Evaluation of the main neurological manifestations in patients from the Post-COVID outpatient clinic of URI Erechim
Bibliographic record
Abstract
The objective of this study was to assess the profile of patients treated at the Post-COVID-19 Rehabilitation Outpatient Clinic of URI Erechim, the neurological manifestations observed, and to correlate patients’ symptoms with the need for orotracheal intubation. This is an observational, retrospective, and mixed-methods (qualitative and quantitative) study. Physiotherapy records of patients receiving care at the Post-COVID-19 Rehabilitation Outpatient Clinic, referred by physicians in 2021, were analyzed. The following instruments were employed: the Neurological Manifestations Assessment Questionnaire, the Montreal Cognitive Assessment (MoCA), and the Prospective and Retrospective Memory Questionnaire (PRMQ). Descriptive statistics and MoCA scores were used to compare pre- and post-rehabilitation data using a paired t-test, and to compare intubated and non-intubated participants using a t-test. Values lower than 0.05 were considered statistically significant. Analyses were performed using GraphPad Prism 9.2 software. A total of 16 patients were evaluated; most reported neurological symptoms, with 50% presenting memory lapses and 13% demonstrating cognitive deficits. This study concluded that COVID-19 caused short-term neurological damage, but no significant memory or cognitive impairment was detected in the sample, nor was any association observed between orotracheal intubation and cognitive alterations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".