Novel 2019 Coronavirus SARS-CoV-2 (COVID-19): An Overview for Emergency Clinicians - 5/1/20

The Brescia-COVID respiratory severity scale/algorithm is a stepwise management approach to COVID-19 patients based on clinical severity; this information is current as of March 27, 2020. This review will discuss the use of clinical prediction scores for pneumonia severity at 3 main decision points to examine which scores may provide value in this unique situation. Initial data from a cohort of over 44,000 COVID-19 patients in China, including risk factors for mortality, were compared with data from cohorts used to study the clinical scores, in order to estimate the potential appropriateness of each score and determine how to best adjust results at the bedside.

PDF: Brescia-COVID Algorithm

PDF: COVID-19 Calculators

1. Brescia-COVID Respiratory Severity Scale (BCRSS)/Algorithm
2. Critical Review: COVID-19 Calculators During Extreme Resource-Limited Situations

Brescia-COVID Respiratory Severity Scale (BCRSS)/Algorithm

• Introduction
• Points & Pearls
• Why and When to Use, and Next Steps
• Calculator Review Author
• Critical Actions
• Instructions
• Evidence Appraisal
• References

Introduction

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Points & Pearls

• The Brescia-COVID respiratory severity scale (BCRSS) and algorithm were rapidly developed in Brescia, Italy, during that nation’s COVID-19 crisis. The scale has not been validated or tested in other populations and was developed as the world continued to learn more about COVID-19 each day.
• Clinicians in Brescia have been referring to COVID-19 patients by level number; in the intensive care unit, a patient’s assigned level is taped above the bed and updated daily.
• Patients are also assigned a subscore using daily chest x-ray findings for further stratification. Three quadrants of each lung are each assigned a score of 0 to 3, with 0 points assigned for no opacification in the quadrant and 3 points for full opacification; the points assigned for each quadrant are then added together. For example, a patient at “Level 3 with 12 points on chest x-ray” would be in much more serious condition than a patient at “Level 3 with 2 points on chest x-ray.”
• Many clinicians in North America have raised concerns about the risk of viral particle spread with the use of noninvasive ventilation and high flow nasal cannulas. The creators of the BCRSS in Italy included those ventilation strategies because they did not have enough ventilators to accommodate all of the patients who needed them, and the only alternative for those patients would have been death.

Why and When to Use, and Next Steps

Calculator Review Authors

Critical Actions

Patients with tachypnea and patients who require significant levels of oxygen or ventilatory support are at very high risk for clinical decompensation and death.

Instructions

• The BCRSS/algorithm presents a stepwise approach to managing patients with confirmed or presumed COVID-19 pneumonia.
• If the patient is not intubated, follow management recommendations, then repeat each of the 4 testing criteria to assess for improvement or deterioration. Repetition frequency is based on clinical judgment to downgrade or upgrade the score.
• The role of the BCRSS/algorithm in guiding man-agement is important, but the numerical score is also used by treating clinicians to easily compare and summarize patients.
• Noninvasive ventilation is concerning for aerosolization, but is included in the BCRSS/algorithm due to ventilator scarcity in Italy.

Evidence Appraisal

This scale has not been externally validated and has been published by MDCalc as a possible method to easily assess and compare patients in a time of crisis.

References

Original/Primary Reference

• Italian Society of Infectious and Tropical Diseases (SIMIT). [Guidelines on therapeutic and supportive management for patients with COVID-19 coronavirus infection.] 2020. Accessed April 1, 2020.

Critical Review: COVID-19 Calculators During Extreme Resource-Limited Situations

• Introduction
  • Table 1. Risk Factors Associated With Poor Prognosis in Subjects Infected with COVID-19s
• Decision Point #1: Discharge Versus Admit
  • Takeaways
• Decision Point #2: ICU, Ventilator, Vasopressors
  • Takeaways
• Decision Point #3: ECMO
  • Takeaways
• Authors and Peer Reviewers
• References

Introduction

Table 1. Risk Factors Associated With Poor Prognosis in Subjects Infected with COVID-19s

There is evidence, based on a much smaller cohort of 191 patients, that a SOFA score > 5 (OR 5.5; 95% confidence interval [CI], 2.6-12.2; P < 0.0001) and D-dimer concentration > 1000 ng/mL on admission (OR 18; 95% CI, 2.6-128.6; P < 0.0001) confer significant mortality risk in COVID-19 patients.¹ In addition, prolactin levels have been found to be normal or even low; if levels are found to be high, this may suggest a bacterial coinfection necessitating administration of antibiotics. C-reactive protein levels have been found to be higher in worsening disease and may provide prognostic value.^4-5

Decision Point #1: Discharge Versus Admit

PSI/PORT may add value; consider the new MuLBSTA score; adjust for elderly patients.

Each of these scores was designed to predict mortality and is used to determine which patients can safely be sent home. A low-risk CURB-65 score (0 or 1) confers a 0.6% to 2.7% risk of mortality.⁶ A low-risk PSI/PORT score (< 90) confers a 0.1% to 2.8% risk of mortality.⁷ Comparing the utility of the 2 scores, CURB-65 may not identify patients requiring ICU admission as well as PSI/PORT. In addition, CURB- 65 does not take into account patients’ comorbidities (eg, COPD), which may have a major impact on outcomes in COVID-19 patients. While CURB-65 is considerably faster to compute, with fewer inputs, this advantage matters less in the age of electronic records and resources. PSI/PORT places a larger emphasis on age than CURB-65, assigning points by absolute age (ie, a 70-year-old gets 70 points), which seems more consistent with what we know about the high mortality of COVID-19 in elderly patients.

In both of these cohorts, community acquired pneumonia (CAP) was generally defined as a combination of clinical (eg, fever, cough, dyspnea, rales) and radiographic (eg, infiltrate on chest x-ray) findings in the absence of risk factors for healthcare-associated pneumonia. Neither the CURB-65 or PSI/PORT studies differentiated between viral and bacterial pathogens as a cause for the pneumonia, although the incidence of viral-associated CAP may be up to 29%, with rhinoviruses and influenza being the most common.^8-9

Recently, the MuLBSTA score was developed as a clinical prediction tool to risk stratify patients specifically diagnosed with viral pneumonia.⁹ The aim of this tool was to predict clinical characteristics that affect mortality in patients with viral pneumonia. Interestingly, the score uses predictors of adverse outcomes that correlate with the clinical characteristics that are reported in COVID-19 patients. The presence of a multilobar infiltrate, low lymphocyte count, smoking history, and advanced age all were independent risk factors for mortality in this population, and are all relatively consistent with risk factors from the Chinese COVID-19 cohort. However, this score was derived from a single-center, retrospective, not-externally-validated study design, which may lead to bias and has unknown applicability and generalizability.

Takeaways

• Due to stronger emphasis on age and comorbidities, the PSI/PORT score may be a more accurate tool than the CURB-65 score in disposition decision-making for COVID-19 patients, as age and underlying disease seem to be the major contributors to adverse patient-oriented outcomes.
• The MuLBSTA score examines a patient population with similar characteristics to those with COVID-19 pneumonia. However, it is based on a single-center, retrospective study, which limits its applicability and reliability. We recommend its use as adjunct to clinical suspicion, but not in isolation.
• All of these scores likely underestimate the importance of advanced age and of low lymphocytes.

Decision Point #2: ICU, Ventilator, Vasopressors

SMART-COP for decision to start respiratory or vasopressors; LIPS to predict acute respiratory distress syndrome (ARDS); CAP-PIRO for mortality after ICU admission. None are designed specifically for viral pneumonia.

For patients presenting to the emergency department with CAP, it has been established that delayed admission to the ICU is associated with higher mortality.¹¹ The SMART-COP score was designed to predict which patients with CAP require intensive respiratory or vasopressor support.¹² It uses readily available information, and is 92.3% sensitive in identifying which patients need ICU-level care. In contrast to other scores, SMART-COP does not explicitly consider age as a variable, although it does include age-adjusted cutoffs for respiratory rate and oxygen level.

The SCAP score uses 8 variables that identify patients at risk for “severe CAP,” defined by adverse outcomes such as need for ICU admission, development of sepsis, or requirement of mechanical ventilation.13 SMART-COP and SCAP share several common predictors of adverse patient-oriented outcomes potentially necessitating a higher level of care: age (SMART-COP, aged > 50 years; SCAP aged > 80 years), multilobar involvement on radiography, respiratory rate > 30 breaths/min, confusion (new onset), PaO₂/FiO₂ < 250 mm Hg, decreased pH (SMART-COP, < 7.35; SCAP, < 7.30), and systolic blood pressure < 90 mm Hg.

If the pandemic stretches resources beyond the ability to care for all patients, some states have developed plans to use a SOFA score > 11 as a cutoff to help with decision-making in these dire situations.14 However, recent studies have shown that SOFA should be used cautiously as part of a decision-making framework and does not meet the ethical cutoffs for prediction across different patient populations.^14-15

The LIPS score is differentiated in that it was designed to estimate risk of ARDS, and it has utility at the time of critical care contact.¹⁶ The CAP-PIRO score was designed to predict mortality of CAP patients who are already admitted to the ICU, therefore limiting its utility in the disposition decision-making process.¹⁷ Like most scores, these scores do not differentiate between causes of pneumonia, nor were they designed to specifically risk stratify patients with viral pneumonia.

Takeaways

• The SMART-COP and SCAP scores are useful tools in predicting a need for a higher level of care for patients with CAP, including patients with viral-associated pneumonia. However, the specific utility of these scores in viral pneumonia is unknown.
• Common predictors of adverse outcomes that may necessitate ICU admission/vasopressors/mechanical ventilation are advanced age, multilobar involvement on radiography, tachypnea, acute confusion, arterial blood gas findings consistent with ARDS, and hypotension.
• More specific to viral pneumonia, a decreased absolute lymphocyte count may predict adverse outcomes.
• The importance of advanced age is likely underestimated by these scores.

Decision Point #3: ECMO

Very little specific experience for COVID-19 patients, but tools exist to guide resource use.

Many of the COVID-19 fatalities are due to ARDS. The Murray score was developed to determine which patients are sick enough for veno-venous ECMO, a critical decision point during this crisis.18 The RESP and PRESET scores attempt to predict mortality of patients on ECMO, which may be helpful during the difficult potential situation when rationing of ECMO may become necessary.^19-20 At this point, there is very limited guidance specific to the use of ECMO in COVID-19 patients, though it has been utilized in China.

For patients with worsening respiratory failure, a Murray score ≥ 3 suggests a condition severe enough to consider initiating ECMO. The score was initially developed to assess the severity of ARDS but was then utilized in the CESAR trial (the first modern randomized controlled trial to compare traditional vent management to ECMO) to determine appropriateness for ECMO.²¹ The initial and validation trials did not specifically address ARDS due to viral causes, but they also did not exclude these patients, so it is likely that the score is applicable to COVID-19 patients.

If the pandemic stretches beyond available healthcare resources, these tools may assist in a framework to develop new crisis standards of care for patients requiring ECMO. The RESP score had a lower predictive ability within its derivation cohort (internal area under receiver operating curve) than PRESET, but PRESET’s patient population had a higher critical illness severity than has been noted in other ECMO cohorts and thus had a lower predictive ability when validated in subsequent cohorts. RESP requires 12 input variables, whereas PRESET requires 5. While this makes RESP more complicated to use, it has been validated in more subsequent cohorts than PRESET, so it may be preferable. RESP also specifically takes into account whether a viral pneumonia is underlying respiratory failure, which may increase its applicability to COVID-19 patients.

Takeaways

• There is little direct evidence or experience supporting the use of ECMO in COVID-19 patients.
• The Murray score can be used to help decide whether or not ARDS is severe enough to consider ECMO for the patient.
• If resources are stretched, the RESP score appears more useful than the PRESET score for helping the clinician assess a patient’s mortality risk on ECMO.

Authors and Peer Reviewers

Authors

Peer Reviewers

References

1. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020 Mar 11 [online ahead of print].
2. Vital surveillances: the epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) — China, 2020. China CDC Weekly. Accessed March 17, 2020.
3. Mortensen EM, Coley CM, Singer DE, et al. Causes of death for patients with community-acquired pneumonia: results from the Pneumonia Patient Outcomes Research Team cohort study. Arch Intern Med. 2002;162(9):1059-1064.
4. Ruan Q, Yang K, Wang W, et al. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. 2020 Mar 3.[online ahead of print].
5. Young BE, Ong SWX, Kalimuddin S, et al. Epidemiologic features and clinical course of patients infected with SARS-CoV-2 in Singapore. JAMA. 2020 Mar 3 [online ahead of print].
6. Lim WS, van der Eerden MM, Laing R, et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003;58(5):377-382.
7. Fine MJ, Auble TE, Yealy DM, et al. A prediction rule to identify low-risk patients with community-acquired pneumonia. N Engl J Med. 1997;336(4):243-250.
8. Jennings LC, Anderson TP, Beynon KA, et al. Incidence and characteristics of viral community-acquired pneumonia in adults. Thorax. 2008;63(1):42-48.
9. Guo L, Wei D, Zhang X, et al. Clinical features predicting mortality risk in patients with viral pneumonia: the MuLBSTA Score. Front Microbiol. 2019;10:2752.
10. Korea Centers for Disease Control and Prevention Dataset. Accessed March 17, 2020
11. Restrepo MI, Mortensen EM, Rello J, et al. Late admission to the ICU in patients with community-acquired pneumonia is associated with higher mortality. Chest. 2010;137(3):552-557.
12. Charles PG, Wolfe R, Whitby M, et al. SMART-COP: a tool for predicting the need for intensive respiratory or vasopressor support in community-acquired pneumonia. Clin Infect Dis. 2008;47(3):375-84.
13. España PP, Capelastegui AM, Gorordo I, et al. Development and validation of a clinical prediction rule for severe community-acquired pneumonia. Am J Respir Crit Care Med. 2006;174(11):1249-1256.
14. United States Department of Health and Human Services. “Topic Collection: Crisis Standards of Care.” Accessed March 17, 2020.
15. Christian MD, Sprung CL, King MA, et al. Triage: care of the critically ill and injured during pandemics and disasters: CHEST consensus statement. Chest. 2014;146(4 Suppl):e61S-e74S.
16. Gajic O, Dabbagh O, Park PK, et al. Early identification of patients at risk of acute lung injury: evaluation of lung injury prediction score in a multicenter cohort study. Am J Respir Crit Care Med. 2011;183(4):462-470.
17. Rello J, Rodriguez A, Lisboa T, et al. PIRO score for community-acquired pneumonia: a new prediction rule for assessment of severity in intensive care unit patients with community-acquired pneumonia. Crit Care Med. 2009;37(2):456-462.
18. Murray JF, Matthay MA, Luce JM, et al. An expanded definition of the adult respiratory distress syndrome. Am Rev Respir Dis. 1988;138(3):720-723.
19. Schmidt M, Bailey M, Sheldrake J, et al. Predicting survival after extracorporeal membrane oxygenation for severe acute respiratory failure. The Respiratory Extracorporeal Membrane Oxygenation Survival Prediction (RESP) score. Am J Respir Crit Care Med. 2014;189(11):1374-1382.
20. Hilder M, Herbstreit F, Adamzik M, et al. Comparison of mortality prediction models in acute respiratory distress syndrome undergoing extracorporeal membrane oxygenation and development of a novel prediction score: the PREdiction of Survival on ECMO Therapy-Score (PRESET-Score). Crit Care. 2017;21(1):301.
21. Peek GJ, Mugford M, Tiruvoipati R, et al. Efficacy and economic assessment of conventional ventilatory support versus extracorporeal membrane oxygenation for severe adult respiratory failure (CESAR): a multicentre randomised controlled trial. Lancet. 2009;374(9698):1351-1363.