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Record W3096792008 · doi:10.4103/aian.aian_652_20

Neurology and COVID-19: Time to burn the candle at both ends

2020· editorial· en· W3096792008 on OpenAlexaboutno aff
AchalK Srivastava, Divyani Garg

Bibliographic record

VenueAnnals of Indian Academy of Neurology · 2020
Typeeditorial
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsCandleCoronavirus disease 2019 (COVID-19)Medicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PandemicMedical emergencyVirologyInternal medicineEngineeringOutbreak

Abstract

fetched live from OpenAlex

Although the most prominent feature of SARS-CoV-2 infection is respiratory involvement, neurological manifestations continue to be increasingly reported from various centers, and a slew of systematic reviews summarizing the same in COVID-19 has emerged in recent literature.[1-4] Notably, multiple levels of neuraxial involvement as well as myriad putative mechanisms ranging from direct infiltration, retrograde transmission, para- and post-infectious immune-mediated mechanisms to explain neurological findings have been described. While we continue to accrue observational data on neurological conditions in patients infected with SARS-CoV-2, we must simultaneously answer one core question, that is, pertaining to causality. Are the neurological features that we report induced by infection with SARS-CoV-2 or are these mere associations? The appropriate tool by which this may be answered is a case-control study design, which is currently not feasible, considering challenges in determining exposure. In this scenario, the next best approach would be a collective effort to create and maintain a registry of COVID-19 patients with neurological conditions, as well as clear and transparent reports of observations which avoid being over-interpretative. Efforts are underway for the former in several countries. The Spanish Neurological Society [www.sen.es], amidst the ongoing pandemic, has created a registry of acute and subacute neurological conditions appearing in patients with SARS-CoV-2 infection. The CoroNerve Studies Group has been set up as a collaborative venture in the United Kingdom (www.CoroNerve.com). It has been learnt that an Indian registry is also being set up under the aegis of the World Federation of Neurology. As has been emphasized by Ellul et al., we must seek to define causality in COVID-19 by applying the Bradford Hill criteria, 1965, key principles of which include strength, specificity and consistency of association, biological plausibility, biological gradient, temporal relationship to proposed agent, and supportive experimental evidence.[5] While acute and subacute de novo neurological conditions continue to be reported, we also need to remember to be on the lookout for long-term or delayed neurological features and complications. Considering the SARS-CoV-1 as well as other historical paradigms, these may perhaps not be uncommon. Following the 2003 outbreak, a Canadian study reported chronic neurological concerns among 22 healthcare workers 13 to 26 months following SARS-CoV-1 infection. These included sleep disturbances with increased Rapid Eye Movement (REM) apneas/hypopneas, depression, myalgias, persistent fatigue, and increased sleep Electroencephalography (EEG) cyclical alternating pattern.[6] Encephalitis lethargica, a form of Parkinsonism, was reported following the 1918–1920 influenza epidemic although epidemiological analyses later suggested that these disorders were possibly co-incidental.[7] Moreover, while we grapple with COVID-19 and its neurological ramifications, let us not forget the non-COVID patients with neurological illnesses. A comprehensive stroke center in Canada has preliminarily documented declining stroke rates, with an average fall of 38% in new stroke cases during the COVID-19 period which was mostly attributable to the smaller proportion of patients accessing healthcare services.[8] Certainly, practical barriers to implementing and sustaining the continuity of neurological care in patients without COVID-19 are tremendous despite which care must be ensured to avoid corollary damage to this group of patients. It is also clear that most of the data on neurological involvement in COVID-19 is anecdotal and fragmentary and likely represents the tip of the iceberg; epidemiological studies would serve as optimal vehicles to answer questions not only related to the neurology of COVID-19 but the disease itself. As neurologists, the battle against COVID-19 is going to be long and hard-won, and we must continue to keep our noses to the grindstone.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.065
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.070
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0030.003
Science and technology studies0.0050.006
Scholarly communication0.0110.034
Open science0.0040.009
Research integrity0.0180.026
Insufficient payload (model declined to judge)0.0650.026

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.347
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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