key: cord-0870339-7ricj3mc
authors: Kong, Jindan; Hao, Yan; Wan, Shan; Li, Zheng; Zou, Di; Zhang, Leisi; Lu, Yin; Wang, Jun; Chen, Xiaochen; Fu, Jianhong
title: Comparative study of hematological and radiological feature of severe/critically ill patients with COVID‐19, influenza A H7N9, and H1N1 pneumonia
date: 2021-11-11
journal: J Clin Lab Anal
DOI: 10.1002/jcla.24100
sha: a783659bca4e3f083fd90492eff1f1788170e515
doc_id: 870339
cord_uid: 7ricj3mc

OBJECTIVES: This study aimed to explore clinical indexes for management of severe/critically ill patients with COVID‐19, influenza A H7N9, and H1N1 pneumonia by comparing hematological and radiological characteristics. METHODS: Severe/critically ill patients with COVID‐19, H7N9, and H1N1 pneumonia were retrospectively enrolled. The demographic data, clinical manifestations, hematological parameters, and radiological characteristics were compared. RESULTS: In this study, 16 cases of COVID‐19, 10 cases of H7N9, and 13 cases of H1N1 who met severe/critically ill criteria were included. Compared with COVID‐19, H7N9 and H1N1 groups had more chronic diseases (80% and 92.3% vs. 25%, p < 0.05), higher APACHE Ⅱ scores (16.00 ± 8.63 and 15.08 ± 6.24, vs. 5.50 ± 2.58, p < 0.05), higher mortality rates (40% and 46.2% vs. 0%, p < 0.05), significant lymphocytopenia (0.59 ± 0.31 × 10(9)/L and 0.56 ± 0.35 × 10(9)/L vs. 0.97 ± 0.33 × 10(9)/L, p < 0.05), and elevated neutrophil‐to‐lymphocyte ratio (NLR; 14.67 ± 6.10 and 14.64 ± 10.36 vs. 6.29 ± 3.72, p < 0.05). Compared with the H7N9 group, ground‐glass opacity (GGO) on chest CT was common in the COVID‐19 group (p = 0.028), while pleural effusion was rare (p = 0.001). CONCLUSIONS: The NLR can be used as a clinical parameter for the predication of risk stratification and outcome in COVID‐19 and influenza A pneumonia. Manifestations of pleural effusion or GGO in chest CT may be helpful for the identification of different viral pneumonia.

In December 2019, a cluster of pneumonia cases of unknown cause attacked Wuhan city in China. The pathogen was later identified to be a previously unknown beta coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 1 caused a global pandemic. 3 In 2013, the novel avian-origin influenza A (H7N9) virus isolated in China had caused a sporadic epidemic, which was characterized by rapid progression and with a high fatality rate. 4, 5 The confirmed diagnosis of COVID-19 and influenza A pneumonia relies on reverse transcription-polymerase chain reaction (RT-PCR) from a nasopharyngeal swab, which need special laboratory and trained medical staffs. Hematological and radiological examinations are two basic methods for contagious viral pneumonias in clinical practice, which have the advantages of availability and short turnout time. In addition to RT-PCR testing, hematological and radiological examinations can be used for presumptive diagnosis.

Although COVID-19 and influenza A pneumonia are caused by two independent pathogens, there is still possibility that superimposed infection of influenza A and SARS-CoV-2 happens in the same patient. 6 Nevertheless, few studies have reported the different clinical features between COVID-19, influenza A H7N9, and H1N1 to date.

In this study, hematological and radiological characteristics of severe/critically ill patients with COVID-19 and influenza A (H7N9 and H1N1) pneumonias in Suzhou were analyzed. In this article, we aimed to find useful index for the management of COVID-19, influenza A H7N9, and H1N1 patients. According to the Chinese guidelines for diagnosis and treatment of novel coronavirus infected pneumonia, patients who met one of the following criterions were regarded as severe/critically ill cases:

1) respiratory rate ≥30 bpm; 2) oxygen saturation ≤93%; 3) arterial partial pressure of oxygen (PaO 2 )/fraction of inspired oxygen (FiO 2 ) <300 mmHg; 4) respiratory failure requires mechanical ventilation, shock, or other organ failures, which requires ICU treatment, and severe/critically ill H7N9 and H1N1 pneumonia patients all met this criterion. Children were excluded. Two neutropenic patients with hematological malignancies after chemotherapy in H1N1 group were excluded.

The laboratory examination including complete blood count (CBC) 

Patients' CT images were searched in the picture archiving and communication system (PACS). The first chest CT images after symptom onset were collected for analysis in different patients. Time (days) from the onset to CT scan was recorded at the same time.

Manifestation of CT images in patients included ground-glass opacity (GGO), consolidation, distribution characteristics, and pleural effusion.

The statistical software SPSS 20.0 (IBM, Armonk, NY, USA) was used for data analysis. Continuous data with normal distribution were presented as mean ± standard deviation, and non-normal distribution was expressed as median (interquartile range). Continuous variables were compared using one-way ANOVA, t-test, or Kruskal-Wallis test (if the test for homogeneity of variance was significant). Categorical variables were presented as a percentage and assessed using χ 2 test and Fisher's exact test. Two-sided p < 0.05 indicated statistical significance.

A total of 16 cases of COVID-19, 10 cases of influenza A H7N9, and 13 cases of influenza A H1N1 were included. All of the patients met the aforementioned clinical classification criteria. The basic information was listed in Table 1 . There was a difference in gender between H7N9 and H1N1 groups (p = 0.029). The proportion of patients combined with underlying chronic diseases in H7N9 and H1N1 groups was higher than that in COVID-19 group (80% vs. 25%, p = 0.014 and 92.3% vs. 25%, p = 0.000).

The common symptoms in the three groups included fever, cough, expectoration, and chest tightness. Cough was less common in the COVID-19 group than the H1N1 group (62.5% vs.

100%, p = 0.020). Compared with the COVID-19 group, chest tightness was more common in the H7N9 and H1N1 groups (12.5% vs. 60%, p = 0.026, and 12.5% vs. 84.6%, p = 0.000). All patients received antivirus, antibiotics, and corticosteroid therapy routinely. 

The results of complete blood count and coagulation panel on admission of all patients were summarized in Table 2 . Although lymphopenia was detectable in all three groups, it was more pronounced in the H7N9 (p = 0.008) and H1N1 (p = 0.002) groups. The neutrophilto-lymphocyte ratio (NLR) was higher in the H7N9 group (Fold In the H7N9 and H1N1 groups, patients were evaluated and regrouped according to their survivals. After a further statistical analysis of their hematological examination, it was found that NLR was significantly higher in the group with patient death, compared to the group without patient death (Fold change = 0.66, p = 0.033; Table 3 ). The ROC and AUC of lymphocytes, neutrophils, and NLR between the two groups were calculated (Figure 1 ). The AUC of NLR is 0.7615, and the AUC of lymphocytes and neutrophils is 0.6731 and 0.6154, respectively. From the onset of symptoms to the first CT examination, the days in the COVID-19 group were significantly shorter than the other two groups (Median: 5.13 ± 3.22 days vs. 14.13 ± 10.01 days and

16.00 ± 9.15 days, p < 0.05).

The In this research, we found the higher proportion of male patients in the H7N9 group, which was similar to the data from some previous clinical studies and which can be explained by more involvement of males in poultry breeding and slaughtering. 5,7-9 By comparison, cough and chest tightness were more common in the influenza groups compared with the COVID-19 group. However, these symptoms belong to the common symptoms of pneumonia, which are un- 

Clinical studies also reported marked lymphopenia in patients with H7N9 infection, among which two death cases showed diffuse alveolar injury with lymphocyte and monocyte infiltration in percutaneous lung biopsies. [7] [8] [9] In the case of COVID-19, it was reported that hospitalized patients had some extent of lymphopenia, which was even more obvious in the patients with disease progression. 16, 17 In our study, the lymphopenia was less obvious in the COVID-19

patients compared with the influenza groups, which is in consistent with the observations in other studies. A systematic review and meta-analysis suggested that peripheral blood leucocyte ratio was useful infection parameter for the distinguish between bacterial and viral infection. 18 NLR is a marker of inflammation and has been shown to be associated with COVID-19. 19 Studies had reported that COVID-19 patients had increased Ddimer and fibrin/fibrinogen degradation products, while abnormalities in prothrombin time, partial thromboplastin time, and platelet counts were relatively rare. 26, 27 Three-to four-fold increase in Ddimer levels was detected in the early stages of COVID-19 patients, which was associated with poor prognosis of COVID-19 patients. 27 Measuring the level of D-dimer and coagulation parameters from the early stage can also be useful in controlling and managing of COVID-19 disease. 27 Our data also showed that fibrinogen was sions, including multiple nodules and "tree-in-bud" sign. 29 Another study compared the CT feature of H7N9 and H1N1 patients with acute respiratory distress syndrome (ARDS), which showed common manifestations, such as consolidation, GGO, air bronchogram, interlobular septal thickening, and nodular shadow, while pleural effusion was more specific in H7N9 pneumonia. 30 Compared with those studies, our study showed more GGO in the COVID-19 group, while pleural effusion was rare in COVID-19 group, but more common in the H7N9 group. The days from the onset to the first CT examination were shorter in the COVID-19 group, due to the active response strategy and screening of patients with fever or respiratory symptoms in COVID-19, which led to the early diagnosis of COVID-19

with milder injury in the lungs.

The limitations of this study were the small number of included cases, the long-time span, the lack of comparison of the characteristics in mild cases, and the lack of inflammatory factors and infection markers.

In summary, patients with H7N9 and H1N1 had a more critical and complex condition. They had received more life support treatment in the ICU and had a higher mortality rate. In the COVID-19 group, hematological examination showed slight decrease in lymphocytes, increase in monocytes, and slight increase in fibrinogen compared with the influenza groups. The NLR in the influenza groups was significantly increased, especially in the subgroup with patient death.

These results suggest that NLR can be used as an important indicator to distinguish the severity of viral pneumonia and predict the prognosis of influenza pneumonia. The comparison of chest CT showed that pleural effusion and GGO may be helpful for distinguishing of the COVID-19 and the influenza pneumonia.

This study was supported by the National Natural Science

Foundation of China (Grant No. 81730003) and Gusu Health Talents Program (No. GSWS2020006). The authors thank patients for participation in this study.

The authors declare no conflict of interests.

J. Kong, J. Fu, Y Hao, and S. Wan designed the work and performed patient data collection, analyzed the data, and wrote the article. D.

Zou, Z Li, L Zhang, Y Lu, and J Wang performed patient data collection in this retrospective clinical study. X. Chen revised the article.

All authors approved the submission.

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Jianhong Fu https://orcid.org/0000-0002-9044-024X

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