Evidence map›Paper›PMID 34338647›Full record

ArticleJMIR medical informatics2021

Usage Patterns of Web-Based Stroke Calculators in Clinical Decision Support: Retrospective Analysis.

Benjamin Kummer, Lubaina Shakir, Rachel Kwon, Joseph Habboushe, Nathalie Jetté

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 36% 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.

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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
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  3. Review
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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 4 institutions in 1 country.

Benjamin KummerDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-1413-8014
Lubaina ShakirMD Aware LLC, New York, NY, United States.ORCID https://orcid.org/0000-0002-0306-1664
Rachel KwonRo, New York, NY, United States.ORCID https://orcid.org/0000-0002-4752-0674
Joseph HabbousheMD Aware LLC, New York, NY, United States.ORCID https://orcid.org/0000-0002-9653-4140
Nathalie JettéDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0003-1351-5866
Aware (United States) · USCornell University · USIcahn School of Medicine at Mount Sinai · USMount Sinai Health System · US

Funding

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) Public Engagement CoreU54NS100064 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOGA, ARTHUR W · 2017 to 2021
$21.7M
Mount Sinai Network of Excellence in Neuroscience Clinical TrialsU24NS107201 · NINDS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI JETTE, NATHALIE, MILLER, AARON · 2018 to 2022
$1.7M
NINDS NIH HHS U24 NS107201NINDS NIH HHS U54 NS100064
6 · The paper itself

Abstract

backgroundClinical scores are frequently used in the diagnosis and management of stroke. While medical calculators are increasingly important support tools for clinical decisions, the uptake and use of common medical calculators for stroke remain poorly characterized.

objectiveWe aimed to describe use patterns in frequently used stroke-related medical calculators for clinical decisions from a web-based support system.

methodsWe conducted a retrospective study of calculators from MDCalc, a web-based and mobile app-based medical calculator platform based in the United States. We analyzed metadata tags from MDCalc's calculator use data to identify all calculators related to stroke. Using relative page views as a measure of calculator use, we determined the 5 most frequently used stroke-related calculators between January 2016 and December 2018. For all 5 calculators, we determined cumulative and quarterly use, mode of access (eg, app or web browser), and both US and international distributions of use. We compared cumulative use in the 2016-2018 period with use from January 2011 to December 2015.

resultsOver the study period, we identified 454 MDCalc calculators, of which 48 (10.6%) were related to stroke. Of these, the 5 most frequently used calculators were the CHA

conclusionsThe most frequently used stroke calculators were the CHA

Indexed as

cerebrovascular diseaseclinical healthclinical informaticsdigital healtheconomic healthelectronic health recordshealth informationhealth information technologyinformation technologymedical calculatorsmedical informaticsmhealth

Identifiers

PMID34338647
PMCPMC8369374
OpenAlexW3172292263

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.