Evidence map›Paper›PMID 32366013›Full record

ArticleSensors (Basel, Switzerland)2020

Smart Electronic Eyedrop Bottle for Unobtrusive Monitoring of Glaucoma Medication Adherence.

Marcelo Aguilar-Rivera, Dieanira T Erudaitius, Vincent M Wu, Justin C Tantiongloc, Dae Y Kang, Todd P Coleman, Sally L Baxter, Robert N Weinreb

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
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  8. Review
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

8 authors.

Marcelo Aguilar-RiveraDepartment of Bioengineering, University of California San Diego, La Jolla, San Diego, CA 92093, USA.
Dieanira T ErudaitiusDepartment of Bioengineering, University of California San Diego, La Jolla, San Diego, CA 92093, USA.
Vincent M WuDepartment of Bioengineering, University of California San Diego, La Jolla, San Diego, CA 92093, USA.
Justin C TantionglocDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, San Diego, CA 92093, USA.
Dae Y KangDepartment of Bioengineering, University of California San Diego, La Jolla, San Diego, CA 92093, USA.
Todd P ColemanDepartment of Bioengineering, University of California San Diego, La Jolla, San Diego, CA 92093, USA.
Sally L BaxterHamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, San Diego, CA 92093, USA.ORCID 0000-0002-5271-7690
Robert N WeinrebDepartment of Bioengineering, University of California San Diego, La Jolla, San Diego, CA 92093, USA.

Funding

San Diego Biomedical Informatics Education & Research (SABER)T15LM011271 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SHAMIM NEMATI · 2012 to 2026
$9.7M
NIH HHS R41EY028488NIH HHS T15LM011271NLM NIH HHS T15 LM011271
6 · The paper itself

Abstract

Glaucoma, the leading cause of irreversible blindness, affects >70 million people worldwide. Lowering intraocular pressure via topical administration of eye drops is the most common first-line therapy for glaucoma. This treatment paradigm has notoriously high non-adherence rates: ranging from 30% to 80%. The advent of smart phone enabled technologies creates promise for improving eyedrop adherence. However, previous eyedrop electronic monitoring solutions had awkward medication bottle adjuncts and crude software for monitoring the administration of a drop that adversely affected their ability to foster sustainable improvements in adherence. The current work begins to address this unmet need for wireless technology by creating a "smart drop" bottle. This medication bottle is instrumented with sensing electronics that enable detection of each eyedrop administered while maintaining the shape and size of the bottle. This is achieved by a thin electronic force sensor wrapped around the bottle and underneath the label, interfaced with a thin electronic circuit underneath the bottle that allows for detection and wireless transmission to a smart-phone application. We demonstrate 100% success rate of wireless communication over 75 feet with <1% false positive and false negative rates of single drop deliveries, thus providing a viable solution for eyedrop monitoring for glaucoma patients.

Indexed as

GlaucomaMedication AdherenceElectronicsHumansIntraocular PressureOphthalmic SolutionsOphthalmic Solutionsadherencealertsclinical decision supportGlaucomainternet of thingsmonitoringsensors

Identifiers

PMID32366013
PMCPMC7248824

What OpenQuestion holds

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Registered trials

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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.