Lower respiratory tract and plasma SARS-CoV-2 RNA load in critically ill adult COVID-19 patients: Relationship with biomarkers of disease severity

Dear Editor,

We read with interest the work published by Lui and colleagues in the Journal of Infection¹, in which the dynamics of SARS-CoV-2 RNA at different body sites was investigated in a rather small cohort including 5 patients with critical/severe COVID-19. The authors supported the assumption that viral loads in lower respiratory tract (LRT) better reflected clinical progression in severe disease than those in upper respiratory tract (URT) samples. To further address this issue, we conducted an observational study (approved by the Ethics Committee of Hospital Clínico Universitario INCLIVA in May,2020) aimed at characterizing the kinetics of SARS-CoV-2 RNA load in the LRT and plasma (viral RNAemia) and assessing how these relate to the inflammatory state and mortality of critically ill COVID-19 patients. Seventy-three consecutive patients (51 males and 22 females; median age, 65 years; range, 21 to 80 years) were recruited during ICU stay (median,18 days; range, 2–67 days), between October 2020 and February 2021 (Supplementary Table 1). Patients were admitted to ICU at a median of 9 days (range, 2–25) after onset of symptoms. Sixty-four patients underwent mechanical ventilation, from whom 165 tracheal aspirates (TA) were collected (median of 2 specimens/patient; range, 1–11). A total of 340 plasma specimens (median, 4 samples/patient; range, 1–16) were available from the 73 patients. SARS-CoV-2 RNA quantitation in TA and plasma was carried out by the Abbott RealTime SARS-CoV-2 assay Abbott Molecular (Des Plaines, IL, USA) (See Supplementary Material). SARS-CoV-2 viral loads (in copies/ml) were estimated using the AMPLIRUN® TOTAL SARS-CoV-2 RNA Control (Vircell SA, Granada, Spain). The analytical sensitivity of the RT-PCR assay in TA and plasma specimens was 100 copies/ml (95%) for both matrices.

SARS-CoV-2 RNA (median, 6.5 log₁₀ copies/ml; range, 3.03–10.6 log₁₀) was detected in 109 TA from 56 patients (91.8%). Viral load remained relatively stable across the first two weeks from symptoms onset and began to decrease afterwards (Fig. 1 A). No patient tested positive for SARS-CoV-2 RNA in TA beyond day 42. As reported for URT^{2 , 3}, neither remdesivir nor tocilizumab administration appeared to have a major impact on the dynamics of SARS-CoV-2 RNA load in TA (Supplementary Table 2).

Fig. 1.

Kinetics of SARS-CoV-RNA load in tracheal aspirates (A) and plasma (B) of critically ill patients undergoing invasive ventilation. Panel C shows the kinetics of SARS-CoV-2 RNA load in the lower tracheal aspirates in patients who either died or

SARS-CoV-2 RNAemia (median, 3.03 log₁₀ copies/ml; range, 1.69 to 5.27 log₁₀) was detected in 37 plasma specimens from 26 patients (35.6%). Median time to first detection of viral RNA in plasma was 10 days after symptoms onset (range, 3–32 days) Viral RNA cleared faster in plasma than in TA (Fig. 1B). Previous studies using a droplet-based digital PCR, which seemingly outperforms conventional RT-PCR assays in terms of sensitivity, reported higher rates of viral RNAemia detection in ICU patients (77% in⁴ and 88% in⁵) than found in the current study. This discrepancy could also be related to different timing of sample collection across studies.

A moderate yet significant correlation was found between SARS-CoV-2 RNA levels in TA and in paired plasma specimens (rho, 0.41; p < 0.001). SARS-CoV-2 RNA load in TA was significantly higher (p < 0.001) in presence than absence of concomitant viral RNAemia (median, 9.5 log₁₀ copies/ml; range, 4.3 to 10.4 log₁₀ copies/ml vs. median, 6.2 log₁₀ copies/ml; range, 3.0–10.6 log₁₀ copies/ml), this suggesting that LRT may be a substantial source of SARS-CoV-2 RNA.

Plasma levels of ferritin, lactose dehydrogenase (LDH), but not interleukin-6 (IL-6), C-reactive protein (CRP), or D-Dimer (D-D), were significantly higher when SARS-CoV-2 RNA was detected in paired TA or plasma specimens (Table 1 ), yet SARS-CoV-2 RNA loads in these specimens correlated modestly (Rho < 0.31) with plasma levels of ferritin and LDH (Supplementary Fig 1). Lymphocyte counts were significantly lower in the presence of SARS-CoV-2 RNA in TA and plasma (Table 1). Nevertheless, the level of correlation (inverse) between SARS-CoV-2 RNA load in TA and plasma and lymphocyte counts was modest ((rho, -0.43; p < 0.01 and rho, -0.25, p < 0.01, respectively). A significant association between SARS-CoV-2 RNAemia detection and blood levels of IL-6, interleukin-10, CRP, ferritin, D-D and LDH was previously reported^{4 , 6}. In these studies, a single time point specimen per patient collected at ICU admission was considered for the analyses, as opposed to the serial specimens used herein.

Table 1.

Qualitative detection of SARS-CoV-2 RNA in the lower respiratory tract or plasma or SARS-CoV-2 N protein in plasma and blood levels of biomarkers of COVID-19 severity.

Qualitative result of a given virological parameter		no. of paired specimens	Parameter (Median range)		p value
SARS-CoV-2 RNA load in tracheal aspirates	Pos	23	IL-6 in pg/ml.	111.4 (4–3,548)	0.84
	Neg	2		142 (22–262)
	Pos	82	Ferritin in ng/ml.	805.5 (69–6,440)	0.01
	Neg	34		421.5 (46–2,659)
	Pos	101	D-D in ng/ml.	1,730 (270–29,940)	0.87
	Neg	49		1,790 (270–16,160)
	Pos	105	LDH in UI/l.	687 (93–2,132)	0.001
	Neg	51		520 (214–1,395)
	Pos	107	CRP in mg/l.	35 (1–746)	0.62
	Neg	54		32.85 (1–606.7)
	Pos	74	Lymphocytes in cell/µl	0.96 (0.02–3.73)	<0.001
	Neg	42		1.40 (0.44–2.43)
SARS-CoV-2 RNAemia	Pos	9	IL-6 in pg/ml.	111.4 (10.8–1363.)	0.92
	Neg	40		141.8 (4–3,548)
	Pos	31	Ferritin in ng/ml.	1,176 (147–6,440)	<0.001
	Neg	211		590 (42–5,847)
	Pos	36	D-D in ng/ml.	1,535 (320–9,170)	0.17
	Neg	274		1740 (270–60,000)
	Pos	36	LDH in UI/l.	765.5 (329–1,720)	0.002
	Neg	281		637 (58–2,132)
	Pos	36	CRP in mg/l.	47.95 (1.2–459)	0.38
	Neg	299		30.7 (1–746)
	Pos	26	Lymphocytes in cell/µl	0.72 (0.02–3.13)	<0.001
	Neg	209		1.13 (0.17–3.73)

CRP, C-reactive protein; D-D, Dimer-D; IL-6, interleukin-6; LDH, lactose dehydrogenase.

Dynamics of SARS-CoV-2 RNA load (initial, peak and trajectory) in TA following ICU admission were comparable across patients who either died or survived (Fig. 1C). Moreover, neither initial nor peak viral load in TA was associated with increased mortality (OR, 0.81; 95% CI, 0.68–2.24; p = 0.68, and OR, 0.39; 95% CI, 0.22–1.82; p = 0.39, respectively) (Supplementary Table 3). Other studies, in contrast, pointed to an association between protracted SARS-CoV-2 RNA clearance in LRT and/or simple presence of SARS-CoV-2 RNA in LRT and increased risk of mortality7, 8, 9. In these studies, a wide variety of LRT specimens were used, and no data proving a dose-dependent relationship between SARS-CoV-2 RNA load in LRT and mortality were provided.

We found a trend towards an association between qualitative detection of SARS-CoV-2 RNA in plasma and increased mortality in adjusted multivariate logistic regression models (OR, 2.82, 95% CI, 0.94–8.47), and failed to demonstrate such a trend for initial or peak viral loads (supplementary Table 3). SARS-CoV-2 RNAemia has been previously associated with poor clinical outcome in series including only ICU patients, in which patients who died displayed higher viral RNA loads in plasma collected at ICU admission than those who survived⁴.

The main limitation of the current study is its relatively small sample size. Analysis of sequential specimens from patients could be considered a strength of the research.

The current study provides a further insight into the pathogenesis of SARS-CoV-2 infection in ICU patients. In our view, our data fit better with a pathogenetic model, in which SARS-CoV-2 replication in the LRT or its presence in blood at a certain point over the course of ICU stay might not be a major driver of systemic inflammation, lymphopenia, lung dysfunction, multisystemic organ failure and death. This does not invalidate the importance of virus replication rate in the URT in the early stage after infection in determining the clinical course of COVID-19¹⁰. Further studies are needed to resolve this issue.

Financial Support

This work received no public or private funds.

Author Contributions

BA, EA, IT, RG-R, RC, JC and JR: Methodology and validation of data. NC, JF and MLB: Medical care of ICU patients. DN: Conceptualization, supervision, writing the original draft. All authors reviewed the original draft.

Declaration of Competing Interest

The authors declare no conflicts of interest.