Evidence map›Paper›PMID 38894385›Full record

ArticleSensors (Basel, Switzerland)2024

Feasibility of Observing Cerebrovascular Disease Phenotypes with Smartphone Monitoring: Study Design Considerations for Real-World Studies.

Stephanie J Zawada, Ali Ganjizadeh, Clint E Hagen, Bart M Demaerschalk, Bradley J Erickson

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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.

Stephanie J ZawadaMayo Clinic College of Medicine and Science, 5777 E. Mayo Boulevard, Scottsdale, AZ 85054, USA.ORCID 0000-0002-2022-4189
Ali GanjizadehMayo Clinic AI Laboratory, 200 1st Street SW, Rochester, MN 55902, USA.ORCID 0000-0001-6968-092X
Clint E HagenMayo Clinic Division of Biomedical Statistics and Informatics, 200 1st Street SW, Rochester, MN 55902, USA.
Bart M DemaerschalkMayo Clinic Center for Digital Health, 5777 E. Mayo Boulevard, Scottsdale, AZ 85054, USA.
Bradley J EricksonMayo Clinic AI Laboratory, 200 1st Street SW, Rochester, MN 55902, USA.ORCID 0000-0001-7926-6095

Funding

Center for Clinical and Translational Science, Mayo Clinic Predoctoral FellowshipPhRMA Foundation Predoctoral Fellowship
6 · The paper itself

Abstract

Accelerated by the adoption of remote monitoring during the COVID-19 pandemic, interest in using digitally captured behavioral data to predict patient outcomes has grown; however, it is unclear how feasible digital phenotyping studies may be in patients with recent ischemic stroke or transient ischemic attack. In this perspective, we present participant feedback and relevant smartphone data metrics suggesting that digital phenotyping of post-stroke depression is feasible. Additionally, we proffer thoughtful considerations for designing feasible real-world study protocols tracking cerebrovascular dysfunction with smartphone sensors.

Indexed as

Cerebrovascular DisordersCOVID-19PhenotypeSmartphoneFeasibility StudiesHumansMaleMonitoring, PhysiologicPandemicsSARS-CoV-2cerebrovascular diseasehealth outcomespost-stroke depressionreal-world dataremote patient monitoringsmartphone sensors

Identifiers

PMID38894385
PMCPMC11175199

What OpenQuestion holds

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LicenceCC BY
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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.