodynamics [22] with the use of PP in invasively ventilated COVID-19 patients, but a consistent effect on mortality is not demonstrated. Le Terrier et al., in a propensity matched analysis, did not find a benefit of early (within 24Hrs) versus no early PP (i.e. both later PP and never prone patients) on clinical outcomes
<table><caption>**Table 1** Characteristics, illness severity profile, and outcomes of ARDS patients with COVID-19 on mechanical ventilation stratified by proning group</caption><thead><tr><th></th><th>n</th><th>Never proned<sup>1</sup><br>1482 (47%)</th><th>Proned only after 48<br>hours<sup>1</sup><br>615 (20%)</th><th>Proned<br>within 48<br>hours<sup>1</sup><br>1034 (33%)</th></tr></thead><tbody><tr><td>Age (years)</td><td>3131</td><td>58 (16)</td><td>58 (14)</td><td>57 (13)</td></tr><tr><td>Sex (male)</td><td>3129</td><td>553 (37%)</td><td>195 (32%)</td><td>301 (29%)</td></tr><tr><td>Body Mass Index (kg/m<sup>2</sup>)</td><td>2855</td><td>29 (8)</td><td>30 (7)</td><td>31 (8)</td></tr><tr><td>Region</td><td>3111</td><td></td><td></td><td></td></tr><tr><td>Europe</td><td></td><td>219 (15%)</td><td>170 (28%)</td><td>345 (34%)</td></tr><tr><td>Rest of World middle income</td><td></td><td>975 (66%)</td><td>391 (64%)</td><td>615 (60%)</td></tr><tr><td>Rest of World High income</td><td></td><td>282 (19%)</td><td>52 (8.5%)</td><td>62 (6.1%)</td></tr><tr><td>Comorbidities</td><td></td><td></td><td></td><td></td></tr><tr><td>Diabetes</td><td>2993</td><td>502 (36%)</td><td>188 (32%)</td><td>284 (28%)</td></tr><tr><td>Hypertension</td><td>3105</td><td>736 (50%)</td><td>311 (51%)</td><td>474 (46%)</td></tr><tr><td>Malignant neoplasm</td><td>2961</td><td>67 (4.7%)</td><td>23 (4.0%)</td><td>30 (3.1%)</td></tr><tr><td>Chronic cardiac disease</td><td>3066</td><td>307 (21%)</td><td>104 (17%)</td><td>116 (11%)</td></tr><tr><td>Organ Injury/Ventilation Parameters</td><td></td><td></td><td></td><td></td></tr><tr><td>SaO<sub>2</sub>/FiO<sub>2</sub> ratio</td><td>2397</td><td>125 (54)</td><td>116 (43)</td><td>113 (42)</td></tr><tr><td>PaO<sub>2</sub>/FiO<sub>2</sub> ratio</td><td>2538</td><td>110 (57)</td><td>100 (50)</td><td>95 (50)</td></tr><tr><td>Positive end-expiratory pressure (PEEP, cmH<sub>2</sub>O)</td><td>2233</td><td>11.1 (3.6)</td><td>12.1 (3.4)</td><td>12.5 (3.4)</td></tr><tr><td>Need for extracorporeal membrane oxygenation (ECMO)</td><td>2618</td><td>107 (8.5%)</td><td>33 (6.6%)</td><td>99 (12%)</td></tr><tr><td>Lowest Tidal Volume (mL)</td><td>1748</td><td>402 (122)</td><td>401 (121)</td><td>401 (121)</td></tr><tr><td>Highest respiratory rate (breaths per minute)</td><td>2239</td><td>26 (9)</td><td>26 (8)</td><td>26 (7)</td></tr><tr><td>Medications</td><td></td><td></td><td></td><td></td></tr><tr><td>Heparin</td><td>1186</td><td>542 (84%)</td><td>198 (91%)</td><td>303 (95%)</td></tr><tr><td>Corticosteroids</td><td>2838</td><td>942 (69%)</td><td>474 (81%)</td><td>729 (82%)</td></tr><tr><td>Antibiotics</td><td>2693</td><td>1254 (95%)</td><td>529 (95%)</td><td>780 (95%)</td></tr><tr><td>Complications</td><td></td><td></td><td></td><td></td></tr><tr><td>Heart failure</td><td>2525</td><td>87 (7.0%)</td><td>20 (3.9%)</td><td>21 (2.7%)</td></tr><tr><td>Stroke</td><td>2670</td><td>52 (4.0%)</td><td>20 (3.6%)</td><td>23 (2.8%)</td></tr><tr><td>Outcomes</td><td></td><td></td><td></td><td></td></tr><tr><td>Days on IMV</td><td>3047</td><td>14 (18)</td><td>20 (19)</td><td>20 (23)</td></tr><tr><td>Days in ICU</td><td>2981</td><td>18 (18)</td><td>25 (23)</td><td>25 (25)</td></tr><tr><td>Days in hospital</td><td>2892</td><td>28 (33)</td><td>34 (38)</td><td>35 (36)</td></tr><tr><td>Days from hospital admission to IMV</td><td>2981</td><td>4.8 (7.6)</td><td>4.4 (5.2)</td><td>4.1 (7.0)</td></tr><tr><td>Days from ICU admission to IMV</td><td>2858</td><td>1.88 (5.14)</td><td>2.53 (4.50)</td><td>1.65 (3.58)</td></tr><tr><td>28-day ICU mortality</td><td>3131</td><td>693 (47%)</td><td>285 (46%)</td><td>391 (38%)</td></tr><tr><td>90-day hospital mortality</td><td>3131</td><td>786 (53%)</td><td>341 (55%)</td><td>472 (46%)</td></tr><tr><td>Days to death</td><td>1622</td><td>14 (24)</td><td>17 (16)</td><td>21 (35)</td></tr><tr><td>Cause of death</td><td>1551</td><td></td><td></td><td></td></tr><tr><td>Cardiac failure</td><td></td><td>53 (7.0%)</td><td>16 (4.8%)</td><td>26 (5.6%)</td></tr><tr><td>Cerebrovascular accident</td><td></td><td>6 (0.8%)</td><td>6 (1.8%)</td><td>10 (2.2%)</td></tr><tr><td>Haemorrhagic shock</td><td></td><td>12 (1.6%)</td><td>4 (1.2%)</td><td>5 (1.1%)</td></tr><tr><td>Multi-organ failure</td><td></td><td>257 (34%)</td><td>137 (41%)</td><td>187 (40%)</td></tr><tr><td>Other</td><td></td><td>52 (6.9%)</td><td>12 (3.6%)</td><td>18 (3.9%)</td></tr><tr><td>Respiratory failure</td><td></td><td>270 (36%)</td><td>134 (40%)</td><td>184 (40%)</td></tr><tr><td>Septic shock</td><td></td><td>100 (13%)</td><td>22 (6.6%)</td><td>35 (7.5%)</td></tr></tbody></table>

1. n (%); Mean (SD)
<table><caption>**Table 2** Hazard ratios for the association between prone positioning and survival, using two outcomes (28-day ICU and 90-day hospital mortality) against a three-level proning exposure: never proned, proned within 48 h, proned only after 48 h</caption><thead><tr><th>Outcome</th><th>Prone group</th><th>Hazard Ratio</th><th>Lower 95%</th><th>Upper 95%</th><th>p-value</th></tr></thead><tbody><tr><td rowspan="4">28-day ICU mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td>Proned within 48 h</td><td>0.818</td><td>0.683</td><td>0.979</td><td>0.029</td></tr><tr><td>Proned only after 48 h</td><td>0.927</td><td>0.754</td><td>1.141</td><td>0.469</td></tr><tr><td rowspan="4">90-day hospital mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td>Proned within 48 h</td><td>0.809</td><td>0.680</td><td>0.962</td><td>0.017</td></tr><tr><td>Proned only after 48 h</td><td>0.948</td><td>0.776</td><td>1.157</td><td>0.590</td></tr></tbody></table>

Each Cox regression model is adjusted for the same set of covariates

<figure><img src="image_6.png" /><figcaption>**Fig. 2** Hazard ratios for proning within and only after 48 h compared to never proning for outcomes of 28-day ICU mortality (left) and 90-day hospital mortality (right)</figcaption></figure>

<table><caption>**Table 3** Hazard ratios for the association between prone positioning and survival, using two outcomes (28-day and 90-day mortality) in a *propensity score matched* cohorts (never proned vs. proned within 48 h, and never proned vs. proned only after 48 h)</caption><thead><tr><th>Outcome</th><th>Prone group</th><th>Hazard Ratio</th><th>Lower 95%</th><th>Upper 95%</th><th>p-value</th></tr></thead><tbody><tr><td rowspan="4">28-day ICU mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td>Proned within 48 h</td><td>0.853</td><td>0.730</td><td>0.997</td><td>0.045</td></tr><tr><td>Proned only after 48 h</td><td>1.002</td><td>0.852</td><td>1.178</td><td>0.984</td></tr><tr><td rowspan="4">90-day hospital mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td>Proned within 48 h</td><td>0.854</td><td>0.741</td><td>0.985</td><td>0.030</td></tr><tr><td>Proned only after 48 h</td><td>1.022</td><td>0.880</td><td>1.188</td><td>0.773</td></tr></tbody></table>

Each patient who was proned was matched with two individuals never proned

in invasively ventilated COVID-19 patients [10]. In this analysis, of the 1504 patients that did not receive early PP, 1013 were proned with a median delay of 3 days. The outcomes in the ‘never’ versus ‘late’ proned patient groups are not distinguished in their analysis, and all their patients were European. Stilma et al., in

their analysis of 734 invasively ventilated COVID-19 patients across 22 ICUs in the Netherlands found no association between PP and outcome [8]. Langer et al. reported that patients receiving IMV in the first wave of the pandemic in Italy had more severe disease and a higher mortality rate, while patients that responded
<figure><img src="image_7.png" /><figcaption>**Fig. 3** Kaplan Meier plots of propensity matched cohorts showing 28-day ICU survival (left) and 90-day hospital survival (right) comparing those proned within 48 h against a matched cohort of those never proned</figcaption></figure>

<table><caption>**Table 4** Hazard ratios for the association between prone positioning and survival, using two outcomes (28-day ICU and 90-day hospital mortality) against a three-level proning exposure: never proned, proned within 48 h, proned only after 48 h</caption><thead><tr><th>Outcome</th><th>Prone group</th><th>Hazard Ratio</th><th>Lower 95%</th><th>Upper 95%</th><th>p-value</th></tr></thead><tbody><tr><td>Europe (n = 902)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>28-day ICU mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td></td><td>Proned within 48 h</td><td>1.012</td><td>0.700</td><td>1.465</td><td>0.948</td></tr><tr><td></td><td>Proned only after 48 h</td><td>1.112</td><td>0.721</td><td>1.715</td><td>0.626</td></tr><tr><td>90-day hospital mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td></td><td>Proned within 48 h</td><td>0.944</td><td>0.661</td><td>1.349</td><td>0.750</td></tr><tr><td></td><td>Proned only after 48 h</td><td>1.119</td><td>0.745</td><td>1.681</td><td>0.582</td></tr><tr><td>High-income rest of the world (n = 2387)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>28-day ICU mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td></td><td>Proned within 48 h</td><td>0.803</td><td>0.672</td><td>0.959</td><td>0.015</td></tr><tr><td></td><td>Proned only after 48 h</td><td>0.956</td><td>0.788</td><td>1.159</td><td>0.643</td></tr><tr><td>90-day hospital mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td></td><td>Proned within 48 h</td><td>0.818</td><td>0.697</td><td>0.961</td><td>0.015</td></tr><tr><td></td><td>Proned only after 48 h</td><td>0.985</td><td>0.821</td><td>1.182</td><td>0.870</td></tr><tr><td>Middle-income rest of the world (n = 412)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>28-day ICU mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td></td><td>Proned within 48 h</td><td>0.968</td><td>0.673</td><td>1.394</td><td>0.862</td></tr><tr><td></td><td>Proned only after 48 h</td><td>1.081</td><td>0.753</td><td>1.553</td><td>0.672</td></tr><tr><td>90-day hospital mortality</td><td>Never versus Later versus Early</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Never Proned (Reference)</td><td>1</td><td></td><td></td><td></td></tr><tr><td></td><td>Proned within 48 h</td><td>0.968</td><td>0.673</td><td>1.393</td><td>0.860</td></tr><tr><td></td><td>Proned only after 48 h</td><td>1.136</td><td>0.795</td><td>1.622</td><td>0.482</td></tr></tbody></table>

Each Cox regression model is adjusted for the same set of covariates. Models were repeated by geographical region (Europe [n = 916]), high-income rest of the world [n = 2393], and middle-income rest of the world [n = 412])
<table><caption>**Table 5** Longitudinal model of PaO2/FiO2 ratio during invasive mechanical ventilation among those prone at any stage. Results show the change in P/F before and after prone positioning</caption><thead><tr><td>Predictors</td><td>Estimates</td><td>Lower 95%</td><td>Upper 95%</td><td>p-value</td></tr></thead><tbody><tr><td>PaO2/FiO2 on day 0 of IMV</td><td>116.38</td><td>113.32</td><td>119.44</td><td>&lt;0.001</td></tr><tr><td>Slope of (i.e. change in) PaO2/FiO2 before prone positioning</td><td>0.26</td><td>-0.60</td><td>1.13</td><td>0.551</td></tr><tr><td>Change to slope after first prone position</td><td>2.04</td><td>1.14</td><td>2.95</td><td>&lt;0.001</td></tr></tbody></table>

<figure><img src="image_8.png" /><figcaption>**Fig. 4** Fitted and actual PaO2/FiO2 ratios for two patients using a linear mixed model with a linear spline term allowing a change in slope on the day of first proning</figcaption></figure>

to PP did not seem to have improved outcomes [23]. In contrast, Mathews et al. in the US, in an inverse probability treatment weighting analysis, reported that in-hospital mortality was lower in mechanically ventilated hypoxemic patients with COVID-19 treated with early proning (within first 48Hrs) [24].

A systematic review and meta-analysis of seven retrospective cohort studies [25] that enrolled 5216 patients reported that ICU mortality risk was twice as high in the prone group, while there was no difference in hospital or overall mortality. A key issue in these analyses is that no distinction was made in regard to the timing of the proning, with all prone (i.e. early and later 'rescue' proning) included in the treatment groups.

The timing of commencement of PP is important because of the potential for PP to homogenise lung stress and thereby reduce the potential for additional ventilator induced lung injury. In 'classic' ARDS the early use

of PP is given a strong recommendation in the recently published ESICM guidelines for ARDS management [26]. This guideline also recommends early proning for COVID-19 ARDS, but acknowledges that there is no RCT evidence to support this recommendation [26].

The need for a clear determination of the effect of PP in this population is underlined by a number of findings. First, studies have demonstrated that implementation of PP in patients with moderate-severe COVID-19 ARDS requiring IMV is associated with higher resource use [27], particularly in terms of the requirement for healthcare personnel to prone patients safely. Second, there is an increased frequency of complications, including haemodynamic instability and pressure ulcers in patients that undergo PP [28]. Third, the use of PP appears to be declining after an initial high uptake in the earlier phases of the COVID-19 pandemic [29]. Consequently, there is
an urgent need to determine both the effectiveness and
optimal timing of PP in this population.

Clinical implications

Our study addresses limitations in the existing literature, and provides significant new insights into the effects of PP, and particularly the importance of timing of PP in patients with COVID-19 managed with IMV. Firstly, we demonstrate that early PP is associated with improved outcomes. Patients who were prone early had lower risk of 28-day ICU mortality and 90-day hospital mortality compared to those who were never prone. Among those patients who died, time to death was earlier on average in those never prone compared to those prone early. A propensity score matched analysis confirmed these findings of a reduced 28-day and 90-day hospital mortality risk in patients receiving early PP. Those prone early were also less likely to suffer complications such as heart failure.

Of equal importance, we could find no evidence that
later proning was associated with improved outcomes in
this population. Those prone after 48 h had no reduc-
tion in the risk of 28-day or 90-day mortality compared
to those never prone. It is clear from these findings that,
for proning to be effective, it should be instituted within
48 h of commencement of IMV.

Strengths and limitations

A strength of this study is its size and diversity, with 3996 patients from 35 countries included. However, since this was an observational study, we cannot draw any causal conclusions about proning–that may require future randomised studies in this population. While the possibility of immortal time bias related to the timing of proning exists, this is less likely to be important given our focus on early proning within 48 h of IMV rather than at later time points. Furthermore, we compare different, time-independent prone position hypotheses.

The ability to prone patients early following IMV
may reflect issues such as greater centre experience
with the manoeuvre, staffing within the ICU etc., all
of which may affect mortality by other mechanisms.
In addition, we cannot exclude the possibility that that
some patients undergoing later proning were deterio-
rating clinically, and underwent ‘rescue’ proning in an
attempt to reduce a high risk of death. The finding that
P/F ratio on day of first proning was similar between
those prone within and after 48 h does suggest that
this was not a major factor. Those prone early tended
to have protective factors against mortality, e.g. less
diabetes and hypertension. While we controlled for
the observed confounding of observed data, there still
may be unmeasured confounding by other, unmeasured
protective factors linked to early prone positioning.

Potential between-hospital heterogeneity exists in
admission criteria for ICU, indication for IMV, and use
of adjuncts such as neuromuscular blockade. These
were not standardised across countries and could have
depended on local practices. We provide a stratified
analysis by region, and this suggests our results were
driven by those non-European high-income countries.
It is possible that geographic differences in duration of
proning sessions might explain these findings. Unfor-
tunately, data on prone duration were not consistently
available in this dataset. Our findings are consist-
ent with prior studies [30] that identified differences
between European and the non-European countries
regarding ARDS severity profiles, and in the duration
of invasive ventilation and length of stay in ICU across
these regions. We suggest that this finding deserves
further exploration in separate studies.

The database had high levels of missing data for some respiratory variables such as plateau pressure data, and data on plateau pressure, driving pressure and respiratory system compliance. However, our analysis included other respiratory dysfunction severity indices, in particular P/F ratio, which is the criterion used in the pivotal PROSEVA study by Guerin et al. as a criterion for prone positioning in the study population. Data on bacterial infection rates in the dataset also had a high rate of missing values. However, among those with data, there were no statistically significant differences between the prone groups. No data on life limiting measures were available in this study, and so we could not explore whether rates differed between the proning groups. We used multiple imputation to address missing data, with no significant differences in main exposures and outcomes between those complete case patients and patients with missing data (Table s1). Furthermore, our results were robust in a sensitivity analysis restricted to complete case patients (Table s2).

Another limitation of our study is the difference in
timing from admission to MV, with those early prone
having a shorter average time (4.1 days) to those never
(4.8 days) or later prone (4.4 days). This is explained
in part by the fact that the time from ICU admission to
commencement of invasive MV is shorter in the group
prone within 48 h. The changing nature of COVID-19
treatment from January 2020 to March 2023 may have
influenced findings. For instance, early in the pandemic,
some ICUs struggled to manage critically ill patients in
understaffed and overwhelmed departments.

Conclusions

Proning is a commonly used treatment in COVID-19
patients receiving IMV, and proning patients within
48 h of IMV initiation is associated with improved
survival. Timing of proning is critical, as there was no significant effect of proning administered after 48 h.

### Abbreviations

**ARDS** Acute respiratory distress syndrome

**CCCC** COVID-19 Critical Care Consortium

**CI** Confidence interval

**HR** Hazard ratio

**ICU** Intensive care unit

**IMV** Invasive mechanical ventilation

**ISARIC** International Severe Acute Respiratory and Emerging Infection Consortium

**PP** Prone positioning

**RCT** Randomised controlled trial

### Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s13613-025-01422-6.

Additional file 1

Additional file 2

### Acknowledgements

We recognize the crucial importance of the ISARIC and SPRINT-SARI networks in developing and expanding the global COVID-19 Critical Care Consortium. We thank the generous support we received from the Extracorporeal Life Support Organization (ELSO) and the International ECMO Network (ECMONet). We greatly acknowledge Adrian Barnett for his invaluable contribution to the analysis plan and statistical insights. We owe Li Wenliang, MD from the Wuhan Central Hospital, an eternal debt of gratitude for reminding the world that doctors should never be censored during a pandemic. Finally, we acknowledge all members of the COVID-19 Critical Care Consortium and various collaborators.

### Author contributions

**Concept and design:** Andrew Simpkin; Bairbre McNicholas; Gianluigi Li Bassi; Jacky Y. Suen; John F. Fraser; John Laffey; **Acquisition, analysis, or interpretation of data:** All Authors **Drafting of the manuscript:** Andrew Simpkin; Bairbre McNicholas; Gianluigi Li Bassi; Jacky Y. Suen; John F. Fraser; John G Laffey; **Critical revision of the manuscript for important intellectual content:** All Authors **Statistical analysis:** Andrew Simpkin; Nicole White. **Administrative, technical, or material support:** Amanda Corley **Supervision:** Robert Bartlett; Daniel Brodie; Davide Chiumello; Giacomo Grasselli; Antoni Torres; John F. Fraser; John G Laffey.

### Funding

This work was funded and supported by the University of Queensland; The Wesley Medical Research; The Prince Charles Hospital Foundation; The Health Research Board of Ireland; Gianluigi Li Bassi is a recipient of the BITRECS fellowship; the "BITRECS" project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 754550 and from the "La Caixa" Foundation (ID 100010434), under the agreement LCF/PR/GN18/50310006. AS is funded by Science Foundation Ireland grant 19/FFP/7002.

### Availability of data materials

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

### Declarations

#### Ethics approval and consent to participate

Participating hospitals obtained local ethics committee approval and a waiver of informed consent was granted in all cases.

#### Consent for publication

Not applicable.

### Competing interests

A/Prof Li Bassi received research support from Fisher and Paykel outside the submitted work. Dr McNicholas has provided consultancy to Teleflex. Prof. Brodie receives research support from ALung Technologies, and he has been on the medical advisory boards for Baxter, Abiomed, Xenios, and Hemovent. Prof. Fraser receives research support from Fisher and Paykel, Xenios and MERA outside the submitted work. Prof. Laffey reports consulting fees from Cellenkos outside the submitted work.

### Author details

¹School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland. ²Department of Anaesthesia and Intensive Care Medicine, School of Medicine, Clinical Sciences Institute, Galway University Hospital, Saolta University Healthcare Group, Galway H91 YR71, Ireland. ³School of Medicine, College of Medicine, Nursing and Health Sciences, University of Galway, Galway, Ireland. ⁴University of Michigan Medical Center, Ann Arbor, MI, USA.

⁵Ospedale San Paolo, Milan, Italy. ⁶University of Milan, Milan, Italy. ⁷INOVA Fairfax Medical Center, Heart and Vascular Institute, Falls Church, VA, USA.

⁸Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia. ⁹Children's Intensive Care Research Program, Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia. ¹⁰ISARIC, Pandemic Sciences Institute, University of Oxford, Oxford, UK. ¹¹University of Toronto, Interdepartmental Division of Critical Care Medicine, Toronto, ON, Canada. ¹²Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico Di Milano, Department of Anesthesia, Intensive Care and Emergency. Milano, Lombardia, Italy. ¹³Centro de Investigación Biomedica En Red - Enfermedades Respiratorias (CIBERES), Madrid, Spain. ¹⁴Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Barcelona, Universitat de Barcelona, Barcelona, Spain. ¹⁵Servei de Pneumologia, Hospital Clinic, University of Barcelona, Barcelona, Spain. ¹⁶Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain. ¹⁷Translational Research in Respiratory Medicine, Respiratory Dept, Hospital Universitari Aranu de Vilanova and Santa Maria, Lleida, Spain. ¹⁸Critical Care Medicine Unit, University of Hong Kong and Queen Mary Hospital, Hong Kong, China. ¹⁹University College Dublin-Clinical Research Centre at St Vincent's University Hospital, Dublin, Ireland. ²⁰Critical Care Research Group, The Prince Charles Hospital, Brisbane, Australia. ²¹School of Pharmacy and Medical Sciences, Griffith University, Southport, Australia. ²²University of Queensland, Brisbane, Australia. ²³Uniting Care Hospitals, Brisbane, Australia. ²⁴Wesley Medical Research, Brisbane, Australia. ²⁵School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, Australia.

²⁶Inserm, CHU Nantes, Center for Research in Transplantation and Translational ¹⁶ Immunology, UMR 1064, Nantes Université, F-44000 Nantes, France.

Received: 23 August 2024 Accepted: 7 December 2024

Published: 10 February 2025

### References

1. Guerin C, Reignier J, Richard JC, Beuret P, Gacouin A, Boulain T, et al. Prone positioning in severe acute respiratory distress syndrome. N Engl J Med. 2013;368(23):2159-68.

2. Gattinoni L, Chiumello D, Caironi P, Busana M, Romitti F, Brazzi L, Camporota L. COVID-19 pneumonia: different respiratory treatments for different phenotypes?. Springer; 2020. p. 1099-102.

3. Beloncle FM. Is COVID-19 different from other causes of acute respiratory distress syndrome? Jf Int Med. 2023;3(03):212-9.

4. Lee H-J, Kim J, Choi M, Choi W-I, Joh J, Park J, Kim J. Efficacy and safety of prone position in COVID-19 patients with respiratory failure: a systematic review and meta-analysis. Eur J Med Res. 2022;27(1):1-19.

5. McNicholas BA, Ibarra-Estrada M, Perez Y, Li J, Pavlov I, Kharat A, et al. Awake prone positioning in acute hypoxaemic respiratory failure. Eur Respir Rev. 2023;32(168):1.

6. Li J, Luo J, Pavlov I, Perez Y, Tan W, Roca O, et al. Awake prone positioning for non-intubated patients with COVID-19-related acute hypoxaemic respiratory failure: a systematic review and meta-analysis. Lancet Respir Med. 2022;10:573-83.

7. Shelhamer MC, Wesson PD, Solari IL, Jensen DL, Steele WA, Dimitrov VG, et al. Prone positioning in moderate to severe acute respiratory distress
syndrome due to COVID-19: a cohort study and analysis of physiology. J Intensive Care Med. 2021;36(2):241–52.

8. Stilma W, Van Meenen DM, Valk CM, De Bruin H, Paulus F, Serpa Neto A, et al. Incidence and practice of early prone positioning in invasively ventilated COVID-19 patients—insights from the PROVENT-COVID observational study. J Clin Med. 2021;10(20):4783.

9. Camporota L, Sanderson B, Chiumello D, Terzi N, Argaud L, Rimmelé T, et al. Prone position in coronavirus disease 2019 and noncoronavirus disease 2019 acute respiratory distress syndrome: an international multicenter observational comparative study. Critical care medicine. 2021.

10. Le Terrier C, Sigaud F, Lebbah S, Desmedt L, Hajage D, Guerin C, et al. Early prone positioning in acute respiratory distress syndrome related to COVID-19: a propensity score analysis from the multicentric cohort COVID-ICU network-the ProneCOVID study. Crit Care. 2022;26(1):71.

11. Group RC, Horby P, Lim WS, Emberson JR, Mafham M, Bell JL, et al. Dexamethasone in Hospitalized Patients with Covid-19. N Engl J Med. 2021;384(8):693–704.

12. Li Bassi G, Suen J, Barnett AG, Corley A, Millar J, Fanning J, et al. Design and rationale of the COVID-19 critical care consortium international, multicentre, observational study. BMJ Open. 2020;10(12): e041417.

13. Cox DR. Regression models and life-tables. J Royal Statist Soc Ser B (Methodological). 1972;34(2):187–202.

14. Guérin C, Albert RK, Beitler J, Gattinoni L, Jaber S, Marini JJ, et al. Prone position in ARDS patients: why, when, how and for whom. Intensive Care Med. 2020;46:2385–96.

15. Ehrmann S, Li J, Ibarra-Estrada M, Perez Y, Pavlov I, McNicholas B, et al. Awake prone positioning for COVID-19 acute hypoxaemic respiratory failure: a randomised, controlled, multinational, open-label meta-trial. Lancet Respir Med. 2021.

16. Rubin DB. Multiple imputation for nonresponse in surveys. John Wiley and Sons. 2004. pp. 81.

17. von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP, Initiative S. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61(4):344–9.

18. Ibarra-Estrada M, Li J, Pavlov I, Perez Y, Roca O, Tavernier E, et al. Factors for success of awake prone positioning in patients with COVID-19-induced acute hypoxemic respiratory failure: analysis of a randomized controlled trial. Crit Care. 2022;26(1):84.

19. Clarke J, Geoghegan P, McEvoy N, Boylan M, Ni Choileain O, Mulligan M, et al. Prone positioning improves oxygenation and lung recruitment in patients with SARS-CoV-2 acute respiratory distress syndrome; a single centre cohort study of 20 consecutive patients. BMC Res Notes. 2021;14(1):20.

20. Emgin O, Rollas K, Yeniay H, Elve R, Guldogan IK. Effect of the prone position on recruitability in acute respiratory distress syndrome due to COVID-19 pneumonia. Rev Assoc Med Bras (1992). 2023;69(5):e20221120.

21. Dos Santos RA, Diaper J, Balogh AL, Marti C, Grosgurin O, Habre W, et al. Effect of body position on the redistribution of regional lung aeration during invasive and non-invasive ventilation of COVID-19 patients. Sci Rep. 2022;12(1):11085.

22. Coxwell Matthewman M, Yanase F, Costa-Pinto R, Jones D, Karalapillai D, Modra L, et al. Haemodynamic changes during prone versus supine position in patients with COVID-19 acute respiratory distress syndrome. Aust Crit Care. 2023.

23. Langer T, Brioni M, Guzzardella A, Carlesso E, Cabrini L, Castelli G, et al. Prone position in intubated, mechanically ventilated patients with COVID-19: a multi-centric study of more than 1000 patients. Crit Care. 2021;25(1):128.

24. Mathews KS, Soh H, Shaefi S, Wang W, Bose S, Coca S, et al. Prone positioning and survival in mechanically ventilated patients with coronavirus disease 2019-related respiratory failure. Crit Care Med. 2021;49(7):1026–37.

25. Fayed M, Maroun W, Elnahla A, Yeldo N, Was JR, Penning DH. Prone Vs. Supine Position Ventilation in Intubated COVID-19 Patients: A Systematic Review and Meta-Analysis. Cureus. 2023;15(5):e39636.

26. Grasselli G, Calfee CS, Camporota L, Poole D, Amato MBP, Antonelli M, et al. ESICM guidelines on acute respiratory distress syndrome: definition, phenotyping and respiratory support strategies. Intensive Care Med. 2023;49(7):727–59.

27. de Miguel-Balsa E, Blasco-Ruso T, Gomez-Medrano N, Mirabet-Guijarro M, Martinez-Perez A, Alcala-Lopez A. [Effect of duration of prone position in ARDS patients during SARS-CoV-2 pandemic]. Med Intensiva. 2023.

28. Barja-Martinez E, Garcia-Gonzalez S, Jimenez-Garcia E, Thuissard-Vasallo IJ, Arias-Rivera S, Blanco-Abril S. Prone positioning in COVID-19 patients with acute respiratory distress syndrome and invasive mechanical ventilation. Enferm Intensiva (Engl Ed). 2023;34(2):70–9.

29. Hochberg CH, Psoter KJ, Eakin MN, Hager DN. Declining use of prone positioning after high initial uptake in COVID-19 adult respiratory distress syndrome. Crit Care Med. 2023;51(11):1547–51.

30. Laffey JG, Madotto F, Bellani G, Pham T, Fan E, Brochard L, et al. Geo-economic variations in epidemiology, patterns of care, and outcomes in patients with acute respiratory distress syndrome: insights from the LUNG SAFE prospective cohort study. Lancet Respir Med. 2017;5(8):627–38.

## Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.