Evidence map›Paper›PMID 39422918›Full record

ArticleInvestigative ophthalmology & visual science2024

Multicenter Normative Data for Mesopic Microperimetry.

Maximilian Pfau, Jasleen K Jolly, Jason Charng, Leon von der Emde, Philipp L Müller, Georg Ansari, Kristina Pfau, Fred K Chen, Zhichao Wu

Abstract readMulticenter Study
In one paragraph

Article in Investigative ophthalmology & visual science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Article
  5. Development of a conceptual, HOV-inspired spatial weighting model for quantifying geographic atrophy severity.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. An Analysis of Scotopic Microperimetry in Healthy Adults.Translational vision science & technology · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Multicenter Normative Data for Mesopic Microperimetry.Investigative ophthalmology & visual science · 2024
    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

9 authors.

Maximilian PfauDepartment of Ophthalmology, University Hospital Basel, Basel, Switzerland.
Jasleen K JollyNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Jason CharngCentre of Ophthalmology and Visual Science (incorporating Lions Eye Institute), University of Western Australia, Perth, Australia.
Leon von der EmdeDepartment of Ophthalmology, University of Bonn, Bonn, Germany.
Philipp L MüllerDepartment of Ophthalmology, University of Bonn, Bonn, Germany.
Georg AnsariDepartment of Ophthalmology, University Hospital Basel, Basel, Switzerland.
Kristina PfauDepartment of Ophthalmology, University Hospital Basel, Basel, Switzerland.
Fred K ChenCentre of Ophthalmology and Visual Science (incorporating Lions Eye Institute), University of Western Australia, Perth, Australia.
Zhichao WuCentre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The purpose of this study was to provide a large, multi-center normative dataset for the Macular Integrity Assessment (MAIA) microperimeter and compare the goodness-of-fit and prediction interval calibration-error for a panel of hill-of-vision models. Methods: Microperimetry examinations of healthy eyes from five independent study groups and one previously available dataset were included (1137 tests from 531 eyes of 432 participants [223 women and 209 men]). Linear mixed models (LMMs) were fitted to the data to obtain interpretable hill-of-vision models. A panel of regression models to predict normative data was compared using cross-validation with site-wise splits. The mean absolute error (MAE) and miscalibration area (area between the calibration curve and the ideal diagonal) were evaluated as the performance measures. Results: Based on the parameters "participant age," "eccentricity from the fovea," "overlap with the central fixation target," and "eccentricity along the four principal meridians," a Bayesian mixed model had the lowest MAE (2.13 decibel [dB]; 95% confidence interval [CI] = 1.9-2.36 dB) and miscalibration area (0.13; 95% CI = 0.07-0.19). However, a parsimonious linear model provided a comparable MAE (2.17 dB; 95% CI = 1.93-2.4 dB) and a similar miscalibration area (0.14; 95% CI = 0.08-0.2). Conclusions: Normal variations in visual sensitivity on mesopic microperimetry can be effectively explained by a linear model that includes age and eccentricity. The dataset and a code vignette are provided for estimating normative values across a large range of retinal locations, applicable to customized testing patterns.

Indexed as

Visual FieldsVisual Field TestsAdolescentAdultAgedAged, 80 and overFemaleHealthy VolunteersHumansMaleMesopic VisionMiddle AgedReference ValuesYoung Adult

Identifiers

PMID39422918
PMCPMC11512566

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.