Procalcitonin Predicts Intensive Care Unit Admission and Mortality in Patients With a COVID-19 Infection in the Emergency Department


 IntroductionPatients with a severe COVID-19 infection often require admission at an intensive care unit (ICU) when they develop acute respiratory distress syndrome (ARDS). Hyperinflammation plays an important role in the development of ARDS in COVID-19. Procalcitonin (PCT) is a biomarker which may be a predictor of hyperinflammation. When patients with COVID-19 are in the emergency department (ED), PCT could be a predictor of severe COVID-19 infection. The goal of this study is to investigate the predictive value of PCT on severe COVID-19 infections in the ED. MethodsThis was a retrospective cohort study including patients with confirmed COVID-19 infection who visited the ED of Erasmus Medical Center in Rotterdam, the Netherlands, between March and December 2020. The primary endpoint was a severe COVID-19 infection, which was defined as patients who required ICU admission, in-hospital mortality and 30-day mortality after hospital discharge. PCT levels were measured during the ED visit. We used logistic regression to calculate the odds ratio (OR) of PCT on a severe COVID-19 infection, adjusting for bacterial coinfections, age, gender and comorbidities. ResultsA total of 332 patients were included in the final analysis of this study, of which 105 patients reached the composite endpoint of a severe COVID-19 infection. PCT showed an unadjusted OR of 4.19 (CI: 2.52-7.69) on a severe COVID-19 infection. Corrected for bacterial coinfection, the OR of PCT was 4.05 (2.45 – 7.41). Adjusted for gender, bacterial coinfection, age and comorbidities, PCT was still an independent predictor of severe COVID-19 infection with an adjusted OR of 3.82 (CI: 2.26-7.48).ConclusionPCT is a predictor of severe COVID-19 infections in patients with a COVID-19 infection in the ED. The routine measurement of PCT in patients with a COVID-19 infection in the ED may assist physicians in the clinical decision making process regarding ICU disposition when PCT levels are elevated.


Introduction
Coronavirus disease  caused by the novel Coronavirus (SARS-CoV-2) was declared a pandemic on the 11th of March 2020 by the World Health Organization 1 . Ever since, COVID-19 caused a high burden on hospital and intensive care unit capacity 2 . Patients with COVID-19 often require hospitalization and treatment at an intensive care unit (ICU) when they develop acute respiratory distress syndrome (ARDS). The exact underlying pathophysiology of ARDS in these severe COVID-19 infections is under research with an exponentially growing amount of studies on this topic 3,4 . Many studies have found that hyperin ammation, caused by an overwhelming upregulation of the immune system, and immune thrombosis play a major role in the development of ARDS in COVID-19 5 .
When patients with a COVID-19 infection present at the emergency department (ED), it is important to be able to identify patients who are at high risk of developing a severe COVID-19 infection. These patients may bene t from more extensive monitoring or early ICU admission. Different biomarkers have been identi ed as predictors of disease severity in COVID-19 6 , including procalcitonin (PCT). PCT is a biomarker previously used for distinguishing viral infections from bacterial infections 7 , although its use in the ED for this purpose is controversial 8,9 . Elevated PCT levels are often seen in patients with a bacterial infection. PCT is the prohormone of calcitonin and in a physiological state produced by C-cells of the thyroid gland. During in ammation, PCT is synthesized in all tissues. Bacterial toxins are well known triggers of synthesis of PCT. Other triggers of synthesis include interleukin-6 and tumor necrosis factor alpha (TNF-alpha). 10,11 High levels of these cytokines have been reported in severe COVID-19 infections 12 . For this reason, PCT may also be elevated in a hyperin ammatory state in the absence of a bacterial pathogen. ARDS is clinically the most important severe complication of COVID-19, therefore PCT may be predictive of hyperin ammation and the development of ARDS 13 . This may aid physicians in the ED to identify patients that are at risk of developing ARDS early.
The goal of this study is to investigate the predictive value of PCT on severe COVID-19 infections in the ED.

Methods
In this retrospective single center cohort study we included patients who visited the ED of Erasmus University Medical Center, in Rotterdam, the Netherlands, with a con rmed COVID-19 infection between 1 March 2020 and 31 December 2020. Erasmus University Medical Center is an academic hospital with 40.000 ED visits annually. The institutional review board waivered informed consent for the retrospective use of clinical data of COVID-19 patients.

Inclusion and exclusion criteria
Patients were included if they tested positive on COVID-19 positive by PCR test at the day of the ED visit, the reason for ED visit was related to the COVID-19 infection and PCT levels were measured in the ED. Patients were excluded if the PCT levels were measured but invalid (e.g. hemolytic blood samples), if the COVID-19 infection was a secondary nding and not the primary reason for ED visit or when no follow-up data were available due to transfer to another hospital.

Data collection
Patient data including demographics, comorbidities, vital signs and laboratory tests were collected from the electronic patient records. Vital signs including heart rate, arterial oxygen saturation, respiratory rate, temperature and blood pressure were recorded from the time of ED visit. Laboratory testing during the ED visit included hemoglobin, red cell distribution width (RDW), leucocyte count, thrombocytes, total bilirubin, alanine aminotransferase (ALAT), aspartate aminotransferase (ALAT), lactate, D-dimer, C-reactive protein (CRP) and PCT. Patients were followed up for 30 days after hospital discharge. Patient disposition from the Mortality data was categorized into in-hospital mortality and mortality at home within 30 days after hospital discharge. To correct for potential bacterial coinfections at ED visit, culture within 48 hour of ED visit were reviewed. If cultures or pneumococcal or legionella antigen tests were positive, patients were classi ed as bacterial coinfection.

Primary outcome
The primary outcome was a severe COVID-19 infection, de ned as patients that were admitted to the ICU and patients that died during 30 days follow-up.

Secondary outcomes
The secondary outcomes of this study were hospital admission, ICU admission and mortality. We calculated odds ratios (ORs) for the primary and secondary outcomes for commonly used cut-off values of PCT of 0.25 ng/mL, 0.5 ng/mL and 1.0 ng/mL.

Procalcitonin measurement
PCT analysis was available as a standard laboratory test in patients who visited the ED with a suspected COVID-19 infection. Blood was collected in a lithium heparin tube and analyzed directly upon arrival in the clinical chemistry laboratory. PCT was measured using E801 Elecsys BRAHMS PCT reagent on a COBAS 8000 (Roche Diagnostics, Switzerland). The PCT values were available to the treating physician during the ED visit.

Statistical analysis
Normally distributed variables were reported as mean with standard deviation (SD), non-normally distributed variables as median with interquartile range (IQR). Multiple imputation was used for handling missing data.
Differences in dichotomous variables between the severe and non-severe COVID-19 infection patients were analyzed with chi-square tests. Differences in continuous variables were analyzed using an independent sample T-test for normally distributed data and a Mann-Whitney-U test for non-normally distributed data.
For the primary outcome, we calculated unadjusted odds ratios of the variables that were signi cantly different between groups using univariate logistic regression analysis. We calculated adjusted ORs of PCT correcting for only bacterial coinfection and for gender, age bacterial coinfection and comorbidities. We constructed receiver operating characteristic (ROC) graphs and calculated the corresponding area under the curve (AUC)of continuous variables to report the predictive value on severe COVID-19 infection.
We reported PCT as a continuous variable for the primary outcome.
For the secondary outcomes, we used prede ned cutoff values of 0.25 ng/mL, 0.5 ng/mL, 1.0 ng/mL of PCT and calculated the unadjusted ORs, the sensitivity, speci city, negative predictive value and positive predictive value on the primary and secondary outcomes of the study. Statistical analyses were performed using 'R' version 3.6.2. We used the MICE package for multiple imputation of missing data.

Results
Between 1 March 2020 and 31 December 2020, a total of 477 patients visited the ED with a con rmed COVID-19 PCR at the day of the ED visit. Procalcitonin was measured in 339 of these patients. Four patients were excluded due to an invalid procalcitonin measurement, two patients were excluded because the ED visit was not related to the COVID-19 infection and one patient was excluded because there was no follow up data available. A total of 332 patients were included in the nal analysis of this study. (Fig. 1) There was missing data in 3% of the data. These missing data were imputated using multiple imputation. The amount of missing data per variable are shown in Supplementary File A.  Table 1. The severe COVID-19 group was signi cantly older, more often male and had more frequently diabetes mellitus and any form of immunode ciency as comorbidity. In vital parameters there was a signi cant difference in heartrate, respiratory rate, oxygen saturation and diastolic blood pressure. In  Table 2).
We performed an univariate logistic regression analysis of the continuous variables that signi cantly differed between the non-severe and severe COVID-19 infection groups. The results of this univariate regression analyses are shown in Table 3.
We tested PCT at different cut-off values on the primary and secondary endpoints as shown in Table 4. We    infections. PCT synthesis is upregulated by different cytokines such as interleukine-6 and TNF-alpha.
Because hyperin ammation is shown to be an important factor in progression of COVID-19 infections, the dysregulated immune response may also trigger PCT production 4 . Similar results of elevated PCT levels were found in patients with isolated severe in uenza virus infections, which supports the hypothesis that PCT is a marker of hyperin ammation 19 .
At different cut-off values, PCT showed a high speci city for the primary and secondary outcomes of this study. On hospital admission, the lowest cut-off value of 0.25 ng/mL resulted in a speci city of 97%. This could be used as tool for hospital disposition decisions because the majority of patients with a PCT above 0.25 ng/mL was admitted to the hospital. Different cut-off values of PCT are recommended in distinguishing bacterial from viral infections, also ranging from 0.25 ng/mL to 1.0 ng/mL 20 . The cut-off values we used in this study correspond to these cut-off values.

Strengths And Limitations
The large patient population strengthens the ndings of this study. Furthermore, the patient population consisted solely of con rmed COVID-19 patients. Therefore, the results are not biased by patients who visited the ED with a suspected COVID-19 infection but were diagnosed with an alternative diagnosis. The results of this study cannot be used for distinguishing a COVID-19 infection from other viral or bacterial infections 17 .
PCT was only measured in patients where the primary reason of the ED visit was suspected COVID-19 infection. Patients that were initially not suspected of having COVID-19, but were diagnosed with a COVID-19 infection, did not have PCT measured and are therefore not included in this study.
PCT was prospectively measured in the ED and available to the treating physician, along with other routinely measured laboratory tests. PCT levels may have been used in clinical decision making and in uenced disposition decisions.

Declarations
Ethics approval and consent to participate Not applicable.

Consent for publication
Not applicable.

Availability of data and materials
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests
The authors declare that they have no competing interests.

Funding
This manuscript was not funded by any funding body.   This is a list of supplementary les associated with this preprint. Click to download. SupplementaryFileA.docx