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Wearable Dark-adaptometer in Normal Adult Healthy Volunteers

U

University of Liverpool

Status

Completed

Conditions

Photoreceptor Sensitivity Thresholds

Treatments

Device: Dark Adaptometer

Study type

Observational

Funder types

Other

Identifiers

NCT02674425
UoL001185

Details and patient eligibility

About

Conventional dark-adaptometers are unsuitable as a mass screening tool due to their high cost, lack of easy portability, need of trained staff and a totally dark room to be operated, arbitrary testing procedures, associated time waste in clinic and patient burden to mention a few. Consequently, dark adaptometers are not routinely used as clinical tools for retinal diagnosis and monitoring despite the inherent benefits over other visual electrophysiology equipment such as the ERG system, whose cost and features may often be surplus to optometrists' requirements.

This trial will assess the dark-adaptometry testing performance of a novel light-emitting system by generating full dark-adaptation threshold functions in normal adult healthy volunteers.

The novel system has been proposed to overcome the issues associated with current instrumentation; it is semi-automatic and easy to use without the need of any skilled operator.

It is envisaged that this system could spread the practice of dark-adaptometry testing and its adoption by high-street optometrists. This will allow diagnosing a number of retinal pathologies more quickly and more reliably that, faced with an ageing population, represents a major asset to the Health Community and the NHS.

This trial will involve 20 healthy volunteers, distributed in equal number in 2 groups of 18-40 and 50-70 years old, respectively. Proven the good health and eye condition of the participants, one of their eyes will be randomly-allocated and undergo dark-adaptometry testing 3 times on separate days within 3 weeks.

Testing will clarify whether by using the novel system it is possible to reproduce state-of-the-art threshold measurements as good or better than those produced by commercially-available dark-adaptometers. Threshold measurements in the elderly will be compared with literature data adjusted to exclude aged crystalline lens and pupillary miosis contributions. Data variability and system usability will be also assessed.

Full description

All details elsewhere in the documentation

Enrollment

20 patients

Sex

All

Ages

18 to 70 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • Refractive error: ≤ ±5 dioptres spherical (myopia/hyperopia) equivalent; ≤ 3 dioptres cylinder (astigmatism) equivalent.

Exclusion criteria

  • Subjects not in age range and/or unable to fully understand the informed consent and/or unable to comply with study procedures.
  • Self-reported history of depression, lack of sleep, psychiatric disorders, or neurological diseases such as Alzheimer's and Parkinson's disease.
  • Self-reported history of diabetes, stroke, or multiple sclerosis.
  • Self-reported hypovitaminosis A, alcoholism, liver or intestinal disease, malabsorption, protein calorie malnutrition, or sickle cell anaemia.
  • Use of psychoactive drugs (including lithium salts for mood stabilisation).
  • Use of dietary intake of ascorbic acid, vitamin A, B, E or other antioxidant supplements in the last two weeks.
  • Recurrent practice of activities that expose the retina to ultra-violet radiation such as sailing, fishing, sunbathing or tanning saloons.

Trial design

20 participants in 2 patient groups

Young adults (18-40)
Description:
Healthy adult volunteers, aged between 18 and 40, with no prior/current eye problems or family history of genetic eye diseases and good general health.
Treatment:
Device: Dark Adaptometer
Older adults (50-70)
Description:
Healthy adult volunteers, aged between 50 and 70, with no prior/current eye problems or family history of genetic eye diseases and good general health.
Treatment:
Device: Dark Adaptometer

Trial documents
2

Trial contacts and locations

1

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Central trial contact

Rachel Williams, Prof; Alessandro Giuliano, PhD

Data sourced from clinicaltrials.gov

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