Evidence map›Paper›PMID 38412008›Full record

ArticleJMIR diabetes2024

COVID-19 Vaccination Reactions and Risk of Breakthrough Infections Among People With Diabetes: Cohort Study Derived From Community Reporters.

Nancy A Dreyer, Kendall B Knuth, Yiqiong Xie, Matthew W Reynolds, Christina D Mack

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JMIR diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04368065 (Registry to Study Factors That May Impact COVID-19 Occurrence and Severity), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 44% of its field
1 · What the graph read from it

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.

2 · The registry

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.

NCT04368065 completednot on this map

Registry to Study Factors That May Impact COVID-19 Occurrence and Severity

Typeobservational_patient_registrySponsorIQVIA Pty LtdRan2020 to 2023Enrolled35,278ConditionsCOVID-19
3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Nancy A DreyerDreyer Strategies LLC, Newton, MA, United States.ORCID https://orcid.org/0000-0003-0153-8286
Kendall B KnuthReal World Solutions, IQVIA, Durham, NC, United States.ORCID https://orcid.org/0000-0003-1803-6311
Yiqiong XieReal World Solutions, IQVIA, Durham, NC, United States.ORCID https://orcid.org/0000-0003-1130-1215
Matthew W ReynoldsFlatiron, New York, NY, United States.ORCID https://orcid.org/0000-0002-7049-7599
Christina D MackReal World Solutions, IQVIA, Durham, NC, United States.ORCID https://orcid.org/0000-0002-3495-3796
IQVIA (United States) · USFlatiron Health (United States) · USSciTech Strategies (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis exploratory study compares self-reported COVID-19 vaccine side effects and breakthrough infections in people who described themselves as having diabetes with those who did not identify as having diabetes.

objectiveThe study uses person-reported data to evaluate differences in the perception of COVID-19 vaccine side effects between adults with diabetes and those who did not report having diabetes.

methodsThis is a retrospective cohort study conducted using data provided online by adults aged 18 years and older residing in the United States. The participants who voluntarily self-enrolled between March 19, 2021, and July 16, 2022, in the IQVIA COVID-19 Active Research Experience project reported clinical and demographic information, COVID-19 vaccination, whether they had experienced any side effects, test-confirmed infections, and consented to linkage with prescription claims. No distinction was made for this study to differentiate prediabetes or type 1 and type 2 diabetes nor to verify reports of positive COVID-19 tests. Person-reported medication use was validated using pharmacy claims and a subset of the linked data was used for a sensitivity analysis of medication effects. Multivariate logistic regression was used to estimate the adjusted odds ratios of vaccine side effects or breakthrough infections by diabetic status, adjusting for age, gender, education, race, ethnicity (Hispanic or Latino), BMI, smoker, receipt of an influenza vaccine, vaccine manufacturer, and all medical conditions. Evaluations of diabetes medication-specific vaccine side effects are illustrated graphically to support the examination of the magnitude of side effect differences for various medications and combinations of medications used to manage diabetes.

resultsPeople with diabetes (n=724) reported experiencing fewer side effects within 2 weeks of vaccination for COVID-19 than those without diabetes (n=6417; mean 2.7, SD 2.0 vs mean 3.1, SD 2.0). The adjusted risk of having a specific side effect or any side effect was lower among those with diabetes, with significant reductions in fatigue and headache but no differences in breakthrough infections over participants' maximum follow-up time. Diabetes medication use did not consistently affect the risk of specific side effects, either using self-reported medication use or using only diabetes medications that were confirmed by pharmacy health insurance claims for people who also reported having diabetes.

conclusionsPeople with diabetes reported fewer vaccine side effects than participants not reporting having diabetes, with a similar risk of breakthrough infection.

trial registrationClinicalTrials.gov NCT04368065; https://clinicaltrials.gov/study/NCT04368065.

Indexed as

clinical datacommunity healthCOVID-19diabetesfatigueheadacheinfectionmedicationnondiabetic adultpatient datapatient-reported outcomesperson-generated health dataregistryriskside effectsvaccinationvaccinevaccine hesitancy

Identifiers

PMID38412008
PMCPMC10933718
OpenAlexW4390353679

What OpenQuestion holds

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LicenceCC BY
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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.