Impact of SARS-CoV-2 Infection on Essential Tremor: A Retrospective Clinical and Kinematic Analysis
Bibliographic record
Abstract
In the past few years, SARS-CoV-2 infection has substantially impacted public health. Alongside respiratory symptoms, some individuals have reported new neurological manifestations or a worsening of pre-existing neurological conditions. We previously documented two cases of essential tremor (ET) who experienced a deterioration in tremor following SARS-CoV-2 infection. However, the effects of SARS-CoV-2 on ET remain largely unexplored. This study aims to evaluate the impact of SARS-CoV-2 infection on a relatively broad sample of ET patients by retrospectively comparing their clinical and kinematic data collected before and after the exposure to SARS-CoV-2. We surveyed to evaluate the impact of SARS-CoV-2 infection on tremor features in ET. Subsequently, we retrospectively analysed clinical and kinematic data, including accelerometric recordings of postural and kinetic tremor. We included 36 ET patients (14 females with a mean age of 71.1 ± 10.6 years). Among the 25 patients who reported SARS-CoV-2 infection, 11 (44%) noted a subjective worsening of tremor. All patients reporting subjective tremor worsening also exhibited symptoms of long COVID, whereas the prevalence of these symptoms was lower (50%) in those without subjective exacerbation. The retrospective analysis of clinical data revealed a tremor deterioration in infected patients, which was not observed in non-infected patients. Finally, kinematic analysis revealed substantial stability of tremor features in both groups. The study highlighted a potential correlation between the SARS-CoV-2 infection and clinical worsening of ET. Long COVID contributes to a greater impact of tremor on the daily life of ET patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".