(Fig. 4 set here)
Discussion
We included a total of 171 patients with SARS-CoV-2 infection in this
retrospective study. The incidence of pneumonia associated with
SARS-CoV-2 was 71.8%. Our findings suggested that
lymphocyte
count was a more reliable indicator for predicting pneumonia in patients
infected with
SARS-CoV-2,
compared to
viral
load. Additionally, CT analysis of pneumonia patients showed that the
percentage of ground-glass opacity (GGO) pattern in CT scans strongly
correlated with the hypoxia level of patients, while consolidation
pattern was associated with PaCO2 level.
Although the lymphocyte was proved to be a strong indicator for severity
of SARS-CoV-2 infection in medical fundamental studies, our findings
confirm that it is the lymphopenia (lymphocyte count
<1.0*109/L) of the patients is the potential
predictor and associated with the developing into pneumonia, instead of
viral load from the aspect of clinic. Cytotoxic lymphocytes, such as
cytotoxic T lymphocytes (CTLs) and natural killer (NK) cells, are
essential for controlling viral infections. The functional exhaustion of
cytotoxic lymphocytes is correlated with disease progression[14].Zheng [15] et al. found that patients with SARS-CoV-2
infection had a significantly decreased total number of NK and
CD8+ T cells. Additionally, the function of NK and
CD8+ T cells was found to be exhausted, with increased
expression of NKG2A in COVID-19 patients. However, during the
convalescence period, the number of NK and CD8+ T
cells was restored, which suggests that the functional exhaustion of
cytotoxic lymphocytes is associated with SARS-CoV-2 infection. Results
of Qiong et al. research[16] indicated compared to mild
infected patients, the blood counts of patients in the severe group
showed
lymphopenia
(lymphocyte
count <1.0×109/L). Moreover, the enriched
annotations of differential genes that were incrementally downregulated
from the healthy control group to severe group were mostly related to T
cell functions. These functions include T cell receptor signaling and
antigen receptor-mediated signaling pathways. Consist with results
above, our findings indicated lymphopenia could be a strong predictor of
SARS-CoV-2 pneumonia dependently from virus load. In some cases, and
certain serial reports [17, 18], the findings of CT and RT-PCR may
be incongruous, which can corroborate our results to some extent.
Furthermore, in the pneumonia cohort, CT patterns appear to be
associated with different pathophysiological changes. Up to now, there
are bench of studies to discuss the diagnostic potential of CT score or
quotative CT analysis for Covid-19 pneumonia[6, 17, 18].
To
our limited knowledge, there has been negligible research investigating
the relationship between CT patterns and pathophysiological changes. Our
research indicates that GGO patterns are associated with the degree of
hypoxia, while consolidation patterns are related to high levels of
PaCO2. GGO pattern are the most common initial findings
in COVID-19 pneumonia[7, 19]. GGOs are a type of abnormality seen on
a chest imaging test like a CT scan or an X-ray. They are characterized
by a hazy area of increased density in the lung tissue, which looks like
ground glass[19]. In COVID-19 pneumonia, these GGOs can appear in
both lungs and are usually located in the peripheral regions.Damiano Caruso et al. [6] included 136 Covid-19 patients and
analysis their CT, finding that
GGO
alterations on chest CT scans could help identify patients with COVID-19
(AUC 0.661, cutoff 0.39 L, 68% sensitivity and 59% specificity,p < 0.001 ). Our data proved that GGO pattern ratio was
strongly associated with hypoxia when adjusted with consolidation
pattern ratio, a possible explanation could be that pulmonary edema and
hyaline membrane formation are considered potential pathological driving
forces behind GGO, which has been confirmed by postmortem biopsy of a
COVID-19 patient[20]. On the contrary, the resolution of GGOs may
indicate an improvement in the patient’s condition[21, 22].
Another
study showed that patients who exhibited GGO had significantly higher
levels of IL-2, IL-4, and INF-γ compared to those who did not exhibit
GGO[9]. Additionally, we found that the consolidation ratio was
positively corelated with PaCO2 level though take GGO
ratio into consideration. As COVID-19 progresses, GGOs may increase in
size and merge with other GGOs, eventually evolving into fibrous streaks
and solid nodules, which contributed the consolidation ratio. Recently
studies showed that consolidation also common pattern in the late stage
of COVID-19[20, 21]. Consolidation was one of mechanism of “baby
lung” for ARDS, which could result in decreasing of lung volume, also
affect ventilation[23, 24].
Hypercapnia
was common symptom in late ARDS stage no matter cased by SARS-CoV-2
infection or classic pythons[25, 26].
Furthermore, our research observed a correlation between consolidation
and NLR. NLR reflects the balance between two aspects of the immune
response: (i) the innate response, primarily mediated by neutrophils,
and (ii) adaptive immunity, supported by lymphocytes. It has been
reported that an elevated NLR is often observed in conditions that
involve tissue damage and activate the systemic inflammatory response,
such as bacterial and fungal infections, sepsis, acute stroke,
atherosclerosis, myocardial infarction, severe trauma, and cancer[27,
28]. Recently, studies revealed that NLR can predict clinical outcomes
and plays as an easy-to-obtain biomarker to evaluate severity for
Covid-19 patients[29, 30]. A multicenter retrospective cohort study
from France investigated the prognostic value of the NLR for disease
severity and mortality in 1035 COVID-19 patients[31]. The NLR at
admission to the emergency department was found to have a predictive
ability for disease severity (area under the curve (AUC), 0.59; cut-off
value, 6.88; sensitivity, 48%; specificity, 66%) and disease mortality
(AUC, 0.62; cut-off value, 8.23; sensitivity, 47%; specificity, 72%).
Consolidation
pattern always emerge in the late stage of illness progress and could be
regarded as the evolving form for GGO[4, 22]. That could be a
potential explanation for our finding.
Analysis is affected by skill and experience of radiologist and clinical
physician in image interpretation, whereas quantitative evaluation is a
reproducible and comparable technique. With this information, we can
begin to hypothesize that as the illness progresses, the GGO evolves
into a consolidation pattern, and hypoxia develops into hypercapnia, and
clinical outcome may getting worsen. The appearance of consolidation
patterns could be a sign of worsening lung function. By understanding
the relationship between CT patterns, oxygenation, and inflammation, we
can gain more insight into the disease process and develop better
strategies for diagnosis and treatment, especially for intubating and
ventilation timing, strength of anti-inflammation etc.
However, our study has several limitations. Firstly, we did not discuss
the relationship between CT patterns and clinical outcomes. The present
study focuses on the immediate associations between CT patterns and
oxygenation, as well as the PCR test for SARS-CoV-2, to reveal the
potential clinical significance of CT patterns. We aim to address this
in our future studies. Secondly, the mechanics of ventilation were not
involved in the present research. Some patients recruited in the cohort
applied high-flow oxygen or non-invasive ventilation, and it was
impossible for us to collect this data. Thirdly, although the sample
size evaluation was performed, a larger sample size would make the
present findings more convincing.
Conclusion
In
conclusion, the present study suggests that lymphocyte count may be a
potential marker for predicting SARS-CoV-2 pneumonia, independent of
virus load. Additionally, ground-glass opacity (GGO) manifested in CT
scans is correlated with hypoxia, while consolidation is associated with
PaCO2 levels and inflammation, which may affect aeration in the lungs.
List of abbreviations
GGO:
ground
glass opacity, CT: computed tomography, PCR: polymerase chain reaction,
WHO: According to World Health Organization, SARS-CoV-2: severe acute
respiratory syndrome coronavirus-2, ABG: arterial blood gas, CBC:
complete blood count.
Data availability statement
Data and materials supporting the findings of this manuscript are
available from the corresponding authors upon request.
Funding statement
This research received no external funding.
Conflict of interest disclosure
The author confirms that the work described has not been published
before; it is not under consideration elsewhere; the publication has
been approved by all co-authors and all co-authors agreed to publication
in this journal. All the authors declare no conflict of interest and
agree to publication.
Ethics approval statement
The studies involving human participants were reviewed and approved by
the Ethics Review Form for Medical Research and Clinical Technology
Application and Ethics Committee of Qingdao Hospital, University of
Health, and Rehabilitation Sciences.
Patient consent statement
The patients/participants provided their written informed consent to
participate in this study. All the associated materials involved in the
present research are in accordance with the Declaration of Helsinki.
Permission to reproduce material from other sources.
Not Applicable
Author contributions
QY and WY conceived, designed, and supervised the study, and WY, MHN
wrote the drafts of the manuscript. WSM participated in the data
recording, JC, LZY and XWF finalized the analysis. All the authors read
and approved the final manuscript, and the authors contributed to the
article and approved the submitted version.
Acknowledgments
This study was supported by Xu Zhipeng, radiologist from the Radiography
Department of Qingdao Hospital, University of Health, and Rehabilitation
Sciences (Qingdao Municipal Hospital).
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