COVID-19 is not influenza

Petersen, Eskild

doi:10.1016/s2213-2600(20)30577-4

Cited by 14 publications

(9 citation statements)

References 10 publications

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“…This is close to three times higher than that observed for other pneumonias in this same age group even though our control cohort also purposely included severe bacterial pneumonias, which have a higher mortality risk in adults with DS [19,20]. Recent analyses in the general population also demonstrated higher mortality rates in SARS-CoV-2 than other respiratory pathogens [21][22][23][24]. However, it has to be borne in mind that the ageing process in DS subjects is premature, leading to high levels of mortality and multi-morbidity in this population [25].…”

Section: Discussionmentioning

confidence: 63%

Comparison of COVID-19 and Non-COVID-19 Pneumonia in Down Syndrome

Asúa

Mayer

Ortega

et al. 2021

JCM

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Whether the increased risk for coronavirus disease 2019 (COVID-19) hospitalization and death observed in Down syndrome (DS) are disease specific or also occur in individuals with DS and non-COVID-19 pneumonias is unknown. This retrospective cohort study compared COVID-19 cases in persons with DS hospitalized in Spain reported to the Trisomy 21 Research Society COVID-19 survey (n = 86) with admissions for non-COVID-19 pneumonias from a retrospective clinical database of the Spanish Ministry of Health (n = 2832 patients). In-hospital mortality rates were significantly higher for COVID-19 patients (26.7% vs. 9.4%), especially among individuals over 40 and patients with obesity, dementia, and/or epilepsy. The mean length of stay of deceased patients with COVID-19 was significantly shorter than in those with non-COVID-19 pneumonias. The rate of admission to an ICU in patients with DS and COVID-19 (4.3%) was significantly lower than that reported for the general population with COVID-19. Our findings confirm that acute SARS-CoV-2 infection leads to higher mortality than non-COVID-19 pneumonias in individuals with DS, especially among adults over 40 and those with specific comorbidities. However, differences in access to respiratory support might also account for some of the heightened mortality of individuals with DS with COVID-19.

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Section: Discussionmentioning

confidence: 63%

Comparison of COVID-19 and Non-COVID-19 Pneumonia in Down Syndrome

Asúa

Mayer

Ortega

et al. 2021

JCM

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“…Firstly, the SARS-CoV-2 pandemic has radically changed the paradigm of what we have known so far about viral infections in the last 50 years. Patients with COVID-19 differ from those diagnosed with influenza, with an up to three-fold higher in-hospital mortality, higher overburdened ICU capacity, ICU admission (16.3% vs. 10.8%, p < 0.0001), ICU mean length of stay (15 vs. 8 days, p < 0.0001), need for mechanical ventilation (71.5% vs. 61.0%, p < 0.0001), and ICU mortality (27.1% vs. 18.0%, p < 0.0001) [ 22 , 30 , 31 ].…”

Section: Discussionmentioning

confidence: 99%

Antimicrobial Consumption among 66 Acute Care Hospitals in Catalonia: Impact of the COVID-19 Pandemic

et al. 2021

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Background: Antimicrobials have been widely used during the COVID-19 pandemic. This study aimed to analyze the impact of the COVID-19 pandemic on the antimicrobial consumption of 66 hospitals in Catalonia. Methods: Adult antibacterial and antimycotic consumption was calculated as defined daily doses (DDD)/100 bed-days and DDD/100 discharges. Firstly, overall and ICU consumption in 2019 and 2020 were compared. Secondly, observed ICU 2020 consumptions were compared with non-COVID-19 2020 estimated consumptions (based on the trend from 2008–2019). Results: Overall, antibacterial consumption increased by 2.31% and 4.15% DDD/100 bed-days and DDD/100 discharges, respectively. Azithromycin (105.4% and 109.08% DDD/100 bed-days and DDD/100 discharges, respectively) and ceftriaxone (25.72% and 27.97% DDD/100 bed-days and DDD/100 discharges, respectively) mainly accounted for this finding. Likewise, antifungal consumption increased by 10.25% DDD/100 bed-days and 12.22% DDD/100 discharges, mainly due to echinocandins or amphotericin B. ICU antibacterial and antimycotic consumption decreased by 1.28% and 4.35% DDD/100 bed-days, respectively. On the contrary, antibacterial and antifungal use, expressed in DDD/100 discharges, increased by 23.42% and 19.58%. Azithromycin (275.09%), ceftriaxone (55.11%), cefepime (106.35%), vancomycin (29.81%), linezolid (31.28%), amphotericin B (87.98%), and voriconazole (96.17%) use changed the most. Observed consumption of amphotericin B, azithromycin, caspofungin, ceftriaxone, vancomycin, and voriconazole were higher than estimated values. Conclusions: The consumption indicators for most antimicrobials deviated from the expected trend pattern. A worrisome increase in antibacterial and antifungal consumption was observed in ICUs in Catalonia.

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“…All sets are transformed into two-class ones (COVID-19 and non-COVID-19), as shown in Table 2 (the original number of classes is C; we present the number of images after cleaning). The images are split into the training T , 2 We will make our implementation publicly available upon acceptance. validation V , and test Ψ sets (20%, 5%, and 75% of all images) with stratification, to preserve the same percentage contribution of each datasource across all subsets.…”

Section: Datasetsmentioning

confidence: 99%

“…The virus whose transmission may occur even from asymptotic patients, infects the respiratory tract and leads to several notable symptoms of dry cough, fever, fatigue, headache, and loss of taste or smell. Although COVID-19 is often compared to other diseases, the recent studies clearly show that it is much more serious than e.g., seasonal influenza [2]. To effectively tackle a rapidly increasing number of infected patients, developing fast, robust, and non-invasive screening systems is of extreme importance, especially given that a standard clinical test (the reverse transcription polymerase chain reaction, RT-PCR) may render long turn-around times, can be uncomfortable, and requires an experienced operator, as the inaccurate sampling leads to false-positive or false-negative results [3].…”

Section: Introductionmentioning

confidence: 99%

Evolving Deep Ensembles For Detecting Covid-19 In Chest X-Rays

Bosowski

Bosowska

Nalepa

2021

2021 IEEE International Conference on Image Processing (ICIP)

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Since its outbreak reported in late 2019 in Wuhan, China, the novel coronavirus disease (COVID-19) has been the major challenge across the globe, affecting virtually all aspects of our lives. To effectively manage the pandemic, we need fast, non-invasive, and precise routines for detecting active COVID-19 cases. Although there exist deep learning approaches for detecting COVID-19 in medical image data, their generalization abilities remain unknown. We tackle this issue and introduce deep ensembles that benefit from a wide range of architectural advances, alongside a new fusing approach to deliver accurate predictions. Also, we evolve their content to not only accelerate the inference but also to boost the classification performance. Our experiments, performed on a number of datasets of chest X-ray images, show that the proposed technique renders high-quality classification and generalizes well over a variety of test scans.

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COVID-19 is not influenza

Abstract: encephalopathy caused by COVID-19, clinicians might be able to safely manage the majority of these patients without the use of deep sedation.I declare no competing interests.

Cited by 14 publications

References 10 publications

Comparison of COVID-19 and Non-COVID-19 Pneumonia in Down Syndrome

Comparison of COVID-19 and Non-COVID-19 Pneumonia in Down Syndrome

Antimicrobial Consumption among 66 Acute Care Hospitals in Catalonia: Impact of the COVID-19 Pandemic

Evolving Deep Ensembles For Detecting Covid-19 In Chest X-Rays

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