ArticleGerms2021
Clinical diagnosis of COVID-19. A multivariate logistic regression analysis of symptoms of COVID-19 at presentation.
Article in Germs, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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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
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Prevalence of comorbid tuberculosis amongst COVID-19 patients: A rapid review and meta-analysis.International journal of clinical practice · 2021Pooled it
- Comparative analysis of frequentist, Bayesian, and machine learning models for predicting SARS-CoV-2 PCR positivity.Frontiers in artificial intelligence · 2025Article
- Omicron in Infants-Respiratory or Digestive Disease?Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe objective of this cross-sectional study was to describe the main symptoms associated with COVID-19, and their diagnostic characteristics, to aid in the clinical diagnosis.
methodsAn analysis of all patients diagnosed by RT-PCR for SARS-CoV-2 between April and May 2020 in Argentina was conducted. The data includes clinical and demographic information from all subjects at the time of presentation (n=67318, where 12% were positive for SARS-CoV-2). The study population was divided into four age groups: pediatric (0-17 years), young adults (18-44 years), adults (45-64 years), and elderly (65-103 years). Multivariate logistic regression was used to measure the association of all symptoms and to create a diagnostic model based on symptoms.
resultsSymptoms associated with COVID-19 were anosmia, dysgeusia, headache, low-grade fever, odynophagia, and malaise. However, the presentation of these symptoms was different between the different age groups. In turn, at the time of presentation, the symptoms associated with respiratory problems (chest pain, abdominal pain, and dyspnea) had a negative association with COVID-19 or did not present statistical relevance. On the other hand, the model based on 16 symptoms, age and sex, presented a sensitivity of 80% and a specificity of 46%.
conclusionsThere were significant differences between the different age groups. Additionally, there were interactions between different symptoms that were highly associated with COVID-19. Finally, our findings showed that a regression model based on multiple factors (age, sex, interaction between symptoms) can be used as an accessory diagnostic method or a rapid screening of suspected COVID-19 cases.
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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.