Impaired ventilation is not independently associated with 28-day mortality in COVID-19 ARDS

Background: Surrogates for impaired ventilation such as estimated dead-space fractions and the ventilatory ratio have been shown to be independently associated with an increased risk of mortality in the acute respiratory distress syndrome and small case series of COVID-19 related ARDS. Methods: Secondary analysis from the PRoVENT-COVID study. The PRoVENT-COVID is a national, multicentre, retrospective observational study done at 22 intensive care units in the Netherlands. Consecutive patients aged at least 18 years were eligible for participation if they had received invasive ventilation for COVID-19 at a participating ICU during the first month of the national outbreak in the Netherlands. The aim was to quantify the dynamics and determine the prognostic value of surrogate markers of impaired ventilation patients with COVID-19 related ARDS. Results: 927 consecutive patients admitted with COVID-19 related ARDS were included in this study. Surrogates of impaired ventilation such as the estimated dead space fraction (by Harris-Benedict and direct method) and ventilatory ratio were significantly higher in non-survivors than survivors at baseline and during the following days of mechanical ventilation (p <0.001). The end-tidal-to-arterial PCO 2 ratio was lower in non-survivors than in survivors (p<0.001). As ARDS severity increased, mortality increased with successive tertiles of dead space fraction by Harris-Benedict and by direct estimation, and for the VR. The same trend was observed with decreased levels in the tertiles for the end-tidal-to-arterial PCO 2 ratio. After adjustment for a base risk model that included chronic comorbidities and ventilation- and oxygenation-parameters, none of the surrogates of impaired ventilation measured at the start of ventilation or the following days were significantly associated with 28-day mortality. Conclusions: There is significant impairment of ventilation in the early course of COVID-19 related ARDS but quantification of this impairment does not add prognostic information when added to a baseline risk-model.

Results: 927 consecutive patients admitted with COVID-19 related ARDS were included in this study. Surrogates of impaired ventilation such as the estimated dead space fraction (by Harris-Benedict and direct method) and ventilatory ratio were significantly higher in non-survivors than survivors at baseline and during the following days of mechanical ventilation (p <0.001). The end-tidal-to-arterial PCO2 ratio was lower in non-survivors than in survivors (p<0.001). As ARDS severity increased, mortality increased with successive tertiles of dead space fraction by Harris-Benedict and by direct estimation, and for the VR.
The same trend was observed with decreased levels in the tertiles for the end-tidal-toarterial PCO2 ratio. After adjustment for a base risk model that included chronic comorbidities and ventilation-and oxygenation-parameters, none of the surrogates of BACKGROUND Since the outbreak of coronavirus disease 2019  in the City of Wuhan, Hubei Province, China, caused by the transmission of the novel coronavirus SARS-CoV-2, millions of individuals have been infected and more than one million have died. Severe disease requiring admission to intensive care unit (ICU) occurs in approximately 5% of infections 1 , and the most common reason for admission is respiratory failure requiring high-level support. Among these patients, two-thirds meet the criteria for the acute respiratory distress syndrome (ARDS) 2 .
Patients with COVID-19 pneumonia that meets criteria for ARDS usually present with a high respiratory drive and minute ventilation, potentially due to hypercapnia and an increased dead space fraction (VD/VT) 3 . In patients with ARDS, an elevated VD/VT is a predictor of death and is one of the few lung-specific physiological variables independently associated with mortality 4,5 . Methods for estimating VD/VT do not require quantitative assessment of exhaled carbon dioxide, are less complicated to perform, and easier to calculate at the bedside 6 . In recent years, the ventilatory ratio (VR) was proposed as an easily acquired bedside index of impaired ventilation that can be computed using routinely measured respiratory variables 7 . In patients with ARDS, the VR correlates well with VD/VT 7 and may function as a surrogate marker for impaired ventilation 8 .
At least two independent groups have described series of patients with COVID-19 related ARDS who may have inefficient CO2 removal due to increased physiologic dead space 3,9 . However, no published study has assessed the impact of estimated VD/VT and VR on mortality in a large cohort of COVID-19 patients undergoing invasive ventilation.
Therefore, we aimed to assess the association between markers of impaired ventilation, such as estimated VD/VT and VR with 28-day mortality in patients undergoing invasive ventilation because of COVID-19 ARDS. We hypothesized that these markers of impaired ventilation are independently associated with 28-day mortality.

Study design and oversight
PRoVENT-COVID is an investigator-initiated, multicenter, observational cohort study undertaken at 22 ICUs in the Netherlands. The study protocol including the statistical analysis plan are available 10 .The approved protocol is available in Supplement 1. A statistical analysis plan for the current analysis was written before assessing the database, and is available online 11 . Study sites were recruited through direct contact by members of the steering committee of PRoVENT-COVID. The institutional review boards of the participating centers approved the study protocol, and need for patient informed consent was waived. Study coordinators contacted the local doctors, trained data collectors to assist the local doctors, and monitored the study according to the International Conference on Harmonization Good Clinical Practice-guidelines. Integrity and timely completion of data collection was ensured by the study coordinators.

Patients
Consecutive patients ≥ 18 years were eligible for participation in PRoVENT-COVID if they were admitted to one of the participating ICUs and had received invasive ventilation for COVID-19 ARDS. COVID-19 infection was defined by a confirmed reverse transcriptasepolymerase chain reaction (RT-PCR), or highly suspected based on presence of typical abnormalities on chest computer tomography (CT) images 12 .
PRoVENT-COVID had no exclusion criteria, but for the current analysis we excluded patients transferred from a non-participating hospital who had been receiving invasive ventilation for more than 2 calendar days, patients without complete data to calculate the VD/VT or VR in the first day of ventilation, and patients with no data about 28-day mortality.

Data collection
Demographics and data regarding premorbid diseases and medication were collected at baseline. In the first hour of invasive ventilation and every 8 hours thereafter, at fixed time points in the first 4 calendar days, ventilator settings and parameters were collected. In the present study, the first day of ventilation is called 'at start of ventilation'.

Data definition and exposure
The primary exposure of interest was the VD/VT calculated using the Harris-Benedict formula as described in Eq. (1) 13 : . (1) RR is the respiratory rate in breaths per minute, VT the tidal volume in liters, PaCO2 the partial pressure of carbon dioxide in mmHg, and VCO2 the CO2 production in mL/min estimated using the Eq. Weight is in kilograms, height is in centimeters and age in years.
In addition, two additional estimations of VD/VT were done considering a direct estimation and the end-tidal-to-arterial PCO2 ratio 14 , and the formulas are described in the Online Supplement.
The secondary exposure of interest is the VR, calculated using the Eq. (4) 15 : VR is the ventilatory ratio, VE measured is the measured minute ventilation in mL/min, PaCO2 measured is the measured PaCO2 in mmHg, VE predicted is the predicted minute ventilation in mL/min (calculated as 100 * predicted body weight) 15 , and PaCO2 predicted is the predicted PaCO2 determined as 37.5 mmHg.
All variables were calculated three times per day and the values were aggregated as the mean in the respective day. Primary analyses focused on the values obtained in the day of start of ventilation.

Outcomes
The outcome assessed in this study was death at 28 days, defined as the mortality 28 days after the start of ventilation. Other clinical outcomes are reported only to describe the cohort but were not used to test their association with the exposures described above.

Statistical analysis
The amount of missing data was low for most of the variables (eTable 1 in Online Supplement). Continuous variables are presented as medians (quartile 25% -quartile 75%) and categorical variables as numbers and percentages. Descriptive data is presented according to the 28-day status (non-survivors vs. survivors), and the two groups were compared using Wilcoxon rank-sum test for continuous variables, and Fisher exact tests for categorical variables.

Trends in markers of impaired ventilation were presented in boxplots between
survivors and non-survivors over the first 4 calendar days. The direction of effect over time of the variables was assessed with mixed-effect linear models with center and patients treated as random effect to account for clustering and repeated measurements, and with 28-day vital status (alive/dead), time (as a continuous variable), and an interaction of 28day vital status and time as fixed effect. Overall P values from this analysis represent the overall difference among groups over time and P values from interaction represent a statistical assessment of whether the trend over time differed among the groups. All daily measurements of variables (three times a day) were aggregated as the mean per day. In addition, to compare variables at each day, the day variable was entered as a categorical variable in the model described above, and the P value for the daily difference was extracted using pairwise comparisons after Bonferroni correction.
We examined the risk of death for each tertile of the lung-specific physiological variables was used to evaluate whether the predictive ability of each variable varied by level. In addition, a simple stratification creating two groups according to the median of the variables was also assessed. The comparison of the two groups was presented in Kaplan-Meier curves and compared using Log-rank tests.
Univariable mixed-effect generalized linear models considering a binomial distribution and with center as random effect were used to estimate the unadjusted effect of each variable on 28-day mortality. A multivariable mixed-effect generalized linear model considering a binomial distribution and with center as random effect were used to test the association of each of the exposures described above with 28-day mortality. A list of candidate confounders was determined a priori, and based on clinical relevance rather than statistical significance. The following baseline variables (measured at baseline or within 1 hour after intubation or ICU admission with ventilation) were considered in the models: age, gender, body mass index, PaO2/FiO2 ratio, plasma creatinine, hypertension, diabetes, use of angiotensin converting enzyme inhibitors, use of angiotensin II receptor blockers, use of a vasopressor or an inotropic drug, fluid balance, pH, mean arterial pressure, heart rate, respiratory system compliance, and PEEP. Multicollinearity was assessed through the analysis of the variance inflation factors, and the final model was assessed for discrimination using c-statistics, and for calibration using the Brier-Score.
In addition to the odds ratio (OR) and its 95% confidence interval, the predictive accuracy of the lung-specific physiological variables was measured by the area under the receiver operating characteristics curve (AUC-ROC). Also, to estimate whether these variables improved predictive accuracy on top of that of the base model described above, the net reclassification improvement (NRI) and the integrated discrimination index (IDI) were assessed.
For the primary analysis, covariates with less than 3% of missing were imputed by the median value of the overall cohort. Since respiratory compliance was missing in 8.2% of the patients (eTable 1 in Online Supplement), an additional sensitivity analysis considering multiple imputation for all missing variables was conducted (described in details in Online Supplement).
All continuous variables were entered after standardization to improve convergence of the models, and the odds ratio (OR) represents the increase in one standard deviation of the variable. All analyses were conducted in R v.4.0.2 (R Foundation, Vienna, Austria) 16 and significance level was set at 0.05.

Study population
From

Markers of impaired ventilation
The dynamic change of markers of impaired ventilation over the first four days of ventilation as shown in Table 2 and Figure 1. VD/VT calculated using the Harris-Benedict formula was higher in non-survivors and increased more during the first four days compared to survivors. Similar trend was found with the direct VD/VT calculation. While VR was also higher in non-survivors, especially after day 2, the end-tidal-to-arterial PCO2 ratio was lower.
Mortality by tertiles of each variable is reported in Figure 2. Tertiles were calculated separately for each variable and each day, to account for potential differences in scaling and measurements. Mortality increased with successive tertiles of dead space fraction by Harris-Benedict and by direct estimation, and of ventilatory ratio, and decreased with successive tertiles of end-tidal-to-arterial PCO2 ratio.  (Figure 3). When assessing the end-tidal-to-arterial PCO2 ratio, 28-day mortality was lower in the highest tertile group (10.7% vs. 17.1%; p < 0.001).

Predictive accuracy of markers of impaired ventilation
The unadjusted impact of each marker of impaired ventilation is shown in eTable 4 in Online Supplement. Estimated dead space fraction (by HB and direct method) and endtidal-to-arterial PCO2 ratio were associated with 28-day mortality at the start of mechanical ventilation. Twenty-four hours after this, dead space fraction by Harris-Benedict, and endtidal-to-arterial PCO2 ratio were associated with 28-day mortality. The final multivariable base risk model is shown in eTable 5 and in the Online Supplement. No problems were found due to multicollinearity or linearity assumption (eTables 6 and 7 in Online Supplement).
After adjustment for the base risk model, none of the markers of impaired ventilation measured at the start of ventilation or the following day was significantly associated with 28-day mortality ( Table 3). The inclusion of these variables did not improve the AUC-ROC compared to the base model (Figure 4). The addition of dead space fraction by direct estimation at start of ventilation, and of end-tidal-to-arterial PCO2 ratio at start of ventilation or day 1 slightly improved the predictive accuracy of the base model in terms of IDI ( Table   3).

Sensitivity analysis
Results after multiple imputation were similar to the primary analysis (eTables 8 and 8, and eFigures 2 and 3 in Online Supplement).

DISCUSSION
The findings of this multicenter, observational cohort study of COVID-19 related ARDS patients showed that surrogate markers for impaired ventilation and increased VD/VT increased over the first days of invasive ventilation and were significantly higher in nonsurvivors than survivors. However, none of these indices was independently associated with mortality when corrected for potential confounders. Therefore, impaired ventilation, and, tentatively, increased dead space fraction, seems to be a marker for disease severity rather than an independent predictor of outcome.
Despite the potential clinical value, VD/VT is not routinely measured in daily critical care practice. One possible barrier is the requirement of volumetric capnography (or other techniques of analyzing exhaled gas) to measure Vd/Vt. Surrogate measures for estimating VD/VT are more frequently utilized and a wide array of these surrogates were included in this study 17,18 . VR is a recently validated index that is appealing because it is simple to calculate using readily available measurements; it compares arterial carbon dioxide tension (PaCO2) and minute ventilation to corresponding "ideal" and "predicted" values as a stand-in for VD/VT 15 . The VR was shown to be high in patients with COVID-19 related ARDS 3,9 and is known to show moderate correlation with VD/VT by volumetric capnography 7 . This index has been validated in controlled modes of mechanical ventilation because the VR depends on the carbon dioxide production (V CO2) 7,15 . Any changes in the latter will have significant changes in its value. Recently, the end-tidal-toarterial PCO2 ratio (PETCO2/PaCO2) has been described as another surrogate for VD/VT in ARDS patients 14  We also validated the association between ventilation impairment and outcome that was previously observed in patients with ARDS due to other causes than COVID-19 4,23 .
However, in our study the investigated surrogates did not add predictive value to a model that included other known predictors for 28-day mortality, with the possible exception of PETCO2/PaCO2 at the start and at day 1 of ventilation. This contrasts with several studies in ARDS that showed increased dead space ventilation to be a robust and independent predictor of mortality risk 4,23-25 . Decreasing PETCO2/PaCO2 was also independently associated with mortality risk in one study 14  volumes. Instrumental dead space may significantly affect the total dead space, mainly when using low tidal volume ventilation. We did not register the type of system humidification device in our study.
For the estimated VD/VT computed by the Harris-Benedict formula, we assumed an RQ of 0.8 for VCO2 calculation based on a previous study 18 . Although the RQ may vary among ARDS patients, a recently previous work showed a good correlation between the VR (which also depends on the VCO2) and the measured dead space by volumetric capnography 7 .
The results of this study imply that surrogate markers of ventilation are not independently associated with mortality and the observed effect sizes were remarkably similar to those observed in non-COVID-19 related ARDS with similar methodology. This contrasts several reports that have hypothesized that profound endothelial injury and coagulopathy may be central mediators of lung injury in COVID-19 33 . We acknowledge that we did not measure these processes in this study, but we do provide evidence that COVID-19 related ARDS appears to be similar to non-COVID ARDS with respect to Vd/Vt. This implies that dead space and its estimates should be understood as a readily available marker of ARDS Availability of data and supporting materials section: Morales-Quinteros, Bos and Serpa Neto had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis; the members of the Steering Committee for PRoVENT-COVID Collaborative Group vouch for the accuracy and completeness of the data and for the fidelity of the study to the protocol. LDB and ASN carried out the supervision the manuscript.
MB, AT participated in the coordination of the study.