Clinical Phenotyping of Long <scp>COVID</scp> Patients Evaluated in a Specialized Neuro‐<scp>COVID</scp> Clinic
Bibliographic record
Abstract
OBJECTIVE: To report Long COVID characteristics and longitudinal courses of patients evaluated between 4/14/21-4/14/22 at the University of Pennsylvania Neurological COVID Clinic (PNCC), including clinical symptoms, neurological examination findings, and neurocognitive screening tests from a standardized PNCC neurological evaluation approach. METHODS: This is a retrospective cross-sectional and longitudinal study in a single-center tertiary care academic center. Participants include 240 patients with documented evidence of a positive SARS-CoV-2 PCR or antibody test who underwent initial evaluation and 182 patients with longitudinal follow-up. Main outcomes evaluated are patient demographics, duration of illness prior to self-reported improvement, and cognitive testing results-including the Montreal Cognitive Assessment (version 8.2) (MoCA) and Oral Trail Making Test-B (OTMT-B). RESULTS: The majority (73%) of patients did not require hospitalization for their acute COVID-19 symptoms. Frequent Long COVID complaints included headache (60%), dizziness/vertigo (40%), and disturbance of taste/smell (40%). Almost all (94%) patients reported cognitive symptoms, and over 30% of patients had abnormal scores on cognitive testing. Severe infection, fewer years of education level, and non-White race were found to be statistically associated with an increased likelihood of having abnormal scores on cognitive testing. Neuroimaging and clinical laboratory testing were largely not informative for patient care. Sixty-two percent of patients with follow-up visits self-reported improvement in their primary neurological complaint within 1 year of evaluation. INTERPRETATION: Performance on standardized cognitive screening tests may not be consistent with frequently reported cognitive complaints in Long COVID patients. The most common clinical trajectory was self-reported improvement in the primary neurological symptom.
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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 | 0.000 | 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 | 0.001 | 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".