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Standardizing PaO2 for PaCO2 in P/F ratio predicts in-hospital mortality in acute respiratory failure due to Covid-19: A pilot prospective study

  • Irene Prediletto
    Affiliations
    IRCCS Azienda Ospedaliero Universitaria di Bologna, University Hospital Sant'Orsola-Malpighi - Respiratory and Critical Care Unit - Bologna, Italy

    Alma Mater Studiorum University of Bologna, Department of Clinical, Integrated and Experimental Medicine (DIMES), Bologna, Italy
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  • Letizia D'Antoni
    Affiliations
    Department of Public Health and Infectious Disease, Sapienza University of Rome – Italy. Pulmonology, Respiratory and Critical Care Unit, Policlinico Umberto I Hospital – Rome, Italy
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  • Paolo Carbonara
    Affiliations
    IRCCS Azienda Ospedaliero Universitaria di Bologna, University Hospital Sant'Orsola-Malpighi - Respiratory and Critical Care Unit - Bologna, Italy

    Alma Mater Studiorum University of Bologna, Department of Clinical, Integrated and Experimental Medicine (DIMES), Bologna, Italy
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  • Federico Daniele
    Affiliations
    IRCCS Azienda Ospedaliero Universitaria di Bologna, University Hospital Sant'Orsola-Malpighi - Respiratory and Critical Care Unit - Bologna, Italy

    Alma Mater Studiorum University of Bologna, Department of Clinical, Integrated and Experimental Medicine (DIMES), Bologna, Italy
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  • Roberto Dongilli
    Affiliations
    Division of Respiratory Diseases with Intermediate Respiratory Intensive Care Units, Central Hospital of Bolzano, Bolzano, Italy
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  • Roberto Flore
    Affiliations
    Department of Public Health and Infectious Disease, Sapienza University of Rome – Italy. Pulmonology, Respiratory and Critical Care Unit, Policlinico Umberto I Hospital – Rome, Italy
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  • Angela Maria Grazia Pacilli
    Affiliations
    IRCCS Azienda Ospedaliero Universitaria di Bologna, University Hospital Sant'Orsola-Malpighi - Respiratory and Critical Care Unit - Bologna, Italy

    Alma Mater Studiorum University of Bologna, Department of Clinical, Integrated and Experimental Medicine (DIMES), Bologna, Italy
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  • Lara Pisani
    Affiliations
    IRCCS Azienda Ospedaliero Universitaria di Bologna, University Hospital Sant'Orsola-Malpighi - Respiratory and Critical Care Unit - Bologna, Italy

    Alma Mater Studiorum University of Bologna, Department of Clinical, Integrated and Experimental Medicine (DIMES), Bologna, Italy
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  • Corina Tomsa
    Affiliations
    Department of Public Health and Infectious Disease, Sapienza University of Rome – Italy. Pulmonology, Respiratory and Critical Care Unit, Policlinico Umberto I Hospital – Rome, Italy
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  • María Laura Vega
    Affiliations
    IRCCS Azienda Ospedaliero Universitaria di Bologna, University Hospital Sant'Orsola-Malpighi - Respiratory and Critical Care Unit - Bologna, Italy
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  • Vito Marco Ranieri
    Affiliations
    IRCCS Azienda Ospedaliero Universitaria di Bologna, University Hospital Sant'Orsola-Malpighi - Anesthesia and Intensive Care Medicine – Bologna, Italy

    Alma Mater Studiorum University of Bologna, Department of Medical and Surgical Sciences, Bologna, Italy
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  • Stefano Nava
    Correspondence
    Corresponding author at: Via Massarenti 9, 40138 Bologna, Italy.
    Affiliations
    IRCCS Azienda Ospedaliero Universitaria di Bologna, University Hospital Sant'Orsola-Malpighi - Respiratory and Critical Care Unit - Bologna, Italy

    Alma Mater Studiorum University of Bologna, Department of Clinical, Integrated and Experimental Medicine (DIMES), Bologna, Italy
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  • Paolo Palange
    Affiliations
    Department of Public Health and Infectious Disease, Sapienza University of Rome – Italy. Pulmonology, Respiratory and Critical Care Unit, Policlinico Umberto I Hospital – Rome, Italy
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      Abstract

      Introduction

      Up to fifteen percent of patients with novel pandemic coronavirus disease (Covid-19) have acute respiratory failure (ARF). Ratio between arterial partial pressure of oxygen (PaO2) and fraction of inspired oxygen (FiO2), P/F, is currently used as a marker of ARF severity in Covid-19. P/F does not reflect the respiratory efforts made by patients to maintain arterial blood oxygenation, such as tachypnea and hyperpnea, leading to hypocapnia. Standard PaO2, the value of PaO2 adjusted for arterial partial pressure of carbon dioxide (PaCO2) of the subject, better reflects the pathophysiology of hypoxemic ARF. We hypothesized that the ratio between standard PaO2 over FiO2 (STP/F) better predicts Covid-19 ARF severity compared to P/F.

      Methods

      Aim of this pilot prospectic observational study was to observe differences between STP/F and P/F in predicting outcome failure, defined as need of invasive mechanical ventilation and/or deaths in Covid-19 ARF. Accuracy was calculated using Receiver Operating Characteristics (ROC) analysis and areas under the ROC curve (AUROC) were compared.

      Results

      349 consecutive subjects admitted to our respiratory wards due to Covid-19 ARF were enrolled. STP/F was accurate to predict mortality and superior to P/F with, respectively, AUROC 0.710 versus 0.688, p = 0.012.Both STP/F and PF were accurate to predict outcome failure (AUROC respectively of 0.747 and 0.742, p = 0.590).

      Discussion

      This is the first study assessing the role of STP/F in describing severity of ARF in Covid-19. According to results, STP/F is accurate and superior to P/F in predicting in-hospital mortality.

      Keywords

      1. Introduction

      Novel coronavirus disease SARS-CoV-2 emerged in December 2019, rapidly became pandemic and it was the cause of the so-called severe acute respiratory coronavirus disease (Covid-19). So far, more than 127 million cases were confirmed worldwide, with more than 2.7 million deaths [

      World health organization (WHO) Coronavirus Disease (COVID-19); https://covid19.who.int. Date last updated: March 31 2021. Date last accessed: March 31 2021.

      ]. Covid-19 typically affects respiratory tracts, leading to pneumonia and acute respiratory failure (ARF). [
      • Stawicki S.P.
      • Jeanmonod R.
      • Miller A.C.
      • Paladino L.
      • Gaieski D.F.
      • Yaffee A.Q.
      • et al.
      The 2019-2020 Novel Coronavirus (Severe Acute Respiratory Syndrome Coronavirus 2) Pandemic: a Joint American College of Academic International Medicine-World Academic Council of Emergency Medicine Multidisciplinary COVID-19 Working Group Consensus Paper.
      ] Morbidity and mortality related to Covid-19 are due to complications, especially acute respiratory distress syndrome (ARDS), which occur in up to 15% of cases. [
      • Grasselli G.
      • Tonetti T.
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      • Langer T.
      • Girardis M.
      • Bellani G.
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      Pathophysiology of COVID-19-associated acute respiratory distress syndrome: a multicentre prospective observational study.
      ,
      • Li L.Q.
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      • Wang Z.P.
      • Liang Y.
      • Huang T.B.
      • et al.
      COVID-19 patients' clinical characteristics, discharge rate, and fatality rate of meta-analysis.
      ].
      The ratio of arterial (PaO2) to inspired (FiO2) partial pressure of oxygen (P/F ratio), is currently utilized to assess the severity of respiratory failure in patients with ARDS [
      • Ranieri V.M.
      • Rubenfeld G.D.
      • Thompson B.T.
      • Ferguson N.D.
      • Caldwell E.
      • Fan E.
      • et al.
      ARDS Definition Task Force
      Acute respiratory distress syndrome: the Berlin Definition.
      ] and correlates to mortality rate [
      • Goligher E.C.
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      • Pinto R.
      • Fan E.
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      Oxygenation response to positive end-expiratory pressure predicts mortality in acute respiratory distress syndrome. A secondary analysis of the LOVS and ExPress trials.
      ,
      • Sakr Y.
      • François B.
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      • Kotfis K.
      • Jaschinski U.
      • Estella A.
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      SOAP and ICON Investigators. Temporal changes in the epidemiology, management, and outcome from acute respiratory distress syndrome in European intensive care units: a comparison of two large cohorts.
      ,
      • Villar J.
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      • del Campo R.
      • Andaluz-Ojeda D.
      • Díaz-Domínguez F.J.
      • Muriel A.
      • et al.
      Spanish initiative for epidemiology, stratification & therapies for ARDS (SIESTA) network. Assessment of PaO2/FiO2 for stratification of patients with moderate and severe acute respiratory distress syndrome.
      ]. P/F ratio has been recently proposed as a prognostic marker in Covid-19 [

      World Health Organization (2021). COVID-19 clinical management: living guidance. 25 January 2021. World Health Organization. https://apps.who.int/iris/handle/10665/338882. License: CC BY-NC-SA 3.0 IGO.

      ,
      • Cortinovis M.
      • Perico N.
      • Remuzzi G.
      Long-term follow-up of recovered patients with COVID-19.
      ]. However, P/F ratio may be poorly representative of the severity of hypoxemia in patients with ARDS [
      • Aboab J.
      • Louis B.
      • Jonson B.
      • Brochard L.
      Relation between PaO2/FIO2 ratio and FIO2: a mathematical description.
      ,
      • Gowda M.S.
      • Klocke R.A.
      Variability of indices of hypoxemia in adult respiratory distress syndrome.
      ] and does not consider the level of respiratory muscles effort and hyperventilation of hypoxemic patients and do not discriminate patients according to their degree of hypocapnia [
      • Winck J.C.
      • Scala R.
      Non-invasive respiratory support paths in hospitalized patients with COVID-19: proposal of an algorithm.
      ]. In addition, considerable evidence supports that alteration of ventilation perfusion rate assessed as pulmonary dead space fraction [
      • Nuckton T.J.
      • Alonso J.A.
      • Kallet R.H.
      • Daniel B.M.
      • Pittet J.F.
      • Eisner M.D.
      • et al.
      Pulmonary dead-space fraction as a risk factor for death in the acute respiratory distress syndrome.
      ] or ventilatory ratio [
      • Grasselli G.
      • Tonetti T.
      • Protti A.
      • Langer T.
      • Girardis M.
      • Bellani G.
      • et al.
      Pathophysiology of COVID-19-associated acute respiratory distress syndrome: a multicentre prospective observational study.
      ] are associated with mortality in ARDS [
      • Lucangelo U.
      • Bernabè F.
      • Vatua S.
      • Degrassi G.
      • Villagrà A.
      • Fernandez R.
      • et al.
      Prognostic value of different dead space indices in mechanically ventilated patients with acute lung injury and ARDS.
      ] and severity of COVID-induced ARDS [
      • Grasselli G.
      • Tonetti T.
      • Protti A.
      • Langer T.
      • Girardis M.
      • Bellani G.
      • et al.
      Pathophysiology of COVID-19-associated acute respiratory distress syndrome: a multicentre prospective observational study.
      ].
      In a seminal paper, Mays emphasized the axiom that PaO2 and arterial carbon dioxide tensions (PaCO2) are inversely related [
      • Rahn H.
      • Fenn W.O.
      A graphical analysis of the respiratory gas exchange.
      ] and suggested that estimation of the severity of ventilation/perfusion mismatch may be optimized standardizing PaO2 for PaCO2 by using the formula: standardized PaO2 (STPaO2) = 1.66*PaCO2 + PaO2 - 66.4 [
      • Mays E.E.
      An arterial blood gas diagram for clinical use.
      ]. In the current pilot observational study we evaluated if substituting PaO2 with STPaO2 in calculating P/F ratio may better stratify patients according to outcome failure, defined as needs of invasive mechanical ventilation (IMV) and/or death in patients with COVID-19.

      2. Material and methods

      The Institutional Ethical Committee approved the study protocol and patients had to sign written informed consent before enrollment. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline [
      • Von Elm E.
      • Altman D.G.
      • Egger M.
      • Pocock S.J.
      • Gøtzsche P.C.
      • Vandenbroucke J.P.
      STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.
      ].
      Patients were prospectively recruited in the period October 31th 2020-January 31th 2021 after admission to pulmonology wards of the following hospitals: IRCCS S.Orsola-Malpighi (Alma Mater University of Bologna); Policlinico Umberto I, (Sapienza University of Rome) and Central Hospital of Bolzano. Inclusion criteria were laboratory-confirmed SARS-CoV-2 infection (positive result of real-time reverse transcriptase-polymerase chain reaction assay from either nasal or pharyngeal swabs, or lower respiratory tract aspirates); presence of consolidation and/or ground glass opacities at Chest X-ray and/or at computed tomography of lungs [
      • Martínez Chamorro E.
      • Díez Tascón A.
      • Ibáñez Sanz L.
      • Ossaba Vélez S.
      • Borruel Nacenta S.
      Radiologic diagnosis of patients with COVID-19.
      ] and presence of acute respiratory failure. Acute respiratory failure was identified when pO2 was <60 mmHg at FiO2 = 21%. [

      British medical journal (BMJ) Best Practice - Acute respiratory failure. https://bestpractice.bmj.com/topics/en-us/853. Date last reviewed: 21 Apr 2021. Date last updated: 13 May 2020. Date last accessed: 22 May 2021.

      ] Exclusion criteria were needs of endotracheal intubation and invasive mechanical ventilation before Pulmonology wards admission and history of chronic respiratory failure. For each study subject we collected clinical history, arterial blood gas analysis (ABGs) data (PaO2, PaCO2, pH, HCO3, FiO2) at hospital admission and at the time of admission to the Pulmonology Unit, respiratory supports applied throughout hospital stay and date of death or recovery from respiratory failure. PaO2 was standardized for PaCO2 by using the formula: standardized PaO2 (STPaO2) = 1.66*PaCO2 + PaO2 - 66.4 [
      • Mays E.E.
      An arterial blood gas diagram for clinical use.
      ]. P/F, STPaO2 and STP/F were calculated for each subject. For STP/F and P/F, we use data from ABG collected on the first day of admission in Pulmonology Unit with the study subject that had inspired oxygen at a fixed FiO2 for at least 10 minutes [
      • Cakar N.
      • Tuŏrul M.
      • Demirarslan A.
      • Nahum A.
      • Adams A.
      • Akýncý O.
      • et al.
      Time required for partial pressure of arterial oxygen equilibration during mechanical ventilation after a step change in fractional inspired oxygen concentration.
      ,
      • Weinreich U.M.
      • Thomsen L.P.
      • Hansen A.
      • Kjærgaard S.
      • Wagner P.D.
      • Rees S.E.
      Time to steady state after changes in FIO(2) in patients with COPD.
      ,
      • Sasse S.A.
      • Jaffe M.B.
      • Chen P.A.
      • Voelker K.G.
      • Mahutte C.K.
      Arterial oxygenation time after an FIO2 increase in mechanically ventilated patients.
      ,
      • Utada K.
      • Matayoshi Y.
      • Fujita F.
      • Nakamura K.
      • Matsuda N.
      • et al.
      Equilibration period for PaO2 following alteration of FIO2 in mechanically ventilated patients.
      ,
      • Chiumello D.
      • Coppola S.
      • Froio S.
      • Mietto C.
      • Brazzi L.
      • et al.
      Time to reach a new steady state after changes of positive end expiratory pressure.
      ]. Occurrence of ARF, was identified when PaO2 was < 60 mmHg with FiO2 = 0.21. Outcome failure was defined as needs of invasive mechanical ventilation (IMV) and/or death. We also evaluated the relationship between duration of ARF and P/F and STP/F. Recovery from ARF occurred before pulmonology ward discharge of the study subjects. Duration of ARF was expressed in days from emergency room (ER) admission to the first day of recovery from ARF (subjects died during hospital stay were censored). End of follow-up for each study subject was fixed hospital stay discharge (for survivors) or date of death.
      Continuous variables are presented as mean value and standard deviation (±SD), median, minimum and maximum values. Categorical ones are expressed by frequencies and percentages. To define accuracy of PF and STPF to predict study outcomes we used the receiver-operating characteristic (ROC) curve and compared the area under curve (AUROC) deriving from the use of conventional P/F vs. STP/F ratio. Comparisons between AUROC of PF and STPF for the study outcomes were made by De Long's test [
      • DeLong E.R.
      • DeLong D.M.
      • Clarke-Pearson D.L.
      Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.
      ] and Best threshold for the ROC analysis was calculated using the Youden index point [
      • Perkins N.J.
      • Schisterman E.F.
      The inconsistency of "optimal" cutpoints obtained using two criteria based on the receiver operating characteristic curve.
      ]. Categorical variables were analyzed using one-way analysis of variance (ANOVA) or χ2-square test, when appropriate. Associations between parameters were calculated using Spearman correlation test. P ≤  0.05 was considered statistically significant. Analysis was performed using IBM SPSS Statistics version 21. Using Buderer's formula, we empirically calculated a minimum sample size of 284 subjects to reach 70% of sensitivity and 70% of specificity [
      • Buderer N.M.
      Statistical methodology: I. Incorporating the prevalence of the disease into the sample size calculation for sensitivity and specificity.
      ]. In previous studies the average prevalence of outcome failure and mortality, respectively, were 43,7% and 19,6%. [[
      • Bonnet N.
      • Martin O.
      • Boubaya M.
      • Levy V.
      • Ebstein N.
      • Karoubi P.
      • et al.
      High flow nasal oxygen therapy to avoid invasive mechanical ventilation in SARS-CoV-2 pneumonia: a retrospective study.
      ,
      • Chalmers J.D.
      • Crichton M.L.
      • Goeminne P.C.
      • Cao B.
      • Humbert M.
      • Shteinberg M.
      • et al.
      Management of hospitalised adults with coronavirus disease-19 (COVID-19): A European Respiratory Society living guideline.
      ,
      • Gupta A.
      • Nayan N.
      • Nair R.
      • Kumar K.
      • Joshi A.
      • Sharma S.
      • et al.
      Diabetes mellitus and hypertension increase risk of death in novel corona virus patients irrespective of age: a prospective observational study of Co-morbidities and COVID-19 from India.
      ,
      • Franco C.
      • Facciolongo N.
      • Tonelli R.
      • Dongilli R.
      • Vianello A.
      • Pisani L.
      • et al.
      Feasibility and clinical impact of out-of-ICU noninvasive respiratory support in patients with COVID-19-related pneumonia.
      ],].

      3. Results

      We enrolled 349 consecutive patients. Characteristics of the study population and outcomes are described in Tables 1A and 1B. Outcome failure was observed in 113 patients (32,4%) and 58 patients died (16.6%). Median survival was 18.5 days (range 4-65, mean 21.0 ± 13.4) and 13.0 days (range 0-65, mean 16.6 ± 13.3) calculated, respectively, from symptoms start to date of death and from ER admission to date of death. All deaths were caused by acute respiratory failure due to Covid-19. Median duration of ARF was 23 days (range 2-58, mean 21.6 ± 9.9).
      Table 1A – Characteristics of the study population and arterial blood gas analysis data at the time of Emergency Room (ER) admission.
      nTot.% of nMeanDS
      Age34969,2013,40
      Sex349
      Male23266,5%
      Female11733,5%
      Smoking277
      Never23584,8%
      Former/current4215,2%
      Comorbidities349
      Systemic arterial hypertension or Chronic Atrial fibrillation23968,5%
      Diabetes mellitus6919,8%
      Cerebrovascular accidents and/or ischemic heart disease5816,6%
      Chronic obstructive pulmonary disease (COPD) or asthma4512,9%
      Chronic kidney failure3510,0%
      Active neoplasm (or diagnosis <5 years)318,9%
      Obesity298,3%
      Immunodepression and/or autoimmune disease216,0%
      Venous thromboembolism72,0%
      Obstructive sleep apnea syndrome (OSAS)72,0%
      Interstitial lung disease20,6%
      Miscellaneous13939,8%
      ≥2 comorbidities34917249,3%
      Symptoms349
      Fever29183,4%
      Dyspnea22464,2%
      Cough15945,6%
      Dysgeusia/ageusia329,2%
      Anosmia3911,2%
      Diarrhea5214,1%
      Abdominal pain267,1%
      Headache369,8%
      Fatigue Mental confusion/delirium132 2935,9% 8,3%
      ER admission
      FiO23490,240,11
      FiO2 > 0,21349257,2%
      SpO226091,85,9
      ABG/PaO2 and P/F available30888,3%
      ABG/PaO2, PaCO2 and P/F available30587,4%
      pH7,470,05
      PaO2 (mmHg)63,816,4
      STPaO2 (mmHg)50,618,5
      PaCO2 (mmHg)32,15,0
      HCO3- standard (mmol/L)24,03,2
      PF286,779,3
      STP/F225,880,5
      PF<2003083110,1%
      STP/F <20030511738,4%
      Days from symptoms start to ER admission6,12,0
      Days from symptoms start to Pulmonology Unit admission9,67,7
      Days from ER admission to Pulmonology Unit admission3,55,7
      Table 1. B – Arterial blood gas analysis data at the time of Pulmonology Unit admission and outcomes of the study population.
      nTot.% of nMeanDS
      Pulmonology Unit admission
      Previous hospital setting349
      ER20157,6%
      General Medicine Units7020,1%
      Infectious diseases Unit4412,6%
      Other units349,7%
      Respiratory treatment/support applied349
      Standard oxygen therapy20257,8%
      High flow nasal oxygen10630,4%
      Continuous positive airway pressure318,9%
      Non invasive ventilation72,0%
      Thoracic high Resolution Computed Tomography/ pattern333
      Ground glass opacities14643,8%
      Consolidation ± Ground glass opacities18756,2%
      FC (bpm)33780,113,4
      FR (breaths/minute)32222,35,4
      FiO23490,510,20
      SpO2 (%)34495,82,7
      ABG available349
      ph7,440,40
      PaO2 (mmHg)85,725,4
      STPaO2 (mmHg)78,326,8
      PaCO2 (mmHg)35,55,0
      PaCO2 ≤ 40 mmhg30988,5%
      HCO3 (mmol/L)25,63,4
      P/F349189,461,9
      STP/F349172,480,1
      P/F<20034919656,2%
      STP/F <20034924971,3%
      Outcomes
      Outcome failure34911332,4%
      Deaths3495816,6%
      Need for Invasive mechanical ventilation (IMV)3497722,1%
      Need for respiratory treatment step up Survival, from symptoms start to date of death (days) Survival, from ER admission to date of death (days)349 58 5817249,3%21,0 16,813.4  13,3
      Days from ER Admission to recovery from ARF29121,69,9
      Considering outcome failure, AUROC was 0.747; (95% CI 0.693-0.801) for STP/F and 0.742 for P/F (95% CI 0.687-0.797), with an advantage for STP/F comparing to P/F, but not statistically significant (p = 0.59), as shown on Fig. 1A. Analyzing only in-hospital mortality as outcome (Fig. 1B), only AUROC of STP/F showed enough accuracy comparing to AUROC of PF (0.710; 95% CI 0.638-0.782 vs. 0.688; 95% CI 0.650-0.846); this difference was statistically significant, p = 0.0189.
      Fig 1
      Fig. 1Predictive receiver-operating characteristic (ROC) curve of the study population by outcome failure (A) and deaths (B) for STP/F and P/F.
      PaO2, STPaO2 and PaCO2 showed not enough accuracy according to the ROC curve both by outcome failure and deaths (AUC<0.7). By outcome failure, PaO2, STPaO2 and PaCO2 showed AUC of, respectively, 0.533 (95% CI 0.491-0.616), 0.582 (95% CI 0.520-0.645), and 0.574 (95% CI 0.509-0.639). By deaths, AUROC of PaO2 was 0.599 (95% CI 0.520-0.677), AUC for STPaO2was 0.623 (95%CI 0.544-0.701) and AUC of PaCO2 was 0.617 (95% CI 0.532-0.702).
      According to ROC analysis, the best cut-off for STP/F was, respectively, 170 for outcome failure and 125 for deaths. The best cut-off for P/F was, respectively, 180 for outcome failure and, even if AUROC was not enough accurate, 150 for deaths. Sensibility, specificity, positive predictive value and negative predictive value for STP/F and P/F are shown on Table 2. There were 146 subjects with STP/F ≤ 170 and 203 with STPF > 170. Among subjects with sP/F ≤ 170, outcome failure rate was 46,8% and morality rate 23.2%. In comparison outcome failure rate and mortality rate were, respectively, 12.3% and 7.5% for the subgroup with STP/F > 170. These differences were statistically significant (p = 0.000). There were 115 subjects with STP/F ≤ 125 and 234 with P/F > 125. Among those with STP/F ≤ 125, outcome failure was 59.1% and mortality rate 33%. In comparison outcome failure rate and mortality rate were, respectively, 19,2% and 8,8% for the subgroup with STP/F > 125. These differences were statistically significant (p = 0.000).
      Table 2Predictive power of standard PF and PF in the study population according to outcomes (SE = sensibility; SP = specificity; PPV = positive predictive value; NPV = negative predictive value).
      AUROCCut-offSESPPPVNPV
      Outcome Failure (IMV or death)
      standard P/F PF0.747170 *54%87%88,00%47,00%
      0.74712581%41%81,00%60,00%
      0.742180 *59%83%85%48,00%
      0.74215076%40%80%54,00%
      Deaths
      standard P/F0.71017047%19%93%23%
      0.710125 *75%66%92%33%
      P/F0.68818053%26%91,00%24,00%
      0.688150 *70%66%91%30%
      * best cut-off
      Stratifying by deaths (Table 3) mean value of both P/F and STP/F showed statistical significant differences between groups: patient died due to Covid-19 ARF had a mean P/F 149.9 ± 67.5, mean STP/F 129.8 ± 58.4 versus, respectively, 197.3 ± 83.3 and 181.0 ± 81.7 of survivors subgroup (p = 0.000 and p = 0.000). No differences between groups were observed according to PaO2, while the subgroup of patients who died showed lower values of PaCO2 and STPaO2 compared to the survivor subgroup (p < 0.05 - Table 3). Similar results were observed by outcome failure (need of IMV and/or deaths) with the exception of PaCO2 (Table 3). Duration of ARF (Table 4) was inversely associated with P/F and STP/F (p = 0.000 and p =  0.000), but not with paO2, STPaO2 and paCO2. Age and Respiratory Rate at the time of admission were positively related with duration of ARF (p < 0.05).
      Table 3Differences in terms of PaO2, PaCO2, standard PaO2 (STPaO2), P/F and STP/F by outcome failure and deaths in the study population (ANOVA).
      nMeanSDMinMaxp value
      Outcome failure
      PaO2 (mmHg)no23687,326,350240
      yes11382,623,151200
      tot34985,725,450240.105
      PaCO2 (mmHg)no23635,64,92061
      yes11334,85,02355
      tot34935,55,02061.057
      STPaO2 (mmHg)no23680,427,830225
      yes11373,924,231183
      tot34978,326,830225.034
      P/Fno236209,184,360629
      yes113148,461,960357
      tot349189,482,760629.000
      STP/Fno236192,283,141623
      yes113131,155,749340
      tot349172,480,141623.000
      Deaths
      PaO2 (mmHg)no29186,725,450,0240,0
      yes5880,124,851,0200,0
      tot34985,725,450,0240,00.112
      PaCO2 (mmHg)no29135,84,920,061,0
      yes5834,35,326,055,0
      tot34935,55,020,061,0.037
      STPaO2 (mmHg)no29179,626,930,0225,0
      yes5871,425,431,0183,0
      tot34978,326,830,0225,0.032
      P/Fno291197,383,360,0629,0
      yes58149,967,560,0357,0
      tot349189,482,760,0629,0.000
      STP/Fno291181,081,741,0623,0
      yes58129,858,449,0306,0
      tot349172,480,541,0623,0.000
      Table 4Association between age, respiratory rate, PaO2, PaCO2, standard PaO2 (STPaO2), P/F, STP/F and ARF duration in days (Spearman's correlation)
      Duration of ARF
      Age Respiratory Rate PaO2 (mmHg)Correlation coefficient sig. n Correlation coefficient sig n Correlation coefficient0.136 0.061 191 0.286 0.000 172 -.022
      sig..764
      n191
      PaCO2 (mmHg)Correlation coefficient-.066
      sig..362
      n191
      STPaO2 (mmHg)Correlation coefficient-.040
      sig..583
      n191
      P/FCorrelation coefficient-.385
      sig..000
      n191
      STP/FCorrelation coefficient-.396
      sig..000
      n191

      4. Discussion

      The main finding of the current investigation is that accuracy of STP/F to predict death was higher than conventional P/F (0.710; 95% CI 0.638-0.782 vs. 0.688; 95% CI 0.650-0.846, p = 0.012), Fig. 1 and Table 2. Interestingly, STP/F is accurate and superior to P/F in predicting in-hospital mortality, but not outcome failure (defined as deaths or need of IMV), as if the need of IMV is not affected by STP/F or P/F values. STP/F can predict mortality in all patients of our study population.
      Mean PaCO2 of the study population was inferior to 40 mmHg, and mean respiratory rate was 22 ± 5 breaths per minute (Table 1B). This confirms the hypocapnic compensation of hypoxemia in Covid-19, mainly obtained by increase of tidal volume. Moreover, mean value of PaCO2 of the subgroup died for ARF due to Covid-19 was inferior to the one of the survivors subgroup (Table 3), p = 0.037, as if low PaCO2 might suggest risk of further ARF worsening, even if AUROC curve of paCO2 is not enough accurate to predict outcome failure.
      Prevalence of never smokers in our study population was 85%; this reflects data emerged from literature about Covid-19 [[
      • Garufi G.
      • Carbognin L.
      • Orlandi A.
      • Tortora G.
      • Bria E.
      Smoking habit and hospitalization for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related pneumonia: the unsolved paradox behind the evidence.
      ,
      • Lippi G.
      • Sanchis-Gomar F.
      • Henry B.M.
      Active smoking and COVID-19: a double-edged sword.
      ],]. Smoking can modulate immunity reducing its effectiveness. Thus could result in a less reactive inflammatory response during Covid-19, preventing the cytokine storm responsible of the progression of the disease in ARF due to Covid-19 and explain the lower prevalence of current or former smokers in Covid-19 reported studies. [[
      • Garufi G.
      • Carbognin L.
      • Orlandi A.
      • Tortora G.
      • Bria E.
      Smoking habit and hospitalization for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related pneumonia: the unsolved paradox behind the evidence.
      ,
      • Lippi G.
      • Sanchis-Gomar F.
      • Henry B.M.
      Active smoking and COVID-19: a double-edged sword.
      ],]. We can speculate, in addition, that usually a fraction of current smokers or former smokers may be affected by chronic obstructive pulmonary disease (COPD). Having a respiratory chronic disease, COPD patient might have a more preventive social behavior strategy and respect strictly rules such as wearing masks and to respect physical distances. Moreover COPD patients could probably early recognize Covid-19 related respiratory symptoms and signs, leading them to have an early access to medical consultation and/or ER.
      According to our findings, STP/F better describes ARF due to Covid-19 in its hypocapnic nature. Using STPaO2 instead of PaO2 (standard P/F versus P/F) better describes this phenomenon and could better relate to prognosis, in particular in-hospital mortality.
      Defining all mechanisms responsible for ARF during SARS-CoV-2 pneumonia with one parameter is not simple, since pathophysiology of lung injury due to Covid-19 is multifactorial and the impact of every single compensatory mechanism varies between subjects and through the course of the disease. [
      • Gattinoni L.
      • Chiumello D.
      • Caironi P.
      • Busana M.
      • Romitti F.
      • Brazzi L.
      • et al.
      COVID-19 pneumonia: different respiratory treatments for different phenotypes?.
      ,
      • Simonson T.S.
      • Baker T.L.
      • Banzett R.B.
      • Bishop T.
      • Dempsey J.A.
      • Feldman J.L.
      • et al.
      Silent hypoxaemia in COVID-19 patients.
      ,
      • Goh K.J.
      • Choong M.C.
      • Cheong E.H.
      • Kalimuddin S.
      • Duu Wen S.
      • Phua G.C.
      • et al.
      Rapid progression to acute respiratory distress syndrome: review of current understanding of critical illness from COVID-19 infection.
      ] In Covid-19, inflammation and oedema in alveoli are the main responsible of hypoxemia in the early phases of disease, so that P/F reasonably relate to severity of diffusing impairment here. With the progression of disease (consolidation phase), V/Q mismatch and shunt mechanism become prevalent, so that hypoxemic ARF becomes less responder to implementation of FiO2 due to incapacity to improve PaO2 in non-ventilated alveoli. In lung regions where shunt is prevalent, P/F could be not so representative of severity of the disease. [[
      • Bendjelid K.
      • Raphaël G.
      Treating hypoxemic patients with SARS-COV-2 pneumonia: back to applied physiology.
      ,
      • Covelli H.D.
      • Nessan V.J.
      • Tuttle W.K.
      Oxygen derived variables in acute respiratory failure.
      ],] Reducing partial pressure of carbon dioxide (PaCO2) represents a protective mechanism: low values of PaO2 increase minute ventilation in response to chemoreceptor stimulation. Hyperventilation is a feedback mechanism to correct hypoxia at the expense of PaCO2 reduction and left shift of the HbO2 dissociation curve. In this way, tachypnea and hyperpnoea, generated by a rise of minute ventilation through increasing respiratory rate and tidal volume, compensate both hypoxemia and prevent blood acidosis [
      • Tobin M.J.
      • Laghi F.
      • Jubran A.
      Why COVID-19 silent hypoxemia is baffling to physicians.
      ].
      Notably, the presence of microvascular thrombosis in subjects with Covid-19 ARF, highlighted by the increase of D-dimer and alveolar dead space; may contribute to the severity and progression of hypoxia observed in Covid-19 [
      • Copin M.C.
      • Parmentier E.
      • Duburcq T.
      • Poissy J.
      • Mathieu D.
      Lille COVID-19 I.C.U. and Anatomopathology Group
      Time to consider histologic pattern of lung injury to treat critically ill patients with COVID-19 infection.
      ]. Several data showed that outcome is related to dead space through measurement of ventilatory ratio in typical ARDS and in Covid-19 [
      • Grasselli G.
      • Tonetti T.
      • Protti A.
      • Langer T.
      • Girardis M.
      • Bellani G.
      • et al.
      Pathophysiology of COVID-19-associated acute respiratory distress syndrome: a multicentre prospective observational study.
      ]. These measurements in subjects in spontaneous breathing are not obtainable, so that STPF could represent a surrogate of the ventilatory ratio.
      There is an urgent need to identify patients at higher risk of intubation and death, since de novo ARF plays a central role in Covid-19, being responsible for morbidity and mortality [
      • Li L.Q.
      • Huang T.
      • Wang Y.Q.
      • Wang Z.P.
      • Liang Y.
      • Huang T.B.
      • et al.
      COVID-19 patients' clinical characteristics, discharge rate, and fatality rate of meta-analysis.
      ,
      • Khan M.
      • Adil S.F.
      • Alkhathlan H.Z.
      • Tahir M.N.
      • Saif S.
      • Khan M.
      • et al.
      COVID-19: a global challenge with old history, epidemiology and progress so far.
      ,
      • Lai X.
      • Liu J.
      • Zhang T.
      • Feng L.
      • Jiang P.
      • Kang L.
      • et al.
      Clinical, laboratory and imaging predictors for critical illness and mortality in patients with COVID-19: protocol for a systematic review and meta-analysis.
      ]. In addition, defining the best setting where to allocate patients affected by SARS-CoV-2 pneumonia could play a central role in this emergency era for health care resources worldwide. Finding a parameter which could help clinicians to detect early which patient will need more resources, in particular the need of respiratory support and so Pulmonology Unit hospitalization, may optimize Covid-19 outcomes and improve costs-benefits ratio.
      This is the first study assessing the role of standard paO2 in relationship to prognosis in acute respiratory failure: this pilot study identifies STPF as a better predictor of mortality than PF in Covid-19 ARF. We propose the use of STP/F because, from a pathophysiological point of view, it better describes the compensatory mechanism present in hypoxemic ARF typical of Covid-19 and our study showed that is more accurate in discriminating prognosis. STPaO2 is a parameter obtainable simply in standard practice using a formula validated since years [
      • Mays E.E.
      An arterial blood gas diagram for clinical use.
      ].
      Limits of this study are its observational nature and the short enrollment phase due to its pilot nature. Moreover it does not take into account patients with ARF due to Covid-19 admitted directly from ER to ICU; this could explain the relatively low outcome failure and mortality ratio seen in our study (respectively 32.4% and 16.6%). However, outcome failure, as defined by need for invasive mechanical ventilation and/or death, was online with previous literature describing patients outside ICU setting [[
      • Bonnet N.
      • Martin O.
      • Boubaya M.
      • Levy V.
      • Ebstein N.
      • Karoubi P.
      • et al.
      High flow nasal oxygen therapy to avoid invasive mechanical ventilation in SARS-CoV-2 pneumonia: a retrospective study.
      ,
      • Chalmers J.D.
      • Crichton M.L.
      • Goeminne P.C.
      • Cao B.
      • Humbert M.
      • Shteinberg M.
      • et al.
      Management of hospitalised adults with coronavirus disease-19 (COVID-19): A European Respiratory Society living guideline.
      ,
      • Gupta A.
      • Nayan N.
      • Nair R.
      • Kumar K.
      • Joshi A.
      • Sharma S.
      • et al.
      Diabetes mellitus and hypertension increase risk of death in novel corona virus patients irrespective of age: a prospective observational study of Co-morbidities and COVID-19 from India.
      ,
      • Franco C.
      • Facciolongo N.
      • Tonelli R.
      • Dongilli R.
      • Vianello A.
      • Pisani L.
      • et al.
      Feasibility and clinical impact of out-of-ICU noninvasive respiratory support in patients with COVID-19-related pneumonia.
      ],]. Outcome failure results could be affected to the decision to start IMV according to PF value of the patient (for example a rapid decline of P/F), so that this could represent a bias of this study, while mortality is independent. To avoid selection bias we enrolled all consecutive patients with ARF due to Covid-19, all admitted at our Units managed by pulmonologists due to a worsening of their clinical condition. Maybe differences emerged from our pilot study are not enough to change the clinical practice, but it may be helpful in considering the pathophysiological features leading to the calculation of this index (P/F).
      Clinical use of STP/F as a predictor of in-hospital mortality could be used to allocate patients in the right setting. Enlarging sample size in an extension future study, and, if properly uniformed, considering uniformed ABGs at the time of ER admission, could better define the impact of using STP/F in hypoxemic Covid-19 ARF and its management. In addition, the prognostic significance of STP/F could be compared in future with other Covid-19 prognostic indices such as C-reactive protein, blood leukocyte count and D-dimer, simpler to obtain in clinical practice.
      More prospective studies are needed to validate the value of STP/F as a marker of outcome in Covid-19 and to define its severity cut-offs. In future, STP/F could also be studied in other ARF settings such as acute exacerbation of chronic obstructive pulmonary disease, interstitial lung diseases and pneumonia due to other infectious agents than Covid-19.

      Author's contribution

      IP study design, study coordination, data collection and analysis, draft manuscript. LDA study design, data integrity and accuracy. PC, FD, RD, RF, AMGP, LP, CT, MLV data collection. VMR manuscript revision. SN study design, supervision, manuscript revision. PP study design, data analysis, manuscript revision, final approval of the version submitted for publication. IP conceptualization, data curation, formal analysis.

      Funding

      This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

      Declaration of Competing Interest

      All Authors declare no conflict of interests.

      Acknowledgments

      Authors thank all the clinicians’ part of the study staff of our Pulmonology Units for the data accuracy of arterial blood gas analysis and clinical history collected from patients during this pandemic emergency period due to Covid-19. This precision has permitted this research.

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      Linked Article

      • Standardised PaO2/FiO2 ratio in COVID-19: Added value or risky assumptions?
        European Journal of Internal MedicineVol. 92
        • Preview
          The coronavirus disease 2019 (COVID-19) causes acute respiratory failure (ARF) altering the pulmonary microvasculature with simultaneous vasoconstriction and thrombosis in ventilated areas, hyperperfusion [1] and neo-angiogenesis in gasless regions [2]. The progressive derangement of the lung vasculature and parenchyma worsens the shunt fraction and deadspace, and consequently hypoxaemia and hypercapnia.
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