Dataset Information

Predictors of laboratory-positive COVID-19 in children and teenagers.

ABSTRACT:

Objective

The aim of the study was to identify factors predicting laboratory-positive coronavirus disease 2019 (COVID-19) in pediatric patients with acute respiratory symptoms.

Study design

We conducted a cross-sectional analysis of a prospective cohort study.

Methods

Data from 1849 individuals were analyzed. COVID-19 was confirmed (reverse transcription-quantitative polymerase chain reaction) in 15.9% of patients, and factors predicting a positive test result were evaluated through prevalence odds ratios and 95% confidence intervals.

Results

Increasing age, personal history of obesity, and household contact with a case were found to be associated, in the multiple regression model, with increased odds of a positive test result. Young patients residing in areas with higher population sizes, as well as those with severe respiratory symptoms, were less likely to be laboratory confirmed.

Conclusions

Early identification and isolation of children and teenagers with suggestive symptoms of COVID-19 is important to limit viral spread. We identified several factors predicting the laboratory test result. Our findings are relevant from a public health policy perspective, particularly after the restart of in-person academic activities.

SUBMITTER: Murillo-Zamora E

PROVIDER: S-EPMC7584439 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Predictors of laboratory-positive COVID-19 in children and teenagers.

Murillo-Zamora E E Aguilar-Sollano F F Delgado-Enciso I I Hernandez-Suarez C M CM

Public health 20201023

<h4>Objective</h4>The aim of the study was to identify factors predicting laboratory-positive coronavirus disease 2019 (COVID-19) in pediatric patients with acute respiratory symptoms.<h4>Study design</h4>We conducted a cross-sectional analysis of a prospective cohort study.<h4>Methods</h4>Data from 1849 individuals were analyzed. COVID-19 was confirmed (reverse transcription-quantitative polymerase chain reaction) in 15.9% of patients, and factors predicting a positive test result were evaluate ...[more]

PMID: 33246302

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Project description:ObjectivesThe purpose of the present study was to assess and describe the severity of symptoms reported by Covid-19 positive patients who vaped (smoked e-cigarettes) when compared to those who did not vape or smoke at the time of the diagnosis of Covid-19.MethodsPatients from this study are from a well-characterized patient cohort collected at Mayo Clinic between March 1, 2020 and February 28, 2021; with confirmed COVID-19 diagnosis defined as a positive result on reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assays from nasopharyngeal swab specimens. Among the 1734 eligible patients, 289 patients reported current vaping. The cohort of vapers (N = 289) was age and gender matched to 1445 covid-19 positive patients who did not vape. The data analyzed included: date of birth, gender, ethnicity, race, marital status, as well as lifestyle history such as vaping and smoking and reported covid-19 symptoms experienced.ResultsA logistic regression analysis was performed separately for each symptom using generalized estimating equations (GEE) with robust variance estimates in order to account for the 1:5 age, sex, and race matched set study design. Patients who vaped and developed Covid-19 infection were more likely to have chest pain or tightness (16% vs 10%, vapers vs non vapers, P = .005), chills (25% vs 19%, vapers vs non vapers, P = .0016), myalgia (39% vs 32%, vapers vs non vapers, P = .004), headaches (49% vs 41% vapers vs non vapers, P = .026), anosmia/dysgeusia (37% vs 30%, vapers vs non vapers, P = .009), nausea/vomiting/abdominal pain (16% vs 10%, vapers vs non vapers, P = .003), diarrhea (16% vs 10%, vapers vs non vapers, P = .004), and non-severe light-headedness (16% vs 9%, vapers vs non vapers, P < .001).ConclusionVapers experience higher frequency of covid-19 related symptoms when compared with age and gender matched non-vapers. Further work should examine the impact vaping has on post-covid symptom experience.

Dataset Information

Predictors of laboratory-positive COVID-19 in children and teenagers.

Objective

Study design

Methods

Results

Conclusions

Publications

Predictors of laboratory-positive COVID-19 in children and teenagers.

Similar Datasets

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