Dataset Information

NeuroCORD: A Language Model to Facilitate COVID-19-Associated Neurological Disorder Studies.

ABSTRACT: COVID-19 can lead to multiple severe outcomes including neurological and psychological impacts. However, it is challenging to manually scan hundreds of thousands of COVID-19 articles on a regular basis. To update our knowledge, provide sound science to the public, and communicate effectively, it is critical to have an efficient means of following the most current published data. In this study, we developed a language model to search abstracts using the most advanced artificial intelligence (AI) to accurately retrieve articles on COVID-19-associated neurological disorders. We applied this NeuroCORD model to the largest benchmark dataset of COVID-19, CORD-19. We found that the model developed on the training set yielded 94% prediction accuracy on the test set. This result was subsequently verified by two experts in the field. In addition, when applied to 96,000 non-labeled articles that were published after 2020, the NeuroCORD model accurately identified approximately 3% of them to be relevant for the study of COVID-19-associated neurological disorders, while only 0.5% were retrieved using conventional keyword searching. In conclusion, NeuroCORD provides an opportunity to profile neurological disorders resulting from COVID-19 in a rapid and efficient fashion, and its general framework could be used to study other COVID-19-related emerging health issues.

SUBMITTER: Wu L

PROVIDER: S-EPMC9408703 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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NeuroCORD: A Language Model to Facilitate COVID-19-Associated Neurological Disorder Studies.

Wu Leihong L Ali Syed S Ali Heather H Brock Tyrone T Xu Joshua J Tong Weida W

International journal of environmental research and public health 20220812 16

COVID-19 can lead to multiple severe outcomes including neurological and psychological impacts. However, it is challenging to manually scan hundreds of thousands of COVID-19 articles on a regular basis. To update our knowledge, provide sound science to the public, and communicate effectively, it is critical to have an efficient means of following the most current published data. In this study, we developed a language model to search abstracts using the most advanced artificial intelligence (AI) ...[more]

PMID: 36011614

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Project description:BackgroundNeurological manifestations of SARS-CoV-2 infection have been reported from many countries around the world, including the South Asian region. This surveillance study aimed to describe the spectrum of neurological disorders associated with COVID-19 in Sri Lanka.MethodsCOVID-19 patients manifesting neurological disorders one week prior and up to six weeks after infection were recruited from all the neurology centres of the government hospitals in Sri Lanka from May 2021 - May 2022. Data was collected using a structured data form that was electronically transmitted to a central repository. All patients were evaluated and managed by a neurologist. Data were analysed using simple descriptive analysis to characterise demographic and disease related variables, and simple comparisons and logistic regression were performed to analyse outcomes and their associations.ResultsOne hundred and eighty-four patients with neurological manifestations associated with COVID-19 were recruited from all nine provinces in Sri Lanka. Ischaemic stroke (31%) was the commonest neurological manifestation followed by encephalopathy (13.6%), Guillain-Barre syndrome (GBS) (9.2%) and encephalitis (7.6%). Ischaemic stroke, encephalitis and encephalopathy presented within 6 days of onset of COVID-19 symptoms, whereas GBS and myelitis presented up to 10 days post onset while epilepsy and Bell palsy presented up to 20 - 40 days post onset. Haemorrhagic stroke presented either just prior to or at onset, or 10 - 25 days post onset of COVID-19 symptomatic infection. An increased frequency of children presenting with encephalitis and encephalopathy was observed during the Omicron variant predominant period. A poor outcome (no recovery or death) was associated with supplemental oxygen requirement during admission (Odds Ratio: 12.94; p = 0.046).ConclusionsThe spectrum and frequencies of COVID-19 associated neurological disorders in Sri Lanka were similar to that reported from other countries, with strokes and encephalopathy being the commonest. Requiring supplemental oxygen during hospitalisation was associated with a poor outcome.

Project description:Importance: There is an unprecedented need to rapidly identify safe and effective treatments for the novel coronavirus disease 2019 (COVID-19). Objective: To systematically investigate if any of the available drugs in Electronic Health Record (EHR), including prescription drugs and dietary supplements, can be repurposed as potential treatment for COVID-19. Design, Setting, and Participants: Based on a retrospective cohort analysis of EHR data, drug-wide association studies (DrugWAS) were performed on COVID-19 patients at Vanderbilt University Medical Center (VUMC). For each drug study, multivariable logistic regression with overlap weighting using propensity score was applied to estimate the effect of drug exposure on COVID-19 disease outcomes. Exposures: Patient exposure to a drug during 1-year prior to the pandemic and COVID-19 diagnosis was chosen as exposure of interest. Natural language processing was employed to extract drug information from clinical notes, in addition to the prescription drug data available in structured format. Main Outcomes and Measures: All-cause of death was selected as primary outcome. Hospitalization, admission to the intensive care unit (ICU), and need for mechanical ventilation were identified as secondary outcomes. Results: The study included 7,768 COVID-19 patients, of which 509 (6.55%) were hospitalized, 82 (1.06%) were admitted to ICU, 64 (0.82%) received mechanical ventilation, and 90 (1.16%) died. Overall, 15 drugs were significantly associated with decreased COVID-19 severity. Previous exposure to either Streptococcus pneumoniae vaccines (adjusted odds ratio [OR], 0.38; 95% CI, 0.14-0.98), diphtheria toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98), and tetanus toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98) were significantly associated with a decreased risk of death (primary outcome). Secondary analyses identified several other significant associations showing lower risk for COVID-19 outcomes: 2 vaccines (acellular pertussis, Streptococcus pneumoniae), 3 dietary supplements (turmeric extract, flaxseed extract, omega-3 fatty acids), methylprednisolone acetate, pseudoephedrine, ethinyl estradiol, estradiol, ibuprofen, and fluticasone. Conclusions and Relevance: This cohort study leveraged EHR data to identify a list of drugs that could be repurposed to improve COVID-19 outcomes. Further randomized clinical trials are needed to investigate the efficacy of the proposed drugs.

Project description:BackgroundNeurological manifestations associated with COVID-19 remain partially described, mainly in low- and middle-income countries where diagnostic tools are limited. To address this, we assembled medical centers in Brazil with the goal of describing neurological syndromes associated with COVID-19 during the first wave of the pandemic.MethodsFrom June 1st, 2020 to June 1st, 2021, non-consecutive adult patients with new onset of six neurological syndromes up to 60 days after confirmed COVID-19 were included. Data were compiled from four tertiary centers and compared with general local COVID-19 data, as well as with a previous cohort focused on vascular syndrome.Results197 patients were included, presenting with vascular syndromes (81), encephalopathy (68), encephalitis (19), Guillain-Barré syndrome (13), other neuropathies (12), and myelitis (4). The incidence curve of neurocovid mirrored that of COVID-19. Neurological syndromes were present regardless of COVID-19 severity. The median time from COVID-19 to onset of neurological symptoms was 14 days, suggesting a post-infectious immune-mediated mechanism. Patients were 10 times more likely to die (χ2 (1) = 356.55, p < 0.01, OR = 10.89) and 38 times more likely to be hospitalized than other COVID-19 patients (χ2 (1) = 1167.9, p < 0.01, OR = 38.22). Those developing vascular syndromes patients were 3 times more likely to require ICU (χ2 (1) = 37.12, p < 0.01, OR = 3.78) and 4 times more likely to die (χ2 (1) = 58.808, p < 0.01, OR = 4.73) than patients with vascular syndromes due to different etiologies.ConclusionsOur study corroborates the association of neurological syndromes with COVID-19. The incidence correlated with local waves of COVID-19, and patients with neurocovid exhibited a higher susceptibility to adverse outcomes compared to other COVID-19 patients. Among all neurological syndromes, vascular syndromes were the most common, and their severity surpassed that of vascular syndromes not attributed to COVID-19.

Dataset Information

NeuroCORD: A Language Model to Facilitate COVID-19-Associated Neurological Disorder Studies.

Publications

NeuroCORD: A Language Model to Facilitate COVID-19-Associated Neurological Disorder Studies.

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