Neurology and COVID-19: Time to burn the candle at both ends
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,023 | 0,070 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,005 | 0,006 |
| Communication savante | 0,011 | 0,034 |
| Science ouverte | 0,004 | 0,009 |
| Intégrité de la recherche | 0,018 | 0,026 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,065 | 0,026 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».