Characteristics and outcomes of patients hospitalized for infection with Influenza, SARS- CoV-2 or Respiratory Syncytial Virus in the season 2022/2023 in a large German primary care center

Characteristics and outcomes of patients hospitalized for infection with Influenza, SARS- CoV-2 or Respiratory Syncytial Virus in the season 2022/2023 in a large German primary care center | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Characteristics and outcomes of patients hospitalized for infection with Influenza, SARS- CoV-2 or Respiratory Syncytial Virus in the season 2022/2023 in a large German primary care center Carolin Quarg, Rudolf A. Jörres, Sebastian Engelhardt, Peter Alter, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3005197/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Dec, 2023 Read the published version in European Journal of Medical Research → Version 1 posted 10 You are reading this latest preprint version Abstract Background In 2022/2023, Influenza A and Respiratory Syncytial Virus (RSV) reappeared in hospitalized patients, which was in parallel to ongoing SARS-CoV-2 infections. The aim of our study was to compare the characteristics and outcomes of these infections during the same time. Methods We included patients of all ages with a positive Polymerase Chain Reaction (PCR) test for Influenza A/B, RSV, or SARS-CoV-2 virus hospitalized in the neurological, internal or paediatric units of the RoMed Hospital Rosenheim, Germany, between October 1st 2022 and February 28th 2023. Results A total of 906 patients were included (45.6% female; median age 68.0 years; 21.9% Influenza A, 48.2% SARS-CoV-2, 28.3% RSV). Influenza B (0.2%) and co-infections (1.5%) played a minor role. In patients aged ≥ 18 years (n = 637, 71%), Influenza A, SARS-CoV-2 and RSV groups differed in age (median 72, 79, 76 years, respectively; p < 0.001). Comorbidities, particularly asthma and COPD, were most prevalent for RSV. 103 patients were admitted to the intensive care unit (ICU) (16.3% Influenza A, 15.3% SARS-CoV-2, 19.2% RSV; p = 0.649), 56 died (6.8% Influenza A, 9% SARS-CoV-2, 11.1% RSV; p = 0.496). RSV showed the highest frequencies of low-flow oxygen supplementation for admission and stay. Differences in the length of stay were minor (median 7 days). Conversely, in patients aged < 18 years (n = 254, 29%), 19.5%, 17.6% and 60.2% were in the Influenza A, SARS-CoV-2 and RSV groups, respectively; 0.4% showed Influenza B and 2.3% co-infections. 17 patients were admitted to ICU (4.5% Influenza A, 10.0% RSV, 0% SARS-CoV-2); none died. RSV showed the highest frequencies of high- and low-flow oxygen supplementation, SARS-CoV-2 the lowest. Young RSV patients stayed longer in the hospital compared to SARS-CoV-2 and Influenza A (median 4 versus 2 and 2 days; p < 0.001). Conclusion When comparing infections with Influenza, SARS-CoV-2 and RSV in the same winter period in hospitalized adult patients, rates of ICU admission and mortality were similar. RSV showed the highest frequencies of comorbidities, especially obstructive airway diseases, and of oxygen supplementation. The latter was also true in children/adolescents, in whom RSV dominated. The data suggest a relatively higher disease burden from RSV compared to Influenza and SARS-CoV-2 across ages. Hospitalization PCR test SARS-CoV-2 RSV Influenza Covid-19 children adults mortality ICU admission Figures Figure 1 Figure 2 Figure 3 Background Lower respiratory tract infections are a common cause of hospitalization and significantly contribute to morbidity and mortality particularly in young children and older adults (1, 2). Among the viral causes, Respiratory Syncytial Virus (RSV) and various strains of Influenza, particularly Influenza A, have been most prominent for a long time (3, 4, 5). Starting in early 2020, SARS-CoV-2 dominated this type of infection, while the role of previously relevant viruses became minor or even disappeared, although this impression might have been favoured by the practice of regular testing for SARS-CoV-2. Those papers that addressed other viruses during this time confirmed the predominant role of SARS-CoV-2 (6, 7). Consequently, nearly all comparisons of the disease burden between viruses were based on historical data (8, 9, 10). Starting in the summer of 2022, the formerly prevalent viruses reappeared, e.g. in terms of Influenza or in terms of RSV, particularly in children (11, 12, 13), and a very recent study used data from the same season 2022/2023 to compared Influenza and SARS-CoV-2 (14); RSV was not included in this analysis. As shown by many studies, the risk from SARS-CoV-2 declined over time, possibly due to the prevalence of less harmful variants (15, 16, 17), improved immunity due to infection or vaccination, and advances in the management of Covid-19 patients. In addition, the population at risk may have changed over time. Thus, in-time comparisons are of great value. The re-appearance of infections with previously prevalent viruses renders it possible to compare disease burden, characteristics of patients at risk, treatment and outcome under comparable conditions. Hospitalized patients are of interest not only due to their disease severity but also, because availability, validity and comparability of data are probably higher than for non-hospitalized patients. Based on these considerations, we studied infections with Influenza A/B, RSV and SARS-CoV-2 in recent time (October 2022 to February 2023) in patients of a large primary care hospital located in a region known as former Covid-19 hotspot (18, 19) covering the full range of age from new-borns to very old individuals. Methods Study population The initial population (n = 1175) comprised patients of all ages with a positive PCR for Influenza A/B, RSV or SARS-CoV-2, who were hospitalized at the RoMed Hospital Rosenheim, Germany, between October 1st 2022 and February 28th 2023. From these, we only included patients admitted to the internal medicine, neurology and paediatric units and excluded patients of other areas, especially gynaecological and surgical units, based on the consideration that the infection was not the primary cause for hospitalization. Initially questionable PCR tests were clarified by follow-up testing. During the time of the study, testing for SARS-CoV-2 upon admission was still obligatory for hospitalized patients, whereas that for Influenza and RSV by tests combined with SARS-CoV-2 was performed in case of clinical hints that these viruses may be present. In case of readmission with the same viral infection within four weeks, only the first admission was considered. Assessments The presence of Influenza A/B, RSV or SARS-CoV-2 infection was determined by PCR tests performed upon admission or during hospitalization. The following PCR test kits were used: Cepheid® Xpert® Xpress SARS-CoV-2 and Cepheid® Xpert® Xpress SARS-CoV-2/Flu/RSV (XP3SARS-COV2-10, Cepheid GmbH, Krefeld, Germany), BD SARS-CoV-2/Flu with BD MAX™ System (445011, BD Becton Dickinson GmbH, Sparks, Maryland, USA), Rhonda player Point-of-care analyser for SARS-CoV-2 (SD003-02-020-A01, Spindiag GmbH, Freiburg i. Br., Germany). The relevant information was extracted from the medical records comprising age, sex, body-mass-index (BMI), comorbidities, symptoms (cough, dyspnoea, fatigue, fever, diarrhoea, nausea) upon admission, and vital signs upon admission (heart rate, respiratory rate, body temperature, blood pressure, oxygen saturation (SpO 2 )). Furthermore, blood gas parameters (pH, arterial pressures of oxygen (pO 2 ) and carbon dioxide (pCO 2 )) were collected, as well as laboratory parameters upon admission (glomerular filtration rate estimated via creatinine (eGFR), leukocyte count, C-reactive protein (CRP), haemoglobin, lactate dehydrogenase (LDH), troponin, N-terminal pro b-type natriuretic peptide (NT-proBNP), D-dimers). The assessment of treatment modalities included invasive mechanical ventilation (MIV), non-invasive ventilation (NIV), and high-flow or low-flow oxygen supplementation. Outcomes As primary outcomes, we defined admission to an intensive care unit (ICU) and in-hospital mortality. Secondary outcomes comprised invasive or non-invasive ventilation, high-flow or low-flow oxygen supplementation, and the length of the hospital stay. Statistical analysis Numbers and percentages, or median values and quartiles were computed to describe the data. To compare the types of infection, chi-square statistics and Fishers’s exact test, or the Kruskal-Wallis test were used, depending on the type and structure of the data. Post hoc-comparisons were performed using the Mann-Whitney U-test with Bonferroni correction. Moreover, we used multiple binary logistic regression to examine the relationships between patients’ characteristics or treatments and outcomes. Receiver operator characteristics (ROC) analysis was performed for the primary outcomes to determine cut-off values for continuous variables. As tests for SARS-CoV-2 were obligatory and those for Influenza and RSV performed on demand in case of clinical hints, we performed a sensitivity analysis for the primary outcomes based on an evaluation of all patients’ files. For this purpose, patients were categorized according to the evidence that their infection was the likely cause of their hospital stay, or secondary. The statistical software SPSS (version 26, IBM Corporation, Armonk, NJ, USA) was used for data analysis. The level of statistical significance was assumed at p < 0.05. Results Anthropometric data and distribution of infections Of 921 cases from the internal medicine, neurology and paediatric units, 906 patients (413 women (45.6%), 493 men (54.4%)) remained eligible for analysis, since they were not admitted a second time with the same virus within four weeks. The median age (quartiles) of the study population was 68.0 (0.4; 81.3) years, the BMI 25.7 (22.9; 29.3) kg/m 2 . The distribution of sex and age according to infection groups is given in Table 1 . The majority of patients were infected with SARS-CoV-2, while the second most common virus was RSV, followed by Influenza A. Due to the fact, that the group of patients with Influenza B comprised only 2 patients and the groups with combined infections were very small, all subsequent statistical comparisons were limited to the groups of Influenza A, SARS-CoV-2 and RSV. Table 1 Baseline characteristics stratified for the type of infection. Numbers (percentages) and median values (quartiles) are given. * Percentages refer to infection group (rows). BMI = Body Mass Index. ** Percentages refer to total group of 906 patients. n.d. = not determined. Viral infection n = 906 ** n (< 18 years)* Sex (m/f)* Age (years) BMI (kg/m 2 ) Influenza A 198 (21.9%) 51 (25.8%) 106/92 (53.5%/46.5%) 64 (15; 78) 26.0 (23.2; 29.8) Influenza B 2 (0.2%) 1 (50%) 1/1 (50%/50%) 22 (n.d.) n.d. SARS-CoV-2 437 (48.2%) 46 (10.5%) 243/194 (55.6%/44.4%) 77 (61; 84) 25.5 (22.8; 29.1) RSV 256 (28.3%) 157 (61.3%) 136/120 (53.1%/46.9%) 2 (0.4; 70) 26.0 (22.4; 29.3) Influenza A + SARS 4 (0.4%) 0 (0%) 3/1 (75%/25%) 83 (75; 86) 25.0 (n.d.) Influenza A + RSV 6 (0.7%) 3 (50%) 2/4 (33.3%/66.7%) 26 (4; 59) 24.1 (n.d.) Influenza B + RSV 1 (0.1%) 1 (100%) 1/0 (100%/0%) n.d. n.d. SARS + RSV 2 (0.2%) 2 (100%) 1/1 (50%/50%) 0.15 (n.d.) n.d. Regarding BMI and sex, there were no significant differences between the three groups. For age, however, all three groups were different from each other (p < 0.001 each). Age distribution is illustrated in Fig. 1 , showing two distinctive peaks. When restricting the analysis to patients with age ≥ 18 years, age again differed between the three groups (p < 0.001), with median values (quartiles) of 72 (62; 80) for Influenza A, 79 (68; 84) for SARS-CoV-2, and 76 (63; 85) years for RSV. In this case, age was only different between Influenza A and SARS-CoV-2 (p < 0.001), whereas the RSV group did not significantly differ from the other two groups. In patients of age < 18 years, age also differed between groups (p < 0.001), with median values (quartiles) of 3.8 (1.9; 8.4) for Influenza A, 0.51 (0.16; 1.87) for SARS-CoV-2, and 0.49 (0.17; 1.92) years for RSV. The SARS-CoV-2 and the RSV group were not different from each other, but age of both significantly differed from age of Influenza A patients (p < 0.001 each). Comorbidities In patients aged ≥ 18 years, heart failure, rheumatic disease, COPD, and a state of immunosuppression were most often present with RSV. In SARS-CoV-2 patients, asthma and COPD showed the least prevalence, peripheral arterial disease (PAD) the highest. Chronic kidney disease (CKD) was least prevalent in Influenza patients. If expressed as sum of the comorbidities given in Table 2 , this sum was significantly greater in RSV patients compared to the other two groups (p ≤ 0.003 each). Table 2 Distribution of comorbidities of patients aged ≥ 18 years. Numbers (percentages) are given, for the sum of all comorbidities median values (quartiles). Statistical comparisons were performed with the chi-square statistics or the Kruskal-Wallis test. COPD = Chronic obstructive pulmonary disease. *except malignant diseases of the lung. **within the last 5 years. *** count of all comorbidities listed in the Table. Prevalence of comorbidities of patients aged ≥ 18 years Influenza A SARS-CoV-2 RSV p value n 147 391 99 - Hypertension 81 (55.1%) 254 (65.0%) 64 (64.6%) 0.098 Peripheral arterial disease (PAD) 4 (2.7%) 38 (9.7%) 5 (5.1%) 0.014 Heart failure 25 (17.0%) 84 (21.5%) 34 (34.3%) 0.005 Coronary artery disease (CAD) 42 (28.6%) 99 (25.3) 36 (36.4%) 0.088 Diabetes mellitus type 2 30 (20.4%) 112 (28.6%) 31 (31.3%) 0.096 COPD 30 (20.4%) 43 (11.0%) 30 (30.3%) < 0.001 Asthma 25 (17.0%) 20 (5.1%) 18 (18.2%) < 0.001 Other lung disease* 7 (4.8%) 19 (4.9%) 5 (5.1%) 0.995 Chronic kidney disease (CKD) 17 (11.6%) 86 (22.0%) 23 (23.2%) 0.017 Active malignant disease** 12 (8.2%) 56 (14.3%) 11 (11.1%) 0.142 Rheumatic disease 6 (4.1%) 18 (4.6%) 11 (11.1%) 0.028 Depression 9 (6.1%) 31 (7.9%) 10 (10.1%) 0.521 Dementia 18 (12.2%) 49 (12.5%) 11 (11.1%) 0.928 State of immunosuppression 19 (12.9%) 50 (12.8%) 22 (22.2%) 0.049 Number of comorbidities*** 2 (1; 3) 2 (1; 4) 3 (2; 4) < 0.001 To clarify, to which extent the differences in prevalence could be attributed to the differences in age, we performed logistic regression analyses with age and the three types of infections as predictors, and the comorbidities as outcomes. Age was significantly (p < 0.05 each) associated with hypertension, PAD, heart failure, coronary artery disease (CAD), diabetes mellitus type 2, asthma, CKD, and dementia but all comorbidities that showed a significant unadjusted difference between infections (Table 2 ) remained significantly (p < 0.05 each) linked to the different infections, suggesting virus-specific, age-independent risk profiles. In patients of age < 18 years, comorbidities were not analyzed due to lack of data. Primary outcomes The distribution of ICU treatment and in-hospital mortality for all patients and all infections is shown in the Supplemental Table S1 . Neither the frequency of ICU admission (p = 0.974) nor that of in-hospital mortality (p = 0.109) differed significantly between the three groups Influenza A, SARS-CoV-2 or RSV. To account for the differences in clinical characteristics, the age groups < 18 years and ≥ 18 years were then analyzed separately (Table 3 ). In adults, the three major infection groups again showed no significant differences regarding ICU admission (p = 0.649) or in-hospital mortality (p = 0.496). Of the younger patients, all survived, and it appeared that ICU admission was more frequent in the RSV group, but due to low case numbers the chi-square statistics was of limited value. Table 3 Outcome data of the three major infection groups stratified according to age. Numbers (percentages) are given. For the results of statistical comparisons, see text. Mortality refers to in-hospital mortality. ICU = Intensive Care Unit. Age group < 18 years ≥ 18 years Infection n ICU admission Mortality n ICU admission Mortality Sample size 254 17 (6.7%) 0 (0%) 637 103 (16.2%) 56 (8.8%) Influenza A 51 2 (3.9%) 0 (0%) 147 24 (16.3%) 10 (6.8%) SARS-CoV-2 46 0 (0%) 0 (0%) 391 60 (15.3%) 35 (9.0%) RSV 157 15 (9.6%) 0 (0%) 99 19 (19.2%) 11 (11.1%) Treatment characteristics Table 4 provides data on the treatment characteristics of patients aged ≥ 18 years. The length of the hospital stay differed between the three groups (p = 0.021), with a significant (p = 0.033) difference between SARS-CoV-2 and RSV. There were no significant differences regarding the other durations. The frequencies of NIV, low-flow oxygen supply during the hospital stay and oxygen supply upon admission differed significantly between the three groups (p < 0.001 each), whereby the highest percentages were observed in the RSV group. Table 4 Treatment characteristics of patients of age ≥ 18 years for the three major infection groups. Numbers (percentages) are given. Statistical comparisons were performed with the chi-square statistics and the Kruskal-Wallis test. Durations refer to the subgroups of patients in whom the respective treatment was applied. Treatment characteristics of patients aged ≥ 18 years Influenza A SARS-CoV-2 RSV p value n 147 391 99 - Length of hospital stay, days 7 (4; 10) 7 (4; 12) 6 (3; 9) 0.021 Intensive care unit Frequency 24 (16.3%) 60 (15.3%) 19 (19.2%) 0.649 Length of stay, days 2.7 (1.0; 6.7) 2.8 (0.9; 7.1) 2.1 (1.2; 5.6) 0.981 Mechanical invasive ventilation Frequency 8 (5.4%) 17 (4.3%) 3 (3.0%) 0.662 Duration, hours 33.6 (11.5; 138.0) 157.1 (20.8; 298.1) 57.7 (n.d.) 0.439 Non-invasive ventilation Frequency 10 (6.8%) 11 (2.8%) 12 (12.1%) 0.001 Duration, hours 7.9 (2.8; 60.5) 13.3 (7.5; 47.2) 28.1 (9.6; 56.5) 0.460 Oxygen supplementation High-flow during stay 13 (8.8%) 25 (6.4%) 9 (9.1%) 0.486 Low-flow during stay 99 (67.3%) 227 (58.1%) 82 (82.8%) < 0.001 Upon admission 46 (31.3%) 102 (26.1%) 46 (46.5%) < 0.001 Table 5 shows analogous data for patients aged < 18 years. The length of the hospital stay differed between the three groups (p < 0.001), with significant differences between RSV and SARS-CoV-2 as well as Influenza A (p ≤ 0.003 each). There were no significant differences regarding the other durations. The frequencies of high-flow and low-flow oxygen supply during the hospital stay also significantly differed between groups (p ≤ 0.004 each), whereby the highest percentages occurred in the RSV group. Table 5 Treatment characteristics of patients of age < 18 years for the three major infection groups. Numbers (percentages) and median values and quartiles are given. n.d. = not determined. Statistical comparisons were performed with the chi-square statistics but partially have to be considered only as hints due to the low case numbers. Durations refer to the subgroups of patients in whom the respective treatment was applied. Treatment characteristics of patients aged < 18 years Influenza A SARS-CoV-2 RSV p value n 51 46 157 - Length of hospital stay, days 2 (1; 5) 2 (1; 3) 4 (2; 6) < 0.001 Intensive care unit Frequency 2 (3.9%) 0 (0%) 15 (9.6%) 0.05 Length of stay, days 4.9 (n.d.) n.d. 3.7 (2.4; 7.8) 0.881 Mechanical invasive ventilation Frequency 0 (0%) 0 (0%) 3 (1.9%) 0.391 Duration, hours n.d. n.d. 108.8 (n.d.) - Non-invasive ventilation Frequency 0 (0%) 0 (0%) 3 (1.9%) 0.391 Duration, hours n.d. n.d. 66.9 (n.d.) - Oxygen supplementation High-flow during stay 3 (5.9%) 1 (2.2%) 29 (18.5%) 0.004 Low-flow during stay 15 (29.4%) 0 (0%) 114 (72.6%) < 0.001 Upon admission 2 (3.9%) 0 (0%) 11 (7.0%) 0.151 As the group of very young patients seemed of particular interest, we analyzed data of children aged < 3 years separately (Supplemental Table S2 ). The majority had RSV infection; these patients again showed the longest duration of their hospital stay and the highest percentage of oxygen therapy, either low-flow or high-flow. Prevalence of symptoms Symptoms were analyzed only for patients aged ≥ 18 years. The prevalence of cough, dyspnoea and fever showed significant differences between the three major types of infection (p < 0.001 each), with low values for cough and dyspnoea in SARS-CoV-2, high values for cough and dyspnoea in RSV, and a high value of fever in Influenza A (Supplemental Table S3). To account for a possible dependence on age, again logistic regression analyses were performed including age and the type of infection as predictors, and each symptom as outcome. The prevalence of nausea decreased with increasing age, while that of fatigue increased but the unadjusted differences between virus type (Supplemental Table S3) remained significant, suggesting virus-specific, age-independent patterns of symptoms. Vital parameters, arterial blood gas and laboratory parameters upon admission For patients ≥ 18 years, vital parameters upon admission are given in the Supplemental Table S4. All of them, except systolic blood pressure, differed significantly (p < 0.05 each) between infection groups. According to post hoc-comparisons, SARS-CoV-2 and RSV differed regarding respiratory rate, heart rate, oxygen saturation and diastolic blood pressure (p < 0.05 each). For heart rate, temperature and oxygen saturation, there were also significant differences between Influenza A and SARS-CoV-2 but we never observed significant differences between the Influenza A and RSV group. pO 2 did not significantly differ between groups, but pCO 2 and pH did. Regarding pH, the SARS-CoV-2 group showed higher values than the other two groups; regarding pCO 2 , values were highest in the RSV group (p < 0.05 each). Among laboratory parameters, only eGFR, CRP and D-dimers were significantly different between groups (p < 0.05 each) and are shown in the table. Specifically, eGFR and CRP differed between Influenza A and SARS-CoV-2 groups, both with higher values for Influenza A. D-dimers differed between SARS-CoV-2 and RSV, with higher values in SARS-CoV-2. Risk factors for ICU admission and in-hospital death The descriptive results given above showed similarities between the three infections, but also pointed towards differences. As some of the risk factors, such as age or comorbidities, were linked to each other, we performed multiple logistic regression analyses with the aim to identify the statistically independent predictors of ICU admission or in-hospital death. The initial choice of variables was guided by their potential relevance for the outcomes; in the final set we eliminated all predictors with p-values of 0.10 or higher. However, the three infection categories (Influenza A, SARS-CoV-2, RSV) were always kept as predictors irrespective of statistical significance, with Influenza A as reference, in order to compare their impact with that of other predictors. The approach followed by us is outlined in the Supplement in detail. Regarding ICU admission, the results and odds ratios of associations are illustrated in Fig. 2 , indicating that oxygen supply upon admission was the most consistent, strongest (p < 0.001) predictor of subsequent ICU admission for all three viruses, with an odds ratio (95% CI) of 3.88 (2.35; 6.42). Age, sex, active malignant diseases, heart rate, body temperature and oxygen saturation upon admission were additional predictors, while the type of infection was not significantly associated with ICU admission, in line with the unadjusted comparisons. Regarding in-hospital mortality, odds ratios are shown in Fig. 3 . eGFR and initial oxygen supply were robust and significant predictors (p < 0.05 each), whereas initial oxygen saturation and systolic blood pressure showed only a tendency. The type of infection was not significant, in accordance with the unadjusted comparisons. Sensitivity analysis For this purpose, we identified patients, in whom the infection was considered to have been the likely cause of their hospital stay. In patients < 18 years of age, only 24 of 254 were excluded as having incidental positive tests for any of the three viruses. The numbers of ICU admission were unchanged. Regarding in-hospital mortality, there were also no changes as this was already zero. In patients of age ≥ 18 years, 202 of 637 were excluded (Supplemental Table S5). More SARS-CoV-2 patients were excluded compared to the other two viruses. The relative frequencies of ICU admission did not change significantly by exclusion, neither for the total group, nor for the three infection groups separately. In contrast, overall in-hospital mortality became lower (5.0% versus 10.6%, p = 0.023), but again without significant difference within the three infection groups, probably due to the low number of deceased patients. Discussion In this study, the clinical characteristics and outcomes of patients hospitalized with Influenza A, SARS-CoV-2 or RSV between October 1st 2022 and February 28th 2023 were analyzed to assess differences and similarities. Its strength is the simultaneous collection of most recent data. This was enabled by the fact that the high numbers of the major infections allowed a direct comparison, whereas nearly all previous studies relied upon data from different seasons. In children and adolescents, the comparatively high disease burden from RSV that is well known from the past was essentially confirmed. In adults, the three infections had a similar impact on the relative risk for ICU admission and in-hospital mortality; although differences were not statistically significant, values were highest for RSV. In terms of clinical and treatment characteristics, respiratory symptoms, a history of obstructive airway disease, non-invasive ventilation and low-flow oxygen supply were most frequent for RSV. Taken together, our findings indicate that in the season 2022/2023 all three infections played an important role in hospitalized adult patients. In particular, they underline that RSV is worth of further attention not only in children. In the beginning of 2020, SARS-CoV-2 became the dominant respiratory viral infection worldwide with regard to hospitalization rate and mortality (20). During this time, the incidence of other respiratory viruses, particularly RSV and Influenza, appeared to decrease drastically (6, 7). Since then, however, the impact of SARS-CoV-2 has declined, as reflected in a reduction of mortality (14), which was already visible when comparing the first and second wave of Covid-19 in 2020/2021 (18). In parallel, respiratory viruses including Influenza and RSV reappeared, particularly RSV in children (11, 12, 13). We confirmed this in both young and adult patients for the season 2022/2023. The large number of hospitalized patients enabled a comparison in the same population at the same time. The season 2022/2023 also provided the most recent information on Influenza, SARS-CoV-2 and RSV, which might be relevant for predicting future developments. Previous comparisons between SARS-CoV-2, Influenza and RSV based on data from different times indicated both similarities and differences. A recent study from Germany (21), that examined outcomes and patients’ characteristics in the three types of infection between 2017 and 2020, found a higher risk of ICU admission and hospital death for RSV compared to Influenza A, whereas the risk for SARS-CoV-2 was even higher. In addition, the RSV patients were more likely to have COPD or CKD. Our findings from 2022/2023, i.e. a much later time, confirmed the high risk from RSV particularly in COPD patients, but did not find an elevated risk from SARS-CoV-2. Another study from Switzerland compared the outcomes of patients infected with Influenza from 2018 to 2022 and with SARS-CoV-2 in 2022 (22). There was no difference in the risk of ICU admission, but mortality was higher for SARS-CoV-2 than for Influenza (7% vs. 4.4%). Similar observations regarding SARS-CoV-2 versus Influenza were made in a recent study on the outcomes of the last season from October 2022 to January 2023 (14). Again, SARS-CoV-2 was associated with higher mortality risk than Influenza, but the results also showed that the difference had decreased compared to 2020 (SARS-CoV-2: 6% versus 17–20% in 2020, Influenza: 3.7% versus 3.8% in 2020). These data again underline that the mortality of Covid-19 patients decreased over time. Our data agree with this regarding ICU admission and length of ICU stay in adults. They also showed a difference between the two infections regarding mortality, irrespective of the fact, whether all patients were included or only those, in whom the infection was considered to be the likely cause of their hospital stay. The differences in mortality between the total group and the subgroup were, however, considerable (see Supplemental Table S5), underlining the need for taking into account the type of approach in the comparison of numerical data. Importantly, our comparison showed that relationship between the infection groups essentially remained the same, thus our conclusion appeared robust. When comparing RSV and Influenza, a study from the US (23) published in 2019 reported higher morbidity and mortality in RSV patients. On average, RSV patients were more likely to have congestive heart failure and COPD, and they had a higher risk for ICU admission. Our findings (see Table 2 , Table 3 , Supplemental Table S5) are in accordance with this, but additionally place SARS-CoV-2 at an intermediate position between the other two viruses, with more similarities to RSV than to Influenza A. In order to identify differences between viruses in the risk profile of patients in the most recent season, we included a comprehensive analysis of comorbidities in adults. Consistent with previous reports (21, 23), adults hospitalized with RSV had the greatest frequency of comorbidities, especially heart failure, rheumatic disease, COPD and asthma, as well as the status of immunosuppression. In the SARS-CoV-2 group, only PAD was more frequent. The higher frequency of comorbidities in RSV patients was supported by the higher median of the sum of comorbidities. Among adults, the SARS-CoV-2 group was the oldest on average, followed by RSV and Influenza A. As comorbidities are often linked to age, we assessed whether the different patterns of comorbidities were due to the differences in age. This was not the case, suggesting intrinsic age-independent risk profiles for the three infections. The respiratory symptoms cough and dyspnoea were most prevalent in RSV patients, followed by Influenza A, and lowest with SARS-CoV-2. These observations are in line with results of a comparison covering different seasons (21). Taken together with the higher frequency of obstructive airway diseases in RSV patients, the findings point at RSV but not SARS-CoV-2 as being primarily associated with clinical affectation of the lung. While the primary outcomes ICU admission and mortality did not show marked differences between the three major infection groups in adults, we observed differences regarding the frequency of NIV, of low-flow oxygen supply during hospital stay and of oxygen supply upon admission. The highest percentages were found in the RSV group, the lowest in the SARS-CoV-2 group. The median length of the hospital stay was similar between groups, but patients infected with SARS-CoV-2 showed a right skewed distribution and based on this a statistically significantly longer hospital stay compared to RSV patients. The overall pattern of differences between infections had two aspects. First, the burden from respiratory impairments appeared to be highest with RSV, underlining previous findings that RSV remains to be a serious concern in adults, particularly in the elderly and those with pre-existing medical conditions (21, 23, 24, 25). In comparison, SARS-CoV-2 and Influenza A appeared to have a more systemic impact. Despite these differences, we could identify common risk factors in a comprehensive analysis of ICU admission and mortality. The strongest predictor for both outcomes was oxygen supplementation upon admission, while comorbidities did not play a role, except malignant disease for ICU admission. Regarding ICU, vital parameters were also relevant. For SARS-CoV-2, renal function played an important role, in accordance with our previous findings (18, 19, 26). It demonstrated the overwhelming role of the requirement for initial oxygen supply for later ICU admission, and in addition younger age, male sex, malignant diseases, increased heart rate, decreased body temperature, and lower oxygen saturation. The predictors of higher in-hospital mortality were slightly different. The role of initial oxygen supplementation was confirmed, but at the same time a reduction in eGFR played a role, while reduced oxygen saturation showed only a tendency. One of the advantages of our study may be that we covered the whole spectrum of patients’ ages and that the population of hospitalized patients comprised a large number of children and adolescents, in whom the dominant role of RSV was clearly visible. This was reflected by the findings regarding prevalence of infection, length of stay, admission to ICU, as well as high-flow and low-flow oxygen therapy. When restricting the analysis to young children of age less than 3 years, essentially the same results were obtained as for the total group of children and adolescents. We did not analyze the data from children and adolescents further, as RSV has already been discussed in many publications. This retrospective study has a number of limitations. First, it does not allow causal inferences but only provides associations. Moreover, it is a single-center study, and there is no guarantee that our findings must be valid for other regions. However, they are well compatible with historical data, suggesting their validity. Moreover, data limited to hospitalized patients cannot quantify the overall burden from the infections; for this, epidemiological studies are needed. As a strength, however, this limitation allowed for the collection of a large set of high-quality data in a well-defined population. A further advantage was that information from previous waves of Covid-19 from the same region was available for comparison (18, 19, 26). A noteworthy limitation was the fact, that hospitalized patients were routinely tested for SARS-CoV-2 upon admission, while the (combined) testing for Influenza A/B and RSV was performed only in case of clinical hints on their potential involvement, both upon admission and during the stay. In case of any uncertainties, however, these hints were taken seriously and the appropriate tests were performed, thus in the sensitivity analysis we not only excluded patients of the SARS-CoV-2 group. Importantly, the sensitivity analysis demonstrated that differences in the indications of tests did not play a role regarding the relationship between infections. Due to incomplete data on patients after discharge from hospital, partly caused by legal issues in Germany, mortality referred to in-hospital mortality and may not reflect the overall mortality of viral infections. Based on previous analyses (18, 19, 26), however, we have reason to assume that mortality after discharge from the RoMed hospital did not play a significant role for the comparative analysis. Conclusion In conclusion, the comparison of infections with Influenza, SARS-CoV-2 and RSV in the same season 2022/2023 in hospitalized patients showed no major differences in the rates of ICU admissions and mortality of adult patients. Overall, SARS-CoV-2 was most frequent. The adult RSV group had the highest frequencies of comorbidities, especially obstructive airway diseases, and of respiratory symptoms. Moreover, the need for oxygen supply, appearing as unfavourable indicator, was most frequent for RSV, both in adults and in children/adolescents. The data indicate a tendency for relatively higher disease burden from RSV compared to Influenza and SARS-CoV-2 in all age groups. ABBREVIATIONS BMI Body Mass Index CAD Coronary artery disease CKD Chronic kidney disease COPD Chronic obstructive pulmonary disease CRP C-reactive protein Ct Cycle threshold eGFR Estimated glomerular filtration rate ICU Intensive Care Unit LDH Lactate dehydrogenase MIV Invasive mechanical ventilation NIV Non-invasive ventilation NT-proBNP N-terminal pro b-type natriuretic peptide PAD Peripheral arterial disease pCO 2 Carbon dioxide PCR Polymerase Chain Reaction pO 2 Arterial pressures of oxygen ROC Receiver operator characteristics RSV Respiratory Syncytial Virus SpO 2 Peripheral oxygen saturation Declarations Ethics approval and consent to participate Approval was obtained from the ethics committee of the University Hospital of Regensburg (number 23-3289-104). Consent for publication Not applicable. Availability of data and materials The datasets analyzed during the current study are not publicly available due to patients’ privacy but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding None. Authors' contributions CQ: Writing and revision of the manuscript, data analysis; RAJ: Writing and revision of the manuscript, data analysis; SE: Revision of the manuscript, support in data acquisition; PA: Revision of the manuscript; SB: Writing and revision of the manuscript, design of the study. Acknowledgements We would like to thank the administration of the RoMed Hospital for their support in data collection from the files. References Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory tract infections in 195 countries: a systematic analysis for the Global Burden of Disease Study 2015. Lancet Infect Dis. 2017;17(11):1133-61. Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory infections in 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Infect Dis. 2018;18(11):1191-210. Wu X, Wang Q, Wang M, Su X, Xing Z, Zhang W, et al. Incidence of respiratory viral infections detected by PCR and real-time PCR in adult patients with community-acquired pneumonia: a meta-analysis. Respiration. 2015;89(4):343-52. Shi T, McLean K, Campbell H, Nair H. Aetiological role of common respiratory viruses in acute lower respiratory infections in children under five years: A systematic review and meta-analysis. J Glob Health. 2015;5(1):010408. Falsey AR, Hennessey PA, Formica MA, Cox C, Walsh EE. Respiratory syncytial virus infection in elderly and high-risk adults. N Engl J Med. 2005;352(17):1749-59. Stamm P, Sagoschen I, Weise K, Plachter B, Munzel T, Gori T, et al. Influenza and RSV incidence during COVID-19 pandemic-an observational study from in-hospital point-of-care testing. Med Microbiol Immunol. 2021;210(5-6):277-82. Groves HE, Piché-Renaud PP, Peci A, Farrar DS, Buckrell S, Bancej C, et al. The impact of the COVID-19 pandemic on influenza, respiratory syncytial virus, and other seasonal respiratory virus circulation in Canada: A population-based study. Lancet Reg Health Am. 2021;1:100015. Hamilton MA, Liu Y, Calzavara A, Sundaram ME, Djebli M, Darvin D, et al. Predictors of all-cause mortality among patients hospitalized with influenza, respiratory syncytial virus, or SARS-CoV-2. Influenza Other Respir Viruses. 2022;16(6):1072-81. Ludwig M, Jacob J, Basedow F, Andersohn F, Walker J. Clinical outcomes and characteristics of patients hospitalized for Influenza or COVID-19 in Germany. Int J Infect Dis. 2021;103:316-22. Taniguchi Y, Kuno T, Komiyama J, Adomi M, Suzuki T, Abe T, et al. Comparison of patient characteristics and in-hospital mortality between patients with COVID-19 in 2020 and those with influenza in 2017-2020: a multicenter, retrospective cohort study in Japan. Lancet Reg Health West Pac. 2022;20:100365. Terliesner N, Unterwalder N, Edelmann A, Corman V, Knaust A, Rosenfeld L, et al. Viral infections in hospitalized children in Germany during the COVID-19 pandemic: Association with non-pharmaceutical interventions. Front Pediatr. 2022;10:935483. Rao S, Armistead I, Messacar K, Alden NB, Schmoll E, Austin E, et al. Shifting Epidemiology and Severity of Respiratory Syncytial Virus in Children During the COVID-19 Pandemic. JAMA Pediatr. 2023. Buda S DR, Biere B, Reiche J, Buchholz U, Tolksdorf K, Schilling J, Goerlitz L, Streib V, Preuß U, Prahm K, Haas W und die AGI-Studiengruppe. ARE-Wochenbericht KW 9/2023; Arbeitsgemeinschaft Influenza – Robert Koch-Institut. 2023. Xie Y, Choi T, Al-Aly Z. Risk of Death in Patients Hospitalized for COVID-19 vs Seasonal Influenza in Fall-Winter 2022-2023. Jama. 2023;329(19):1697-9. Nyberg T, Ferguson NM, Nash SG, Webster HH, Flaxman S, Andrews N, et al. Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study. Lancet. 2022;399(10332):1303-12. Lewnard JA, Hong VX, Patel MM, Kahn R, Lipsitch M, Tartof SY. Clinical outcomes associated with SARS-CoV-2 Omicron (B.1.1.529) variant and BA.1/BA.1.1 or BA.2 subvariant infection in Southern California. Nat Med. 2022;28(9):1933-43. Wolter N, Jassat W, Walaza S, Welch R, Moultrie H, Groome MJ, et al. Clinical severity of SARS-CoV-2 Omicron BA.4 and BA.5 lineages compared to BA.1 and Delta in South Africa. Nat Commun. 2022;13(1):5860. Budweiser S, Baş Ş, Jörres RA, Engelhardt S, Thilo C, Delius SV, et al. Comparison of the First and Second Waves of Hospitalized Patients With SARS-CoV-2. Dtsch Arztebl Int. 2021;118(18):326-7. Budweiser S, Baş Ş, Jörres RA, Engelhardt S, von Delius S, Lenherr K, et al. Patients' treatment limitations as predictive factor for mortality in COVID-19: results from hospitalized patients of a hotspot region for SARS-CoV-2 infections. Respir Res. 2021;22(1):168. Zylke JW, Bauchner H. Mortality and Morbidity: The Measure of a Pandemic. Jama. 2020;324(5):458-9. Andreas A, Doris L, Frank K, Michael K. Focusing on severe infections with the respiratory syncytial virus (RSV) in adults: Risk factors, symptomatology and clinical course compared to influenza A / B and the original SARS-CoV-2 strain. J Clin Virol. 2023;161:105399. Portmann L, de Kraker MEA, Fröhlich G, Thiabaud A, Roelens M, Schreiber PW, et al. Hospital Outcomes of Community-Acquired SARS-CoV-2 Omicron Variant Infection Compared With Influenza Infection in Switzerland. JAMA Netw Open. 2023;6(2):e2255599. Ackerson B, Tseng HF, Sy LS, Solano Z, Slezak J, Luo Y, et al. Severe Morbidity and Mortality Associated With Respiratory Syncytial Virus Versus Influenza Infection in Hospitalized Older Adults. Clin Infect Dis. 2019;69(2):197-203. Nguyen-Van-Tam JS, O'Leary M, Martin ET, Heijnen E, Callendret B, Fleischhackl R, et al. Burden of respiratory syncytial virus infection in older and high-risk adults: a systematic review and meta-analysis of the evidence from developed countries. Eur Respir Rev. 2022;31(166). Branche AR, Saiman L, Walsh EE, Falsey AR, Sieling WD, Greendyke W, et al. Incidence of Respiratory Syncytial Virus Infection Among Hospitalized Adults, 2017-2020. Clin Infect Dis. 2022;74(6):1004-11. Kurzeder L, Jörres RA, Unterweger T, Essmann J, Alter P, Kahnert K, et al. A simple risk score for mortality including the PCR Ct value upon admission in patients hospitalized due to COVID-19. Infection. 2022;50(5):1155-63. Additional Declarations No competing interests reported. Supplementary Files QuargMay2023OutcomesinfectionsSupplementalFigure1.pptx QuargMay2023SupplementV30.docx Cite Share Download PDF Status: Published Journal Publication published 06 Dec, 2023 Read the published version in European Journal of Medical Research → Version 1 posted Editorial decision: Major revision 28 Sep, 2023 Reviews received at journal 22 Sep, 2023 Reviews received at journal 28 Jun, 2023 Reviewers agreed at journal 06 Jun, 2023 Reviewers agreed at journal 03 Jun, 2023 Reviewers agreed at journal 03 Jun, 2023 Reviewers invited by journal 03 Jun, 2023 Editor assigned by journal 02 Jun, 2023 Submission checks completed at journal 01 Jun, 2023 First submitted to journal 31 May, 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. 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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-3005197","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":205958410,"identity":"1fb613c3-1d7e-42b8-a091-a132a8cd3de1","order_by":0,"name":"Carolin Quarg","email":"","orcid":"","institution":"RoMed Hospital Rosenheim","correspondingAuthor":false,"prefix":"","firstName":"Carolin","middleName":"","lastName":"Quarg","suffix":""},{"id":205958411,"identity":"7013f7ef-3f83-43fe-8ecc-1d1eb90c42ab","order_by":1,"name":"Rudolf A. Jörres","email":"","orcid":"","institution":"LMU Hospital, Member of the German Center for Lung Research (DZL)","correspondingAuthor":false,"prefix":"","firstName":"Rudolf","middleName":"A.","lastName":"Jörres","suffix":""},{"id":205958412,"identity":"06823993-4ab1-4ab5-8967-1fdf10ef0c71","order_by":2,"name":"Sebastian Engelhardt","email":"","orcid":"","institution":"RoMed Hospital Rosenheim","correspondingAuthor":false,"prefix":"","firstName":"Sebastian","middleName":"","lastName":"Engelhardt","suffix":""},{"id":205958413,"identity":"3733659b-b0a0-49fc-83a2-26bc1f2931fd","order_by":3,"name":"Peter Alter","email":"","orcid":"","institution":"University of Marburg, Member of the German Center for Lung Research (DZL)","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Alter","suffix":""},{"id":205958414,"identity":"a342fee8-2fd5-4797-b0b9-c6a328633a56","order_by":4,"name":"Stephan Budweiser","email":"data:image/png;base64,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","orcid":"","institution":"RoMed Hospital Rosenheim","correspondingAuthor":true,"prefix":"","firstName":"Stephan","middleName":"","lastName":"Budweiser","suffix":""}],"badges":[],"createdAt":"2023-05-31 12:44:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3005197/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3005197/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40001-023-01482-z","type":"published","date":"2023-12-06T15:01:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":38028832,"identity":"fa7edfe6-c8db-4e6b-be47-16f2b92897ac","added_by":"auto","created_at":"2023-06-05 14:40:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":38823,"visible":true,"origin":"","legend":"\u003cp\u003eAge distribution in the three major infection groups (see Table 1) that are indicated by different colors. Absolute numbers for each age bin are given\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3005197/v1/a555de62e4ef7e629e90730c.png"},{"id":38028833,"identity":"6f81a056-af93-4cf0-8417-ed594aaae50d","added_by":"auto","created_at":"2023-06-05 14:40:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15263,"visible":true,"origin":"","legend":"\u003cp\u003eOdds ratios and 95% confidence intervals for the predictors of ICU admission - Influenza A served as reference\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3005197/v1/3e57583c864e830f7976efd3.png"},{"id":38028835,"identity":"06bf51ab-3640-4b5c-8976-dfd2bd6e7d66","added_by":"auto","created_at":"2023-06-05 14:40:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":12488,"visible":true,"origin":"","legend":"\u003cp\u003eOdds ratios and 95% confidence intervals for the predictors of in-hospital mortality - Influenza A served as reference\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3005197/v1/7027ede8af40293424e13130.png"},{"id":47989440,"identity":"fede487f-b9e4-41af-98ac-0fe4a901e051","added_by":"auto","created_at":"2023-12-11 15:09:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":624984,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3005197/v1/a0c574a2-d39b-4f8d-be8f-4d9dcef9e0f8.pdf"},{"id":38031061,"identity":"5ed9e1ca-42ee-489e-910e-b9204d766415","added_by":"auto","created_at":"2023-06-05 14:48:55","extension":"pptx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":88348,"visible":true,"origin":"","legend":"","description":"","filename":"QuargMay2023OutcomesinfectionsSupplementalFigure1.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3005197/v1/3d2d708d9034c62d1ec4f501.pptx"},{"id":38028836,"identity":"78562ef3-e370-4d96-ac22-9c33b734fc04","added_by":"auto","created_at":"2023-06-05 14:40:55","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":35634,"visible":true,"origin":"","legend":"","description":"","filename":"QuargMay2023SupplementV30.docx","url":"https://assets-eu.researchsquare.com/files/rs-3005197/v1/d86a325e01d2f96ebdcfaa79.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Characteristics and outcomes of patients hospitalized for infection with Influenza, SARS- CoV-2 or Respiratory Syncytial Virus in the season 2022/2023 in a large German primary care center","fulltext":[{"header":"Background","content":"\u003cp\u003eLower respiratory tract infections are a common cause of hospitalization and significantly contribute to morbidity and mortality particularly in young children and older adults (1, 2). Among the viral causes, Respiratory Syncytial Virus (RSV) and various strains of Influenza, particularly Influenza A, have been most prominent for a long time (3, 4, 5). Starting in early 2020, SARS-CoV-2 dominated this type of infection, while the role of previously relevant viruses became minor or even disappeared, although this impression might have been favoured by the practice of regular testing for SARS-CoV-2. Those papers that addressed other viruses during this time confirmed the predominant role of SARS-CoV-2 (6, 7). Consequently, nearly all comparisons of the disease burden between viruses were based on historical data (8, 9, 10).\u003c/p\u003e \u003cp\u003eStarting in the summer of 2022, the formerly prevalent viruses reappeared, e.g. in terms of Influenza or in terms of RSV, particularly in children (11, 12, 13), and a very recent study used data from the same season 2022/2023 to compared Influenza and SARS-CoV-2 (14); RSV was not included in this analysis. As shown by many studies, the risk from SARS-CoV-2 declined over time, possibly due to the prevalence of less harmful variants (15, 16, 17), improved immunity due to infection or vaccination, and advances in the management of Covid-19 patients. In addition, the population at risk may have changed over time. Thus, in-time comparisons are of great value.\u003c/p\u003e \u003cp\u003eThe re-appearance of infections with previously prevalent viruses renders it possible to compare disease burden, characteristics of patients at risk, treatment and outcome under comparable conditions. Hospitalized patients are of interest not only due to their disease severity but also, because availability, validity and comparability of data are probably higher than for non-hospitalized patients.\u003c/p\u003e \u003cp\u003eBased on these considerations, we studied infections with Influenza A/B, RSV and SARS-CoV-2 in recent time (October 2022 to February 2023) in patients of a large primary care hospital located in a region known as former Covid-19 hotspot (18, 19) covering the full range of age from new-borns to very old individuals.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003eStudy population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe initial population (n\u0026thinsp;=\u0026thinsp;1175) comprised patients of all ages with a positive PCR for Influenza A/B, RSV or SARS-CoV-2, who were hospitalized at the RoMed Hospital Rosenheim, Germany, between October 1st 2022 and February 28th 2023. From these, we only included patients admitted to the internal medicine, neurology and paediatric units and excluded patients of other areas, especially gynaecological and surgical units, based on the consideration that the infection was not the primary cause for hospitalization. Initially questionable PCR tests were clarified by follow-up testing. During the time of the study, testing for SARS-CoV-2 upon admission was still obligatory for hospitalized patients, whereas that for Influenza and RSV by tests combined with SARS-CoV-2 was performed in case of clinical hints that these viruses may be present. In case of readmission with the same viral infection within four weeks, only the first admission was considered.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAssessments\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe presence of Influenza A/B, RSV or SARS-CoV-2 infection was determined by PCR tests performed upon admission or during hospitalization. The following PCR test kits were used: Cepheid\u0026reg; Xpert\u0026reg; Xpress SARS-CoV-2 and Cepheid\u0026reg; Xpert\u0026reg; Xpress SARS-CoV-2/Flu/RSV (XP3SARS-COV2-10, Cepheid GmbH, Krefeld, Germany), BD SARS-CoV-2/Flu with BD MAX\u0026trade; System (445011, BD Becton Dickinson GmbH, Sparks, Maryland, USA), Rhonda player Point-of-care analyser for SARS-CoV-2 (SD003-02-020-A01, Spindiag GmbH, Freiburg i. Br., Germany).\u003c/p\u003e \u003cp\u003eThe relevant information was extracted from the medical records comprising age, sex, body-mass-index (BMI), comorbidities, symptoms (cough, dyspnoea, fatigue, fever, diarrhoea, nausea) upon admission, and vital signs upon admission (heart rate, respiratory rate, body temperature, blood pressure, oxygen saturation (SpO\u003csub\u003e2\u003c/sub\u003e)). Furthermore, blood gas parameters (pH, arterial pressures of oxygen (pO\u003csub\u003e2\u003c/sub\u003e) and carbon dioxide (pCO\u003csub\u003e2\u003c/sub\u003e)) were collected, as well as laboratory parameters upon admission (glomerular filtration rate estimated via creatinine (eGFR), leukocyte count, C-reactive protein (CRP), haemoglobin, lactate dehydrogenase (LDH), troponin, N-terminal pro b-type natriuretic peptide (NT-proBNP), D-dimers). The assessment of treatment modalities included invasive mechanical ventilation (MIV), non-invasive ventilation (NIV), and high-flow or low-flow oxygen supplementation.\u003c/p\u003e \u003cp\u003e \u003cb\u003eOutcomes\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs primary outcomes, we defined admission to an intensive care unit (ICU) and in-hospital mortality. Secondary outcomes comprised invasive or non-invasive ventilation, high-flow or low-flow oxygen supplementation, and the length of the hospital stay.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eNumbers and percentages, or median values and quartiles were computed to describe the data. To compare the types of infection, chi-square statistics and Fishers\u0026rsquo;s exact test, or the Kruskal-Wallis test were used, depending on the type and structure of the data. Post hoc-comparisons were performed using the Mann-Whitney U-test with Bonferroni correction. Moreover, we used multiple binary logistic regression to examine the relationships between patients\u0026rsquo; characteristics or treatments and outcomes. Receiver operator characteristics (ROC) analysis was performed for the primary outcomes to determine cut-off values for continuous variables. As tests for SARS-CoV-2 were obligatory and those for Influenza and RSV performed on demand in case of clinical hints, we performed a sensitivity analysis for the primary outcomes based on an evaluation of all patients\u0026rsquo; files. For this purpose, patients were categorized according to the evidence that their infection was the likely cause of their hospital stay, or secondary. The statistical software SPSS (version 26, IBM Corporation, Armonk, NJ, USA) was used for data analysis. The level of statistical significance was assumed at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eAnthropometric data and distribution of infections\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOf 921 cases from the internal medicine, neurology and paediatric units, 906 patients (413 women (45.6%), 493 men (54.4%)) remained eligible for analysis, since they were not admitted a second time with the same virus within four weeks. The median age (quartiles) of the study population was 68.0 (0.4; 81.3) years, the BMI 25.7 (22.9; 29.3) kg/m\u003csup\u003e2\u003c/sup\u003e. The distribution of sex and age according to infection groups is given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The majority of patients were infected with SARS-CoV-2, while the second most common virus was RSV, followed by Influenza A. Due to the fact, that the group of patients with Influenza B comprised only 2 patients and the groups with combined infections were very small, all subsequent statistical comparisons were limited to the groups of Influenza A, SARS-CoV-2 and RSV.\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 stratified for the type of infection. Numbers (percentages) and median values (quartiles) are given. * Percentages refer to infection group (rows). BMI\u0026thinsp;=\u0026thinsp;Body Mass Index. ** Percentages refer to total group of 906 patients. n.d. = not determined.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eViral infection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;906 **\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (\u0026lt;\u0026thinsp;18 years)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSex (m/f)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfluenza A\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e198 (21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (25.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106/92 (53.5%/46.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64 (15; 78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.0 (23.2; 29.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfluenza B\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1/1 (50%/50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (n.d.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.d.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSARS-CoV-2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e437 (48.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (10.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e243/194 (55.6%/44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77 (61; 84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.5 (22.8; 29.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRSV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e256 (28.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e157 (61.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e136/120 (53.1%/46.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.4; 70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.0 (22.4; 29.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfluenza A\u0026thinsp;+\u0026thinsp;SARS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3/1 (75%/25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83 (75; 86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.0 (n.d.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfluenza A\u0026thinsp;+\u0026thinsp;RSV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2/4 (33.3%/66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (4; 59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.1 (n.d.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfluenza B\u0026thinsp;+\u0026thinsp;RSV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1/0 (100%/0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.d.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.d.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSARS\u0026thinsp;+\u0026thinsp;RSV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1/1 (50%/50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15 (n.d.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.d.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding BMI and sex, there were no significant differences between the three groups. For age, however, all three groups were different from each other (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 each). Age distribution is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, showing two distinctive peaks. When restricting the analysis to patients with age\u0026thinsp;\u0026ge;\u0026thinsp;18 years, age again differed between the three groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with median values (quartiles) of 72 (62; 80) for Influenza A, 79 (68; 84) for SARS-CoV-2, and 76 (63; 85) years for RSV. In this case, age was only different between Influenza A and SARS-CoV-2 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas the RSV group did not significantly differ from the other two groups. In patients of age\u0026thinsp;\u0026lt;\u0026thinsp;18 years, age also differed between groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with median values (quartiles) of 3.8 (1.9; 8.4) for Influenza A, 0.51 (0.16; 1.87) for SARS-CoV-2, and 0.49 (0.17; 1.92) years for RSV. The SARS-CoV-2 and the RSV group were not different from each other, but age of both significantly differed from age of Influenza A patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 each).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eComorbidities\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years, heart failure, rheumatic disease, COPD, and a state of immunosuppression were most often present with RSV. In SARS-CoV-2 patients, asthma and COPD showed the least prevalence, peripheral arterial disease (PAD) the highest. Chronic kidney disease (CKD) was least prevalent in Influenza patients. If expressed as sum of the comorbidities given in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, this sum was significantly greater in RSV patients compared to the other two groups (p\u0026thinsp;\u0026le;\u0026thinsp;0.003 each).\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\u003eDistribution of comorbidities of patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years. Numbers (percentages) are given, for the sum of all comorbidities median values (quartiles). Statistical comparisons were performed with the chi-square statistics or the Kruskal-Wallis test. COPD\u0026thinsp;=\u0026thinsp;Chronic obstructive pulmonary disease. *except malignant diseases of the lung. **within the last 5 years. *** count of all comorbidities listed in the Table.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ePrevalence of comorbidities of patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfluenza A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSARS-CoV-2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (55.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e254 (65.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 (64.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral arterial disease (PAD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeart failure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (34.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoronary artery disease (CAD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes mellitus type 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (20.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCOPD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (20.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (30.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eAsthma\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eOther lung disease*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic kidney disease (CKD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (23.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eActive malignant disease**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRheumatic disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDepression\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.521\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDementia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eState of immunosuppression\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of comorbidities***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1; 3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1; 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2; 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo clarify, to which extent the differences in prevalence could be attributed to the differences in age, we performed logistic regression analyses with age and the three types of infections as predictors, and the comorbidities as outcomes. Age was significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 each) associated with hypertension, PAD, heart failure, coronary artery disease (CAD), diabetes mellitus type 2, asthma, CKD, and dementia but all comorbidities that showed a significant unadjusted difference between infections (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) remained significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 each) linked to the different infections, suggesting virus-specific, age-independent risk profiles. In patients of age\u0026thinsp;\u0026lt;\u0026thinsp;18 years, comorbidities were not analyzed due to lack of data.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePrimary outcomes\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe distribution of ICU treatment and in-hospital mortality for all patients and all infections is shown in the Supplemental Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Neither the frequency of ICU admission (p\u0026thinsp;=\u0026thinsp;0.974) nor that of in-hospital mortality (p\u0026thinsp;=\u0026thinsp;0.109) differed significantly between the three groups Influenza A, SARS-CoV-2 or RSV. To account for the differences in clinical characteristics, the age groups\u0026thinsp;\u0026lt;\u0026thinsp;18 years and \u0026ge;\u0026thinsp;18 years were then analyzed separately (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In adults, the three major infection groups again showed no significant differences regarding ICU admission (p\u0026thinsp;=\u0026thinsp;0.649) or in-hospital mortality (p\u0026thinsp;=\u0026thinsp;0.496). Of the younger patients, all survived, and it appeared that ICU admission was more frequent in the RSV group, but due to low case numbers the chi-square statistics was of limited value.\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\u003eOutcome data of the three major infection groups stratified according to age. Numbers (percentages) are given. For the results of statistical comparisons, see text. Mortality refers to in-hospital mortality. ICU\u0026thinsp;=\u0026thinsp;Intensive Care Unit.\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 \u003cp\u003eAge group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18 years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;18 years\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfection\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICU admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eICU admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSample size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e103 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfluenza A\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSARS-CoV-2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35 (9.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRSV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (19.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTreatment characteristics\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e provides data on the treatment characteristics of patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years. The length of the hospital stay differed between the three groups (p\u0026thinsp;=\u0026thinsp;0.021), with a significant (p\u0026thinsp;=\u0026thinsp;0.033) difference between SARS-CoV-2 and RSV. There were no significant differences regarding the other durations. The frequencies of NIV, low-flow oxygen supply during the hospital stay and oxygen supply upon admission differed significantly between the three groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 each), whereby the highest percentages were observed in the RSV group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment characteristics of patients of age\u0026thinsp;\u0026ge;\u0026thinsp;18 years for the three major infection groups. Numbers (percentages) are given. Statistical comparisons were performed with the chi-square statistics and the Kruskal-Wallis test. Durations refer to the subgroups of patients in whom the respective treatment was applied.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eTreatment characteristics of patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfluenza A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSARS-CoV-2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of hospital stay, days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (4; 10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (4; 12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (3; 9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntensive care unit\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (19.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay, days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7 (1.0; 6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8 (0.9; 7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1 (1.2; 5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMechanical invasive ventilation\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.662\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration, hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.6 (11.5; 138.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e157.1 (20.8; 298.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.7 (n.d.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-invasive ventilation\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration, hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.9 (2.8; 60.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3 (7.5; 47.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.1 (9.6; 56.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOxygen supplementation\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-flow during stay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (6.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-flow during stay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99 (67.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227 (58.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82 (82.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003eUpon admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102 (26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (46.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows analogous data for patients aged\u0026thinsp;\u0026lt;\u0026thinsp;18 years. The length of the hospital stay differed between the three groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with significant differences between RSV and SARS-CoV-2 as well as Influenza A (p\u0026thinsp;\u0026le;\u0026thinsp;0.003 each). There were no significant differences regarding the other durations. The frequencies of high-flow and low-flow oxygen supply during the hospital stay also significantly differed between groups (p\u0026thinsp;\u0026le;\u0026thinsp;0.004 each), whereby the highest percentages occurred in the RSV group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment characteristics of patients of age\u0026thinsp;\u0026lt;\u0026thinsp;18 years for the three major infection groups. Numbers (percentages) and median values and quartiles are given. n.d. = not determined. Statistical comparisons were performed with the chi-square statistics but partially have to be considered only as hints due to the low case numbers. Durations refer to the subgroups of patients in whom the respective treatment was applied.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eTreatment characteristics of patients aged\u0026thinsp;\u0026lt;\u0026thinsp;18 years\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfluenza A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSARS-CoV-2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of hospital stay, days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1; 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1; 3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (2; 6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eIntensive care unit\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay, days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.9 (n.d.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.d.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.7 (2.4; 7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.881\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMechanical invasive ventilation\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration, hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en.d.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.d.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108.8 (n.d.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-invasive ventilation\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration, hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en.d.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.d.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.9 (n.d.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOxygen supplementation\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-flow during stay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (18.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-flow during stay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (29.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114 (72.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003eUpon admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (7.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs the group of very young patients seemed of particular interest, we analyzed data of children aged\u0026thinsp;\u0026lt;\u0026thinsp;3 years separately (Supplemental Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). The majority had RSV infection; these patients again showed the longest duration of their hospital stay and the highest percentage of oxygen therapy, either low-flow or high-flow.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePrevalence of symptoms\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSymptoms were analyzed only for patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years. The prevalence of cough, dyspnoea and fever showed significant differences between the three major types of infection (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 each), with low values for cough and dyspnoea in SARS-CoV-2, high values for cough and dyspnoea in RSV, and a high value of fever in Influenza A (Supplemental Table S3). To account for a possible dependence on age, again logistic regression analyses were performed including age and the type of infection as predictors, and each symptom as outcome. The prevalence of nausea decreased with increasing age, while that of fatigue increased but the unadjusted differences between virus type (Supplemental Table S3) remained significant, suggesting virus-specific, age-independent patterns of symptoms.\u003c/p\u003e \u003cp\u003e \u003cb\u003eVital parameters, arterial blood gas and laboratory parameters upon admission\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFor patients\u0026thinsp;\u0026ge;\u0026thinsp;18 years, vital parameters upon admission are given in the Supplemental Table S4. All of them, except systolic blood pressure, differed significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 each) between infection groups. According to post hoc-comparisons, SARS-CoV-2 and RSV differed regarding respiratory rate, heart rate, oxygen saturation and diastolic blood pressure (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 each). For heart rate, temperature and oxygen saturation, there were also significant differences between Influenza A and SARS-CoV-2 but we never observed significant differences between the Influenza A and RSV group. pO\u003csub\u003e2\u003c/sub\u003e did not significantly differ between groups, but pCO\u003csub\u003e2\u003c/sub\u003e and pH did. Regarding pH, the SARS-CoV-2 group showed higher values than the other two groups; regarding pCO\u003csub\u003e2\u003c/sub\u003e, values were highest in the RSV group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 each). Among laboratory parameters, only eGFR, CRP and D-dimers were significantly different between groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 each) and are shown in the table. Specifically, eGFR and CRP differed between Influenza A and SARS-CoV-2 groups, both with higher values for Influenza A. D-dimers differed between SARS-CoV-2 and RSV, with higher values in SARS-CoV-2.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRisk factors for ICU admission and in-hospital death\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe descriptive results given above showed similarities between the three infections, but also pointed towards differences. As some of the risk factors, such as age or comorbidities, were linked to each other, we performed multiple logistic regression analyses with the aim to identify the statistically independent predictors of ICU admission or in-hospital death. The initial choice of variables was guided by their potential relevance for the outcomes; in the final set we eliminated all predictors with p-values of 0.10 or higher. However, the three infection categories (Influenza A, SARS-CoV-2, RSV) were always kept as predictors irrespective of statistical significance, with Influenza A as reference, in order to compare their impact with that of other predictors. The approach followed by us is outlined in the Supplement in detail.\u003c/p\u003e \u003cp\u003eRegarding ICU admission, the results and odds ratios of associations are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, indicating that oxygen supply upon admission was the most consistent, strongest (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) predictor of subsequent ICU admission for all three viruses, with an odds ratio (95% CI) of 3.88 (2.35; 6.42). Age, sex, active malignant diseases, heart rate, body temperature and oxygen saturation upon admission were additional predictors, while the type of infection was not significantly associated with ICU admission, in line with the unadjusted comparisons.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRegarding in-hospital mortality, odds ratios are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. eGFR and initial oxygen supply were robust and significant predictors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 each), whereas initial oxygen saturation and systolic blood pressure showed only a tendency. The type of infection was not significant, in accordance with the unadjusted comparisons.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSensitivity analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFor this purpose, we identified patients, in whom the infection was considered to have been the likely cause of their hospital stay. In patients\u0026thinsp;\u0026lt;\u0026thinsp;18 years of age, only 24 of 254 were excluded as having incidental positive tests for any of the three viruses. The numbers of ICU admission were unchanged. Regarding in-hospital mortality, there were also no changes as this was already zero.\u003c/p\u003e \u003cp\u003eIn patients of age\u0026thinsp;\u0026ge;\u0026thinsp;18 years, 202 of 637 were excluded (Supplemental Table S5). More SARS-CoV-2 patients were excluded compared to the other two viruses. The relative frequencies of ICU admission did not change significantly by exclusion, neither for the total group, nor for the three infection groups separately. In contrast, overall in-hospital mortality became lower (5.0% versus 10.6%, p\u0026thinsp;=\u0026thinsp;0.023), but again without significant difference within the three infection groups, probably due to the low number of deceased patients.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the clinical characteristics and outcomes of patients hospitalized with Influenza A, SARS-CoV-2 or RSV between October 1st 2022 and February 28th 2023 were analyzed to assess differences and similarities. Its strength is the simultaneous collection of most recent data. This was enabled by the fact that the high numbers of the major infections allowed a direct comparison, whereas nearly all previous studies relied upon data from different seasons. In children and adolescents, the comparatively high disease burden from RSV that is well known from the past was essentially confirmed. In adults, the three infections had a similar impact on the relative risk for ICU admission and in-hospital mortality; although differences were not statistically significant, values were highest for RSV. In terms of clinical and treatment characteristics, respiratory symptoms, a history of obstructive airway disease, non-invasive ventilation and low-flow oxygen supply were most frequent for RSV. Taken together, our findings indicate that in the season 2022/2023 all three infections played an important role in hospitalized adult patients. In particular, they underline that RSV is worth of further attention not only in children.\u003c/p\u003e \u003cp\u003eIn the beginning of 2020, SARS-CoV-2 became the dominant respiratory viral infection worldwide with regard to hospitalization rate and mortality (20). During this time, the incidence of other respiratory viruses, particularly RSV and Influenza, appeared to decrease drastically (6, 7). Since then, however, the impact of SARS-CoV-2 has declined, as reflected in a reduction of mortality (14), which was already visible when comparing the first and second wave of Covid-19 in 2020/2021 (18). In parallel, respiratory viruses including Influenza and RSV reappeared, particularly RSV in children (11, 12, 13). We confirmed this in both young and adult patients for the season 2022/2023. The large number of hospitalized patients enabled a comparison in the same population at the same time. The season 2022/2023 also provided the most recent information on Influenza, SARS-CoV-2 and RSV, which might be relevant for predicting future developments.\u003c/p\u003e \u003cp\u003ePrevious comparisons between SARS-CoV-2, Influenza and RSV based on data from different times indicated both similarities and differences. A recent study from Germany (21), that examined outcomes and patients\u0026rsquo; characteristics in the three types of infection between 2017 and 2020, found a higher risk of ICU admission and hospital death for RSV compared to Influenza A, whereas the risk for SARS-CoV-2 was even higher. In addition, the RSV patients were more likely to have COPD or CKD. Our findings from 2022/2023, i.e. a much later time, confirmed the high risk from RSV particularly in COPD patients, but did not find an elevated risk from SARS-CoV-2.\u003c/p\u003e \u003cp\u003eAnother study from Switzerland compared the outcomes of patients infected with Influenza from 2018 to 2022 and with SARS-CoV-2 in 2022 (22). There was no difference in the risk of ICU admission, but mortality was higher for SARS-CoV-2 than for Influenza (7% vs. 4.4%). Similar observations regarding SARS-CoV-2 versus Influenza were made in a recent study on the outcomes of the last season from October 2022 to January 2023 (14). Again, SARS-CoV-2 was associated with higher mortality risk than Influenza, but the results also showed that the difference had decreased compared to 2020 (SARS-CoV-2: 6% versus 17\u0026ndash;20% in 2020, Influenza: 3.7% versus 3.8% in 2020).\u003c/p\u003e \u003cp\u003eThese data again underline that the mortality of Covid-19 patients decreased over time. Our data agree with this regarding ICU admission and length of ICU stay in adults. They also showed a difference between the two infections regarding mortality, irrespective of the fact, whether all patients were included or only those, in whom the infection was considered to be the likely cause of their hospital stay. The differences in mortality between the total group and the subgroup were, however, considerable (see Supplemental Table S5), underlining the need for taking into account the type of approach in the comparison of numerical data. Importantly, our comparison showed that relationship between the infection groups essentially remained the same, thus our conclusion appeared robust.\u003c/p\u003e \u003cp\u003eWhen comparing RSV and Influenza, a study from the US (23) published in 2019 reported higher morbidity and mortality in RSV patients. On average, RSV patients were more likely to have congestive heart failure and COPD, and they had a higher risk for ICU admission. Our findings (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplemental Table S5) are in accordance with this, but additionally place SARS-CoV-2 at an intermediate position between the other two viruses, with more similarities to RSV than to Influenza A.\u003c/p\u003e \u003cp\u003eIn order to identify differences between viruses in the risk profile of patients in the most recent season, we included a comprehensive analysis of comorbidities in adults. Consistent with previous reports (21, 23), adults hospitalized with RSV had the greatest frequency of comorbidities, especially heart failure, rheumatic disease, COPD and asthma, as well as the status of immunosuppression. In the SARS-CoV-2 group, only PAD was more frequent. The higher frequency of comorbidities in RSV patients was supported by the higher median of the sum of comorbidities. Among adults, the SARS-CoV-2 group was the oldest on average, followed by RSV and Influenza A. As comorbidities are often linked to age, we assessed whether the different patterns of comorbidities were due to the differences in age. This was not the case, suggesting intrinsic age-independent risk profiles for the three infections.\u003c/p\u003e \u003cp\u003eThe respiratory symptoms cough and dyspnoea were most prevalent in RSV patients, followed by Influenza A, and lowest with SARS-CoV-2. These observations are in line with results of a comparison covering different seasons (21). Taken together with the higher frequency of obstructive airway diseases in RSV patients, the findings point at RSV but not SARS-CoV-2 as being primarily associated with clinical affectation of the lung.\u003c/p\u003e \u003cp\u003eWhile the primary outcomes ICU admission and mortality did not show marked differences between the three major infection groups in adults, we observed differences regarding the frequency of NIV, of low-flow oxygen supply during hospital stay and of oxygen supply upon admission. The highest percentages were found in the RSV group, the lowest in the SARS-CoV-2 group. The median length of the hospital stay was similar between groups, but patients infected with SARS-CoV-2 showed a right skewed distribution and based on this a statistically significantly longer hospital stay compared to RSV patients.\u003c/p\u003e \u003cp\u003eThe overall pattern of differences between infections had two aspects. First, the burden from respiratory impairments appeared to be highest with RSV, underlining previous findings that RSV remains to be a serious concern in adults, particularly in the elderly and those with pre-existing medical conditions (21, 23, 24, 25). In comparison, SARS-CoV-2 and Influenza A appeared to have a more systemic impact. Despite these differences, we could identify common risk factors in a comprehensive analysis of ICU admission and mortality. The strongest predictor for both outcomes was oxygen supplementation upon admission, while comorbidities did not play a role, except malignant disease for ICU admission. Regarding ICU, vital parameters were also relevant. For SARS-CoV-2, renal function played an important role, in accordance with our previous findings (18, 19, 26).\u003c/p\u003e \u003cp\u003eIt demonstrated the overwhelming role of the requirement for initial oxygen supply for later ICU admission, and in addition younger age, male sex, malignant diseases, increased heart rate, decreased body temperature, and lower oxygen saturation. The predictors of higher in-hospital mortality were slightly different. The role of initial oxygen supplementation was confirmed, but at the same time a reduction in eGFR played a role, while reduced oxygen saturation showed only a tendency.\u003c/p\u003e \u003cp\u003eOne of the advantages of our study may be that we covered the whole spectrum of patients\u0026rsquo; ages and that the population of hospitalized patients comprised a large number of children and adolescents, in whom the dominant role of RSV was clearly visible. This was reflected by the findings regarding prevalence of infection, length of stay, admission to ICU, as well as high-flow and low-flow oxygen therapy. When restricting the analysis to young children of age less than 3 years, essentially the same results were obtained as for the total group of children and adolescents. We did not analyze the data from children and adolescents further, as RSV has already been discussed in many publications.\u003c/p\u003e \u003cp\u003eThis retrospective study has a number of limitations. First, it does not allow causal inferences but only provides associations. Moreover, it is a single-center study, and there is no guarantee that our findings must be valid for other regions. However, they are well compatible with historical data, suggesting their validity. Moreover, data limited to hospitalized patients cannot quantify the overall burden from the infections; for this, epidemiological studies are needed. As a strength, however, this limitation allowed for the collection of a large set of high-quality data in a well-defined population. A further advantage was that information from previous waves of Covid-19 from the same region was available for comparison (18, 19, 26). A noteworthy limitation was the fact, that hospitalized patients were routinely tested for SARS-CoV-2 upon admission, while the (combined) testing for Influenza A/B and RSV was performed only in case of clinical hints on their potential involvement, both upon admission and during the stay. In case of any uncertainties, however, these hints were taken seriously and the appropriate tests were performed, thus in the sensitivity analysis we not only excluded patients of the SARS-CoV-2 group. Importantly, the sensitivity analysis demonstrated that differences in the indications of tests did not play a role regarding the relationship between infections. Due to incomplete data on patients after discharge from hospital, partly caused by legal issues in Germany, mortality referred to in-hospital mortality and may not reflect the overall mortality of viral infections. Based on previous analyses (18, 19, 26), however, we have reason to assume that mortality after discharge from the RoMed hospital did not play a significant role for the comparative analysis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the comparison of infections with Influenza, SARS-CoV-2 and RSV in the same season 2022/2023 in hospitalized patients showed no major differences in the rates of ICU admissions and mortality of adult patients. Overall, SARS-CoV-2 was most frequent. The adult RSV group had the highest frequencies of comorbidities, especially obstructive airway diseases, and of respiratory symptoms. Moreover, the need for oxygen supply, appearing as unfavourable indicator, was most frequent for RSV, both in adults and in children/adolescents. The data indicate a tendency for relatively higher disease burden from RSV compared to Influenza and SARS-CoV-2 in all age groups.\u003c/p\u003e"},{"header":"ABBREVIATIONS","content":"\u003cp\u003eBMI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Body Mass Index\u003c/p\u003e\n\u003cp\u003eCAD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Coronary artery disease\u003c/p\u003e\n\u003cp\u003eCKD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Chronic kidney disease\u003c/p\u003e\n\u003cp\u003eCOPD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Chronic obstructive pulmonary disease\u003c/p\u003e\n\u003cp\u003eCRP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;C-reactive protein\u003c/p\u003e\n\u003cp\u003eCt\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Cycle threshold\u003c/p\u003e\n\u003cp\u003eeGFR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Estimated glomerular filtration rate\u003c/p\u003e\n\u003cp\u003eICU\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Intensive Care Unit\u003c/p\u003e\n\u003cp\u003eLDH\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Lactate dehydrogenase\u003c/p\u003e\n\u003cp\u003eMIV\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Invasive mechanical ventilation\u003c/p\u003e\n\u003cp\u003eNIV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Non-invasive ventilation\u003c/p\u003e\n\u003cp\u003eNT-proBNP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;N-terminal pro b-type natriuretic peptide\u003c/p\u003e\n\u003cp\u003ePAD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Peripheral arterial disease\u003c/p\u003e\n\u003cp\u003epCO\u003csub\u003e2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/sub\u003eCarbon dioxide\u003c/p\u003e\n\u003cp\u003ePCR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Polymerase Chain Reaction\u003c/p\u003e\n\u003cp\u003epO\u003csub\u003e2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/sub\u003eArterial pressures of oxygen\u003c/p\u003e\n\u003cp\u003eROC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Receiver operator characteristics\u003c/p\u003e\n\u003cp\u003eRSV\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Respiratory Syncytial Virus\u003c/p\u003e\n\u003cp\u003eSpO\u003csub\u003e2\u003c/sub\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Peripheral oxygen saturation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eApproval was obtained from the ethics committee of the University Hospital of Regensburg (number 23-3289-104).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the current study are not publicly available due to patients\u0026rsquo; privacy but are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eCQ: Writing and revision of the manuscript, data analysis; RAJ: Writing and revision of the manuscript, data analysis; SE: Revision of the manuscript, support in data acquisition; PA: Revision of the manuscript; SB: Writing and revision of the manuscript, design of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe would like to thank the administration of the RoMed Hospital for their support in data collection from the files. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEstimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory tract infections in 195 countries: a systematic analysis for the Global Burden of Disease Study 2015. Lancet Infect Dis. 2017;17(11):1133-61.\u003c/li\u003e\n\u003cli\u003eEstimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory infections in 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Infect Dis. 2018;18(11):1191-210.\u003c/li\u003e\n\u003cli\u003eWu X, Wang Q, Wang M, Su X, Xing Z, Zhang W, et al. Incidence of respiratory viral infections detected by PCR and real-time PCR in adult patients with community-acquired pneumonia: a meta-analysis. Respiration. 2015;89(4):343-52.\u003c/li\u003e\n\u003cli\u003eShi T, McLean K, Campbell H, Nair H. Aetiological role of common respiratory viruses in acute lower respiratory infections in children under five years: A systematic review and meta-analysis. J Glob Health. 2015;5(1):010408.\u003c/li\u003e\n\u003cli\u003eFalsey AR, Hennessey PA, Formica MA, Cox C, Walsh EE. Respiratory syncytial virus infection in elderly and high-risk adults. N Engl J Med. 2005;352(17):1749-59.\u003c/li\u003e\n\u003cli\u003eStamm P, Sagoschen I, Weise K, Plachter B, Munzel T, Gori T, et al. Influenza and RSV incidence during COVID-19 pandemic-an observational study from in-hospital point-of-care testing. Med Microbiol Immunol. 2021;210(5-6):277-82.\u003c/li\u003e\n\u003cli\u003eGroves HE, Pich\u0026eacute;-Renaud PP, Peci A, Farrar DS, Buckrell S, Bancej C, et al. The impact of the COVID-19 pandemic on influenza, respiratory syncytial virus, and other seasonal respiratory virus circulation in Canada: A population-based study. Lancet Reg Health Am. 2021;1:100015.\u003c/li\u003e\n\u003cli\u003eHamilton MA, Liu Y, Calzavara A, Sundaram ME, Djebli M, Darvin D, et al. Predictors of all-cause mortality among patients hospitalized with influenza, respiratory syncytial virus, or SARS-CoV-2. Influenza Other Respir Viruses. 2022;16(6):1072-81.\u003c/li\u003e\n\u003cli\u003eLudwig M, Jacob J, Basedow F, Andersohn F, Walker J. Clinical outcomes and characteristics of patients hospitalized for Influenza or COVID-19 in Germany. Int J Infect Dis. 2021;103:316-22.\u003c/li\u003e\n\u003cli\u003eTaniguchi Y, Kuno T, Komiyama J, Adomi M, Suzuki T, Abe T, et al. Comparison of patient characteristics and in-hospital mortality between patients with COVID-19 in 2020 and those with influenza in 2017-2020: a multicenter, retrospective cohort study in Japan. Lancet Reg Health West Pac. 2022;20:100365.\u003c/li\u003e\n\u003cli\u003eTerliesner N, Unterwalder N, Edelmann A, Corman V, Knaust A, Rosenfeld L, et al. Viral infections in hospitalized children in Germany during the COVID-19 pandemic: Association with non-pharmaceutical interventions. Front Pediatr. 2022;10:935483.\u003c/li\u003e\n\u003cli\u003eRao S, Armistead I, Messacar K, Alden NB, Schmoll E, Austin E, et al. Shifting Epidemiology and Severity of Respiratory Syncytial Virus in Children During the COVID-19 Pandemic. JAMA Pediatr. 2023.\u003c/li\u003e\n\u003cli\u003eBuda S DR, Biere B, Reiche J, Buchholz U, Tolksdorf K, Schilling J, Goerlitz L, Streib V, Preu\u0026szlig; U, Prahm K, Haas W und die AGI-Studiengruppe. ARE-Wochenbericht KW 9/2023; Arbeitsgemeinschaft Influenza \u0026ndash; Robert Koch-Institut. 2023.\u003c/li\u003e\n\u003cli\u003eXie Y, Choi T, Al-Aly Z. Risk of Death in Patients Hospitalized for COVID-19 vs Seasonal Influenza in Fall-Winter 2022-2023. Jama. 2023;329(19):1697-9.\u003c/li\u003e\n\u003cli\u003eNyberg T, Ferguson NM, Nash SG, Webster HH, Flaxman S, Andrews N, et al. Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study. Lancet. 2022;399(10332):1303-12.\u003c/li\u003e\n\u003cli\u003eLewnard JA, Hong VX, Patel MM, Kahn R, Lipsitch M, Tartof SY. Clinical outcomes associated with SARS-CoV-2 Omicron (B.1.1.529) variant and BA.1/BA.1.1 or BA.2 subvariant infection in Southern California. Nat Med. 2022;28(9):1933-43.\u003c/li\u003e\n\u003cli\u003eWolter N, Jassat W, Walaza S, Welch R, Moultrie H, Groome MJ, et al. Clinical severity of SARS-CoV-2 Omicron BA.4 and BA.5 lineages compared to BA.1 and Delta in South Africa. Nat Commun. 2022;13(1):5860.\u003c/li\u003e\n\u003cli\u003eBudweiser S, Baş Ş, J\u0026ouml;rres RA, Engelhardt S, Thilo C, Delius SV, et al. Comparison of the First and Second Waves of Hospitalized Patients With SARS-CoV-2. Dtsch Arztebl Int. 2021;118(18):326-7.\u003c/li\u003e\n\u003cli\u003eBudweiser S, Baş Ş, J\u0026ouml;rres RA, Engelhardt S, von Delius S, Lenherr K, et al. Patients\u0026apos; treatment limitations as predictive factor for mortality in COVID-19: results from hospitalized patients of a hotspot region for SARS-CoV-2 infections. Respir Res. 2021;22(1):168.\u003c/li\u003e\n\u003cli\u003eZylke JW, Bauchner H. Mortality and Morbidity: The Measure of a Pandemic. Jama. 2020;324(5):458-9.\u003c/li\u003e\n\u003cli\u003eAndreas A, Doris L, Frank K, Michael K. Focusing on severe infections with the respiratory syncytial virus (RSV) in adults: Risk factors, symptomatology and clinical course compared to influenza A / B and the original SARS-CoV-2 strain. J Clin Virol. 2023;161:105399.\u003c/li\u003e\n\u003cli\u003ePortmann L, de Kraker MEA, Fr\u0026ouml;hlich G, Thiabaud A, Roelens M, Schreiber PW, et al. Hospital Outcomes of Community-Acquired SARS-CoV-2 Omicron Variant Infection Compared With Influenza Infection in Switzerland. JAMA Netw Open. 2023;6(2):e2255599.\u003c/li\u003e\n\u003cli\u003eAckerson B, Tseng HF, Sy LS, Solano Z, Slezak J, Luo Y, et al. Severe Morbidity and Mortality Associated With Respiratory Syncytial Virus Versus Influenza Infection in Hospitalized Older Adults. Clin Infect Dis. 2019;69(2):197-203.\u003c/li\u003e\n\u003cli\u003eNguyen-Van-Tam JS, O\u0026apos;Leary M, Martin ET, Heijnen E, Callendret B, Fleischhackl R, et al. Burden of respiratory syncytial virus infection in older and high-risk adults: a systematic review and meta-analysis of the evidence from developed countries. Eur Respir Rev. 2022;31(166).\u003c/li\u003e\n\u003cli\u003eBranche AR, Saiman L, Walsh EE, Falsey AR, Sieling WD, Greendyke W, et al. Incidence of Respiratory Syncytial Virus Infection Among Hospitalized Adults, 2017-2020. Clin Infect Dis. 2022;74(6):1004-11.\u003c/li\u003e\n\u003cli\u003eKurzeder L, J\u0026ouml;rres RA, Unterweger T, Essmann J, Alter P, Kahnert K, et al. A simple risk score for mortality including the PCR Ct value upon admission in patients hospitalized due to COVID-19. Infection. 2022;50(5):1155-63.\u003c/li\u003e\n\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":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hospitalization, PCR test, SARS-CoV-2, RSV, Influenza, Covid-19, children, adults, mortality, ICU admission","lastPublishedDoi":"10.21203/rs.3.rs-3005197/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3005197/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIn 2022/2023, Influenza A and Respiratory Syncytial Virus (RSV) reappeared in hospitalized patients, which was in parallel to ongoing SARS-CoV-2 infections. The aim of our study was to compare the characteristics and outcomes of these infections during the same time.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe included patients of all ages with a positive Polymerase Chain Reaction (PCR) test for Influenza A/B, RSV, or SARS-CoV-2 virus hospitalized in the neurological, internal or paediatric units of the RoMed Hospital Rosenheim, Germany, between October 1st 2022 and February 28th 2023.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 906 patients were included (45.6% female; median age 68.0 years; 21.9% Influenza A, 48.2% SARS-CoV-2, 28.3% RSV). Influenza B (0.2%) and co-infections (1.5%) played a minor role. In patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years (n\u0026thinsp;=\u0026thinsp;637, 71%), Influenza A, SARS-CoV-2 and RSV groups differed in age (median 72, 79, 76 years, respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Comorbidities, particularly asthma and COPD, were most prevalent for RSV. 103 patients were admitted to the intensive care unit (ICU) (16.3% Influenza A, 15.3% SARS-CoV-2, 19.2% RSV; p\u0026thinsp;=\u0026thinsp;0.649), 56 died (6.8% Influenza A, 9% SARS-CoV-2, 11.1% RSV; p\u0026thinsp;=\u0026thinsp;0.496). RSV showed the highest frequencies of low-flow oxygen supplementation for admission and stay. Differences in the length of stay were minor (median 7 days). Conversely, in patients aged\u0026thinsp;\u0026lt;\u0026thinsp;18 years (n\u0026thinsp;=\u0026thinsp;254, 29%), 19.5%, 17.6% and 60.2% were in the Influenza A, SARS-CoV-2 and RSV groups, respectively; 0.4% showed Influenza B and 2.3% co-infections. 17 patients were admitted to ICU (4.5% Influenza A, 10.0% RSV, 0% SARS-CoV-2); none died. RSV showed the highest frequencies of high- and low-flow oxygen supplementation, SARS-CoV-2 the lowest. Young RSV patients stayed longer in the hospital compared to SARS-CoV-2 and Influenza A (median 4 versus 2 and 2 days; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eWhen comparing infections with Influenza, SARS-CoV-2 and RSV in the same winter period in hospitalized adult patients, rates of ICU admission and mortality were similar. RSV showed the highest frequencies of comorbidities, especially obstructive airway diseases, and of oxygen supplementation. The latter was also true in children/adolescents, in whom RSV dominated. The data suggest a relatively higher disease burden from RSV compared to Influenza and SARS-CoV-2 across ages.\u003c/p\u003e","manuscriptTitle":"Characteristics and outcomes of patients hospitalized for infection with Influenza, SARS- CoV-2 or Respiratory Syncytial Virus in the season 2022/2023 in a large German primary care center","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-06-05 14:40:50","doi":"10.21203/rs.3.rs-3005197/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-09-28T10:19:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-09-22T20:23:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-06-29T02:38:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5a124453-1975-47af-843d-1d1465b60689","date":"2023-06-06T09:35:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4b1b7d59-5b8b-4df8-bb5c-07c8d4166011","date":"2023-06-04T00:16:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2e285e87-02bb-4cd2-9369-1e6234c6ab16_SNPRID","date":"2023-06-03T13:26:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-06-03T09:10:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-06-02T12:54:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-06-01T13:12:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Medical Research","date":"2023-05-31T12:33:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"14f12d19-4302-430a-9056-91dbbe08ac4f","owner":[],"postedDate":"June 5th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-12-11T15:06:38+00:00","versionOfRecord":{"articleIdentity":"rs-3005197","link":"https://doi.org/10.1186/s40001-023-01482-z","journal":{"identity":"european-journal-of-medical-research","isVorOnly":false,"title":"European Journal of Medical Research"},"publishedOn":"2023-12-06 15:01:24","publishedOnDateReadable":"December 6th, 2023"},"versionCreatedAt":"2023-06-05 14:40:50","video":"","vorDoi":"10.1186/s40001-023-01482-z","vorDoiUrl":"https://doi.org/10.1186/s40001-023-01482-z","workflowStages":[]},"version":"v1","identity":"rs-3005197","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3005197","identity":"rs-3005197","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}