Changes in respiratory infection trends during the COVID-19 pandemic in patients with haematologic malignancy

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However, its impact on community-acquired pneumonia (CAP) in high-risk patients with haematological malignancies (HM) is uncertain. We aimed to examine how community-acquired pneumonia aetiology in patients with haematological malignancies changed during the COVID-19 pandemic. Methods : This was a retrospective study that included 524 patients with haematological malignancies hospitalised with community-acquired pneumonia between March 2018 and February 2022. Patients who underwent bronchoscopy within 24 hours of admission to identify community-acquired pneumonia aetiology were included. Data on patient characteristics, laboratory findings, and results of bronchioalveolar lavage fluid cultures and polymerase chain reaction tests were analysed and compared to identify changes and in-hospital mortality risk factors. Results : Patients were divided into the ‘pre-COVID-19 era’ (44.5%) and ‘COVID-19 era’ (55.5%) groups. The incidence of viral community-acquired pneumonia significantly decreased in the COVID-19 era, particularly for influenza A, parainfluenza, adenovirus, and rhinovirus (pre-COVID-19 era vs. COVID-19 era: 3.0% vs. 0.3%, P = 0.036; 6.5% vs. 0.7%, P = 0.001; 5.6% vs. 1.4%, P = 0.015; and 9.5% vs. 1.7%, P < 0.001, respectively), whereas that of bacterial, fungal, and unknown community-acquired pneumonia aetiologies remain unchanged. Higher Sequential Organ Failure Assessment scores and lower platelet counts correlated with in-hospital mortality after adjusting for potential confounding factors. Conclusions : In the COVID-19 era, the incidence of community-acquired pneumonia with viral aetiologies markedly decreased among patients with haematological malignancies, with no changes in the incidence of bacterial and fungal pneumonia. Further studies are required to evaluate the impact of COVID-19 on the prognosis of patients with haematological malignancies and community-acquired pneumonia. COVID-19 community-acquired pneumonia immune deficiency haematologic malignancy Figures Figure 1 Figure 2 Figure 3 Figure 4 Background The coronavirus disease 2019 (COVID-19) pandemic led to significant changes in respiratory infection patterns. After its outbreak in December 2019, in Wuhan, China, COVID-19 spread rapidly worldwide. Governments globally have extensively advocated for a range of measures to curb the COVID-19 pandemic, such as wearing masks, education on hand hygiene, social distancing, and travel restrictions. The Korean government has implemented several measures since February 2020 to prevent COVID-19 outbreaks, including active epidemiological investigations, quarantine of patients suspected of having the disease, and extensive public lockdowns [ 1 ]. The implementation of these strategies not only resulted in a decrease in the spread of COVID-19 but also substantially reduced that of other respiratory infections. Previous studies have reported a reduction in seasonal influenza activity [ 2 – 4 ], leading to a subsequent decrease in the occurrence of community-acquired pneumonia and hospital as well as intensive care unit (ICU) admissions [ 5 ]. Owing to both the characteristics of their condition and antineoplastic therapies, patients with haematological malignancies (HM) are immunocompromised and at high risk of infectious complications. They have a high incidence of community-acquired pneumonia (CAP), leading to substantial morbidity and mortality within this population [ 6 , 7 ]. Early identification of CAP aetiology in patients with HM is important; however, despite the use of a comprehensive diagnostic workup, the aetiology of pneumonia is often under identified [ 8 , 9 ]. Previous studies have revealed that immunocompromised patients with pneumonia of unknown aetiology have increased mortality rates [ 10 , 11 ]. Furthermore, due to their immunocompromised status, the aetiology of CAP in these patients presents distinct characteristics from that in the general population. Therefore, a thorough exploration of the changing patterns in the aetiology of CAP, specifically in patients with HM, is warranted. Moreover, the impact of the COVID-19 era on the changing patterns of CAP in patients with HM remains uncertain. Methods Patients This study aimed to examine the changes in CAP aetiology in patients with HM during the COVID-19 pandemic. We retrospectively studied a cohort of patients with HM who visited the emergency department or outpatient clinic of Seoul St. Mary’s Hospital (Seoul, Korea) with respiratory symptoms and required admission between March 2018 and February 2022. In this hospital, more than 500 patients undergo haematopoietic stem cell transplantations annually. Eligible patients included those who exhibited abnormal findings on chest radiographs and underwent bronchoscopy (BRS) within 24 hours of admission. Patients who did not undergo BRS within 24 hours of admission, those diagnosed with hospital-acquired pneumonia (HAP), those diagnosed with a non-infectious disease, and those newly diagnosed with COVID-19 were excluded (Fig. 1 ). Patients with COVID-19 were excluded because they could not undergo invasive procedures, such as bronchoalveolar lavage (BAL), to determine the aetiology of their respiratory infection, in accordance with hospital policy. Patients with HM were defined as those who underwent concurrent evaluations and treatment without remission [ 12 ]. This study was approved by the Institutional Review Board of Seoul St. Mary’s Hospital (KC23RISI0113), and the requirement for informed consent was waived by the Institutional Review Board of Seoul St. Mary’s Hospital. [insert Fig. 1 ] Data collection Epidemiological and clinical data were collected from the patients’ medical charts at admission. Data included sex; age; laboratory findings, including white blood cell (WBC) count, absolute neutrophil count (ANC), absolute lymphocyte count (ALC), haemoglobin level, haematocrit level, platelet count, and C-reactive protein (CRP) level; characteristics of the HMs, including the type of malignancy, current status, and prior treatments; Sequential Organ Failure Assessment (SOFA) score at admission; body temperature at admission; and pattern of chest radiographic abnormalities. The results of BAL fluid culture, BAL galactomannan test, special staining (Gomori methenamine silver, periodic acid Schiff, or Ziehl–Neelsen) of BAL cells, atypical pneumonia serological panel ( Chlamydia, Legionella , and Mycoplasma ), blood culture, and serum galactomannan were also reviewed. A respiratory virus polymerase chain reaction (PCR) multiplex panel (AdvanSure RV real-time PCR Kit; LG Life Sciences, Seoul, Korea) was used to test for influenza A and B viruses, parainfluenza, respiratory syncytial virus (RSV), adenovirus, bocavirus, human metapneumovirus, coronavirus, and human rhinovirus in BAL samples. Nucleic acid extraction was performed using a QIAamp DNA Mini Kit in an automated extractor (Qiacube, Qiagen, Hilden, Germany). Pneumonia was defined as the presence of a new infiltration on a chest radiograph at the time of the hospital visit with more than one of the following criteria: (1) new or increased cough with or without sputum production, (2) fever (temperature ≥ 38.0℃) or hypothermia (< 35.0℃), and (3) evidence of systemic inflammation (abnormal WBC count or increased CRP level) [ 6 ]. Invasive fungal diseases, including pulmonary aspergillosis, were defined based on the presence of compatible host factors, clinical features, and mycological evidence according to the European Organisation for Research and Treatment of Cancer/Mycoses Study Group criteria [ 13 ]. The diagnosis of Pneumocystis jirovecii pneumonia was based on the identification of the organism and/or positive PCR results from the BAL fluid, along with compatible clinical features and radiological findings [ 13 ]. CAP cases of unknown aetiology were characterised by negative results in both BAL culture and PCR tests as well as negative serological examinations where no other identifiable cause of pulmonary infiltration could be found. Patients with HAP were defined as those admitted to the hospital for a reason other than acute respiratory infection, in whom respiratory symptoms developed ≥ 72 hours after admission. Finally, we examined the clinical outcomes, including ICU admission and in-hospital mortality. Statistical analysis Continuous variables were reported as median (range), whereas categorical variables were described as numbers (%). Patient characteristics were compared using the chi-squared test or Fisher’s exact test, as appropriate, for categorical variables and independent sample t-tests for continuous variables. The odds ratios (OR) and their corresponding confidence intervals (CI) were computed. Goodness-of-fit was computed to assess the relevance of the logistic regression model. All tests were two-sided, and a P value < 0.05 was considered statistically significant. All statistical analyses were performed using SPSS for Windows software (ver. 20.0; IBM Corp., Armonk, NY, USA) and R (ver. 4.3.1, R Foundation, Venna, Austria). Results Patient characteristics Among the 1,296 patients with HM, respiratory symptoms, and chest radiographic infiltration admitted to our hospital between March 2018 and February 2022, 524 were included in our analysis (Fig. 1 ). As the Korean government implemented COVID-19 containment policies in February 2020, we divided the timeline into ‘pre-COVID-19’ and ‘COVID-19’ eras, using February 2020 as the point of demarcation [ 1 ]. The ‘pre-COVID-19 era’ and ‘COVID-19 era’ groups comprised 233 (44.5%) and 291 (55.5%) patients, respectively. Aside from a higher proportion of patients with bilateral pulmonary infiltration on their chest radiographs in the pre-COVID-19 era group than in the COVID-19 era group (81.1% vs. 69.4%, respectively, P = 0.003), no significant differences were observed between the two groups in terms of patient characteristics (Table 1 ). Table 1 Baseline characteristics Variables Pre-COVID-19 era (n = 233) COVID-19 era (n = 291) P value Age 57.0 (45.0–66.0) 60.0 (49.0–68.0) 0.054 Sex, male 136 (58.4) 181 (62.2) 0.423 Underlying haematologic malignancies Acute myeloid leukaemia 77 (33.0%) 101 (34.7%) 0.997 Acute lymphoblastic leukaemia 28 (12.0%) 35 (12.0%) Chronic myeloid leukaemia 11 (4.7%) 11 (3.8%) Multiple myeloma 26 (11.2%) 35 (12.0%) Myelodysplastic syndromes 36 (15.5%) 44 (15.1%) Lymphoma 29 (12.4%) 35 (12.0%) Others 26 (11.2%) 30 (10.3%) Disease status Active 169 (72.5) 217 (74.6) 0.670 Relapsed 49 (21.0) 77 (26.5) 0.179 HSCT recipients Autologous HSCT 14 (6.0) 30 (10.3) 0.108 Allogenic HSCT 91 (39.1) 123 (42.3) 0.513 SOFA score 3.0 (2.0–5.0) 3.0 (2.0–5.0) 0.233 Fever (temperature ≥ 38°C) 158 (67.8%) 175 (60.1%) 0.085 Bilateral pulmonary infiltration on chest radiograph 189 (81.1) 202 (69.4) 0.003 Prognosis ICU admission 50 (21.5) 69 (23.7) 0.612 In-hospital mortality 43 (18.5) 63 (21.6) 0.427 Data are presented as a number (percentage) or median (interquartile range). HSCT, haematopoietic stem cell transplantation; SOFA, Sequential Organ Failure Assessment; ICU, intensive care unit. [insert Table 1 ] Changes in CAP aetiology No significant differences were evident between the pre-COVID-19 era and COVID-19 era groups in the number of patients admitted due to CAP (Fig. 2 ). Table 2 and Fig. 3 show the changes in the aetiology of CAP during the pandemic. During the pre-COVID-19 era, the proportions of aetiologies were as follows: unknown aetiology (36.5%), respiratory virus (30.7%), bacteria (23.2%), and fungus (16.3%). During the COVID-19 era, the proportion of aetiologies changed to the following: unknown aetiology (41.6%), bacteria (24.4%), fungus (18.9%), and respiratory virus (6.6%). From the pre-COVID-19 era to the COVID-19 era, the proportions of bacterial, fungal, and unknown aetiology CAP remained unchanged, whereas that of viral CAP significantly decreased. As shown in Table 2 and Fig. 4 , the proportion of respiratory viruses decreased during the pandemic. In particular, a significant reduction in the incidence of influenza A (pre-COVID-19 era vs. COVID-19 era: 3.0% vs. 0.3%, P = 0.036), parainfluenza (6.5% vs. 0.7%, P = 0.001), adenovirus (5.6% vs. 1.4%, P = 0.015), and rhinovirus (9.5% vs. 1.7%, P < 0.001) were observed during the pandemic. Table 2 Changes in pneumonia aetiology from the pre-COVID-19 era to the COVID-19 era Pathogen species Pre-COVID-19 era (n = 233) COVID-19 era (n = 291) P value Bacteria 54 (23.2) 71 (24.4) 0.823 Gram-positive bacteria Staphylococcus aureus 4 (1.7) 8 (2.7) 0.623 Streptococcus pneumoniae 4 (1.7) 0 (0.0) 0.082 Enterococci 5 (2.1) 4 (1.4) 0.736 Gram-negative bacteria Klebsiella pneumoniae 5 (2.1) 11 (3.8) 0.409 Escherichia coli 1 (0.4) 5 (1.7) 0.335 Pseudomonas aeruginosa 9 (3.9) 11 (3.8) 1.000 Chlamydia pneumoniae 5 (2.1) 9 (3.1) 0.693 Acinetobacter baumannii 2 (0.9) 3 (1.0) 1.000 Mycoplasma pneumoniae 8 (3.4) 7 (2.4) 0.662 Mycobacterium tuberculosis 10 (4.3) 11 (3.8) 0.942 Others * 8 (2.8) 10 (3.4) 0.822 Fungus 38 (16.3) 55 (18.9) 0.512 Invasive aspergillosis 20 (8.6) 41 (14.1) 0.069 Pneumocystis jirovecii 18 (7.7) 20 (6.9) 0.838 Respiratory virus 71 (30.7) 19 (6.6) < 0.001 Influenza A 7 (3.0) 1 (0.3) 0.036 Influenza B 1 (0.4) 0 (0.0) 0.913 Respiratory syncytial virus 10 (4.3) 6 (2.1) 0.227 Parainfluenza virus 15 (6.5) 2 (0.7) 0.001 Adenovirus 13 (5.6) 4 (1.4) 0.015 Metapneumovirus 2 (0.9) 0 (0.0) 0.386 Rhinovirus 22 (9.5) 5 (1.7) < 0.001 Human coronavirus 7 (3.0) 2 (0.7) 0.093 Bocavirus 1 (0.4) 1 (0.3) 1.000 Diffuse alveolar haemorrhage 1 (0.4) 3 (1.0) 0.778 Bronchiolitis obliterans 1 (0.4) 6 (2.1) 0.217 Cryptogenic organising pneumonia 7 (3.0) 19 (6.5) 0.100 Cytomegalovirus 7 (3.0) 2 (0.7) 0.093 Unknown aetiology 85 (36.5) 121 (41.6) 0.272 Data are presented as number (percentage) or median (interquartile range). * Others: Non-tuberculosis mycobacterium (4), Legionella pneumoniae (3), Corynebacterium striatum (3), Enterobacter species (2), Achromobacter species (1), Staphylococcus haemolyticus (1), Moraxella catarrhalis (1), Stenotrophomonas maltophilia (1), Rothia mucilaginosa (1), Haemophilus influenzae (1) [insert Fig. 2 ] [insert Table 2 ] [insert Fig. 3 ] [insert Fig. 4 ] Factors associated with increased mortality An additional table presents comparisons of the clinical characteristics between patients experiencing in-hospital death and survivors [see Additional file 1]. Non-survivors had higher active HM rates (non-survivors vs. survivors: 83.0% vs. 71.3%, P = 0.020), CRP levels (12.2 [6.4–21.3] vs. 8.4 [3.7–17.5], P = 0.001), disease relapse rates (34.9% vs. 21.3%, P = 0.005), and SOFA scores (4.0 [2.0–5.0] vs. 3.0 [2.0–5.0], P < 0.001) and lower ANCs (1.4 [0.2–6.1] vs. 3.3 [0.6–6.4], P = 0.049), haemoglobin levels (8.6 [7.6–10,60] vs. 9.7 [8.4–11.8], P < 0.001), haematocrit levels (25.1 [22.1–31.2] vs. 29.3 [25.2–35.5], P < 0.001), and platelet counts (27.5 [14.0–73.0] vs. 98.0 [36.0–191.0], P < 0.001) than survivors. The results of the logistic regression analysis of the clinical parameters used to evaluate the risk factors associated with in-hospital mortality are shown in Table 3 . A high SOFA score and CRP level, an active disease, and a low haemoglobin level, haematocrit level, and platelet count were independent risk factors for in-hospital mortality. After adjusting for potential confounding factors, high SOFA scores and low platelet counts were independently associated with in-hospital mortality (P < 0.001 and P = 0.004, respectively). Table 3 Logistic regression analysis results for in-hospital mortality Univariable Multivariable Variables Crude OR 95% CI P value Adjusted OR 95% CI P value SOFA score 1.42 1.29–1.57 < 0.001 1.28 1.15–1.44 < 0.001 Active disease 1.97 1.14–3.41 0.016 Relapsed disease 1.98 1.25–3.15 0.004 1.62 0.99–2.68 0.057 COVID-19 era 1.22 0.79–1.88 0.366 Absolute neutrophil count 1.00 0.97–1.03 0.946 Haemoglobin level 0.84 0.77–0.92 < 0.001 Haematocrit level 0.94 0.91–0.96 < 0.001 Platelet count 0.99 0.99–0.99 < 0.001 0.99 0.99–1.00 0.004 C-reactive protein level 1.03 1.01–1.05 0.004 OR: odds ratio; CI: confidence interval; SOFA: Sequential Organ Failure Assessment Discussion In the present study, we compared the aetiology of CAP among patients with HM before and during the COVID-19 pandemic. During the pandemic, numerous studies have focused on the incidence and treatment of COVID-19 in immunocompromised patients; however, limited research has been conducted on aetiologies of CAP other than COVID-19, particularly on changes in them, in such patients. Nonetheless, considering the susceptibility of immunocompromised patients to various opportunistic infections, it is crucial to examine the changes in pathogens that can cause CAP in the COVID-19 era. In contrast to the findings of previous studies that reported a decrease in the incidence of CAP in the COVID-19 era [ 14 – 17 ], in this study, the number of patients with HM hospitalised with CAP in the COVID-19 era did not decrease compared with that during the pre-COVID-19 era. Notably, the incidence of viral pneumonia demonstrated a significant decrease; however, the incidence of bacterial and fungal pneumonia remained unaffected, in contrast to other research findings. Although previous studies have reported a decline in the incidence of bacterial pneumonia [ 14 ], this study has not exhibited any decrease in its incidence during the COVID-19 pandemic. The unchanged incidence of bacterial pneumonia despite the rigorous infection control measures adopted during the COVID-19 pandemic indicates that the most significant risk factor for bacterial CAP in patients with HM is their immune status [ 18 ]. The incidence of pneumonia caused by respiratory viruses, including influenza A, parainfluenza, adenovirus, and rhinovirus, decreased significantly during the COVID-19 pandemic. Bilateral pulmonary infiltration on chest radiographs also showed a significant decrease during the COVID-19 pandemic, which was hypothesised to be a result of a decreased incidence of viral pneumonia [ 19 ]. Respiratory viruses usually cause mild upper respiratory tract infections; however, previous studies have reported that respiratory viruses are important pathogens causing CAP in immunocompromised patients and older adults [ 20 , 21 ]. As reported in other studies, the implementation of various preventive measures following COVID-19 outbreaks is likely to not only curtail the transmission of COVID-19 but also reduce the incidence of viral pneumonia caused by other respiratory viruses [ 2 – 4 ]. In this study, we observed an increase in the incidence of RSV during the winter of 2021, which is likely attributable to the RSV outbreak in South Korea due to the relaxation of domestic infection control measures in November 2021 [ 22 ]. CAP of unknown aetiology is relatively common among immunocompromised patients [ 23 , 24 ]. In this study, a substantial number of patients (39.3%) presented with CAP of unknown aetiology, despite our only including patients who underwent BRS to minimise the number of patients with an undetermined aetiology. The incidence of CAP of unknown aetiology did not decrease during the COVID-19 pandemic; however, this may not necessarily indicate that these cases were not caused by pathogens such as viruses or bacteria. The lack of testing for atypical infections and diagnostic limitations of laboratory techniques prevents us from drawing a definitive conclusion. It is plausible that these cases were associated with the patients' underlying diseases or immunocompromised status, but further investigation is needed to establish a causal relationship. We investigated the risk factors for in-hospital mortality in patients with HM who had CAP. Consistent with previous studies [ 25 , 26 ], high SOFA scores and low platelet counts were found to be risk factors for in-hospital mortality in patients with HM who had CAP. In general, while the CURB-65 (confusion, uraemia, respiratory rate, blood pressure, age ≥ 65 years) criteria or pneumonia severity index (PSI) are commonly used to predict the prognosis of patients with pneumonia, previous studies have shown that they are not effective in immunocompromised patients with cancer [ 27 ]. Thus, we opted to use the SOFA score instead. Thrombocytopenia is also associated with the severity of and poor prognosis in patients with infections [ 28 , 29 ]. Platelets play a role in inflammation and host defence mechanisms against microbial agents. Additionally, thrombocytopenia reflects bone marrow failure in patients with HM [ 30 ]. Therefore, thrombocytopenia could be a significant predictor of poor prognosis in patients with HM and CAP. This study has several limitations. First, its retrospective design and single-centre implementation may introduce a selection bias, potentially affecting the significance of our findings. Nevertheless, we meticulously examined all admitted patients with CAP who underwent BRS in this single, large, 4-year cohort with consistent treatment protocols. The objective of our study was to assess the impact of the COVID-19 pandemic on the changing pattern of aetiology of CAP in patients with HM; thus, the setting of this study did not significantly deviate from that of a prospective observational study. Second, conducting a single-centre study may have had limitations in determining the overall aetiology of CAP in all patients with HM. However, this institution serves as the largest Asian centre for haematological disorders, performing over 500 bone marrow transplantations annually. Therefore, these data can be considered reasonably representative. Third, patients’ COVID-19 histories were not investigated. Previous studies reported that COVID-19 is a risk factor for bacterial or fungal co-infections and can play a significant role in patient prognosis [ 31 , 32 ]. However, due to the retrospective nature of the study, it was not possible to conduct an investigation. Additional studies are needed to evaluate the impact of a COVID-19 history on the prognosis of patients with CAP and HM. Conclusions In the context of pandemic eras such as that of COVID-19, understanding the changes in CAP aetiology among immunocompromised patients, including those with HM, is crucial. The CAP incidence in patients with HM did not decrease during the COVID-19 pandemic, unlike that in the general population. A notable shift in the aetiology of CAP emerged among patients with HM during the COVID-19 pandemic, with a significant reduction in the incidence of viral pneumonia but no change in that of bacterial and fungal pneumonia. Further research is needed to evaluate the effects of COVID-19 on the prognosis of patients with HM and CAP. Abbreviations ALC absolute lymphocyte count ANC absolute neutrophil count BAL bronchoalveolar lavage BRS bronchoscopy CAP community-acquired pneumonia CI confidence intervals COVID-19 coronavirus disease 2019 CRP C-reactive protein HAP hospital-acquired pneumonia HM haematological malignancies ICU intensive care unit OR odds ratios PCR polymerase chain reaction PSI pneumonia severity index RSV respiratory syncytial virus SOFA Sequential Organ Failure Assessment WBC white blood cell Declarations Ethics approval and consent to participate This study was approved by the Institutional Review Board of Seoul St. Mary’s Hospital (KC23RISI0113), and the requirement for informed consent was waived by the Institutional Review Board of Seoul St. Mary’s Hospital. Consent for publication Not applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors’ contributions JW analysed and interpreted the patient data and drafted the work. SC made substantial contributions to the conception. JM made design of the work and interpreted the data and substantively revised the manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable References Park IN, Yum HK. Stepwise strategy of social distancing in Korea. J Korean Med Sci. 2020;35:e264. Lee H, Lee H, Song KH, Kim ES, Park JS, Jung J, et al. Impact of public health interventions on seasonal influenza activity during the COVID-19 outbreak in Korea. 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Salacz ME, Lankiewicz MW, Weissman DE. Management of thrombocytopenia in bone marrow failure: a review. J Palliat Med. 2007;10:236–44. Hoenigl M, Seidel D, Sprute R, Cunha C, Oliverio M, Goldman GH, et al. COVID-19-associated fungal infections. Nat Microbiol. 2022;7:1127–40. Shafran N, Shafran I, Ben-Zvi H, Sofer S, Sheena L, Krause I, et al. Secondary bacterial infection in COVID-19 patients is a stronger predictor for death compared to influenza patients. Sci Rep. 2021;11:12703. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Published Journal Publication published 26 May, 2024 Read the published version in BMC Pulmonary Medicine → Version 1 posted Editorial decision: Revision requested 17 Feb, 2024 Reviews received at journal 11 Feb, 2024 Reviews received at journal 13 Jan, 2024 Reviewers agreed at journal 02 Jan, 2024 Reviewers invited by journal 02 Jan, 2024 Editor assigned by journal 01 Jan, 2024 Editor invited by journal 27 Dec, 2023 Submission checks completed at journal 27 Dec, 2023 First submitted to journal 26 Dec, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3810411","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":264451393,"identity":"2c4fa5e2-eeba-4900-9ac6-c56305f6fbd3","order_by":0,"name":"Jiwon Ryoo","email":"","orcid":"","institution":"Bucheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea","correspondingAuthor":false,"prefix":"","firstName":"Jiwon","middleName":"","lastName":"Ryoo","suffix":""},{"id":264451394,"identity":"73a57b02-dcdc-4ba5-ad35-a98a91874278","order_by":1,"name":"Seok Chan Kim","email":"","orcid":"","institution":"Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea","correspondingAuthor":false,"prefix":"","firstName":"Seok","middleName":"Chan","lastName":"Kim","suffix":""},{"id":264451395,"identity":"c6b7b9af-df96-4374-a954-354c450c1e60","order_by":2,"name":"Jongmin Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIie3RsQrCMBCA4SsBp1jXFqF9hQsFJ+mzXCk4OTg6Cg5O7t18Bt+gclCXalfBpY8QcHUwik5KrJtD/ukIfHBHAFyuf4wlAOHYTGZo8fEmvhM9mwD0HrYLKSV4heYngQ7E3/f5IrGJB5v1rqVZCoNVKZK5hYTsT4YSz6qo/BwJcwhqElltIchyJAwhqOQoICwBTiB2CztJzGJHil8k7kAwLLAkfBE0JLOR+y2Bxlxtq2lyv0WqOlsqG/GbA2u6pnHEtWr1NY2iPXNoI2+Z3/F+Ai6Xy+X60A0PiUk7gc5bDwAAAABJRU5ErkJggg==","orcid":"","institution":"Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea","correspondingAuthor":true,"prefix":"","firstName":"Jongmin","middleName":"","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2023-12-27 03:59:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3810411/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3810411/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12890-024-03071-0","type":"published","date":"2024-05-26T19:47:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49080465,"identity":"7b91e42f-4e55-46ac-9a1f-fe3f87c671e0","added_by":"auto","created_at":"2024-01-02 19:56:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":392243,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy flow diagram. \u003c/strong\u003eHM, haematologic malignancy; BAL, bronchoalveolar lavage; COVID-19, coronavirus disease 2019; CAP, community-acquired pneumonia.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3810411/v1/7be1a1913dab33c5df61406b.png"},{"id":49081554,"identity":"c761889f-4519-4d5b-ac61-b62485db9947","added_by":"auto","created_at":"2024-01-02 20:04:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":514043,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTotal number of admitted patients with CAP between March 2019 and February 2022. \u003c/strong\u003eSpring, from March to May; Summer, from June to August; Fall, from September to November; Winter, from December to February.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3810411/v1/9a31bd5040321b4c131852d2.png"},{"id":49080468,"identity":"916b9c61-38a0-4a61-bb18-cd20b4df7a73","added_by":"auto","created_at":"2024-01-02 19:56:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":256446,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChange in CAP aetiology over time. \u003c/strong\u003eSpring, from March to May; Summer, from June to August; Fall, from September to November; Winter, from December to February.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3810411/v1/c7dc35617d3d0b07def59ed1.png"},{"id":49080466,"identity":"f1431d06-db30-491c-a555-3e5cc2045f3d","added_by":"auto","created_at":"2024-01-02 19:56:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":885425,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSeasonal distribution of respiratory virus infections. \u003c/strong\u003eADENO, adenovirus; BOCA, bocavirus; CORONA, human coronavirus; INF A, Influenza A; INF B, Influenza B; META, metapneumovirus; PARA, parainfluenza virus; RHINO, rhinovirus; RSV, respiratory syncytial virus. Spring, from March to May; Summer, from June to August; Fall, from September to November; Winter, from December to February.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3810411/v1/883f682a5ac18fa6577e060b.png"},{"id":57169326,"identity":"5108d2c4-1508-463c-872a-ae3976e7b1da","added_by":"auto","created_at":"2024-05-26 19:47:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2360079,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3810411/v1/21358056-c18b-479d-9e66-f33bbd79944c.pdf"},{"id":49080469,"identity":"832c3360-c6d5-4850-8cd4-7088c64932b7","added_by":"auto","created_at":"2024-01-02 19:56:31","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":18976,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-3810411/v1/471563e90ee7db4242d2548f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Changes in respiratory infection trends during the COVID-19 pandemic in patients with haematologic malignancy","fulltext":[{"header":"Background","content":"\u003cp\u003eThe coronavirus disease 2019 (COVID-19) pandemic led to significant changes in respiratory infection patterns. After its outbreak in December 2019, in Wuhan, China, COVID-19 spread rapidly worldwide. Governments globally have extensively advocated for a range of measures to curb the COVID-19 pandemic, such as wearing masks, education on hand hygiene, social distancing, and travel restrictions. The Korean government has implemented several measures since February 2020 to prevent COVID-19 outbreaks, including active epidemiological investigations, quarantine of patients suspected of having the disease, and extensive public lockdowns [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The implementation of these strategies not only resulted in a decrease in the spread of COVID-19 but also substantially reduced that of other respiratory infections. Previous studies have reported a reduction in seasonal influenza activity [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], leading to a subsequent decrease in the occurrence of community-acquired pneumonia and hospital as well as intensive care unit (ICU) admissions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOwing to both the characteristics of their condition and antineoplastic therapies, patients with haematological malignancies (HM) are immunocompromised and at high risk of infectious complications. They have a high incidence of community-acquired pneumonia (CAP), leading to substantial morbidity and mortality within this population [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Early identification of CAP aetiology in patients with HM is important; however, despite the use of a comprehensive diagnostic workup, the aetiology of pneumonia is often under identified [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Previous studies have revealed that immunocompromised patients with pneumonia of unknown aetiology have increased mortality rates [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Furthermore, due to their immunocompromised status, the aetiology of CAP in these patients presents distinct characteristics from that in the general population. Therefore, a thorough exploration of the changing patterns in the aetiology of CAP, specifically in patients with HM, is warranted. Moreover, the impact of the COVID-19 era on the changing patterns of CAP in patients with HM remains uncertain.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003ePatients\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study aimed to examine the changes in CAP aetiology in patients with HM during the COVID-19 pandemic. We retrospectively studied a cohort of patients with HM who visited the emergency department or outpatient clinic of Seoul St. Mary\u0026rsquo;s Hospital (Seoul, Korea) with respiratory symptoms and required admission between March 2018 and February 2022. In this hospital, more than 500 patients undergo haematopoietic stem cell transplantations annually. Eligible patients included those who exhibited abnormal findings on chest radiographs and underwent bronchoscopy (BRS) within 24 hours of admission. Patients who did not undergo BRS within 24 hours of admission, those diagnosed with hospital-acquired pneumonia (HAP), those diagnosed with a non-infectious disease, and those newly diagnosed with COVID-19 were excluded (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Patients with COVID-19 were excluded because they could not undergo invasive procedures, such as bronchoalveolar lavage (BAL), to determine the aetiology of their respiratory infection, in accordance with hospital policy. Patients with HM were defined as those who underwent concurrent evaluations and treatment without remission [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This study was approved by the Institutional Review Board of Seoul St. Mary\u0026rsquo;s Hospital (KC23RISI0113), and the requirement for informed consent was waived by the Institutional Review Board of Seoul St. Mary\u0026rsquo;s Hospital.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[insert Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e \u003cb\u003eData collection\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEpidemiological and clinical data were collected from the patients\u0026rsquo; medical charts at admission. Data included sex; age; laboratory findings, including white blood cell (WBC) count, absolute neutrophil count (ANC), absolute lymphocyte count (ALC), haemoglobin level, haematocrit level, platelet count, and C-reactive protein (CRP) level; characteristics of the HMs, including the type of malignancy, current status, and prior treatments; Sequential Organ Failure Assessment (SOFA) score at admission; body temperature at admission; and pattern of chest radiographic abnormalities. The results of BAL fluid culture, BAL galactomannan test, special staining (Gomori methenamine silver, periodic acid Schiff, or Ziehl\u0026ndash;Neelsen) of BAL cells, atypical pneumonia serological panel (\u003cem\u003eChlamydia, Legionella\u003c/em\u003e, and \u003cem\u003eMycoplasma\u003c/em\u003e), blood culture, and serum galactomannan were also reviewed. A respiratory virus polymerase chain reaction (PCR) multiplex panel (AdvanSure RV real-time PCR Kit; LG Life Sciences, Seoul, Korea) was used to test for influenza A and B viruses, parainfluenza, respiratory syncytial virus (RSV), adenovirus, bocavirus, human metapneumovirus, coronavirus, and human rhinovirus in BAL samples. Nucleic acid extraction was performed using a QIAamp DNA Mini Kit in an automated extractor (Qiacube, Qiagen, Hilden, Germany).\u003c/p\u003e \u003cp\u003ePneumonia was defined as the presence of a new infiltration on a chest radiograph at the time of the hospital visit with more than one of the following criteria: (1) new or increased cough with or without sputum production, (2) fever (temperature\u0026thinsp;\u0026ge;\u0026thinsp;38.0℃) or hypothermia (\u0026lt;\u0026thinsp;35.0℃), and (3) evidence of systemic inflammation (abnormal WBC count or increased CRP level) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Invasive fungal diseases, including pulmonary aspergillosis, were defined based on the presence of compatible host factors, clinical features, and mycological evidence according to the European Organisation for Research and Treatment of Cancer/Mycoses Study Group criteria [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The diagnosis of \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e pneumonia was based on the identification of the organism and/or positive PCR results from the BAL fluid, along with compatible clinical features and radiological findings [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. CAP cases of unknown aetiology were characterised by negative results in both BAL culture and PCR tests as well as negative serological examinations where no other identifiable cause of pulmonary infiltration could be found. Patients with HAP were defined as those admitted to the hospital for a reason other than acute respiratory infection, in whom respiratory symptoms developed\u0026thinsp;\u0026ge;\u0026thinsp;72 hours after admission. Finally, we examined the clinical outcomes, including ICU admission and in-hospital mortality.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were reported as median (range), whereas categorical variables were described as numbers (%). Patient characteristics were compared using the chi-squared test or Fisher\u0026rsquo;s exact test, as appropriate, for categorical variables and independent sample t-tests for continuous variables. The odds ratios (OR) and their corresponding confidence intervals (CI) were computed. Goodness-of-fit was computed to assess the relevance of the logistic regression model. All tests were two-sided, and a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All statistical analyses were performed using SPSS for Windows software (ver. 20.0; IBM Corp., Armonk, NY, USA) and R (ver. 4.3.1, R Foundation, Venna, Austria).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003ePatient characteristics\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAmong the 1,296 patients with HM, respiratory symptoms, and chest radiographic infiltration admitted to our hospital between March 2018 and February 2022, 524 were included in our analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As the Korean government implemented COVID-19 containment policies in February 2020, we divided the timeline into \u0026lsquo;pre-COVID-19\u0026rsquo; and \u0026lsquo;COVID-19\u0026rsquo; eras, using February 2020 as the point of demarcation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The \u0026lsquo;pre-COVID-19 era\u0026rsquo; and \u0026lsquo;COVID-19 era\u0026rsquo; groups comprised 233 (44.5%) and 291 (55.5%) patients, respectively. Aside from a higher proportion of patients with bilateral pulmonary infiltration on their chest radiographs in the pre-COVID-19 era group than in the COVID-19 era group (81.1% vs. 69.4%, respectively, P\u0026thinsp;=\u0026thinsp;0.003), no significant differences were observed between the two groups in terms of patient characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-COVID-19 era\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;233)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCOVID-19 era\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;291)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.0 (45.0\u0026ndash;66.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.0 (49.0\u0026ndash;68.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136 (58.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e181 (62.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderlying haematologic malignancies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute myeloid leukaemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77 (33.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101 (34.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute lymphoblastic leukaemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic myeloid leukaemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple myeloma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyelodysplastic syndromes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36 (15.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44 (15.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169 (72.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e217 (74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.670\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelapsed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSCT recipients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAutologous HSCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllogenic HSCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91 (39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123 (42.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.513\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.0 (2.0\u0026ndash;5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.0 (2.0\u0026ndash;5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever (temperature\u0026thinsp;\u0026ge;\u0026thinsp;38\u0026deg;C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e158 (67.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175 (60.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBilateral pulmonary infiltration on chest radiograph\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e189 (81.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e202 (69.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrognosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.612\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-hospital mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are presented as a number (percentage) or median (interquartile range). HSCT, haematopoietic stem cell transplantation; SOFA, Sequential Organ Failure Assessment; ICU, intensive care unit.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e \u003cb\u003eChanges in CAP aetiology\u003c/b\u003e \u003c/p\u003e \u003cp\u003eNo significant differences were evident between the pre-COVID-19 era and COVID-19 era groups in the number of patients admitted due to CAP (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e show the changes in the aetiology of CAP during the pandemic. During the pre-COVID-19 era, the proportions of aetiologies were as follows: unknown aetiology (36.5%), respiratory virus (30.7%), bacteria (23.2%), and fungus (16.3%). During the COVID-19 era, the proportion of aetiologies changed to the following: unknown aetiology (41.6%), bacteria (24.4%), fungus (18.9%), and respiratory virus (6.6%). From the pre-COVID-19 era to the COVID-19 era, the proportions of bacterial, fungal, and unknown aetiology CAP remained unchanged, whereas that of viral CAP significantly decreased. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the proportion of respiratory viruses decreased during the pandemic. In particular, a significant reduction in the incidence of influenza A (pre-COVID-19 era vs. COVID-19 era: 3.0% vs. 0.3%, P\u0026thinsp;=\u0026thinsp;0.036), parainfluenza (6.5% vs. 0.7%, P\u0026thinsp;=\u0026thinsp;0.001), adenovirus (5.6% vs. 1.4%, P\u0026thinsp;=\u0026thinsp;0.015), and rhinovirus (9.5% vs. 1.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were observed during the pandemic.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in pneumonia aetiology from the pre-COVID-19 era to the COVID-19 era\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogen species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-COVID-19 era\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;233)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCOVID-19 era\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;291)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54 (23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.823\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram-positive bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.623\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEnterococci\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram-negative bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlamydia pneumoniae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.693\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcinetobacter baumannii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMycoplasma pneumoniae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.662\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMycobacterium tuberculosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFungus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55 (18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvasive aspergillosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePneumocystis jirovecii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71 (30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfluenza A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfluenza B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory syncytial virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParainfluenza virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdenovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetapneumovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRhinovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman coronavirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBocavirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiffuse alveolar haemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.778\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBronchiolitis obliterans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCryptogenic organising pneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCytomegalovirus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown aetiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85 (36.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e121 (41.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are presented as number (percentage) or median (interquartile range). \u003csup\u003e*\u003c/sup\u003eOthers: Non-tuberculosis mycobacterium (4), \u003cem\u003eLegionella pneumoniae\u003c/em\u003e (3), \u003cem\u003eCorynebacterium striatum\u003c/em\u003e (3), \u003cem\u003eEnterobacter species\u003c/em\u003e (2), \u003cem\u003eAchromobacter\u003c/em\u003e species (1), \u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e (1), \u003cem\u003eMoraxella catarrhalis\u003c/em\u003e (1), \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e (1), \u003cem\u003eRothia mucilaginosa\u003c/em\u003e (1), \u003cem\u003eHaemophilus influenzae\u003c/em\u003e (1)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[insert Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e[insert Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e[insert Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e \u003cb\u003eFactors associated with increased mortality\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAn additional table presents comparisons of the clinical characteristics between patients experiencing in-hospital death and survivors [see Additional file 1]. Non-survivors had higher active HM rates (non-survivors vs. survivors: 83.0% vs. 71.3%, P\u0026thinsp;=\u0026thinsp;0.020), CRP levels (12.2 [6.4\u0026ndash;21.3] vs. 8.4 [3.7\u0026ndash;17.5], P\u0026thinsp;=\u0026thinsp;0.001), disease relapse rates (34.9% vs. 21.3%, P\u0026thinsp;=\u0026thinsp;0.005), and SOFA scores (4.0 [2.0\u0026ndash;5.0] vs. 3.0 [2.0\u0026ndash;5.0], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and lower ANCs (1.4 [0.2\u0026ndash;6.1] vs. 3.3 [0.6\u0026ndash;6.4], P\u0026thinsp;=\u0026thinsp;0.049), haemoglobin levels (8.6 [7.6\u0026ndash;10,60] vs. 9.7 [8.4\u0026ndash;11.8], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), haematocrit levels (25.1 [22.1\u0026ndash;31.2] vs. 29.3 [25.2\u0026ndash;35.5], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and platelet counts (27.5 [14.0\u0026ndash;73.0] vs. 98.0 [36.0\u0026ndash;191.0], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than survivors.\u003c/p\u003e \u003cp\u003eThe results of the logistic regression analysis of the clinical parameters used to evaluate the risk factors associated with in-hospital mortality are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. A high SOFA score and CRP level, an active disease, and a low haemoglobin level, haematocrit level, and platelet count were independent risk factors for in-hospital mortality. After adjusting for potential confounding factors, high SOFA scores and low platelet counts were independently associated with in-hospital mortality (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and P\u0026thinsp;=\u0026thinsp;0.004, respectively).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression analysis results for in-hospital mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude OR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.29\u0026ndash;1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.15\u0026ndash;1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14\u0026ndash;3.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelapsed disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.25\u0026ndash;3.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u0026ndash;2.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19 era\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u0026ndash;1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsolute neutrophil count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u0026ndash;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaemoglobin level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u0026ndash;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaematocrit level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u0026ndash;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u0026ndash;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOR: odds ratio; CI: confidence interval; SOFA: Sequential Organ Failure Assessment\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, we compared the aetiology of CAP among patients with HM before and during the COVID-19 pandemic. During the pandemic, numerous studies have focused on the incidence and treatment of COVID-19 in immunocompromised patients; however, limited research has been conducted on aetiologies of CAP other than COVID-19, particularly on changes in them, in such patients. Nonetheless, considering the susceptibility of immunocompromised patients to various opportunistic infections, it is crucial to examine the changes in pathogens that can cause CAP in the COVID-19 era.\u003c/p\u003e \u003cp\u003eIn contrast to the findings of previous studies that reported a decrease in the incidence of CAP in the COVID-19 era [\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], in this study, the number of patients with HM hospitalised with CAP in the COVID-19 era did not decrease compared with that during the pre-COVID-19 era. Notably, the incidence of viral pneumonia demonstrated a significant decrease; however, the incidence of bacterial and fungal pneumonia remained unaffected, in contrast to other research findings. Although previous studies have reported a decline in the incidence of bacterial pneumonia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], this study has not exhibited any decrease in its incidence during the COVID-19 pandemic. The unchanged incidence of bacterial pneumonia despite the rigorous infection control measures adopted during the COVID-19 pandemic indicates that the most significant risk factor for bacterial CAP in patients with HM is their immune status [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe incidence of pneumonia caused by respiratory viruses, including influenza A, parainfluenza, adenovirus, and rhinovirus, decreased significantly during the COVID-19 pandemic. Bilateral pulmonary infiltration on chest radiographs also showed a significant decrease during the COVID-19 pandemic, which was hypothesised to be a result of a decreased incidence of viral pneumonia [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Respiratory viruses usually cause mild upper respiratory tract infections; however, previous studies have reported that respiratory viruses are important pathogens causing CAP in immunocompromised patients and older adults [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. As reported in other studies, the implementation of various preventive measures following COVID-19 outbreaks is likely to not only curtail the transmission of COVID-19 but also reduce the incidence of viral pneumonia caused by other respiratory viruses [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In this study, we observed an increase in the incidence of RSV during the winter of 2021, which is likely attributable to the RSV outbreak in South Korea due to the relaxation of domestic infection control measures in November 2021 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCAP of unknown aetiology is relatively common among immunocompromised patients [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In this study, a substantial number of patients (39.3%) presented with CAP of unknown aetiology, despite our only including patients who underwent BRS to minimise the number of patients with an undetermined aetiology. The incidence of CAP of unknown aetiology did not decrease during the COVID-19 pandemic; however, this may not necessarily indicate that these cases were not caused by pathogens such as viruses or bacteria. The lack of testing for atypical infections and diagnostic limitations of laboratory techniques prevents us from drawing a definitive conclusion. It is plausible that these cases were associated with the patients' underlying diseases or immunocompromised status, but further investigation is needed to establish a causal relationship.\u003c/p\u003e \u003cp\u003eWe investigated the risk factors for in-hospital mortality in patients with HM who had CAP. Consistent with previous studies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], high SOFA scores and low platelet counts were found to be risk factors for in-hospital mortality in patients with HM who had CAP. In general, while the CURB-65 (confusion, uraemia, respiratory rate, blood pressure, age\u0026thinsp;\u0026ge;\u0026thinsp;65 years) criteria or pneumonia severity index (PSI) are commonly used to predict the prognosis of patients with pneumonia, previous studies have shown that they are not effective in immunocompromised patients with cancer [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Thus, we opted to use the SOFA score instead. Thrombocytopenia is also associated with the severity of and poor prognosis in patients with infections [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Platelets play a role in inflammation and host defence mechanisms against microbial agents. Additionally, thrombocytopenia reflects bone marrow failure in patients with HM [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Therefore, thrombocytopenia could be a significant predictor of poor prognosis in patients with HM and CAP.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, its retrospective design and single-centre implementation may introduce a selection bias, potentially affecting the significance of our findings. Nevertheless, we meticulously examined all admitted patients with CAP who underwent BRS in this single, large, 4-year cohort with consistent treatment protocols. The objective of our study was to assess the impact of the COVID-19 pandemic on the changing pattern of aetiology of CAP in patients with HM; thus, the setting of this study did not significantly deviate from that of a prospective observational study. Second, conducting a single-centre study may have had limitations in determining the overall aetiology of CAP in all patients with HM. However, this institution serves as the largest Asian centre for haematological disorders, performing over 500 bone marrow transplantations annually. Therefore, these data can be considered reasonably representative. Third, patients\u0026rsquo; COVID-19 histories were not investigated. Previous studies reported that COVID-19 is a risk factor for bacterial or fungal co-infections and can play a significant role in patient prognosis [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, due to the retrospective nature of the study, it was not possible to conduct an investigation. Additional studies are needed to evaluate the impact of a COVID-19 history on the prognosis of patients with CAP and HM.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn the context of pandemic eras such as that of COVID-19, understanding the changes in CAP aetiology among immunocompromised patients, including those with HM, is crucial. The CAP incidence in patients with HM did not decrease during the COVID-19 pandemic, unlike that in the general population. A notable shift in the aetiology of CAP emerged among patients with HM during the COVID-19 pandemic, with a significant reduction in the incidence of viral pneumonia but no change in that of bacterial and fungal pneumonia. Further research is needed to evaluate the effects of COVID-19 on the prognosis of patients with HM and CAP.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eabsolute lymphocyte count\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eabsolute neutrophil count\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBAL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebronchoalveolar lavage\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBRS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebronchoscopy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecommunity-acquired pneumonia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence intervals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOVID-19\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecoronavirus disease 2019\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehospital-acquired pneumonia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehaematological malignancies\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintensive care unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eodds ratios\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epolymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epneumonia severity index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRSV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erespiratory syncytial virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSequential Organ Failure Assessment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ewhite blood cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of Seoul St. Mary\u0026rsquo;s Hospital (KC23RISI0113), and the requirement for informed consent was waived by the Institutional Review Board of Seoul St. Mary\u0026rsquo;s Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJW analysed and interpreted the patient data and drafted the work. SC made substantial contributions to the conception. JM made design of the work and interpreted the data and substantively revised the manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePark IN, Yum HK. Stepwise strategy of social distancing in Korea. J Korean Med Sci. 2020;35:e264.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee H, Lee H, Song KH, Kim ES, Park JS, Jung J, et al. Impact of public health interventions on seasonal influenza activity during the COVID-19 outbreak in Korea. Clin Infect Dis. 2021;73:e132\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSakamoto H, Ishikane M, Ueda P. Seasonal influenza activity during the SARS-CoV-2 outbreak in Japan. JAMA. 2020;323:1969\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuitunen I, Artama M, M\u0026auml;kel\u0026auml; L, Backman K, Heiskanen-Kosma T, Renko M. Effect of social distancing due to the COVID-19 pandemic on the incidence of viral respiratory tract infections in children in Finland during early 2020. Pediatr Infect Dis J. 2020;39:e423\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang HJ, Lai CC, Chao CM. Changing epidemiology of respiratory tract infection during COVID-19 pandemic. Antibiot (Basel). 2022;11:315.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDi Pasquale MF, Sotgiu G, Gramegna A, Radovanovic D, Terraneo S, Reyes LF, et al. Prevalence and etiology of community-acquired pneumonia in immunocompromised patients. Clin Infect Dis. 2019;68:1482\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmedt N, Heuer OD, H\u0026auml;ckl D, Sato R, Theilacker C. Burden of community-acquired pneumonia, predisposing factors and health-care related costs in patients with cancer. BMC Health Serv Res. 2019;19:30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharma S, Nadrous HF, Peters SG, Tefferi A, Litzow MR, Aubry MC, et al. Pulmonary complications in adult blood and marrow transplant recipients: autopsy findings. Chest. 2005;128:1385\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoychowdhury M, Pambuccian SE, Aslan DL, Jessurun J, Rose AG, Manivel JC, et al. Pulmonary complications after bone marrow transplantation: an autopsy study from a large transplantation center. Arch Pathol Lab Med. 2005;129:366\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzoulay E, Mokart D, Rabbat A, Pene F, Kouatchet A, Bruneel F, et al. Diagnostic bronchoscopy in hematology and oncology patients with acute respiratory failure: prospective multicenter data. Crit Care Med. 2008;36:100\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHilbert G, Gruson D, Vargas F, Valentino R, Gbikpi-Benissan G, Dupon M, et al. Noninvasive ventilation in immunosuppressed patients with pulmonary infiltrates, fever, and acute respiratory failure. N Engl J Med. 2001;344:481\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark JY, Guo W, Al-Hijji M, El Sabbagh A, Begna KH, Habermann TM, et al. Acute coronary syndromes in patients with active hematologic malignancies - Incidence, management, and outcomes. Int J Cardiol. 2019;275:6\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonnelly JP, Chen SC, Kauffman CA, Steinbach WJ, Baddley JW, Verweij PE, et al. Revision and update of the consensus definitions of invasive fungal disease from the European Organization for Research and Treatment of Cancer and the mycoses study group education and research consortium. Clin Infect Dis. 2020;71:1367\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang C. The COVID-19 pandemic and the incidence of the non-COVID-19 pneumonia in adults. Front Med (Lausanne). 2021;8:737999.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang LN, Cao L, Meng LH. Pathogenic changes of community-acquired pneumonia in a Children\u0026rsquo;s Hospital in Beijing, China before and after COVID-19 onset: a retrospective study. World J Pediatr. 2022;18:746\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamamoto T, Komiya K, Fujita N, Okabe E, Hiramatsu K, Kadota JI. COVID-19 pandemic and the incidence of community-acquired pneumonia in elderly people. Respir Investig. 2020;58:435\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMetlay JP, Waterer GW. Treatment of community-acquired pneumonia during the coronavirus disease 2019 (COVID-19) pandemic. Ann Intern Med. 2020;173:304\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarris B, Geyer AI. Diagnostic evaluation of pulmonary abnormalities in patients with hematologic malignancies and hematopoietic cell transplantation. Clin Chest Med. 2017;38:317\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnstone J, Majumdar SR, Fox JD, Marrie TJ. Viral infection in adults hospitalized with community-acquired pneumonia: prevalence, pathogens, and presentation. Chest. 2008;134:1141\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartino R, Porras RP, Rabella N, Williams JV, R\u0026aacute;mila E, Margall N, et al. Prospective study of the incidence, clinical features, and outcome of symptomatic upper and lower respiratory tract infections by respiratory viruses in adult recipients of hematopoietic stem cell transplants for hematologic malignancies. Biol Blood Marrow Transplant. 2005;11:781\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee J, Kim SC, Rhee CK, Lee J, Lee JW, Lee DG. Prevalence and clinical course of upper airway respiratory virus infection in critically ill patients with hematologic malignancies. PLoS ONE. 2021;16:e0260741.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim JH, Kim HY, Lee M, Ahn JG, Baek JY, Kim MY, et al. Respiratory syncytial virus outbreak without influenza in the second year of the coronavirus disease 2019 pandemic: A national sentinel surveillance in Korea, 2021\u0026ndash;2022 season. J Korean Med Sci. 2022;37:e258.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRa\u0026ntilde;\u0026oacute; A, Agust\u0026iacute; C, Jimenez P, Angrill J, Benito N, Dan\u0026eacute;s C, et al. Pulmonary infiltrates in non-HIV immunocompromised patients: a diagnostic approach using non-invasive and bronchoscopic procedures. Thorax. 2001;56:379\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChaoui D, Legrand O, Roche N, Cornet M, Lefebvre A, Peffault de Latour R, et al. Incidence and prognostic value of respiratory events in acute leukemia. Leukemia. 2004;18:670\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Dorzi HM, Al Orainni H, Al Eid F, Tlayjeh H, Itani A, Al Hejazi A, et al. Characteristics and predictors of mortality of patients with hematologic malignancies requiring invasive mechanical ventilation. Ann Thorac Med. 2017;12:259\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMirsaeidi M, Peyrani P, Aliberti S, Filardo G, Bordon J, Blasi F, et al. Thrombocytopenia and thrombocytosis at time of hospitalization predict mortality in patients with community-acquired pneumonia. Chest. 2010;137:416\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGonzalez C, Johnson T, Rolston K, Merriman K, Warneke C, Evans S. Predicting pneumonia mortality using CURB-65, PSI, and patient characteristics in patients presenting to the emergency department of a comprehensive cancer center. Cancer Med. 2014;3:962\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaquet J, Lafaurie M, Sommet A, Moulis G. Thrombocytopenia is independently associated with poor outcome in patients hospitalized for COVID-19. Br J Haematol. 2020;190:e276\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHui P, Cook DJ, Lim W, Fraser GA, Arnold DM. The frequency and clinical significance of thrombocytopenia complicating critical illness: a systematic review. Chest. 2011;139:271\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalacz ME, Lankiewicz MW, Weissman DE. Management of thrombocytopenia in bone marrow failure: a review. J Palliat Med. 2007;10:236\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoenigl M, Seidel D, Sprute R, Cunha C, Oliverio M, Goldman GH, et al. COVID-19-associated fungal infections. Nat Microbiol. 2022;7:1127\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShafran N, Shafran I, Ben-Zvi H, Sofer S, Sheena L, Krause I, et al. Secondary bacterial infection in COVID-19 patients is a stronger predictor for death compared to influenza patients. Sci Rep. 2021;11:12703.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, community-acquired pneumonia, immune deficiency, haematologic malignancy","lastPublishedDoi":"10.21203/rs.3.rs-3810411/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3810411/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: The coronavirus disease 2019 (COVID-19) pandemic has changed respiratory infection patterns globally. However, its impact on community-acquired pneumonia (CAP) in high-risk patients with haematological malignancies (HM) is uncertain. We aimed to examine how community-acquired pneumonia aetiology in patients with haematological malignancies changed during the COVID-19 pandemic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This was a retrospective study that included 524 patients with haematological malignancies hospitalised with community-acquired pneumonia between March 2018 and February 2022. Patients who underwent bronchoscopy within 24 hours of admission to identify community-acquired pneumonia aetiology were included. Data on patient characteristics, laboratory findings, and results of bronchioalveolar lavage fluid cultures and polymerase chain reaction tests were analysed and compared to identify changes and in-hospital mortality risk factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Patients were divided into the ‘pre-COVID-19 era’ (44.5%) and ‘COVID-19 era’ (55.5%) groups. The incidence of viral community-acquired pneumonia significantly decreased in the COVID-19 era, particularly for influenza A, parainfluenza, adenovirus, and rhinovirus (pre-COVID-19 era vs. COVID-19 era: 3.0% vs. 0.3%, P = 0.036; 6.5% vs. 0.7%, P = 0.001; 5.6% vs. 1.4%, P = 0.015; and 9.5% vs. 1.7%, P \u0026lt; 0.001, respectively), whereas that of bacterial, fungal, and unknown community-acquired pneumonia aetiologies remain unchanged. Higher Sequential Organ Failure Assessment scores and lower platelet counts correlated with in-hospital mortality after adjusting for potential confounding factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: In the COVID-19 era, the incidence of community-acquired pneumonia with viral aetiologies markedly decreased among patients with haematological malignancies, with no changes in the incidence of bacterial and fungal pneumonia. Further studies are required to evaluate the impact of COVID-19 on the prognosis of patients with haematological malignancies and community-acquired pneumonia.\u003c/p\u003e","manuscriptTitle":"Changes in respiratory infection trends during the COVID-19 pandemic in patients with haematologic malignancy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-02 19:56:26","doi":"10.21203/rs.3.rs-3810411/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-02-17T05:16:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-02-12T03:24:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-01-13T15:27:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2dbbb7e6-57b0-4e90-9744-b36fb77533ad","date":"2024-01-02T09:46:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-02T06:37:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-02T01:23:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-12-27T07:17:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-12-27T07:15:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2023-12-27T03:54:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ec93d19a-00d0-443f-9740-7a63b778a276","owner":[],"postedDate":"January 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-26T19:47:12+00:00","versionOfRecord":{"articleIdentity":"rs-3810411","link":"https://doi.org/10.1186/s12890-024-03071-0","journal":{"identity":"bmc-pulmonary-medicine","isVorOnly":false,"title":"BMC Pulmonary Medicine"},"publishedOn":"2024-05-26 19:47:12","publishedOnDateReadable":"May 26th, 2024"},"versionCreatedAt":"2024-01-02 19:56:26","video":"","vorDoi":"10.1186/s12890-024-03071-0","vorDoiUrl":"https://doi.org/10.1186/s12890-024-03071-0","workflowStages":[]},"version":"v1","identity":"rs-3810411","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3810411","identity":"rs-3810411","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}