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Record W3193901438 · doi:10.1177/21501327211039709

The Influence of Coronavirus Disease-2019 (COVID-19) On Parkinson’s Disease: An Updated Systematic Review

2021· review· en· W3193901438 on OpenAlexaff
Vikash Jaiswal, Danah Alquraish, Zouina Sarfraz, Azza Sarfraz, Shavy Nagpal, Prakriti Singh Shrestha, Dattatreya Mukherjee, Prathima Guntipalli, Diana Sánchez, Arushee Bhatnagar, Saloni Savani, Elmjedina Halilaj, Samir Ruxmohan, Wilson Cueva

Bibliographic record

VenueJournal of Primary Care & Community Health · 2021
Typereview
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsSt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsMedicineCytokine stormDiseaseEncephalopathyPandemicSystematic reviewParkinson's diseaseCochrane LibraryDementiaMultiple sclerosisInternal medicineIntensive care medicineCoronavirus disease 2019 (COVID-19)MEDLINEPediatricsMeta-analysisImmunologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: COVID-19 has affected global communities with multiple neurological complications in addition to other critical medical issues. COVID-19 binds to the host's angiotensin-converting enzyme 2 (ACE2) receptors, which are expressed in the neurons and glial cells, acting as an entry port to the central nervous system (CNS). ACE2 receptors are abundantly expressed on dopamine neurons, which may worsen the prognosis of motor symptoms in Parkinson's disease (PD). SARS-CoV-2 may lead to an indirect response via immune-mediated cytokine storms and propagate through the CNS leading to damage. In this systematic review, we aim to provide thorough analyses of associations between COVID-19 and neurological outcomes for patients with PD. METHODS: Using PRISMA statement 2020, a systematic review was conducted to isolate confirmed COVID-19 patients and analyze the PD-associated neurological outcomes using the following databases: PubMed, Science Direct, Google Scholar, and Cochrane databases. The following keywords were used "COVID19, SARS-CoV-2, Parkinson's disease, Pandemic, Mortality." A modified Delphi process was employed. RESULTS: Of the 355 studies located during the initial round of screening, 16 were included in the final synthesis. Of PD patients who tested positive for SARS-CoV-2, worsening motor symptoms and other viral-associated symptoms were reported. These symptoms included bradykinesia, tremors, gait disturbances, delirium and dementia, and severe spasms of arms and legs. Encephalopathy was presented in 2 of the included studies. Increased mortality rates were identified for hospitalized patients due to COVID-19 and PD as compared to other patient groups. CONCLUSION: Patients with PD may experience substantial worsening of symptoms due to COVID 19. Given the novelty of neurological-viral associations, clinical studies in the future ought to explore the disease severity and neurological outcomes in COVID-19 positive patients with PD as compared to non-PD patients, in addition to understanding the role of ACE2 in increased vulnerability to contracting the infection and as a treatment modality.

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)0.007
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.009
Bibliometrics0.0120.012
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.081
GPT teacher head0.435
Teacher spread0.355 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations19
Published2021
Admission routes1
Has abstractyes

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