Dataset Information

Frequency of Neurological Diseases After COVID-19, Influenza A/B and Bacterial Pneumonia.

ABSTRACT:

Introduction

COVID-19 might affect the incidence of specific neurological diseases, but it is unknown if this differs from the risk following other infections. Here, we characterized the frequency of neurodegenerative, cerebrovascular, and immune-mediated neurological diseases after COVID-19 compared to individuals without COVID-19 and those with other respiratory tract infections.

Methods

This population-based cohort study utilized electronic health records covering ~50% of Denmark's population (n = 2,972,192). Between 02/2020 and 11/2021, we included individuals tested for COVID-19 or diagnosed with community-acquired bacterial pneumonia in hospital-based facilities. Additionally, we included individuals tested for influenza in the corresponding pre-pandemic period between 02/ 2018 and 11/2019. We stratified cohorts for in- and outpatient status, age, sex, and comorbidities.

Results

In total, 919,731 individuals were tested for COVID-19, of whom 43,375 tested positive (35,362 outpatients, 8,013 inpatients). Compared to COVID-negative outpatients, COVID-19 positive outpatients had an increased RR of Alzheimer's disease (RR = 3.5; 95%CI: 2.2-5.5) and Parkinson's disease (RR = 2.6; 95%CI: 1.7-4.0), ischemic stroke (RR = 2.7; 95%CI: 2.3-3.2) and intracerebral hemorrhage (RR = 4.8; 95%CI: 1.8-12.9). However, when comparing to other respiratory tract infections, only the RR for ischemic stroke was increased among inpatients with COVID-19 when comparing to inpatients with influenza (RR = 1.7; 95%CI: 1.2-2.4) and only for those >80 years of age when comparing to inpatients with bacterial pneumonia (RR = 2.7; 95%CI: 1.2-6.2). Frequencies of multiple sclerosis, myasthenia gravis, Guillain-Barré syndrome and narcolepsy did not differ after COVID-19, influenza and bacterial pneumonia.

Conclusion

The risk of neurodegenerative and cerebrovascular, but not neuroimmune, disorders was increased among COVID-19 positive outpatients compared to COVID-negative outpatients. However, except for ischemic stroke, most neurological disorders were not more frequent after COVID-19 than after other respiratory infections.

SUBMITTER: Zarifkar P

PROVIDER: S-EPMC9259944 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectivesGround-glass opacity and consolidation are recognized typical features of Coronavirus disease-19 (COVID-19) pneumonia on Chest CT, yet ancillary findings have not been fully described. We aimed to describe ancillary findings of COVID-19 pneumonia on CT, to define their prevalence, and investigate their association with clinical data.MethodsWe retrospectively reviewed our CT chest cases with coupled reverse transcriptase polymerase chain reaction (rt-PCR). Patients with negative rt-PCR or without admission chest CT were excluded. Ancillary findings included: vessel enlargement, subpleural curvilinear lines, dependent subpleural atelectasis, centrilobular solid nodules, pleural and/or pericardial effusions, enlarged mediastinal lymph nodes. Continuous data were expressed as median and 95% confidence interval (95% CI) and tested by Mann-Whitney U test.ResultsAncillary findings were represented by 106/252 (42.1%, 36.1 to 48.2) vessel enlargement, 50/252 (19.8%, 15.4 to 25.2) subpleural curvilinear lines, 26/252 (10.1%, 7.1 to 14.7) dependent subpleural atelectasis, 15/252 (5.9%, 3.6 to 9.6) pleural effusion, 15/252 (5.9%, 3.6 to 9.6) mediastinal lymph nodes enlargement, 13/252 (5.2%, 3 to 8.6) centrilobular solid nodules, and 6/252 (2.4%, 1.1 to 5.1) pericardial effusion. Air space disease was more extensive in patients with vessel enlargement or centrilobular solid nodules (p < 0.001). Vessel enlargement was associated with longer history of fever (p = 0.035) and lower admission oxygen saturation (p = 0.014); dependent subpleural atelectasis with lower oxygen saturation (p < 0.001) and higher respiratory rate (p < 0.001); mediastinal lymph nodes with shorter history of cough (p = 0.046); centrilobular solid nodules with lower prevalence of cough (p = 0.023), lower oxygen saturation (p < 0.001), and higher respiratory rate (p = 0.032), and pericardial effusion with shorter history of cough (p = 0.015). Ancillary findings associated with longer hospital stay were subpleural curvilinear lines (p = 0.02), whereas centrilobular solid nodules were associated with higher rate of intensive care unit admission (p = 0.01).ConclusionTypical high-resolution CT findings of COVID-19 pneumonia are frequently associated with ancillary findings that variably associate with disease extent, clinical parameters, and disease severity.Advances in knowledgeAncillary findings might reflect the broad range of heterogeneous mechanisms in severe acute respiratory syndrome from viral pneumonia, and potentially help disease phenotyping.

Project description:Introduction: Diagnosis of severe influenza pneumonia remains challenging because of the lack of correlation between presence of influenza virus and patient’s clinical status. We conducted gene expression profiling in the whole blood of critically ill patients to identify a gene signature that would allow clinicians to distinguish influenza infection from other causes of severe respiratory failure (e.g. bacterial pneumonia, non-infective systemic inflammatory response syndrome). Methods: Whole blood samples were collected from critically ill individuals and assayed on Illumina HT-12 gene expression beadarrays. Differentially expressed genes were determined by linear mixed model analysis and over-represented biological pathways determined using GeneGo MetaCore. Results: The gene expression profile of H1N1 influenza A pneumonia was distinctly different from bacterial pneumonia and systemic inflammatory response syndrome. The influenza gene expression profile is characterized by up-regulation of genes from cell cycle regulation, apoptosis and DNA-damage response pathways. In contrast, no distinctive gene-expression signature was found in patients with bacterial pneumonia or systemic inflammatory response syndrome. The gene expression profile of influenza infection persisted through five days of follow-up. Furthermore, in patients with primary H1N1 influenza A infection who subsequently developed bacterial co-infection, the influenza gene-expression signature remained unaltered, despite the presence of a super-imposed bacterial infection. Conclusions: The whole blood expression profiling data indicates that the host response to influenza pneumonia is distinctly different from that caused by bacterial pathogens. This information may speed up identification of the cause of infection in patients presenting with severe respiratory failure, allowing appropriate patient care to be undertaken more rapidly. Daily PAXgene samples for up to 5 days for; influenza A pneumonia patients (n=8), bacterial pneumonia patients (n=16), mixed bacterial and influenza A pneumonia patients (n=3), systemic inflammatory response patients (SIRS, n=13). Days 1 and 5 PAXgene samples for healthy control individuals