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Comparison of Patients Hospitalized with COVID-19, H7N9 and H1N1

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Comparison of Patients Hospitalized with COVID-19, H7N9 and H1N1 Deng et al. Infect Dis Poverty (2020) 9:163 https://doi.org/10.1186/s40249-020-00781-5 RESEARCH ARTICLE Open Access Comparison of patients hospitalized with COVID-19, H7N9 and H1N1 Li‑Si Deng1†, Jing Yuan2†, Li Ding1†, Yuan‑Li Chen3, Chao‑Hui Zhao1, Gong‑Qi Chen1, Xing‑Hua Li1, Xiao‑He Li2, Wen‑Tao Luo1, Jian‑Feng Lan2, Guo‑Yu Tan2, Sheng‑Hong Tang2, Jin‑Yu Xia1* and Xi Liu1* Abstract Background: There is an urgent need to better understand the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2), for that the coronavirus disease 2019 (COVID‑19) continues to cause considerable mor‑ bidity and mortality worldwide. This paper was to diferentiate COVID‑19 from other respiratory infectious diseases such as avian‑origin infuenza A (H7N9) and infuenza A (H1N1) virus infections. Methods: We included patients who had been hospitalized with laboratory‑confrmed infection by SARS‑CoV‑2 (n 83), H7N9 (n 36), H1N1 (n 44) viruses. Clinical presentation, chest CT features, and progression of patients were= compared. We= used the Logistic= regression model to explore the possible risk factors. Results: Both COVID‑19 and H7N9 patients had a longer duration of hospitalization than H1N1 patients (P < 0.01), a higher complication rate, and more severe cases than H1N1 patients. H7N9 patients had higher hospitalization‑fatality ratio than COVID‑19 patients (P 0.01). H7N9 patients had similar patterns of lymphopenia, neutrophilia, elevated alanine aminotransferase, C‑reactive= protein, lactate dehydrogenase, and those seen in H1N1 patients, which were all signifcantly diferent from patients with COVID‑19 (P < 0.01). Either H7N9 or H1N1 patients had more obvious symptoms, like fever, fatigue, yellow sputum, and myalgia than COVID‑19 patients (P < 0.01). The mean duration of viral shedding was 9.5 days for SARS‑CoV‑2 vs 9.9 days for H7N9 (P 0.78). For severe cases, the meantime from illness onset to severity was 8.0 days for COVID‑19 vs 5.2 days for H7N9 (P= < 0.01), the comorbidity of chronic heart disease was more common in the COVID‑19 patients than H7N9 (P 0.02). Multivariate analysis showed that chronic heart disease was a possible risk factor (OR > 1) for COVID‑19, compared= with H1N1 and H7N9. Conclusions: The proportion of severe cases were higher for H7N9 and SARS‑CoV‑2 infections, compared with H1N1. The meantime from illness onset to severity was shorter for H7N9. Chronic heart disease was a possible risk factor for COVID‑19.The comparison may provide the rationale for strategies of isolation and treatment of infected patients in the future. Keywords: SARS‑CoV‑2, COVID‑19, H7N9, H1N1, Comparison Background Te emergence of human infections with the SARS- CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) virus and its rapid national and international spread poses a global health emergency [1]. As of 15 April 2020, *Correspondence: [email protected]; [email protected] the number of patients infected with SARS-CoV-2 has † Li‑Si Deng, Jing Yuan, and Li Ding contributed equally to this work exceeded two million globally, with the highest mortal- 1 Department of Infectious Diseases, The Fifth Afliated Hospital, Sun Yat‑ Sen University, Zhuhai 519000, China ity rate of beyond 10.0% in several countries. Although Full list of author information is available at the end of the article the outbreak was likely to have started from a zoonotic © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/publi cdoma in/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Deng et al. Infect Dis Poverty (2020) 9:163 Page 2 of 9 transmission and associated with live wild animals, it has patients and had been laboratory confrmed by real- soon been confrmed that direct human-to-human trans- time reverse transcriptase polymerase chain reaction mission was occurring [2]. (RT-PCR). Besides, all patients with H1N1and H7N9 It has been reported that highest viral loads (inversely had been hospitalized for pneumonia or severe symp- related to CT value) were detected soon after symptom toms (eg, uncontrollable fever, shortness of breath, severe onset, with higher viral loads detected in the nose than cough, hemoptysis, symptoms associated with comorbid- in the throat; it has suggested that the viral nucleic acid ities); but for hospitalized COVID-19 cases, only patients shedding pattern of patients infected with SARS-CoV-2 with pneumonia were included in the analysis. resembles that of patients with infuenza and appears diferent from that seen in patients infected with SARS- Data collection CoV [3]. Besides, the pattern of transmission and the All the clinical data on signs and symptoms, underlying characteristics of the disease are similar to infuenza ini- comorbidities, laboratory results, chest CT scans, and tially, although they are from diferent viral families [4]. It treatment measures were retrospectively extracted from may confuse in identifying infuenza and COVID-19 (the electronic medical records and checked by both on-site Coronavirus disease 2019) for that common symptoms and of-site doctors. We extracted the baseline data from include fever and cough, whereas gastrointestinal symp- the patients after admission. Te RT-PCR test was per- toms (eg, nausea, vomiting, diarrhea) [4]. In the past formed using nasal and pharyngeal swab specimens, decade, two highly pathogenic infuenza virus, the avian RT-PCR was performed every other day and three con- infuenza A (H7N9) and infuenza A/H1N1/2009 virus secutive days once negative for SARS-CoV-2 test after have emerged in two separate events. admission to hospital, RT-PCR was performed every Te pandemic caused by the infuenza A/H1N1/2009 other day and two consecutive days once negative for virus starting in the spring of 2009 has caused signifcant H7N9′s test. Chest CT scans were performed on admis- morbidity and mortality in certain patients [5, 6]. During sion (except for two pregnant patients with H1N1 virus the spring of 2013, cases of human infection with avian infections), and analyzed according to the number of infuenza A (H7N9) virus were frst reported in China, lung lobes involvement. Te total CT score was the sum evidence emerged in many cities and regions; most of the of the individual lobar involvement. Fever was defned as cases were severe, with high fatality; as of May 9 2013, the axillary temperature of at least 37.3 °C. Severe cases the World Health Organization (WHO) had reported 131 were defned by the patient experiencing an oxygenation laboratory-confrmed cases, including 32 deaths [7–9]. index under 300 mmHg or admission to an intensive care Understanding the clinical characteristics and determi- unit. nants of the severity of disease due to SARS-CoV-2 virus infection is essential both for the identifcation and clini- Statistical analysis cal management of high-risk cases. To provide insights We used χ2 and Fischer’s exact tests for categorical vari- into the pathogenesis of SARS-CoV-2 virus infection, ables, whereas we used the student’s t-test or Mann– we compared the clinical presentation, chest CT fea- Whitney U test for continuous variables to assess the tures, and progression of patients hospitalized with diferences. We did statistical analyses using SPSS soft- SARS-CoV-2, H7N9, and H1N1 virus infections. We also ware (version 13.0 SPSS, Chicago, Illinois). Te signif- compared the characteristics of severe cases between cance for all statistical analyses was defned as P < 0.05. COVID-19 and H7N9, severe cases with H1N1 were not We used the Kaplan–Meier method to estimate survival included in the comparison because the number was just curves for death. Te same approach was used to deter- fve and small amounts of data may not be representative. mine the time for invasive mechanical ventilation or tracheal intubation. Te Logistic regression model was Methods used to explore the possible risk factors. We used kernel Study design and participants density to determine the distribution of the number of Te patients with laboratory confrmed SARS-CoV-2 days of hospitalization, and the days from illness onset to infection were hospitalized between 17 January 2020 and severity. Severity was defned by the patient experiencing 20 March 2020, and H1N1 virus infections were hospi- an oxygenation index under 300 mmHg or or admission talized between 20 March 2017 and 8 March 2019, at to an intensive care unit. Te Fifth Afliated Hospital of Sun Yat-Sen University. Patients with H7N9 virus infection were hospitalized Results between 18 December 2013 and 28 Febuary 2015, at Patient characteristics Shenzhen Tird People’s Hospital. All subjects with virus Data were included 83 patients with COVID-19, 36 infection reported in this manuscript were hospitalized patients with H7N9, and 44 patients with H1N1 virus Deng et al.
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