A multicenter cohort of 102 individuals with neuroPASC and 74 controls enrolled between February 2022 and June 2024. Ana I. Silva authored this dataset, which likely contains clinical, behavioral, sociodemographic, and biomarker data to identify factors associated with high symptom burden. The data was last updated on March 19, 2026.
Use Cases
- Predicting high-burden neuroPASC based on pre-existing endocrine/metabolic and gastrointestinal conditions.
- Clustering patients by neurological symptom burden using unsupervised algorithms.
- Analyzing associations between cumulative alcohol use and neuroPASC severity.
- Comparing quality-of-life and cognitive function deficits between neuroPASC clusters and controls.
- Evaluating the predictive power of the Charlson Comorbidity Index and Framingham Risk Score for neuroPASC.
Strengths
- Includes 102 neuroPASC cases and 74 controls, totaling 176 participants.
- Data collection spanned over two years, from February 2022 to June 2024.
- Multivariable logistic regression identified a 3.5-fold odds increase for high-burden neuroPASC linked to specific pre-existing conditions.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The dataset is 3.1 MB, suggesting a relatively small scale.
Provenance
- Source
- Ana I. Silva via figshare.
- Collection Method
- Prospective, observational study across five academic sites.
- Time Range
- Enrollment between February 2022 and June 2024.
- Freshness
- Last updated 2026-03-19 06:49:47; freshness should be verified.