Influenza-associated in-hospital mortality during the 2017/2018 influenza season: a retrospective multicentre cohort study in central Germany

Rößler, Steve; Ankert, Juliane; Baier, Michael; Pletz, Mathias W.; Hagel, Stefan

doi:10.1007/s15010-020-01529-x

Cited by 8 publications

(10 citation statements)

References 6 publications

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“…Since Brazil faced a major COVID-19 outbreak, with the health system's collapse and almost 100% occupancy in Brazilian intensive care units (Buss et al, 2021 ; Naveca et al, 2021 ; Sabino et al, 2021 ; Silva and Pena, 2021 ), perhaps the attending doctors reserved the few remaining intensive care unit beds for those with confirmed COVID-19 diagnoses. Furthermore, we observed the mortality of those with SARI due to an undefined etiological agent to be lower if compared to SARI due to COVID-19, which is similar to the literature, in which the hospitalized patients with COVID-19 accounted for nearly 37% of lethality rate and hospitalized Influenza patients for only 6.7% of lethality rate (Rößler et al, 2021 ; Zeiser et al, 2022 ). Importantly, in Brazil, the severe SARI cases were more tested than other patients (Boschiero et al, 2021a , b ), which could be associated with a low number of deaths among the patients with SARI due to an undefined etiological agent.…”

Section: Discussionsupporting

confidence: 89%

Epidemiologic Profile of Severe Acute Respiratory Infection in Brazil During the COVID-19 Pandemic: An Epidemiological Study

2022

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BackgroundThe COVID-19 is a significant public health issue, and monitoring confirmed cases and deaths is an essential epidemiologic tool. We evaluated the features in Brazilian hospitalized patients due to severe acute respiratory infection (SARI) during the COVID-19 pandemic in Brazil. We grouped the patients into the following categories: Influenza virus infection (G1), other respiratory viruses' infection (G2), other known etiologic agents (G3), SARS-CoV-2 infection (patients with COVID-19, G4), and undefined etiological agent (G5).MethodsWe performed an epidemiological study using data from DataSUS (https://opendatasus.saude.gov.br/) from December 2019 to October 2021. The dataset included Brazilian hospitalized patients due to SARI. We considered the clinical evolution of the patients with SARI during the COVID-19 pandemic according to the SARI patient groups as the outcome. We performed the multivariate statistical analysis using logistic regression, and we adopted an Alpha error of 0.05.ResultsA total of 2,740,272 patients were hospitalized due to SARI in Brazil, being the São Paulo state responsible for most of the cases [802,367 (29.3%)]. Most of the patients were male (1,495,416; 54.6%), aged between 25 and 60 years (1,269,398; 46.3%), and were White (1,105,123; 49.8%). A total of 1,577,279 (68.3%) patients recovered from SARI, whereas 701,607 (30.4%) died due to SARI, and 30,551 (1.3%) did not have their deaths related to SARI. A major part of the patients was grouped in G4 (1,817,098; 66.3%) and G5 (896,207; 32.7%). The other groups account for <1% of our sample [G1: 3,474 (0.1%), G2: 16,627 (0.6%), and G3: 6,866 (0.3%)]. The deaths related to SARI were more frequent in G4 (574,887; 34.7%); however, the deaths not related to SARI were more frequent among the patients categorized into the G3 (1,339; 21.3%) and G5 (25,829; 4.1%). In the multivariate analysis, the main predictors to classify the patients in the G5 when compared with G4 or G1-G4 were female sex, younger age, Black race, low educational level, rural place of residence, and the use of antiviral to treat the clinical signs. Furthermore, several features predict the risk of death by SARI, such as older age, race (Black, Indigenous, and multiracial background), low educational level, residence in a flu outbreak region, need for intensive care unit, and need for mechanical ventilatory support.ConclusionsThe possible COVID-19 underreporting (G5) might be associated with an enhanced mortality rate, more evident in distinct social groups. In addition, the patients' features are unequal between the patients' groups and can be used to determine the risk of possible COVID-19 underreporting in our population. Patients with a higher risk of death had a different epidemiological profile when compared with patients who recovered from SARI, like older age, Black, Indigenous, and multiracial background races, low educational level, residence in a flu outbreak region, need for intensive care unit and need for mechanical ventilatory support.

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Section: Discussionsupporting

confidence: 89%

Epidemiologic Profile of Severe Acute Respiratory Infection in Brazil During the COVID-19 Pandemic: An Epidemiological Study

2022

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“…The overall mortality rate was 6.0% in all 182 adult patients, the in-hospital mortality was 7.6% of 145 hospitalized adults. This rate corresponds to the in-hospital mortality rate of 6.7% out of 1539 influenza patients hospitalized in eight hospitals in central Germany during the influenza season 2017–2018 [ 10 ] and the in-hospital mortality rate of 8.2% out of 195 hospitalized patients in an Austrian tertiary care hospital [ 11 ]. In a University Hospital in Hamburg, the in-hospital mortality was 12.8%; this was due to a high percentage of referred patients from other hospitals for extracorporeal membrane oxygenation (ECMO) treatment [ 12 ].…”

Section: Discussionmentioning

confidence: 99%

Complications of influenza in 272 adult and pediatric patients in a German university hospital during the seasonal epidemic 2017–2018

Geerdes-Fenge

Klein

Schuldt

et al. 2021

Wien Med Wochenschr

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Summary Background The influenza season 2017–2018 of the northern hemisphere was the highest since 2001 and was caused predominantly by influenza B virus. Methods We performed a retrospective analysis of all patients in a university hospital in northern Germany with laboratory-confirmed influenza during the winter season 2017–2018 and analyzed underlying conditions, complications, and outcome. Results A total of 272 cases of influenza were diagnosed: 70 influenza A (25.7%), 201 influenza B (73.9%), and 1 co-infection. Of 182 adults, 145 were hospitalized, 73 developed pneumonia, 11 developed myocardial infarction, two a transient ischemic attack, one a stroke, and one perimyocarditis. Eleven of the 145 hospitalized adult patients (7.6%) died, ten of them because of pneumonia. All of them had preexisting diseases. Pneumonia was associated with a mortality of 13.7%. Underlying cardiac insufficiency was correlated with higher mortality (7/51 with versus 4/126 patients without cardiac insufficiency; p < 0.05). Ninety cases of influenza were diagnosed in 89 children (30 A, 60 B), one child had first influenza B, then influenza A. Twenty-eight children (31%) were hospitalized, 15 children developed one or more complications (lower respiratory tract infections, meningeal irritations, febrile seizures, otitis media, myositis). No child died. Influenza vaccination status was known in 149 adult patients, pneumonia occurred more frequently in non-vaccinated individuals (43/90; 47.8%) than in vaccinated patients (18/59; 30.5%, p < 0.05). Conclusion Patients with influenza should be monitored for secondary pneumonia and myocardial infarction, and vaccination should be enforced especially in patients with coronary heart disease and cardiac insufficiency.

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“…The mortality rate in our study is similar to that reported from the others, 0.4%-6.7%. 1,[26][27][28] Most of the severe cases were elderly aged and had comorbidities. 27,28 There are some limitations of this study.…”

Section: Discussionmentioning

confidence: 99%

“…Influenza is a respiratory virus that is highly contagious and easily spreads from person to person by droplet transmission. 1 , 2 , 3 It can involve multiple organ systems such as respiratory tract, cardiovascular, and musculoskeletal, leading to morbidity and mortality. 1 , 2 , 3 Accordingly, there is a high number of influenza cases in Thailand.…”

Section: Introductionmentioning

confidence: 99%

“… 1 , 2 , 3 It can involve multiple organ systems such as respiratory tract, cardiovascular, and musculoskeletal, leading to morbidity and mortality. 1 , 2 , 3 Accordingly, there is a high number of influenza cases in Thailand. The overall influenza cases during 2017‐2019 are more than 150 000 cases per year, with an estimated annual incidence of more than 250 per 100 000 population.…”

Section: Introductionmentioning

confidence: 99%

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Clinical manifestations of influenza and performance of rapid influenza diagnostic test: A university hospital setting

Phetcharakupt

Pasomsub

Kiertiburanakul

2021

Health Science Reports

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Background Rapid influenza diagnostic test (RIDT) is a diagnostic tool that detects the influenza virus nucleoprotein antigen. The RIDT is widely used in clinical practice because it is simple and cost‐effective, and provides results within 10‐15 minutes. Objective We aimed at evaluating the sensitivity and specificity of the Sofia® RIDT compared with the Luminex® multiplex polymerase chain reaction (PCR). The other goal was to determine the predicting factors for diagnosing influenza among individuals with influenza‐like illness (ILI). Method Patients with ILI who had the results of both tests were retrospectively reviewed. We determined the performances of the RIDT. Results A total of 473 patients were included with a median age of 58 (interquartile range 41‐74) years. Of these, 47.1% were male, and 16.2% were diagnosed with influenza by the RIDT or RT‐PCR's positive test. For influenza A, the RIDT showed a sensitivity of 76.3% (95% confidence interval [CI] 59.8‐88.6) and a specificity of 97.9% (95% CI 96.1‐99.0), whereas for influenza B, it showed a sensitivity of 47.1% (95% CI 23.0‐72.2) and a specificity of 97.1% (95% CI 95.2‐98.5). Patients with influenza were more likely to present with fever (81.8% vs 63.1%), cough (81.8% vs 66.1%), and rhinorrhea (41.6% vs 26.5%) compared to those without influenza ( P < 0.05, all), and had a higher proportion of pneumonia (19.5% vs 10.6%, P = 0.029) and acute respiratory distress syndrome (5.2% vs 1.5%, P = 0.063). The predicting factors for influenza among patients presented with ILI were cough (odds ratio [OR] 2.77; 95% CI 0.21‐0.81, P = 0.010), rhinorrhea (OR 1.87; 95% CI 1.03‐3.36, P = 0.037), and higher body temperature (OR 1.64; 95% CI 1.23‐2.19, P = 0.001). Conclusions The sensitivity of the RIDT for the diagnosis of influenza is fair in contrast to the specificity. Among patients with ILI, cough, rhinorrhea, and higher body temperature might be factors for predicting influenza.

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Influenza-associated in-hospital mortality during the 2017/2018 influenza season: a retrospective multicentre cohort study in central Germany

Cited by 8 publications

References 6 publications

Epidemiologic Profile of Severe Acute Respiratory Infection in Brazil During the COVID-19 Pandemic: An Epidemiological Study

Epidemiologic Profile of Severe Acute Respiratory Infection in Brazil During the COVID-19 Pandemic: An Epidemiological Study

Complications of influenza in 272 adult and pediatric patients in a German university hospital during the seasonal epidemic 2017–2018

Clinical manifestations of influenza and performance of rapid influenza diagnostic test: A university hospital setting

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