Evidence map›Paper›PMID 39080113›Full record

ArticleArchives of osteoporosis2024

Factors associated with non-adherence to dual-energy x-ray absorptiometry screening during the COVID-19 pandemic in an academic medical center.

Qiming Shi, Jonathan T Cheah, Adrian H Zai

Erratum issuedAbstract read
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In one paragraph

Article in Archives of osteoporosis, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Qiming ShiCenter for Clinical and Translational Science, UMass Chan Medical School, 55 N Lake Ave, Worcester, MA, 01605, USA. Qiming.shi@umassmed.edu.
Jonathan T CheahDepartment of Medicine, UMass Chan Medical School, Worcester, MA, USA.
Adrian H ZaiCenter for Clinical and Translational Science, UMass Chan Medical School, 55 N Lake Ave, Worcester, MA, 01605, USA.

Funding

University of Massachusetts Center for Clinical Science and Translational SupplementUL1TR001453 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI LUZURIAGA, KATHERINE F · 2015 to 2024
$39.0M
NCATS NIH HHS UL1-TR001453
6 · The paper itself

Abstract

This study explored why some elderly females do not adhere to their bone density tests. It found that factors like age, race, marital status, insurance type, social vulnerability index, and vaccination status influence completion of these tests. Addressing these differences could improve the management of bone health in older adults. PURPOSE: This study investigated factors influencing the cancellation of dual-energy x-ray absorptiometry (DXA) scans among females aged 65 and above during the COVID-19 pandemic.

methodsUtilizing a dataset of 19,066 females from 2021 to 2023, the research employed chi-squared tests and logistic regression analyses to examine demographic, socio-economic, and health-related determinants of DXA scan adherence.

resultsKey findings revealed that younger seniors, White patients, married individuals, those with commercial/private or Medicare insurance, and vaccinated persons were more likely to complete DXA scans. In contrast, Asian and African American females, along with those from higher Social Vulnerability Index areas, showed lower completion rates.

conclusionThese results highlight the need for tailored strategies to improve osteoporosis screening adherence, focusing on identified demographic groups to enhance overall healthcare outcomes in osteoporosis management.

Indexed as

Absorptiometry, PhotonCOVID-19OsteoporosisAcademic Medical CentersAgedAged, 80 and overBone DensityFemaleHumansMass ScreeningPatient ComplianceSARS-CoV-2AdherenceDXA scanNo showOsteoporosis

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.