How Routine Biomarkers and Blood Leucocytes Count Can Assist Diagnosis of COVID-19 in Emergency Department

December 2019 was the onset of an outbreak of an infection related to SARS-CoV-2, a new coronavirus detected in January 2020 and responsible for a disorder termed COVID-19. Since then, COVID-19 has spread worldwide and is responsible for an unprecedented pandemic with major threat on global health and social and economic stability.

Covid-19 has a large spectrum of symptoms. Most patients experience mild or moderate flu-like disorder with cough, fever, and shortness of breath. More severe presentations may occur; patients sometimes develop an acute pneumonia that can lead to adult respiratory distress syndrome. A considerable number of publications have been released for the last 10 weeks to help physicians making diagnosis and treat patients. Chinese authors have extensively proposed description of the disease. As signs and symptoms are poorly specific, diagnosis mostly relies on detection of the virus by RT-PCR in the upper respiratory tract. Some uncommon images and localization are highly specific and sensitive on chest CT-scan, which is cornerstone for initial diagnosis. However, resources may lack during healthcare crisis and results of these investigations may be delayed or unavailable developper. Special attention should also be paid to usual laboratory analysis. Indeed, decreased lymphocytes and eosinophilic counts are frequently described as well as increase in D-dimers levels. Variation of C-reactive protein (CRP) and procalcitonin (PCT) have been reported. Coronavirus may have cardiac tropism and changes in cardiac biomarkers concentration may occur. Therefore, some data suggest that values of routine biomarkers and blood cell count may assist physicians at bedside to support diagnosis of COVID-19.

To face the outbreak, organization of emergency departments (ED) was mandatory to separate patients flows and avoid mixing patients with COVID-19 and others. Most patients visiting EDs dedicated to initial COVID-19 management suffered of pneumonia-like symptoms. Despite initial triage, patients had either COVID-19-related pneumonia either alternative diagnoses. We took advantage of this to evaluate the ability of routine biomarkers and leucocytes count helping identification of COVID-19 from alternative diagnoses.

Methods Setting Investigator designed a single center, retrospective, observational study conducted from February 2020 to April 2020 in the emergency department (ED) of Princesse Grace Hospital center, a general hospital in Monaco. The study was monitored by the research department of the Hospital Center. No specific funding was obtained for this study. The institutional review board for the protection of human subjects approved the study protocol and waved the need for written informed consent for inclusion.

Objectives The primary objective was to assess sensitivity of routine biomarkers and blood cell count for diagnosis of COVID-19-related pneumonia in low and high probability groups for level of certainty using the adjudication committee classification.

Secondary objectives were :

* to compare values in the four different categories of level of certainty and between low and high probability groups;
* to assess performance of combined routine biomarkers and blood cell count for diagnosis of COVID-19-related pneumonia;
* to assess whether usual biomarkers and blood cell count were associated with diagnosis of COVID-19-related pneumonia using sensitivity analyses in two predefinite subgroups chosen a priori; Group 1 : when considering patients classified as having low probability and high probability COVID-19-related pneumonia; Group 2 : when patients with excluded COVID-19-related pneumonia and diagnosed extra-pulmonary infectious disease were not taken into account, in the low probability COVID-19-related pneumonia group.

Adjudication committee Based on data collected from baseline on standardized case report forms, results of low dose chest CT-scan, of SARS-Cov-2 specific RT-PCR, and full access to all available data including patients' discharge summary, an adjudication committee consisting of three independent senior experts in infectious diseases, pneumology and radiology retrospectively assigned the probability of COVID-19-related pneumonia diagnosis using the 4-level Likert scale. For this study, the gold standard was the diagnosis assessed by the adjudication committee. Alternative diagnoses were established for low probability COVID-19-related pneumonia and classified as non-COVID pulmonary diseases and extra-pulmonary infectious diseases and others.

A Likert scale allowed distribution of patients in four categories:

1. absence of COVID-19-related pneumonia hereafter referred to as excluded;
2. possible COVID-19-related pneumonia;
3. probable COVID-19-related pneumonia;
4. definite COVID-19-related pneumonia. After this first classification, patients were distributed in two groups: low probability COVID-19-related pneumonia (excluded and possible) and high probability COVID-19-related pneumonia (probable and definite).

Study population For the study purpose and to ensure quality of the final adjudication committee diagnosis, investigator selected consecutive adults (18 years of age and above) visiting the COVID-19-dedicated ED if they presented with clinically suspected COVID-19-related pneumonia and had SARS-Cov-2 RT-PCR and/or low dose chest CT-scan.

Patient management and usual biomarkers and blood cell count Patients' management in the COVID-19-dedicated ED was based on local protocoled practices based upon collegial multidisciplinary decision if they presented with suspected COVID-19-related pneumonia. Recorded baseline data consisted of demographic data (age, gender), coexisting illnesses, treatments, symptoms, clinical findings and predetermined laboratory tests including: SARS-Cov-2 specific RT-PCR obtained on nasopharyngeal swab; low-dose chest CT-scan; standard blood analysis (complete blood count, hemostasis, metabolic panel, creatinine, blood urea nitrogen, liver enzymes), D-dimers (Vidas, Biomérieux), procalcitonin, C-reactive protein (CRP), high sensitive cardiac troponin T (cTnT-hs, Cobas, Roche diagnostics), NT-pro-brain natriuretic peptide (NT-proBNP, Cobas, Roche diagnostics). For each individual, CRB65 and Pneumonia Severity Index (PSI) were calculated.

Microbiological samples Naso-pharyngeal swabs were collected at admission and placed in a Middle Virocult MWE (Sigma®) transport medium. Samples were kept at room temperature and sent to the laboratory immediately after collection. For the presence of SARS-COV-2, swabs were sent to French referent centers of virology (Nice, Marseille, Paris). Routine microbiological examinations were also performed at the discretion of the emergency physicians and included : presence of influenza A and B viruses and respiratory syncytial virus (RSV) A and B on nasopharyngeal swabs, blood culture, urine antigens for Streptococcus pneumoniae and Legionella pneumophila type I, serodiagnosis of Mycoplasma pneumoniae. These results were available to the adjudication committee.

Low dose chest CT-scan data and COVID-19-related pneumonia diagnosis classification Multidetector low dose thoracic CT-scan was performed for each individual patient and interpretation was recorded using a standardized report form according to guidelines. The level of COVID-19-related pneumonia probability according to low dose chest CT scan were defined.

Statistical analysis Baseline and follow-up characteristics were described by means and standard deviations (SD) or by median and interquartile range (IQR) for continuous variables with normal or with skewed distribution, respectively, and by percentages for categorical variables. Chi-square or Fisher exact tests were performed when appropriate for qualitative variables. The Student or Mann-Whitney tests were used to compare baseline characteristics and study outcomes between study groups for continuous variables with skewed distributions.

The distribution of values for usual biomarkers and blood cell count were determined in the different populations of patients using boxplots. The performances of current laboratory data in predicting definite COVID-19-related pneumonia were evaluated by sensitivity analysis (definite vs excluded COVID-19-related pneumonia). CRP was evaluated at several cut-off points of 20 mg/L, 30 mg/L, 50 mg/L, 70 mg/L, and 100 mg/L, values used in previous studies. Several cut-off points for PCT were chosen at the level of 0.10 μg/L, and at the two levels for suspected bacterial infection as stated by the manufacturer, i.e., 0.25 μg/L and 0.50 μg/L. Cut-offs for cTnT-hs were 0.014ng/mL and 50ng/mL. Cut-offs for D-dimers test were 500µg/ml and age-adjusted threshold. Sensitivities, specificities, positive predictive values (PPVs), negative predictive values (NPVs), and likelihood ratio were calculated. Receiver operating characteristic (ROC) curves were drawn, area under the curve AUC was computed and optimal cut-off was identified by the maximization of the Youden's index, comparing laboratory results values in patients with excluded COVID-19-related pneumonia and definite COVID-19-related pneumonia. From these optimal cut-offs for laboratory results, sensitivity analyses were performed combining cut-offs.

A multivariate logistic regression model was built to identify factors associated with having definite COVID-19-related pneumonia as compared to having an excluded COVID-19-related pneumonia diagnosis. Investigator excluded from the excluded CAP diagnosis group, patients with an extra-pulmonary infectious disease. All variables with a p value of \< 0.25 in the bivariate analysis were entered into a multivariate logistic regression with a backward stepwise approach; the discrimination was evaluated by the C-index and its 95 % confidence interval (95 % CI) and the calibration was evaluated by the Hosmer Lemeshow goodness-of-fit test.

All tests were two-sided, and p-values below 0.05 were considered to denote statistical significance. All statistical analyses were performed using SPSS statistical software version 21.0 (SPSS Inc., Chicago, IL, USA).

Eligibility Criteria:
Inclusion Criteria:

* patient suspected of COVID19

Exclusion Criteria:

* patient unsuspected of COVID19