ArticlePloS one2023
Heterogeneity of COVID-19 symptoms and associated factors: Longitudinal analysis of laboratory-confirmed COVID-19 cases in San Antonio.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Few studies have examined heterogeneous associations of risk factors with Coronavirus Disease-2019 (COVID-19) symptoms by type. The objectives of this study were to estimate the prevalence of and risk factors associated with COVID-19 symptoms and to investigate whether the associations differ by the type of symptoms. This study obtained longitudinal data over 6 months from laboratory-confirmed COVID-19 cases in a citywide sample in San Antonio. Sixteen symptoms of COVID-19 infection, measured at baseline and three follow-up times (1, 3, and 6 months), were analyzed using generalized estimating equations (GEE) to investigate potential risk factors while accounting for the repeated measurements. The risk factors included time in months, sociodemographic characteristics, and past or current medical and psychiatric conditions. To obtain interpretable results, we categorized these sixteen symptoms into five categories (cardiopulmonary, neuro-psychological, naso-oropharyngeal, musculoskeletal, and miscellaneous). We fitted GEE models with a logit link using each category as the outcome variable. Our study demonstrated that the associations were heterogeneous by the categories of symptoms. The time effects were the strongest for naso-oropharyngeal symptoms but the weakest for neuro-psychological symptoms. Female gender was associated with increased odds of most of the symptoms. Hispanic ethnicity was also associated with higher odds of neuro-psychological, musculoskeletal, and miscellaneous symptoms. Depression was the most robust psychiatric condition contributing to most of the symptoms. Different medical conditions seemed to contribute to different symptom expressions of COVID-19 infection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.