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Test-retest reliability and short-term variability of quantitative light reflex pupillometry in a mixed memory clinic
Mathias Holsey Gramkow1, Frederikke Kragh Clemmensen1, Gunhild Waldemar2
1Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
Background:
Quantitative light reflex pupillometry (qLRP) may be a promising digital biomarker in neurodegenerative diseases such as Alzheimer's disease (AD), as neuropathological changes have been found in the midbrain structures governing the light reflex. Studies investigating test-retest reliability and short-term, intra-subject variability of qLRP in these patient groups are missing. Our objective was therefore to investigate the test-retest reliability and short-term, intra-subject variability of qLRP in a memory clinic setting, where patients with neurodegenerative disease are frequently evaluated.
Methods:
Test-retest reliability study. We recruited patients from a tertiary memory clinic and qLRP was carried out at a baseline visit and then repeated on day 3-14 and on day 21-35 using a hand-held pupillometer. We evaluated the test-retest reliability of qLRP by calculating intraclass correlation coefficients (ICCs) and intra-subject, short-term variability by fitting linear mixed models. We compared ICCs for subgroups based on age, sex, disease severity (MCI vs. mild dementia), AD diagnosis, and amount of neurodegeneration (cerebrospinal fluid-total tau levels).
Results:
In total, 40 patients (mean age 72 years, 15 female, 22 with mild dementia) were included in the study. We found good-excellent reliability (ICC range 0.86-0.93) for most qLRP parameters. qLRP parameters exhibited limited intra-subject variability and we found no large sources of variability when examining subgroups.
Conclusion:
qLRP was found to have acceptable test-retest reliability and the study results pave the way for research using longitudinal or cross-sectional measurements to assess the construct in identifying and prognosticating neurodegenerative diseases.

