(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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