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Clinical Infection & Immunity

Original Article

Volume 6, Number 1, March 2021, pages 6-10

Prognostic Utility of Estimated Pulmonary Dead Space to Tidal Volume Fraction in Patients With COVID-19 Respiratory Failure Treated With Invasive Mechanical Ventilation

The coronavirus disease 2019 (COVID-19) pandemic has afflicted greater than 20 million individuals in the United States with mortality in excess of 350,000. The majority of deaths are directly resultant from severe acute respiratory distress syndrome (ARDS). The lung disease associated with COVID-19 has been labelled as not “typical “ARDS [1], although other investigators have not identified differences in respiratory system mechanics between COVID-19 and non-COVID-19 causes of ARDS [2]. Despite this atypical ARDS pattern, standard ARDS-directed lung treatments have been uniformly applied including neuromuscular paralysis, prone positioning and high levels of both positive end-expiratory airway pressure (PEEP) and fractional inspired concentrations of oxygen (FiO₂). Once intubated and invasive mechanical ventilation is required, mortality related to COVID-19 lung disease remains high with estimates based upon method of reporting and data analyses generating the range of possible mortality between 25% and 95% [3]. Currently multiple investigations are in process to potentially identify biomarkers, clinical parameters and laboratory tests that may be predictive of survival or death [4]. Acknowledging the primary function of the lung is gas exchange and the multiple studies identifying measurements of pulmonary dead space fraction (Vd/Vt) as mortality predictors in ARDS [5], we have previously published peer-reviewed articles deploying a mathematically derived prediction equation using clinically available information to estimate Vd/Vt (Vd/Vt = 0.320 + 0.0106 (PaCO₂ - ETCO₂) + (0.003 × RR) + (0.0015 × age)). Our findings have shown such a calculation is predictive of clinical outcome, noting Vd/Vt values in excess of 65% uncorrected by therapy represent high associated mortality [6, 7]. To date, there exists only a single publication reporting measurements of Vd/Vt in patients with COVID-19 respiratory failure treated with invasive mechanical ventilation (mean Vd/Vt = 0.45) [8]. This study reported an overall mortality of 16.7% but was designed to describe the respiratory pathophysiology of the study reported patients and did not provide statistical comparisons between clinical outcomes and the reported lung mechanics and gas exchange measurements [8]. The current study was designed to expand our previous investigations using calculations of Vd/Vt via our prediction equation as applicable for severely ill intubated and mechanically ventilated patients with COVID-19 lung disease.

This study was reviewed by the Institutional Review Board (IRB) and the Human Subjects Protection Office (HSPO) of the Penn State Health Milton S. Hershey Medical Center and was granted “exemption determination”. Eligible patients 18 years and older were identified from the patient log of admissions with a diagnosis of COVID-19-related respiratory failure requiring endotracheal intubation and invasive mechanical ventilatory support. All patients had confirmed positive COVID-19 identification on nasal-pharyngeal swab and/or tracheal aspirate by RT-PCR analyses and available arterial blood gas (ABG) measurements for arterial partial pressure of carbon dioxide (PaCO₂) during initial acute presentation. Patients were retrospectively identified over the inclusive time period of January 1, 2020 through October 25, 2020. Calculations of Vd/Vt using the validated prediction equation were obtained using all available ABG analyses with specific measurement of PaCO₂ in mm Hg and using the electronic medical record (EMR) recordings of both expired/end-tidal carbon dioxide (ETCO₂) converted to mm Hg and respiratory rate (RR) per minute within the closest time frame to ABG measurement but not exceeding 30 min. Invasive mechanical ventilation study day 1 was set as the date of first endotracheal intubation. Data are reported as mean (standard deviation). Study-related clinical outcome patient groups were identified as: 1) Survivors; 2) Non-survivors resultant from withdrawal of care; and 3) Non-survivors with lung-related death.

Study data were collected and managed using Research Electronic Data Capture (REDCap) electronic data capture tools hosted at Penn State Health Milton S. Hershey Medical Center and Penn State College of Medicine [9, 10]. REDCap is a secure, web-based software platform designed to support data capture for research studies, providing: 1) An intuitive interface for validated data capture; 2) Audit trails for tracking data manipulation and export procedures; 3) Automated export procedures for seamless data downloads to common statistical packages; and 4) Procedures for data integration and interoperability with external sources.

All variables were summarized prior to analysis to check their distribution and missing data. The distributions of continuous variables were assessed for normality using normal probability plots and the Anderson-Darling test. An analysis of variance was used to make comparisons of the mean Vd/Vt calculations made on the first/initial and final/last day between the three study groups. The last day ranged from 1 to 42 days. The P-values and confidence limits for the group comparisons were adjusted using Tukey’s method of adjustment for multiple comparisons to maintain an overall type I error rate of 0.05. A secondary analysis was applied using all of the Vd/Vt calculations over time in a repeated measures means model. Since the time points were not the same for each patient, we categorized them into four groups based on quartiles. The model included the study group, the time quartile and the interaction between the two variables. The group means were compared within each time quartile and were plotted over the time as well. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).

During the time period from January 1, 2020 through October 25, 2020, 20 study eligible patients were identified at the Penn State Health Milton S. Hershey Medical Center, Hershey, PA (ineligible patients were excluded based upon absence of ABG data or confirmatory RT-PCR). Patient specific characteristics stratified per clinical outcome are detailed in Table 1. There was a statistically significant difference in comparison of the age distributions between clinical outcome groups of survivors and non-survivors with lung-related death (59 (12) years vs. 74 (11) years, respectively; P = 0.04). Overall mortality in this series due directly to COVID-19 lung disease was 45%. Survivors had fewer days of mechanical ventilation than non-survivors which was most evident in comparison of survivors to non-survivors with death primarily related to progressive lung disease (9.1 (7.6) days vs. 23.1 (11.7) days, respectively; P = 0.021). The numbers of Vd/Vt calculations in clinical outcome groups were 34 in survivors, 24 in non-survivors with withdrawal of care and 253 in non-survivors with lung-related death. Comparison of Vd/Vt data for the most relevant clinical outcome study groups (survivors versus non-survivors related to lung disease progression) demonstrated: 1) No observed differences in first/initial Vd/Vt calculations (0.58 (0.06) vs. 0.62 (0.06), respectively; P = 0.311) and 2) Marked and statistically significant differences in final/last Vd/Vt calculations (0.52 (0.04) vs. 0.83 (0.07), respectively; P < 0.001) (Table 2). Review of longitudinal data stratified by time quartile demonstrated the temporal worsening of lung disease severity as assessed by Vd/Vt calculations over time for the non-survivors with lung-related death clinical outcome group (Fig. 1).

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Table 1. Patient Characteristics Stratified per Clinical Outcome

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Table 2. Relationship of First/Initial and Final/Last Vd/Vt Calculation to Clinical Outcome

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Figure 1. Mean Vd/Vt calculation over time by clinical outcome. Vd/Vt: pulmonary dead space fraction; LD: lung-related death; WC: withdrawal of care.

Measurements of Vd/Vt have established validity as an objective quantifiable parameter of lung ventilation efficiency and also as having prognostic significance in a variety of acute lung diseases [5, 7, 11]. However, technical complexities have limited the routine application of Vd/Vt measurements either per Bohr equation or Enghoff modification of the Bohr equation. Additional surrogates to approximate Vd/Vt have been developed to overcome practical restrictions including prediction equations using clinically available data and a mathematically derived unit-less variable termed the ventilatory ratio (VR) referenced to ideal PaCO₂ equal to 37.5 mm Hg [6, 7, 11]. To date, no methodology has been established as routine standard of care.

Variability in the number of Vd/Vt calculations across clinical outcome groups is expected given the known relatively rapid recovery of survivors in contrast to the protracted and long durations of progressively worsening lung destruction in non-survivor patients. Acknowledging both the inclusion of age (years) as a variable in the prediction equation calculation of Vd/Vt and the statistical significance between the age distributions for survivors and non-survivors with lung-related death (P = 0.04), there still exists no expectation of age influencing the association of Vd/Vt calculations and clinical outcomes given: 1) Age as being only one of four variables in the equation; and 2) The robust difference in mean final/last Vd/Vt calculations between groups of 31%. In addition, previous derivation and validation of Vd/Vt prediction equation demonstrated that gender, height, weight, tidal volume, minute ventilation, body temperature, arterial partial pressure of oxygen (PaO₂) and sequential organ failure assessment (SOFA) score did not improve predictive value of the equation [6].

Potential limitations to this study include the retrospective design of data accrual based upon review of the EMR and the non-simultaneous data analyses for variables PaCO₂, ETCO₂ and RR. The large number of Vd/Vt data point calculations and the consistency of Vd/Vt measurements over time would be expected to reduce the probability of this latter potential limitation as artifactually affecting data results and study outcomes. In addition, these same study limitations have also been acknowledged in other peer-reviewed publications of similar design [12].

In agreement with results from our previous publication in patients with non-COVID-19 ARDS, the results of this retrospective study again confirm the validity of the Vd/Vt prediction equation using clinically available data to predict mortality in patients with COVID-19 respiratory failure treated with invasive mechanical ventilation [7]. As communicated by multiple publications, the wide diversity of lung mechanics and gas exchange parameters as reflected by lung elastance, total respiratory system compliance and PaO₂/FiO₂ ratio, for patients with non-COVID-19 ARDS indeed mirror the diversity of lung mechanics and gas exchange abnormalities reported in patients with COVID-19 ARDS [2, 13, 14]. Such heterogeneity would be expected for any clinical entity characterized as a “syndrome”. Similarly as previously reported in patients with non-COVID-19 ARDS and as reported in this study, estimations for prediction calculations of Vd/Vt remain a validated predictor of mortality for Vd/Vt values in excess of 70% which remain uncorrected by treatments and therapies [5, 7]. In addition, the progressive worsening of lung disease severity in non-survivor patients reflects a sub-population of COVID-19 patients with lung disease unresponsive to current standard of care therapies and interventions.

Acknowledgments

None to declare.

Financial Disclosure

None to declare.

Conflict of Interest

None to declare.

Informed Consent

Not applicable.

Author Contributions

RLV: study design, data accrual, Vd/Vt calculations, data analysis, preparation of manuscript, approval and submission of manuscript. DCF: derivation of Vd/Vt equation, data analysis, manuscript review and editing. PAV-M: data entry, data analysis and manuscript review. EBL: data analysis and manuscript review.

Data Availability

The authors declare that data supporting the findings of this study are available within the article.

Abbreviations

COVID-19: coronavirus disease 2019; ARDS: acute respiratory distress syndrome; PEEP: positive end-expiratory airway pressure; FiO₂: fractional inspired concentrations of oxygen; Vd/Vt: pulmonary dead space fraction; IRB: Institutional Review Board; HSPO: Human Subjects Protection Office; ABG: arterial blood gas; PaCO₂: arterial partial pressure of carbon dioxide; ETCO₂: expired/end-tidal carbon dioxide; EMR: electronic medical record; RR: respiratory rate; REDCap: Research Electronic Data Capture; VR: ventilatory ratio; SD: standard deviation; PaO₂: arterial partial pressure of oxygen; ECMO: extracorporeal membrane oxygenation; LD: lung-related death; WC: withdrawal of care; SOFA: sequential organ failure assessment

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