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Record W4388495828 · doi:10.2147/jmdh.s432969

Cognitive Dysfunction in Hospitalized Patient with Moderate-to-Severe COVID-19: A 1-Year Prospective Observational Study

2023· article· en· W4388495828 on OpenAlexaboutno aff
Mihaela-Camelia Vasile, Claudiu Ionuț Vasile, Anca-Adriana Arbune, Alexandru Nechifor, Manuela Arbune

Bibliographic record

VenueJournal of Multidisciplinary Healthcare · 2023
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyCoronavirus disease 2019 (COVID-19)Medicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)CognitionProspective cohort studyIntensive care medicinePediatricsPsychiatryInternal medicinePathologyDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Purpose: To screen the neurocognitive impairment persistent post-COVID-19. Patients and Methods: We assessed the neuropsychiatric disorders associated with COVID-19 in a prospective study, by "Mini-Mental State Examination" (MMSE) and Montreal Cognitive Assessment (MoCA) questionnaires, applied in the discharge to COVID-19 hospitalized patients for moderate and severe forms of disease. They were followed-up in 6 and 12 months. Results: The tests were performed in the baseline and were reevaluated after 6 and 12 months. Baseline cognitive dysfunction was found in 12.4% of patients, according to the MMSE test and in 19.7% by the MoCA scores. Overall cognitive dysfunction in COVID-19 was returned to normal after 6 months, although some tasks are more severe and persistently impaired, such as attention, concentration, short memory, and execution skills. The male gender and the degree of hypoxia, related to the severity of COVID-19 infection, were related to cognitive dysfunction in the study group. Conclusion: Cognitive domain impairments related to COVID-19 could persist over 6 months post-acute infectious episode requiring systematic screening for early diagnosis of progressive brain pathologies and rehabilitation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.060
GPT teacher head0.387
Teacher spread0.327 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations14
Published2023
Admission routes1
Has abstractyes

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