Increased prevalence of mild myopathic changes in the post-COVID-19 duration
Bibliographic record
Abstract
OBJECTIVE: There are reports of peripheral nerve and muscle involvement during or after coronavirus disease 2019 (COVID-19), even following a mild infection. Here, we aimed to analyze the objective findings regarding peripheral nerve, neuromuscular junction, and muscle function using electrophysiology in patients with a previous COVID-19 infection. METHODS: All consecutive patients with a history of COVID-19 were questioned for post-COVID-19 duration-related neurological complaints via Composite Autonomic Symptom Score-31 (COMPASS-31), modified Toronto Neuropathy score (mTORONTO), and Fatigue Severity Scale (FSS). Patients were dichotomized into two groups based on their scores in the questionnaire. Group 1 (patients with high scores in any area of the questionnaire) and Group 2 (patients with normal scores in all sections of the questionnaire). In the second step, Group 1 was invited to a preplanned hospital visit for electrophysiological analysis, including nerve conduction studies, repetitive nerve stimulation, needle electromyography (EMG), quantitative motor unit potential analysis (qMUP), and single fiber EMG. We included 106 patients in the study. According to the questionnaire, 38 patients constituted Group 1, and 68 formed Group 2. RESULTS: Of the 38 patients, 14 accepted and underwent preplanned electrophysiological examinations. Needle EMG revealed small, short, polyphasic MUPs with early recruitment, and qMUP analysis demonstrated an increased percentage of polyphasic potentials in three patients. The examinations in other patients were unremarkable. CONCLUSIONS: The high prevalence of complaints and objective myopathic findings in our cohort implicated the role of muscle involvement in the post-COVID-19 duration. Considering the socioeconomic and psychological burden of the post-COVID-19 duration among individuals and societies, a better understanding of the symptoms and myopathy is warranted.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".