Evidence map›Paper›PMID 41031415›Full record

ArticleAnnals of medicine2025

Tracking myopia development through axial length progression: a retrospective longitudinal study.

Zhengyang Tao, Jiao Wang, Zongyue Lv, Guorui Hu, Zhixing Xu, Lifei Chen, Hongwei Deng

Abstract read
In one paragraph

Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. The application of artificial intelligence in myopia prediction for children and adolescents: a review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
    Review
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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

7 authors.

Zhengyang TaoShenzhen Eye Hospital, Shenzhen Eye Medical Center, Southern Medical University, Shenzhen, China.
Jiao WangShenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China.
Zongyue LvShenzhen Eye Hospital, Shenzhen Eye Medical Center, Southern Medical University, Shenzhen, China.
Guorui HuShenzhen Eye Hospital, Shenzhen Eye Medical Center, Southern Medical University, Shenzhen, China.
Zhixing XuShenzhen Eye Hospital, Shenzhen Eye Medical Center, Southern Medical University, Shenzhen, China.
Lifei ChenShenzhen Eye Hospital, Shenzhen Eye Medical Center, Southern Medical University, Shenzhen, China.
Hongwei DengShenzhen Eye Hospital, Shenzhen Eye Medical Center, Southern Medical University, Shenzhen, China.ORCID 0000-0001-8453-8737

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrent prediction models for myopia progression remain limited in their ability to provide personalized risk assessments.

objectiveTo examine the predictive role of axial length (AL) progression in progressive myopia.

introductionThis retrospective cohort study analysed longitudinal ocular biometric data collected through repeated measurements in a school-based population. SUBJECTS: The study population comprised a longitudinal cohort of 1697 Chinese students aged 6-14 years, with ocular biometric data collected between December 2017 and May 2019 (18-month follow-up period).

methodThe dataset was randomly partitioned into development and validation cohorts at a 2:1 ratio, with two-thirds of the data allocated for nomogram model construction and the remaining one-third reserved for validation. The axial length-to-corneal radius (AL/CR) ratio was defined as the AL divided by the mean CR value measured in 90° meridians and 180° meridians: AL/CR = 2AL/(CR

resultsThe baseline subjects (

conclusionsThis study develops a personalized prediction model for progressive myopia, grounded on factors of the first visit AL progression and baseline AL/CR. The model offers a dynamic and reliable foundation for selecting effective myopia control measures in future stages.

Indexed as

Axial Length, EyeMyopiaMyopia, DegenerativeAdolescentBiometryChildChinaDisease ProgressionFemaleHumansLongitudinal StudiesMaleNomogramsRetrospective Studiesaxial lengthlongitudinal studynomogramProgressive myopia

Identifiers

PMID41031415
PMCPMC12490353

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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.