A cytokine panel and procalcitonin in COVID-19, a comparison between intensive care and non-intensive care patients.

OBJECTIVES: Procalcitonin (PCT) is an acute-phase reactant with concentrations ≥0.5 μg/L indicative of possible bacterial infection in patients with SARS-CoV-2 infection (COVID-19). Some with severe COVID-19 develop cytokine storm secondary to virally driven hyper-inflammation. However, increased pro-inflammatory cytokines are also seen in bacterial sepsis. This study aimed to assess the clinical utility of a cytokine panel in the assessment of COVID-19 with bacterial superinfections along with PCT and C-reactive protein (CRP).
METHODS: The retrospective analysis included serum cytokines (interleukins; IL-1β, IL-6, IL-8 and tumour necrosis factor (TNFα)) measured using Ella™ (Bio-Techne, Oxford, UK) and PCT measured by Roche Cobas (Burgess Hill, UK) in patients admitted with COVID-19 between March 2020 and January 2021. Patients enrolled into COVID-19 clinical trials, treated with Remdesivir/IL-6 inhibitors were excluded. The cytokine data was compared between intensive care unit (ICU) patients, age matched non-ICU patients and healthy volunteers as well as ICU patients with high and normal PCT (≥0.5 vs. <0.5 μg/L).
RESULTS: Cytokine concentrations and CRP were higher in COVID-19 patients (76; ICU & non-ICU) vs. healthy controls (n = 24), all p<0.0001. IL-6, IL-8, TNFα and were higher in ICU patients (n = 46) vs. non-ICU patients (n = 30) despite similar CRP. Among 46 ICU patients, the high PCT group (n = 26) had higher TNFα (p<0.01) and longer ICU stay (mean 47 vs. 25 days, p<0.05). There was no difference in CRP and blood/respiratory culture results between the groups.
CONCLUSIONS: Pro-inflammatory cytokines and PCT were higher in COVID-19 patients requiring ICU admission vs. non-ICU admissions despite no difference in CRP. Furthermore, TNFα was higher in those with high PCT and requiring longer ICU admission despite no difference in CRP or rate of bacterial superinfection.

Introduction

Coronavirus disease 2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to challenge medical centres across the world. Severe COVID-19 infection in some patients can activate excessive inflammatory response leading to overproduction of pro-inflammatory cytokines including interleukin 6 (IL-6), interleukin 1β (IL-1β) and tumour necrosis factor α (TNFα) which has been described as cytokine storm (CS) [1]. CS is a life-threatening condition that can lead to extensive tissue damage. In patients with severe COVID-19, CS is associated with lung injury, multi organ failure and poor prognosis [2-4]. Thus, early recognition and management of CS by targeting cytokines and modulating immune response could improve the outcome in these patients [1, 5]. While effective treatment options for COVID-19 remain limited, this clinical approach is widely used in many institutions.

IL-6 is one of the key mediators of the immune system and recently has been reported as a critical cytokine in COVID-19 associated CS [6]. While several studies have shown that elevated concentrations of IL-8 and TNFα correlate with severity of COVID-19 [4, 7, 8], IL-6 dysregulations appear to have the most profound effect in CS, with high concentrations associated with respiratory failure, poor prognosis and mortality [4, 6, 9, 10].

C-reactive protein (CRP) is an inflammatory marker that is raised in majority of patients with COVID-19 [11]. However, CRP does not necessarily indicate bacterial infection, with the highest concentrations commonly seen in more severe cases [11]. The major limitation of CRP is its low specificity in differentiating bacterial infection from autoimmune diseases and some haematological malignancies [12].

Procalcitonin (PCT) is an acute phase reactant peptide that increases significantly in the presence of bacterial infections while its concentrations are usually not elevated in viral infections [13]. Thus, PCT has been suggested as a useful biomarker to differentiate bacterial and viral infections with concentration ≥0.5 μg/L suggestive of a possible bacterial infection [14]. Furthermore, decrease in PCT could also indicate a good response to antibiotic therapy [15]. Nonetheless, similar to CRP, elevated PCT is not 100% specific for bacterial infections and can be seen in other systemic inflammatory responses [12]. For example, following major surgery, trauma, burns, invasive fungal infections and prolonged septic shock [14].

Several studies have shown that patients with more severe COVID-19 have higher PCT concentrations. Yet, it is not clear whether this is related to bacterial superinfection, severity of viral infection or combination of both [16]. Low specificity of PCT and its relatively long half-life have limited its use [12]. Using cytokines in combination with PCT may help to identify bacterial superinfection in COVID-19 [12]. Holub et al. reported that PCT, IL-6 and TNFα concentrations were significantly higher in bacterial infection compared to viral infection [12]. The same study showed that raised IL-6 and TNFα dropped within three days of antibiotic therapy to concentrations seen in control group, which included healthy participants [12].

In 2020, we introduced a cytokine panel (IL-1β, IL-6, IL-8 and TNFα) in our laboratory at King’s College Hospital, UK, in response to the pandemic to help in the assessment of COIVD-19 patients. Each component in the panel was selected based on published literature on SARS-CoV-2 infection [17, 18]. The panel was validated within our laboratory as per our standard operating procedure with meets the medical laboratory standards (ISO 15189) of the National Accreditation Body for the United Kingdom (UKAS). While IL-6 assay is more widely available in the UK, the above cytokine panel is unique to King’s College Hospital. The panel was offered for patients with suspected COVID-19 as part of their laboratory work-up.

The aim of our study was to compare PCT and CRP with the cytokine panel between ICU and non-ICU patients admitted to a London teaching hospital during the COVID-19 pandemic. Cytokine data was also compared with healthy volunteers.

Methods

We retrospectively reviewed the laboratory information management system (LIMS–Clinisys) to identify patients admitted to King’s College Hospital NHS Foundation Trust, London, a 950 bedded tertiary hospital, between March 2020 and January 2021, with positive SARS-CoV-2 RT-PCR and having had a cytokine panel and PCT requested as part of their clinical care. Lambda and Gamma variants of SARS-CoV-2 were more prevalent in London during the initial study period followed by Alpha variant in the latter months. The study was approved by the King’s College Hospital Clinical Audit Committee (Ref ENDOC01) and the need for informed consent was waived. Medical records were accessed between June and December 2021. All data was anonymised prior to analysis and confidentially was maintained during analysis and storage.

102 ICU patients from COVID-19 ICU, and 62 age-matched non-ICU patients were randomly selected during the study period and their electronic medical records were reviewed. The primary reason for hospital admission of the patients in this study was suspected COVID-19 infection based on clinical/radiological evidence, which was subsequently confirmed with positive SARS-CoV-2 RT-PCR. 75 patients were excluded from the study as they were either enrolled into COVID-19 clinical trials or were on Remdesivir or IL-6 antagonist as part of COVID-19 treatment which could modify cytokine concentrations. Patients who did not have same day PCT with cytokine panel were also excluded to minimise variations in patients’ individual infective state. A total of 46 ICU patients and 30 non-ICU patients were included in final analysis along with 24 healthy volunteers (Fig 1).

Fig 1

Flow chart of patient selection based on inclusion and exclusion criteria.

Healthy volunteers were recruited from our laboratory. They had no known medical conditions, had normal body mass index (BMI), were not on any medications and were asymptomatic at the time of blood sampling. All volunteers provided written consent as part of our evaluation process of the cytokine panel. This recruitment took place in April 2020, when diagnostic testing for asymptomatic individuals was not implemented in the UK. However, neither the volunteers nor their households had the common symptoms of COIVD-19 (high temperature, new or persistent cough, shortness of breath, loss of taste or loss of smell). Furthermore, their CRP was 1.00 (1.00–1.75) mg/L median (IQR) which suggested that they did not have active inflammation.

The local policy for ICU admission was based on the 40% (10L) or more oxygen requirement of the patient or rapid increase in oxygen requirements. In this study, all ICU patients receiving mechanical ventilation. Based on our ICU clinical guidelines, patients were divided into two groups; those with elevated PCT ≥ 0.5 and those with normal PCT < 0.5 μg/L. All patients (ICU + non-ICU) were on Empiric Antibiotic therapy. Bacterial infection was identified base on positive cultures within 48 hours from the request for PCT and cytokine panel. In our cohort, bacterial infections occurred ≥48 hours following admission to hospital for COVID-19 thus, these infections are defined as superinfections. Among all patients admitted with COVID-19, 75% (58% ICU and 96% non-ICU) were on glucocorticoid as part of COVID-19 treatment.

Sample collection

For cytokine panel, samples were collected in a serum separator tube (BD Vacutainer SST). All samples were kept at room temperature for 30 minutes prior to centrifugation for 15 minutes at 1000 x g. Serum aliquots were stored at -80°C and analysed within two days. IL-1β, IL-6, IL-8 and TNFα concentrations were quantified using the Simple PlexTM Ella (EllaTM) (ProteinSimple, Bio-Techne, Oxford, UK), an automated immunoassay platform that allows the rapid quantitation of these four analytes from a single disposable microfluidic cartridge. PCT samples were collected in SST or lithium heparin plasma (BD Vacutainer) and analysed by Roche Cobas (Burgess Hill, UK).

Cytokine panel performance characteristics

Quality Control (QC) material

Bio-Techne cytokine quality controls (QC) include a high and a low level, which were analysed with every assay. Each QC has predetermined values that are reagent lot specific. Performance was further assured through the linear standard curve with a percent coefficient of variance (%CV) of < 10% and a recovery of 80–120%.

Limits of Quantification (LoQ)

The lower and upper limits of quantification in serum diluted 1:2 were; IL-1β (0.32–3060 pg/ml), IL-6 (0.56–5304 pg/ml), IL-8 (0.38–3608 pg/ml) and TNFα (0.6–2320 pg/ml).

Endogenous concentrations

The serum endogenous cytokine concentrations calculated from the 24 healthy volunteers were; IL-1β (0.00–0.66 pg/ml), IL-6 (0.00–3.26 pg/ml), IL-8 (2.20–21.87 pg/ml) and TNFα (6.10–13.58 pg/ml).

Precision

The %CV of inter-assay precision for all four cytokines ranged between 3–5% for low QC and 4–9% for high QC. The % CV for intra-assay precision ranged between 3–5% for low QC and 4–9% for high QC.

Correlation

EllaTM IL-6 correlation with IMMULITE® 2000 IL-6 (Siemens Healthineers, Frimley, UK) and Evidence Investigator™ (Randox, Crumlin, UK). Cytokine and Growth Factors High-Sensitivity Array showed comparable data with R2 values of 0.98 and 0.98 respectively.

Freeze/Thaw cycle

The effects of up-to two freeze thaw cycles on cytokine concentrations were evaluated for IL-6, IL-8 and TNFα. The results from one and two freeze thaw cycles were comparable with R2 values of 0.99. All test samples included in the final analysis underwent only one freeze thaw cycle.

Statistical analysis

Analyse IT (Microsoft, version 5.2) was used for statistical analysis. Distribution of the data were assessed using Shapiro- Wilk test and were analysed by non-parametric Mann Whitney U or Kruskul Wallis test as appropriate. Chi-square was performed for binary data. Spearman’s Rank Correlation Coefficient was used for correlations between analysts. A p value < 0.05 was considered a statistically significant result. Data is reported as mean (SD) or median (inter-quartile range (IQR)).

Results

The final analysis of the clinical cohort included, 24 healthy volunteers aged 33 (7) years, 46 ICU patients and 30 non-ICU age-matched (55 (9) years) patients. 56% of ICU patients, 63% of non-ICU patients and 38% of healthy volunteers were males.

Cytokine panel in patients with COVID-19 vs. healthy volunteers

IL-1β, IL-6, IL-8, TNFα and CRP in the hospitalised patients with COVID-19 (n = 76) was higher (all p<0.0001) compared to the healthy volunteers. The higher values vs. the healthy volunteers were noted in COVID-19 patients irrespective of ICU or non-ICU admission (Table 1).

Table 1

Cytokine panel and CRP between ICU, non-ICU patients and healthy volunteers.

Analyte	ICU patients	Non-ICU patients	Healthy Volunteers	P value
	(n = 46)	(n = 30)	(n = 24)
IL-1β (ng/L)	0.35 (0.32–0.66)	0.32 (0.32–0.32)	0.11 (0.05–0.21)	<0.0001
IL-6 (ng/L)	36.50 (16.07–127.50)	17.45 (7.90–51.60)	0.99 (0.62–1.42)	<0.0001
IL-8 (ng/L)	72.20 (49.47–115.50)	40.60 (29.00–60.50)	10.55 (7.58–15.67)	<0.0001
TNFα (ng/L)	25.00 (18.08–35.75)	16.35 (14.10–19.80)	9.83 (8.40–11.27)	<0.0001
CRP (mg/L)	92.5 (54.9–137.3)	105.0 (68.2–146.2)	1.00 (1.00–1.7)	<0.0001

Data is presented as median (IQR).

Abbreviations: IL-1β, interleukin-1β; IL-6, interleukin-6; IL-8, interleukin-8; TNFα, tumour necrosis factor alpha; CRP, C-reactive protein.

Cytokine panel in ICU patients and non-ICU patients with COVID-19

The length of stay for ICU patients was 35 (23–59) days. The total duration of hospital admission for ICU patients was longer 60 (32–87) days compared to non-ICU patients 10 (7–15) days, p<0.00001.

Overweight/obesity (BMI ≥ 25 kg/m2), followed by hypertension and diabetes were the most common co-morbidities in our COVID-19 cohort. The BMI and prevalence of hypertension, diabetes, lung disease, cardiovascular disease and chronic kidney disease were similar between ICU and non-ICU patients (Table 2).

Table 2

Common co-morbidities in ICU vs. non-ICU patients with COVID-19.

Comorbidities	ICU patients	Non-ICU patients	P value
	(n = 46)	(n = 30)
BMI ≥ 25 kg/m 2	31 (67%)	17 (57%)	0.34
Hypertension	17 (37%)	14 (47%)	0.40
Diabetes	11 (24%)	10 (33%)	0.37
Lung disease *	9 (20%)	5 (17%)	0.75
CVD	5 (11%)	5 (17%)	0.46
CKD	7 (15%)	3 (10%)	0.51

Abbreviations: BMI, body mass index; CVD, cardiovascular disease; CKD, chronic kidney disease.

*Patients with background of lung disease had one of the following: Chronic obstructive pulmonary disease (COPD), Obstructive sleep apnoea (OSA), interstitial lung disease (ILD) and Asthma (moderate and severe)

The comparison of IL-1β, IL-6, IL-8 and TNFα, PCT and CRP concentrations in both groups are summarised in Table 3. IL-6, IL-8, TNFα and PCT were higher in ICU patients vs. non-ICU patients (all, p<0.05). However, there was no difference in CRP between the two groups. In non-ICU group, only four patients (13%) had high PCT (≥ 0.5 μg/L) compared to 26 (57%) in ICU patients.

Table 3

Cytokines, PCT and CRP in ICU vs. non-ICU patients with COVID-19.

Analyte	ICU patients	Non-ICU patients	P value
	(n = 46)	(n = 30)
IL-1β (ng/L)	0.35 (0.32–0.66)	0.32 (0.32–0.32)	0.07
IL-6 (ng/L)	36.50 (16.07–127.50)	17.45 (7.90–51.60)	0.03
IL-8 (ng/L)	72.20 (49.47–115.50)	40.60 (29.00–60.50)	<0.001
TNFα (ng/L)	25.00 (18.08–35.75)	16.35 (14.10–19.80)	<0.0001
PCT (μg/L)	0.65 (0.30–1.98)	0.18 (0.12–0.29)	<0.0001
CRP (mg/L)	92.5 (54.9–137.3)	105.0 (68.2–146.2)	0.77

Data is presented as median (IQR).

Abbreviations: PCT, procalcitonin; IL-1β, interleukin-1β; IL-6, interleukin-6; IL-8, interleukin-8; TNFα, tumour necrosis factor alpha; CRP, C-reactive protein.

Since fewer patients (58%) in ICU were receiving glucocorticoid compared to non-ICU (96%) patients, we compared cytokine concentrations, PCT and CRP between ICU patients on glucocorticoids (n = 27) vs. those not on glucocorticoids (n = 19) and there were no differences (all, p>0.05). We also compared ICU patients on glucocorticoids (n = 27) with non-ICU patients on glucocorticoids (n = 29). The IL-6, IL-8, TNFα and PCT were higher in ICU patients (all, p<0.05) with no difference in CRP or IL-1β between the two groups (both, p>0.05).

Cytokine panel in ICU patients with COVID-19 (high PCT vs. normal PCT)

Among ICU patients, 26 (56%) had a PCT ≥ 0.5 μg/L. Cytokine and CRP in patients with high PCT (≥ 0.5 μg/L) and normal PCT (< 0.5 μg/L) are summarised in Table 4. TNFα concentration was higher in high PCT group vs. normal PCT group, p<0.01. Patients with high PCT had longer ICU stay 47 (27–64) vs. 25 (20–38) days, p<0.05.

Table 4

Cytokines and CRP in ICU patients with high and normal PCT.

Analyte	PCT ≥ 0.5 μg/L	PCT < 0.5 μg/L	P value
	(n = 26)	(n = 20)
IL-1β (ng/L)	0.45 (0.32–1.03)	0.32 (0.33–0.40)	0.12
IL-6 (ng/L)	44.95 (25.85–119.75)	25.30 (14.97–130.50)	0.41
IL-8 (ng/L)	72.20 (51.05–116.57)	69.00 (47.70–112.50)	0.92
TNFα(ng/L)	33.55 (24.92–38.92)	20.25 (13.97–23.35)	<0.01
CRP (mg/L)	108.6 (60.0–223.7)	81.8 (54.9–106.5)	0.11

Data is presented as median (IQR).

Abbreviations: PCT, procalcitonin; IL-1β, interleukin-1β; IL-6, interleukin-6; IL-8, interleukin-8; TNFα, tumour necrosis factor alpha; CRP, C-reactive protein

At the time of sample collection for the cytokine panel, all patients were receiving broad-spectrum antibiotics and in total nine (19%) were on adjunctive anti-fungal treatment (25% in normal PCT group and 15% in high PCT group). Forty eight percent of patients in ICU had positive culture for bacterial growth within 48 hours from PCT and cytokine requests compared to 10% in the non-ICU group. Out of all positive cultures, 84% were respiratory samples (sputum, bronchial washing and bronchoalveolar lavage), 8% were blood samples and 8% were urine samples. The most common pathogens identified from cultures were Gram negative bacteria including Klebsiella pneumoniae, Pseudomonas aeruginosa, Serratia marcescens, Enterobacter cloacae and E.coli. The only two gram-positive bacteria that was isolated were Staphylococcus aureus (sputum) and Enterococcus faecium (urine). There was no difference in rate of positive cultures between the high PCT and normal PCT ICU patients (p = 0.73).

There was no difference in age (p = 0.58) or BMI (p = 0.76) between female and male patients admitted to ICU. However, males had higher concentrations of PCT (p<0.00001) and TNFα (p<0.001) and longer ICU stay (p<0.01) compared to the females.

Correlation of cytokine panel, PCT and CRP

In ICU patients, PCT concentrations correlated with TNFα (r = 0.79, p<0.0001), IL-1β (r = 0.36, p = 0.009) and IL-8 (r = 0.43, p = 0.02) while CRP correlated with both IL-6 (r = 0.66, p<0.001) and IL-1β (r = 0.42, p = 0.02). In non-ICU patients, PCT correlated only with TNFα (r = 0.37, p = 0.04). No correlations were observed between CRP and the cytokines.

Discussion

We have demonstrated that using a cytokine panel (pro-inflammatory cytokines; IL-1β, IL-6, IL-8 and TNFα) in combination with PCT could be useful in the assessment SARS-CoV-2 infection severity. IL-6, IL-8, TNFα and PCT were significantly higher in ICU patients compared to non-ICU patients. Furthermore, ICU patients with elevated PCT had higher TNFα and longer ICU stay compared to normal PCT group. In our ICU cohort, males had higher TNFα, PCT and longer ICU stay with COVID-19 compared to females.

Cytokines are essential part of the host immune response against various pathogens. IL-1, IL-6 and TNFα are three main pro-inflammatory cytokines that are produced by endothelial and epithelial cells, macrophages and mast cells during innate immune response against viral infection [1]. Furthermore, IL-1, IL-6 and TNFα, have been reported as the pathogenic factors produced by macrophages after T lymphocytes bearing T-cell receptors recognise SARS-CoV-2 bound to the surface of cells [19]. SARS-CoV-2 enter the bronchial epithelium of the upper and lower airway and provoke local inflammatory cascades that involve neutrophil recruitment, T lymphocyte trafficking and activation of resident monocytes. The virus activates the humoral immune response to cause increased secretion of pro-inflammatory cytokines [20]. These cytokines maybe responsible for tissue destruction in various organs in patients with COVID-19 [19].

SARS-CoV-2 infection in some patients can trigger an acute exaggerated immune response with sudden increase in pro-inflammatory cytokines, which is known as CS [1, 21, 22]. In our study, selected inflammatory cytokines were analysed as potential biomarkers to help identify virally driven inflammation and bacterial superinfection.

Differentiating between inflammatory response driven by the virus and secondary bacterial infection could be challenging in managing patients with COVID-19. High CRP is seen in majority of patients with COVID-19 with higher concentrations associated with severity of COVID-19 and it does not necessarily help identify bacterial superinfection [11]. A meta-analysis of four studies showed PCT concentrations were associated with more severe COVID-19 infection [16]. However, in patients with non-complicated COVID-19, PCT could remain within normal reference limits [16]. The authors suggested that elevated PCT in patients developing severe COVID-19 could possibly reflect bacterial superinfection [16]. In accordance with this meta-analysis, our study showed that ICU patients had higher PCT compared to non-ICU patients. Furthermore, ICU patients with PCT >0.5 μg/L had longer ICU stay vs. the low PCT group, whilst there was no difference in CRP between the two groups.

PCT has a relatively long half-life, which could limit its use [12]. Using cytokines in addition to PCT may help in identifying bacterial infections in COVID-19. We also reviewed the correlation of cytokines with CRP and PCT in order to assess whether they will equally assist in identifying bacterial infections. Holub et al, analysed several inflammatory cytokines along with CRP and PCT in 21 patients with community acquired pneumonia and 26 patients with viral infections [12]. Their results showed that IL-6 and TNFα were higher in bacterial infections compared to viral infections and elevated cytokine concentrations dropped within three days of antibiotic therapy [12]. The same study also showed positive correlation between TNFα and PCT which was in keeping with our data in the COVID-19 cohort. In addition, in our cohort both IL-1β and IL-8 correlated positively with PCT. Nonetheless, these correlations were weak and larger studies are required to better assess them.

Gong et al, analysed inflammation markers in 100 patients suffering from mild, severe and critical COVID-19 infection and reported that IL-8 concentrations were associated with COVID-19 severity [7]. In our study, high PCT group had higher TNFα and longer ICU stay and there was a positive correlation between PCT and TNFα. In clinical setting, this positive correlation may strengthen the predictability of the disease severity. One possible explanation for the high PCT group requiring longer ICU stay could be bacterial superinfection. However, no difference was found between the rates of confirmed bacterial infections based on positive cultures between high vs. normal PCT groups. This could have been due to treating patients with antibiotics prior to requesting samples for cultures. Our results were similar to the study by Hu et al. in which PCT was associated with disease severity however; the percentage of bacterial infections in severe and critical COVID-19 were lower than the percentage of elevated PCT [22]. Thus, larger studies are needed to investigate the underlying mechanisms driving PCT concentrations in SARS-CoV-2 infection.

CRP production and release from liver is stimulated by IL-6. Additionally, IL-6 and CRP have been associated with COVID-19 severity, with IL-6 being the most frequently reported cytokine elevated in COVID-19 associated CS [21, 23]. Furthermore, higher IL-6 has been shown to be associated with severity and higher mortality rate in COVID-19 [4, 6, 24, 25]. The Randomised Evaluation of COVID-19 Therapy (RECOVERY trial) reported that treatment with Tocilizumab (IL-6 receptor antagonist), improves outcome in patients hospitalised with severe COVID-19 infection [26]. This effect was additional to benefits previously reported for Dexamethasone treatment in patients hospitalized with COVID-19 [24]. The National Institute for Health and Care Excellence (NICE) guidelines has recommended Tocilizumab treatment in patients with COVID-19 receiving Oxygen treatment with a CRP of ≥ 75 mg/L provided there is no evidence of bacterial or other viral infections that could be worsened by immunosuppression [27]. A prospective cohort study of 89 patients showed that high concentrations of IL-6 followed by CRP could predict respiratory failure and the need for mechanical ventilation in patients admitted with COVID-19 with significant time difference between CRP and IL-6 in favour of IL-6 [28]. In our study however, despite significant increase in IL-6 in ICU patients vs. non-ICU patients, there was no difference in CRP between the two groups.

IL-1 is another important cytokine family in CS. One of the actions of IL-1β, which belongs to the IL-1 family, is upregulation of IL-6. Thus, the IL-1/IL-6/CRP axis plays a key role in the inflammation process [29]. In our COVID-19 cohort, CRP correlated positively with both IL-6 and IL-1β but there was no significant correlation between PCT and IL-6. It could be that the severity of COVID-19 in these patients with high IL-6 was due to virus driven inflammation rather than bacterial superinfection.

Our study has several limitations. It was a retrospective study design involving a small cohort. The healthy volunteer group was younger than the patient groups and their COVID-19 status was not confirmed by RT-PCR. We did not match for common co-morbidities between ICU and non-ICU patients however, the overall rate of co-morbidities between the two groups were similar.

Conclusions

We have reported the application of a cytokine panel (serum, IL-1β, IL-6, IL-8 and TNFα) using the automated Ella™ platform and its potential clinical utility in the assessment of patients with COVID-19. In our cohort, ICU patients had higher IL-6, IL-8, TNFα and PCT compared to non-ICU patients. Despite no difference in CRP or rate of confirmed bacterial superinfection, ICU patients with high PCT had higher TNFα and longer ICU admission with COVID-19. Further prospective studies are needed in larger well-defined cohorts to establish the routine use of this cytokine panel in an ICU setting and to elucidate the mechanisms by which PCT is increased in severe COVID-19.

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Abstract:

- in general, the "intensive care unit" is referred to the "ICU". Many health care system will also indicate whether the patient will be managed in the different specific ICUs, like medical ICU (MICU) or surgical ICU (SICU), but typically we refer to this level of care as an ICU. In the UK, where this study was done, ITU refers to the "intensive therapy unit" which from what I am reading is a direct correlate to the ICU as described in areas of the world like the United States. Since this publication is likely going to reach a global audience, I would suggest using ICU throughout the manuscript but if ITU is kept then the abbreviation should be placed in the title and "intensive therapy unit" should be used throughout.

Methods:

- Line 122: please indicate how many patient beds are available at the hospital and the exact name of the Hospital where the study was conducted

- In the methods section, you should include what were the general requirements for those admitted to the ICU at your hospital. For example, what level of oxygen supplementation was the minimum requirement to be admitted? Were these all patients placed on mechanical ventilation? I would include that in you methods and would even consider to include in the analysis.

- a small flow diagram of those inlcuded/excluded and reasons would be useful for the readers

- From the 63 age-matched non-ITU patients, how did you make that match? Did you match other chronic conditions? There could be a sampling bias at hand but this should be discussed.

- Do we know who was on glucocorticoids and who was not?

- Do we know which SARS-CoV-2 variant was circulating in this regions during the study period? I would include that.

Results:

- I think it is very important to discuss the clinical factors of those with and without COVID-19 as it relates to the cytokine and CRP testing; it is great to compare to healthy volunteers as a control but were they tested for COVID-19? Could they have been asymptomatically infected? Please explain the recruitment of the healthy volunteers.

- Common comorbidities to consider in the analysis would be: Diabetes Mellitus, Hypertension, Obesity, Chronic Kidney Disease, Chronic Obstructive Pulmonary Disease, and others processes.

Discussion:

- I would add some discussion on IL-6 and CRP in the clinical context of COVID-19 and initiation of certain immune-modulating medications, like tocilizumab, or barcitinib, among others, who are found to have high initial CRP and IL-6. In the U.S., guidelines are now suggesting use in certain populations who have CRP greater than or equal to 75 mg/L and rapidly increasing oxygen requirements. I would also cite a large trial like the RECOVRY trial which was conducted in the UK. NHS also recommends IL-6 inhibitors in certain populations. A discussion on the results as it pertains to clinical use is suggested.

Limitations needs attention. Do we know who was glucocorticoids (I would not use steroids). Small sample size is a big limitation and needs to be acknowledged. What does "some patients were requiring organ support" mean? This is why it is important to assess how patients were matched, what level of ICU care was needed and comorbidities of the cohort.

Reviewer #2: This article discussed relationships between cytokines, procalcitonin, and C-reactive protein among COVID-19 patients in London during certain months of the pandemic. The authors compared cytokines, PCT, and CRP between COVID-19 patients and healthy volunteers and also between ITU patients and non-ITU patients. The authors suggest previous research with cytokines to help determine any difference between viral infection and bacterial infection. The authors also admit that further research is needed to assess the relationship between findings from a cytokine panel and COVID-19.

Investigation of the inflammatory response among COVID-19 patients, such as those in an ITU setting, is important for clinical practice. While the intentions of this study are valid, it is difficult to follow the main aim and resulting comparisons included in the analysis. The Methods need to be clearer, especially with defining the study population and inclusion terms, and the overall organization of the paper needs improvement.

Major Comments:

In the Introduction, include a description or paragraph about the “recently validated cytokine panel” as stated in lines 115-116. Give more background information on this panel, as this cytokine panel is one of main topics of this paper. How was this particular panel validated? How was this panel used previously? Briefly, how does this panel work?

The aim of the paper states that there were assessments of concurrent bacterial infections with COVID-19; however, there is a lack of descriptions about concurrent bacterial infections. In the Methods section, include how bacterial infections were assessed. Which bacterial testing was used? Which bacteria could be detected on these tests? When were patients included in this study tested for concurrent bacterial infection? In the Discussion, it is unclear how the findings are directly related to the main aim of assessing bacterial co-infection.

The Methods and Results sections include comparisons with 24 healthy volunteers; however, it is unclear how the volunteers were chosen for this study. How were these volunteers chosen? Were these volunteers matched at all (the non-ITU patients were age-matched)? When were these volunteers sampled? Were the volunteers sampled during the same timeframe as the other patients? Describe the criteria needed to be considered “healthy.” Also, the Introduction sets up the study to compare ITU and non-ITU patients, so some explanation about the COVID-19 patients versus “healthy” volunteers is needed earlier in the paper. Were comparisons made between ITU patients, non-ITU patients, and “healthy” volunteers? A three-way comparison with “healthy” volunteers as the referent may be more elucidating.

Minor Comments:

Line 87: Make a new paragraph for CRP descriptions.

Lines 111-113: Clarify which study is referenced here and describe the control group used in that study. Introduce the study more clearly earlier in this paragraph.

Lines 117-118: Give some context about COVID-19 incidence in London during the study period and how the cytokine panel was used at this particular hospital. Give the months/year of the “peak” pandemic time.

Line 122: State the specific months/year that included the patients in this study.

Line 123: When were patients tested for SARS-CoV-2? Was there a specific timeframe from exposure that these patients were tested? Was the testing implemented for diagnostic purposes or as a general hospital screening test during that time period?

Line 127: Specify how many of the 75 excluded patients were ITU or non-ITU.

Line 130: Explain why patients needed to have a same-day PCT result as the cytokine panel to be included in the study. Give the number of patients excluded based on not having same-day tests—was it 14 patients (make sure that the total numbers reflect the 76 included patients)?

Consider making a flow chart delineating the inclusion/exclusion factors for included patients.

Lines 142-144: Is this the test that was mentioned within the introduction?

Line 152: Spell out CV when it is first mentioned.

Table 1: The row for PCT is missing. Add PCT results.

Line 211: Indicate that the finding was statistically significant.

Line 247: Interleukin is misspelled.

Within the Discussion, explain why correlations were used for PCT and CRP among the ITU and non-ITU patients. Even though the correlations are statistically significant, most correlations seemed weak. How do these findings translate to clinical practice?

Line 269: How was “severity” defined? How can these higher cytokines be shown with certain clinical signs in patients?

Line 289: Add an in-text citation.

Lines 291-292: How were concurrent bacterial infections confirmed in this reference study and also in the present study?

Line 304: Add an in-text citation.

Lines 311-314: Please re-phrase this sentence, as it is difficult to follow.

Line 315: Are the “two groups” mentioned here the high and low PCT groups?

Line 328: Please specify the “two values.”

Line 355: State the number of patients (46) instead of “good number.”

There are many typographical errors, such as missing hyphens and inconsistent hyphenation, missing commas, missed spacing between words, missing articles before nouns, and missing or incorrect punctuation.

**********

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10 Jan 2022

Reviewer #1: Some suggestions:

Abstract:

- in general, the "intensive care unit" is referred to the "ICU". Many health care system will also indicate whether the patient will be managed in the different specific ICUs, like medical ICU (MICU) or surgical ICU (SICU), but typically we refer to this level of care as an ICU. In the UK, where this study was done, ITU refers to the "intensive therapy unit" which from what I am reading is a direct correlate to the ICU as described in areas of the world like the United States. Since this publication is likely going to reach a global audience, I would suggest using ICU throughout the manuscript but if ITU is kept then the abbreviation should be placed in the title and "intensive therapy unit" should be used throughout.

Response: Thank you for the suggestion. We have revised the manuscript to the preferred terminology for intensive care, ICU throughout the article.

Methods:

- Line 122: please indicate how many patient beds are available at the hospital and the exact name of the Hospital where the study was conducted.

Response: We have now included the name and bed capacity of our hospital – lines 121 -122.

- In the methods section, you should include what were the general requirements for those admitted to the ICU at your hospital. For example, what level of oxygen supplementation was the minimum requirement to be admitted?

Response: The admission to ICU was considered when the oxygen requirement of the patient was 40% (10L) or more or those who show a rapid increase in oxygen requirement – lines 155-156.

Were these all patients placed on mechanical ventilation? I would include that in your methods and would even consider to include in the analysis.

Response: All ICU patients were receiving mechanical ventilation. Included in method section– lines 156-157.

- a small flow diagram of those included/excluded and reasons would be useful for the readers

Response: We have now included the flow diagram as suggested – figure 1.

- From the 63 age-matched non-ITU patients, how did you make that match? Did you match other chronic conditions? There could be a sampling bias at hand but this should be discussed.

Response: We only matched the groups for age. Chronic conditions were not matched between ICU and non-ICU patients. However, the common chronic conditions like Diabetes, Hypertension, lung disease, chronic kidney disease and cardiovascular disease between two groups were similar and have now added in results section Table 2, Page 11.

- Do we know who was on glucocorticoids and who was not?

Response: This has now been included in lines 166-167. A new Paragraph has now added in Results section because fewer patients in ICU were on glucocorticoids compared to non-ICU patients–lines 281-287.

- Do we know which SARS-CoV-2 variant was circulating in this regions during the study period? I would include that.

Response: This has now been included in lines 127-129.

Results:

- I think it is very important to discuss the clinical factors of those with and without COVID-19 as it relates to the cytokine and CRP testing; it is great to compare to healthy volunteers as a control but were they tested for COVID-19? Could they have been asymptomatically infected? Please explain the recruitment of the healthy volunteers.

Response: Details around the recruitment of the healthy volunteers has now been included – lines 149-156.

- Common comorbidities to consider in the analysis would be: Diabetes Mellitus, Hypertension, Obesity, Chronic Kidney Disease, Chronic Obstructive Pulmonary Disease, and others processes.

Response: This has now been included in results-line 247-251 and Table 2.

Discussion:

- I would add some discussion on IL-6 and CRP in the clinical context of COVID-19 and initiation of certain immune-modulating medications, like tocilizumab, or barcitinib, among others, who are found to have high initial CRP and IL-6. In the U.S., guidelines are now suggesting use in certain populations who have CRP greater than or equal to 75 mg/L and rapidly increasing oxygen requirements. I would also cite a large trial like the RECOVRY trial which was conducted in the UK. NHS also recommends IL-6 inhibitors in certain populations. A discussion on the results as it pertains to clinical use is suggested.

Response: We have now included the conclusions of the RECOVERY trial and NICE guidelines recommendations for Tocilizumab–lines 391-399.

Limitations needs attention. Do we know who was glucocorticoids (I would not use steroids).

Response: 75% of patients (ICU & non-ICU) were on glucocorticoids as part of the management of COVID-19 and associated complications. This has now been included in the manuscript –lines 166-167 and lines 281-287.

Small sample size is a big limitation and needs to be acknowledged.

Response: We have included the small sample size as a limitation of this study. The numbers however represent a high percentage of patients to have had cytokine results vs. other hospitals in the UK treating large number of COVID-19 patients. This is due to the limited availability of routine cytokine measurement in UK labs.

What does "some patients were requiring organ support" mean? This is why it is important to assess how patients were matched, what level of ICU care was needed and comorbidities of the cohort.

Response:

All ICU patients required mechanical ventilation, which is now included – lines 159-160.

Co-morbidities between ICU/non-ICU groups is now included in table 2 and lines 247-251.

\f

Reviewer #2:

This article discussed relationships between cytokines, procalcitonin, and C-reactive protein among COVID-19 patients in London during certain months of the pandemic. The authors compared cytokines, PCT, and CRP between COVID-19 patients and healthy volunteers and also between ITU patients and non-ITU patients. The authors suggest previous research with cytokines to help determine any difference between viral infection and bacterial infection. The authors also admit that further research is needed to assess the relationship between findings from a cytokine panel and COVID-19.

Investigation of the inflammatory response among COVID-19 patients, such as those in an ITU setting, is important for clinical practice. While the intentions of this study are valid, it is difficult to follow the main aim and resulting comparisons included in the analysis. The Methods need to be clearer, especially with defining the study population and inclusion terms, and the overall organization of the paper needs improvement.

Response: We thank the reviewer for the above comments. We have now re-structured the manuscript to address this and hope it now provides better clarity.

Major Comments:

In the Introduction, include a description or paragraph about the “recently validated cytokine panel” as stated in lines 115-116. Give more background information on this panel, as this cytokine panel is one of main topics of this paper.

How was this particular panel validated?

How was this panel used previously? Briefly, how does this panel work?

Response: We have now expended on the cytokine panel to clarify when it was introduced and the process uses to validate its routine use – Lines 109-115. More details about validation mentioned in Method section under Cytokine Panel Performance Characteristics - Lines 182 -208.

The aim of the paper states that there were assessments of concurrent bacterial infections with COVID-19; however, there is a lack of descriptions about concurrent bacterial infections. In the Methods section, include how bacterial infections were assessed.

Which bacterial testing was used? Which bacteria could be detected on these tests? When were patients included in this study tested for concurrent bacterial infection?

Response: This is now included in method section (Lines 163-165) and in result section (lines 305-308).

In the Discussion, it is unclear how the findings are directly related to the main aim of assessing bacterial co-infection.

Response: we have now simplified the aim of this study (Lines 117-119) as our data is observational for bacterial co-infection. Described in the discussion–Lines 359-385.

The Methods and Results sections include comparisons with 24 healthy volunteers; however, it is unclear how the volunteers were chosen for this study.

How were these volunteers chosen?

Were these volunteers matched at all (the non-ITU patients were age-matched)?

When were these volunteers sampled? Were the volunteers sampled during the same timeframe as the other patients?

Describe the criteria needed to be considered “healthy.”

Response: The recruitment of the healthy volunteers has now been included – lines 149-156.

The volunteers were younger than the COVID-19 patients which is now included in result section (lines 221-222) and limitations (lines 414-415).

All volunteers sampled in April 2020 for the validation of the cytokine panel within our laboratory (line 151). A proportion of patients’ samples were collected during this period.

Also, the Introduction sets up the study to compare ITU and non-ITU patients, so some explanation about the COVID-19 patients versus “healthy” volunteers is needed earlier in the paper.

Response: We have now referred to the healthy volunteers in the abstract (line 47 and 51) and under Introduction (line 119).

Were comparisons made between ITU patients, non-ITU patients, and “healthy” volunteers? A three-way comparison with “healthy” volunteers as the referent may be more elucidating.

Response: We have now compared three groups as suggested (lines 229-232) and results are summarised in Table 1

Minor Comments:

Line 87: Make a new paragraph for CRP descriptions.

Response: CRP description is now in separated paragraph - Lines 84 – 88.

Lines 111-113: Clarify which study is referenced here and describe the control group used in that study. Introduce the study more clearly earlier in this paragraph.

Response: Reference given and control group is described - Lines 105-108.

Lines 117-118: Give some context about COVID-19 incidence in London during the study period and how the cytokine panel was used at this particular hospital. Give the months/year of the “peak” pandemic time.

Response: Included in the methods (Lines 125 -129), Introduction (line 109 to 115). ‘Peak’ pandemic time has been omitted from the Introduction as not relevant to our study data.

Line 122: State the specific months/year that included the patients in this study.

Response: March 2020 to January 2021, included in the methods (Lines 125-126)

Line 123: When were patients tested for SARS-CoV-2? Was there a specific timeframe from exposure that these patients were tested? Was the testing implemented for diagnostic purposes or as a general hospital screening test during that time period?

Response: The reason for admission of all patients in this study was suspected COVID-19 infection based on clinical/radiological evidence which was confirmed with positive (RT-PCR) SARS-CoV-2. Included in method section (Lines 137-139).

Line 127: Specify how many of the 75 excluded patients were ITU or non-ITU.

Response: 55 ICU and 20 non-ICU, now included in Figure 1.

Line 130: Explain why patients needed to have a same-day PCT result as the cytokine panel to be included in the study. Give the number of patients excluded based on not having same-day tests—was it 14 patients (make sure that the total numbers reflect the 76 included patients)?

Response: Included in line 143 in method and Fig 1.

Consider making a flow chart delineating the inclusion/exclusion factors for included patients.

Response: We have now included a figure to highlight this (fig 1, page 6).

Lines 142-144: Is this the test that was mentioned within the introduction?

Response: No in these references, they have used different methods for PCT.

Line 152: Spell out CV when it is first mentioned.

Response: Amended as suggested–Line 185.

Table 1: The row for PCT is missing. Add PCT results.

Response: PCT is not included in Table 1 as PCT was not measured in healthy volunteers. PCT is however included In Table 3.

Line 211: Indicate that the finding was statistically significant.

Response: we have made this change (Line 263).

Line 247: Interleukin is misspelled.

Response: This has now been corrected (Line 300).

Within the Discussion, explain why correlations were used for PCT and CRP among the ITU and non-ITU patients. Even though the correlations are statistically significant, most correlations seemed weak. How do these findings translate to clinical practice?

Response: We have suggested that correlation of cytokines with CRP and PCT may help to assist in identifying bacterial infections. Included under in discussion, lines 361 -363, 370-371, 375-376). We agree with the reviewer that the correlations are weak and larger studies are required to better assess this.

Line 269: How was “severity” defined? How can these higher cytokines be shown with certain clinical signs in patients?

Response: In general ICU patients with elevated PCT had higher TNFα and longer ICU length of stay. (Severity has been replaced by ICU length of stay- lines 330-333)

Line 289: Add an in-text citation.

Response: This has now been included–line 351 and 352.

Lines 291-292: How were concurrent bacterial infections confirmed in this reference study and also in the present study?

Response: In our study, concurrent bacterial infection has changed to concurrent and/or super added bacterial infection. Concurrent and/or super added bacterial infection were identified based on positive blood or respiratory cultures within 48 hours from cytokine panel request time. This is included under Methods - lines 163-175

In reference study, authors suggested significant increase in PCT could possibly reflect bacterial coinfection in those developing severe COVID-19 thus contributing to complicate its clinical picture, this is now included in lines 352-353)

Line 304: Add an in-text citation.

Response: Added-line 367.

Lines 311-314: Please re-phrase this sentence, as it is difficult to follow.

Response: This sentence has now been rephrased as requested–Lines 373-378.

Line 315: Are the “two groups” mentioned here the high and low PCT groups?

Response: Yes, now Corrected for clarity–Line 379.

Line 328: Please specify the “two values.”

Response: The two values were CRP and IL-6. We have now stated this as suggested–line 402.

Line 355: State the number of patients (46) instead of “good number.”

Response: This has now been corrected.

There are many typographical errors, such as missing hyphens and inconsistent hyphenation, missing commas, missed spacing between words, missing articles before nouns, and missing or incorrect punctuation.

Response: We have reviewed the entire manuscript and corrected as relevant.

Submitted filename: Response to Reviewers .docx

Click here for additional data file.

14 Feb 2022

23 Mar 2022

Comment: *Please cite the top-tier papers.

#1. Yang JM, Koh HY, Moon SY, Yoo IK, Ha EK, You S, Kim SY, Yon DK, Lee SW. Allergic disorders and susceptibility to and severity of COVID-19: A nationwide cohort study. J Allergy Clin Immunol. 2020 Oct;146(4):790-798. doi: 10.1016/j.jaci.2020.08.008. Epub 2020 Aug 15. PMID: 32810517; PMCID: PMC7428784.
#2. Shin YH, Shin JI, Moon SY, Jin HY, Kim SY, Yang JM, Cho SH, Kim S, Lee M, Park Y, Kim MS, Won HH, Hong SH, Kronbichler A, Koyanagi A, Jacob L, Smith L, Lee KH, Suh DI, Lee SW, Yon DK. Autoimmune inflammatory rheumatic diseases and COVID-19 outcomes in South Korea: a nationwide cohort study. Lancet Rheumatol. 2021 Oct;3(10):e698-e706. doi: 10.1016/S2665-9913(21)00151-X. Epub 2021 Jun 18. PMID: 34179832; PMCID: PMC8213376.

Response: The above two references have now been included under ‘Discussion’ – reference number 19 and 20.

Comment: There are numerous misspellings/typographical errors. Thorough proofreading of phrases is needed.

Response: Thank you for highlighting this. We have reviewed the manuscript and made relevant corrections throughout.

Comment: The terminology of co-infection, superadded infection, superinfection needs to be clearer. If the intent is for the same meaning across the manuscript, there needs to be consistency with the appropriate term. The nuances of these terms may need to be defined in the manuscript if the intent is for a molecular-based definition.

Response: Concurrent bacterial infection and co-infection is now replaced with

super-infection throughout because all confirmed bacterial infection in this cohort, occurred ≥48 hours after admission to hospital for COVID-19. (Lines 170-172)

Comment: Lines 111-112: At the very least, cite the published literature concerning the cytokine panel creation. It is unclear if this particular cytokine panel is location-specific or more widely used.

Response: Two additional references cited (Line 112). In addition the following sentence is now included in the manuscript - ‘While IL-6 is widely being used in the UK, this panel is unique to King’s College Hospital’. (Lines 111-116)

Comment:Line 149: Which co-morbidities were defined as absent from “healthy” volunteers?

Response: The sentence has now been re-structured for better clarity - Lines 153-155.

Comment:Methods: Which specific bacterial infections were included in the testing?

Response: We have now included the details of the culture results - Lines 310-317.

Comment: Methods: There are discrepancies between the number of patients in certain groups and the numbers listed in Figure 1. Please review and correct the patient numbers.

Response: The patient numbers have been corrected as relevant - Line 138.

Comment: Discussion: The discussion states that there are few limitations, but that is not accurate. As a retrospective study, there are several inherent limitations. Also, healthy volunteers were not tested for COVID-19 (as explained in the Methods), but this is still another limitation due to lack of confirmation.

Response: This has now been addressed – Lines 432-436.

Yours sincerely,

Tina Mazaheri

Submitted filename: Response to reviewers .docx

Click here for additional data file.

25 Mar 2022

A cytokine panel and procalcitonin in COVID-19, a comparison between intensive care and non-intensive care patients

PONE-D-21-26044R2

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Additional Editor Comments (optional):

I congratulate you on this mesmerizing paper.

Reviewers' comments:

8 Apr 2022

PONE-D-21-26044R2

A cytokine panel and procalcitonin in COVID-19, a comparison between intensive care and non-intensive care patients

Dear Dr. Mazaheri:

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