COVID-19: more than “a little flu”? Insights from the Swiss hospital-based surveillance of Influenza and COVID-19

AbstractBackgroundCoronavirus disease 19 (COVID-19) has frequently been colloquially compared to the seasonal influenza, but comparisons based on empirical data are scarce.AimsTo compare in-hospital outcomes for patients admitted with community-acquired COVID-19 to patients with community-acquired influenza in Switzerland.MethodsPatients >18 years, who were admitted with PCR proven COVID-19 or influenza A/B infection to 14 participating Swiss hospitals were included in a prospective surveillance. Primary and secondary outcomes were the in-hospital mortality and intensive care unit (ICU) admission between influenza and COVID-19 patients. We used Cox regression (cause-specific models, and Fine & Gray subdistribution) to account for time-dependency and competing events with inverse probability weighting to account for confounders.ResultsIn 2020, 2843 patients with COVID-19 were included from 14 centers and in years 2018 to 2020, 1361 patients with influenza were recruited in 7 centers. Patients with COVID-19 were predominantly male (n=1722, 61% vs. 666 influenza patients, 48%, p<0.001) and were younger than influenza patients (median 67 years IQR 54-78 vs. median 74 years IQR 61-84, p<0.001). 363 patients (12.8%) died in-hospital with COVID-19 versus 61 (4.4%) patients with influenza (p<0.001). The final, adjusted subdistribution Hazard Ratio for mortality was 3.01 (95% CI 2.22-4.09, p<0.001) for COVID-19 compared to influenza, and 2.44 (95% CI, 2.00-3.00, p<0.001) for ICU admission.ConclusionEven in a national healthcare system with sufficient human and financial resources, community-acquired COVID-19 was associated with worse outcomes compared to community-acquired influenza, as the hazards of in-hospital death and ICU admission were ∼3-fold higher.

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Hospital outcomes of community-acquired COVID-19 versus influenza: Insights from the Swiss hospital-based surveillance of influenza and COVID-19

Eurosurveillance ◽

10.2807/1560-7917.es.2022.27.1.2001848 ◽

2022 ◽

Vol 27 (1) ◽

Author(s):

Georg Marcus Fröhlich ◽

Marlieke E. A. De Kraker ◽

Mohamed Abbas ◽

Olivia Keiser ◽

Amaury Thiabaud ◽

...

Keyword(s):

Influenza A ◽

Seasonal Influenza ◽

Cox Regression ◽

Hospital Death ◽

Rt Pcr ◽

Hospital Outcomes ◽

Subdistribution Hazard ◽

Inverse Probability ◽

Icu Admission ◽

Competing Events

Background Since the onset of the COVID-19 pandemic, the disease has frequently been compared with seasonal influenza, but this comparison is based on little empirical data. Aim This study compares in-hospital outcomes for patients with community-acquired COVID-19 and patients with community-acquired influenza in Switzerland. Methods This retrospective multi-centre cohort study includes patients > 18 years admitted for COVID-19 or influenza A/B infection determined by RT-PCR. Primary and secondary outcomes were in-hospital mortality and intensive care unit (ICU) admission for patients with COVID-19 or influenza. We used Cox regression (cause-specific and Fine-Gray subdistribution hazard models) to account for time-dependency and competing events with inverse probability weighting to adjust for confounders. Results In 2020, 2,843 patients with COVID-19 from 14 centres were included. Between 2018 and 2020, 1,381 patients with influenza from seven centres were included; 1,722 (61%) of the patients with COVID-19 and 666 (48%) of the patients with influenza were male (p < 0.001). The patients with COVID-19 were younger (median 67 years; interquartile range (IQR): 54–78) than the patients with influenza (median 74 years; IQR: 61–84) (p < 0.001). A larger percentage of patients with COVID-19 (12.8%) than patients with influenza (4.4%) died in hospital (p < 0.001). The final adjusted subdistribution hazard ratio for mortality was 3.01 (95% CI: 2.22–4.09; p < 0.001) for COVID-19 compared with influenza and 2.44 (95% CI: 2.00–3.00, p < 0.001) for ICU admission. Conclusion Community-acquired COVID-19 was associated with worse outcomes compared with community-acquired influenza, as the hazards of ICU admission and in-hospital death were about two-fold to three-fold higher.

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Insights into the association of ACEIs/ARBs use and COVID-19 prognosis: a multistate modelling study of nationwide hospital surveillance data from Belgium

BMJ Open ◽

10.1136/bmjopen-2021-053393 ◽

2021 ◽

Vol 11 (9) ◽

pp. e053393

Author(s):

José L. Peñalvo ◽

Els Genbrugge ◽

Elly Mertens ◽

Diana Sagastume ◽

Marianne A B van der Sande ◽

...

Keyword(s):

Markov Models ◽

Transition Probabilities ◽

Angiotensin Receptor Blockers ◽

Surveillance Data ◽

Hospital Death ◽

Hospital Data ◽

Health States ◽

Converting Enzyme Inhibitors ◽

Icu Admission ◽

Competing Events

ObjectivesThe widespread use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) by patients with chronic conditions raised early concerns on the potential exacerbation of COVID-19 severity and fatality. Previous studies addressing this question have used standard methods that may lead to biased estimates when analysing hospital data because of the presence of competing events and event-related dependency. We investigated the association of ACEIs/ARBs’ use with COVID-19 disease outcomes using time-to-event data in a multistate setting to account for competing events and minimise bias.SettingNationwide surveillance data from 119 Belgian hospitals.ParticipantsMedical records of 10 866 patients hospitalised from 14 March 2020to 14 June 2020 with a confirmed SARS-CoV-19 infection and information about ACEIs/ARBs’ use.Primary outcome measureMultistate, multivariate Cox-Markov models were used to estimate the hazards of patients transitioning through health states from admission to discharge or death, along with transition probabilities calculated by combining the baseline cumulative hazard and regression coefficients.ResultsAfter accounting for potential confounders, there was no discernable association between ACEIs/ARBs’ use and transfer to intensive care unit (ICU). Contrastingly, for patients without ICU transfer, ACEIs/ARBs’ use was associated with a modest increase in recovery (HR 1.07, 95% CI 1.01 to 1.13, p=0.027) and reduction in fatality (HR 0.83, 95% CI 0.75 to 0.93, p=0.001) transitions. For patients transferred to ICU admission, no evidence of an association between ACEIs/ARBs’ use and recovery (HR 1.16, 95% CI 0.97 to 1.38, p=0.098) or in-hospital death (HR 0.91, 95% CI 0.73 to 1.12, p=0.381) was observed. Male gender and older age were significantly associated with higher risk of ICU admission or death. Chronic cardiometabolic comorbidities were also associated with less recovery.ConclusionsFor the first time, a multistate model was used to address magnitude and direction of the association of ACEIs/ARBs’ use on COVID-19 progression. By minimising bias, this study provided a robust indication of a protective, although modest, association with recovery and survival.

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Subdistribution-Based Imputation for Deep Survival Analysis with Competing Events

10.21203/rs.3.rs-912257/v1 ◽

2021 ◽

Author(s):

Shekoufeh Gorgi Zadeh ◽

Charlotte Behning ◽

Matthias Schmid

Keyword(s):

Survival Analysis ◽

Survival Data ◽

Cox Regression ◽

Classical Model ◽

Event Analysis ◽

Survival Times ◽

Subdistribution Hazard ◽

Time To Event Data ◽

Competing Events ◽

Real World Datasets

Abstract With the popularity of deep neural networks (DNNs) in recent years, many researchers have proposed DNNs for the analysis of survival data (time-to-event data). These networks learn the distribution of survival times directly from the predictor variables without making strong assumptions on the underlying stochastic process. In survival analysis, it is common to observe several types of events, also called competing events. The occurrences of these competing events are usually not independent of one another and have to be incorporated in the modeling process in addition to censoring. In classical survival analysis, a popular method to incorporate competing events is the subdistribution hazard model, which is usually fitted using weighted Cox regression. In the DNN framework, only few architectures have been proposed to model the distribution of time to a specific event in a competing events situation. These architectures are characterized by a separate subnetwork/pathway per event, leading to large networks with huge amounts of parameters that may become difficult to train. In this work, we propose a novel imputation strategy for data preprocessing that incorporates the subdistribution weights derived from the classical model. With this, it is no longer necessary to add multiple subnetworks to the DNN to handle competing events. Our experiments on synthetic and real-world datasets show that DNNs with multiple subnetworks per event can simply be replaced by a DNN designed for a single-event analysis without loss in accuracy.

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MO206MALE SEX IS ASSOCIATED WITH IN-HOSPITAL DEATH IN NON-DIALYSIS CKD PATIENTS WITH COVID-19

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfab092.0084 ◽

2021 ◽

Vol 36 (Supplement_1) ◽

Author(s):

Armando Coca ◽

Carla Burballa ◽

Francisco Javier Centellas Pérez ◽

Isabel Acosta-Ochoa ◽

María Dolores Arenas ◽

...

Keyword(s):

Proportional Hazards ◽

Cox Regression ◽

Cox Proportional Hazards ◽

Organ Injury ◽

Hospital Death ◽

Cox Regression Analysis ◽

Icu Admission ◽

Matched Design ◽

Male Sex ◽

Age And Sex

Abstract Background and Aims Coronavirus disease (COVID-19), caused by Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) can lead to significant organ injury. CKD has been associated with increased mortality in previous epidemics, and male sex has been correlated with worse outcomes during COVID-19 in the general population. Our aim was to describe the differential effect of sex as a risk factor for in-hospital mortality among non-dialysis CKD subjects. Method Multicenter, observational cohort study including 136 adult patients with CKD and 136 age- and sex-matched controls who required admission for COVID-19 in three academic hospitals in Spain. Viral infection was confirmed by real-time RT-qPCR and/or serologic testing in all cases. Disease severity on admission was classified according to the WHO—China Joint Mission Report on COVID-19. The presence of CKD was defined as sustained eGFR <60 and >15 ml/min/1.73m2 within the 6 months prior to COVID-19 hospitalization. Demographic and clinical data were gathered from medical records. Outcomes were recorded during the following 28 days after admission. We applied Cox proportional hazards models, adjusted for age, sex, hypertension, diabetes and severe or critical disease at presentation. Results Due to the matched design, no differences were found regarding age and sex between cohorts. CKD patients suffered more frequently from hypertension and diabetes and presented higher 28-day mortality after hospital admission due to COVID-19 compared with age- and sex-matched controls (40.4 vs. 24.3%; P=0.004). In adjusted Cox regression analysis among CKD patients, only age (HR: 1.087, 95% CI: 1.047-1.128) and male sex (HR: 1.883, 95% CI: 1.045-3.391) were independent predictors of 28-day mortality. Comparatively, among patients without CKD, only age acted as an independent predictor for 28-day mortality (HR: 1.082, 95% CI: 1.033-1.133). None of the variables included in adjusted regression was able to predict ICU admission in any of the cohorts. Conclusion Male sex is associated with increased mortality, but not with ICU admission, after hospitalization due to COVID-19 among non-dialysis CKD patients. That effect was not observed among hospitalized controls without CKD.

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Influence of comorbidity on hospital outcomes among patients with COVID-19 using electronic records from a nationwide Healthcare System in Peru

10.21203/rs.3.rs-211137/v1 ◽

2021 ◽

Author(s):

Janeth Tenorio-Mucha ◽

Percy Soto-Becerra ◽

Roger V. Araujo-Castillo ◽

YAMILEE HURTADO-ROCA

Keyword(s):

Hospital Mortality ◽

Cox Regression ◽

Social Health Insurance ◽

Rank Test ◽

Hospital Death ◽

Middle Income ◽

Significance Level ◽

Icu Admission ◽

Log Rank Test ◽

Context Specific

Abstract Background Large cases reported that older age and comorbidity are predictors for poor prognosis in COVID-19 patients. Nevertheless, context-specific evidence relevant in low-and middle-income countries is still pending. Methods Retrospective cohort study using electronic health records of confirmed cases admitted in hospitalization areas from the Peruvian Social Health Insurance. The main variable was the presence of comorbidities and the outcomes were in-hospital mortality or intensive care unit admission, and in/out hospital mortality. We used Kaplan-Meier survival curves with the Log-Rank test to compare time-to-event outcomes between comorbidities groups. Crude and adjusted Cox regression models were used to estimate hazard ratios (HR). Statistical analyses were conducted with a significance level of 5%. Results In patients with ICU admission or in-hospital death, 45.99% had one comorbidity and 50.26% had two or more comorbidities. Using in/out hospital deaths up to 60 days as the outcome, the overall survival of patients with two comorbidities is lower than patients with one comorbidity, and both are lowest than a patient without comorbidities (Log-rank test p = 0.001). After adjusting for sex, age, severity, and hospital care network patients with one comorbidity (HR: 1.16; IC 95 %: 1.04–1.31) and with two or more comorbidities (HR: 1.13; IC 95%: 1.01–1.26) are at higher risk to die compared with those without comorbidities. Conclusion The presence of comorbidities in hospitalized patients with COVID-19 are risk factors for ICU admission and mortality. Proper identification of these factors can help to identify patients at higher risk in hospital admission and provide specialized care to prevent deaths.

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Low Brachial Artery Flow-Mediated Dilation Predicts Worse Prognosis in Hospitalized Patients with COVID-19

Journal of Clinical Medicine ◽

10.3390/jcm10225456 ◽

2021 ◽

Vol 10 (22) ◽

pp. 5456

Author(s):

Vanessa Bianconi ◽

Massimo Raffaele Mannarino ◽

Filippo Figorilli ◽

Elisabetta Schiaroli ◽

Elena Cosentini ◽

...

Keyword(s):

Hospital Admission ◽

Brachial Artery ◽

Cox Regression ◽

Composite Endpoint ◽

Hospital Death ◽

Flow Mediated Dilation ◽

Cox Regression Analysis ◽

Icu Admission ◽

Non Invasive ◽

Artery Flow

Background: Endothelial injury can be induced by coronavirus disease 2019 (COVID-19) and seems to exert a crucial pathogenic role in its most severe clinical manifestations. We aimed to investigate the association between brachial artery flow-mediated dilation (bFMD), a potential clinical and non-invasive measure of endothelial function, and in-hospital prognosis of COVID-19 patients. Methods: Brachial artery flow-mediated dilation was assessed in hospitalized COVID-19 patients within 48 h of hospital admission. The association between bFMD and either intensive care unit (ICU) admission or in-hospital death was explored using univariable and multivariable analyses. Results: Four hundred and eight patients were enrolled. Significantly lower bFMD values emerged in COVID-19 patients with either radiographic signs of pneumonia, respiratory distress, or the need for non-invasive ventilation compared with patients without these signs (p < 0.001, p = 0.001, and p < 0.001, respectively). Forty-two (10%) patients were admitted to the ICU, 76 (19%) patients died, and 118 (29%) patients met the composite endpoint of ICU admission/in-hospital death. At unadjusted Cox regression analysis showed that low bFMD (<4.4%, the median value) was associated with a higher risk for the composite endpoint of ICU admission/in-hospital death compared with high bFMD (≥4.4%, the median value) (HR 1.675, 95% CI 1.155–2.428, p = 0.007). Multi-adjusted Cox regression analyses showed that low bFMD was independently associated with a 1.519- to 1.658-fold increased risk for the composite endpoint of ICU admission/in-hospital death. Conclusions: Low bFMD predicts an unfavorable in-hospital prognosis in COVID-19 patients. The measurement of bFMD may be clinically useful in the prognostic stratification of COVID-19 patients upon hospital admission.

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Faculty Opinions recommendation of The global circulation of seasonal influenza A (H3N2) viruses.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1108999.566163 ◽

2008 ◽

Author(s):

Oliver Pybus

Keyword(s):

Influenza A ◽

Seasonal Influenza ◽

Global Circulation

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Cardiovascular risk factors and COVID-19 outcomes in hospitalised patients: a prospective cohort study

BMJ Open ◽

10.1136/bmjopen-2020-045482 ◽

2021 ◽

Vol 11 (2) ◽

pp. e045482

Author(s):

Didier Collard ◽

Nick S Nurmohamed ◽

Yannick Kaiser ◽

Laurens F Reeskamp ◽

Tom Dormans ◽

...

Keyword(s):

Risk Factors ◽

Cox Regression ◽

Lipid Lowering ◽

Lipid Lowering Therapy ◽

Cvd Risk Factors ◽

Cvd Risk ◽

Icu Admission ◽

Lowering Therapy ◽

Secondary Outcomes ◽

Age And Sex

ObjectivesRecent reports suggest a high prevalence of hypertension and diabetes in COVID-19 patients, but the role of cardiovascular disease (CVD) risk factors in the clinical course of COVID-19 is unknown. We evaluated the time-to-event relationship between hypertension, dyslipidaemia, diabetes and COVID-19 outcomes.DesignWe analysed data from the prospective Dutch CovidPredict cohort, an ongoing prospective study of patients admitted for COVID-19 infection.SettingPatients from eight participating hospitals, including two university hospitals from the CovidPredict cohort were included.ParticipantsAdmitted, adult patients with a positive COVID-19 PCR or high suspicion based on CT-imaging of the thorax. Patients were followed for major outcomes during the hospitalisation. CVD risk factors were established via home medication lists and divided in antihypertensives, lipid-lowering therapy and antidiabetics.Primary and secondary outcomes measuresThe primary outcome was mortality during the first 21 days following admission, secondary outcomes consisted of intensive care unit (ICU) admission and ICU mortality. Kaplan-Meier and Cox regression analyses were used to determine the association with CVD risk factors.ResultsWe included 1604 patients with a mean age of 66±15 of whom 60.5% were men. Antihypertensives, lipid-lowering therapy and antidiabetics were used by 45%, 34.7% and 22.1% of patients. After 21-days of follow-up; 19.2% of the patients had died or were discharged for palliative care. Cox regression analysis after adjustment for age and sex showed that the presence of ≥2 risk factors was associated with increased mortality risk (HR 1.52, 95% CI 1.15 to 2.02), but not with ICU admission. Moreover, the use of ≥2 antidiabetics and ≥2 antihypertensives was associated with mortality independent of age and sex with HRs of, respectively, 2.09 (95% CI 1.55 to 2.80) and 1.46 (95% CI 1.11 to 1.91).ConclusionsThe accumulation of hypertension, dyslipidaemia and diabetes leads to a stepwise increased risk for short-term mortality in hospitalised COVID-19 patients independent of age and sex. Further studies investigating how these risk factors disproportionately affect COVID-19 patients are warranted.

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Next generation methodology for updating HA vaccines against emerging human seasonal influenza A(H3N2) viruses

Scientific Reports ◽

10.1038/s41598-020-79590-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

James D. Allen ◽

Ted M. Ross

Keyword(s):

Influenza Virus ◽

Immune Responses ◽

Influenza A ◽

Seasonal Influenza ◽

Influenza Viruses ◽

Next Generation ◽

Virus Infections ◽

Wild Type ◽

Influenza Hemagglutinin ◽

H3n2 Influenza

AbstractWhile vaccines remain the best tool for preventing influenza virus infections, they have demonstrated low to moderate effectiveness in recent years. Seasonal influenza vaccines typically consist of wild-type influenza A and B viruses that are limited in their ability to elicit protective immune responses against co-circulating influenza virus variant strains. Improved influenza virus vaccines need to elicit protective immune responses against multiple influenza virus drift variants within each season. Broadly reactive vaccine candidates potentially provide a solution to this problem, but their efficacy may begin to wane as influenza viruses naturally mutate through processes that mediates drift. Thus, it is necessary to develop a method that commercial vaccine manufacturers can use to update broadly reactive vaccine antigens to better protect against future and currently circulating viral variants. Building upon the COBRA technology, nine next-generation H3N2 influenza hemagglutinin (HA) vaccines were designed using a next generation algorithm and design methodology. These next-generation broadly reactive COBRA H3 HA vaccines were superior to wild-type HA vaccines at eliciting antibodies with high HAI activity against a panel of historical and co-circulating H3N2 influenza viruses isolated over the last 15 years, as well as the ability to neutralize future emerging H3N2 isolates.

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Prognostic impact of elevated lactate levels on mortality in critically ill patients with and without preadmission metformin treatment: a Danish registry-based cohort study

Annals of Intensive Care ◽

10.1186/s13613-020-00652-0 ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 3

Author(s):

Rene A. Posma ◽

Trine Frøslev ◽

Bente Jespersen ◽

Iwan C. C. van der Horst ◽

Daan J. Touw ◽

...

Keyword(s):

Cohort Study ◽

Mortality Rate ◽

Critically Ill ◽

Critically Ill Patients ◽

Cox Regression ◽

Lower Mortality ◽

Prognostic Impact ◽

Icu Admission ◽

Lactate Levels ◽

Restricted Cubic Splines

Abstract Background Lactate is a robust prognostic marker for the outcome of critically ill patients. Several small studies reported that metformin users have higher lactate levels at ICU admission without a concomitant increase in mortality. However, this has not been investigated in a larger cohort. We aimed to determine whether the association between lactate levels around ICU admission and mortality is different in metformin users compared to metformin nonusers. Methods This cohort study included patients admitted to ICUs in northern Denmark between January 2010 and August 2017 with any circulating lactate measured around ICU admission, which was defined as 12 h before until 6 h after admission. The association between the mean of the lactate levels measured during this period and 30-day mortality was determined for metformin users and nonusers by modelling restricted cubic splines obtained from a Cox regression model. Results Of 37,293 included patients, 3183 (9%) used metformin. The median (interquartile range) lactate level was 1.8 (1.2–3.2) in metformin users and 1.6 (1.0–2.7) mmol/L in metformin nonusers. Lactate levels were strongly associated with mortality for both metformin users and nonusers. However, the association of lactate with mortality was different for metformin users, with a lower mortality rate in metformin users than in nonusers when admitted with similar lactate levels. This was observed over the whole range of lactate levels, and consequently, the relation of lactate with mortality was shifted rightwards for metformin users. Conclusion In this large observational cohort of critically ill patients, early lactate levels were strongly associated with mortality. Irrespective of the degree of hyperlactataemia, similar lactate levels were associated with a lower mortality rate in metformin users compared with metformin nonusers. Therefore, lactate levels around ICU admission should be interpreted according to metformin use.

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