ArticleEye and vision (London, England)2026
Prediction of axial elongation in adults with high myopia: the Wenzhou High Myopia Cohort Study.
Article in Eye and vision (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
backgroundIdentifying individuals at high risk of axial elongation is crucial for managing adults with high myopia, as further elongation substantially increases the risk of vision-threatening complications. This study aimed to identify the optimal predictors for axial elongation in this population.
methodsThis prospective cohort study enrolled 1025 eyes from 532 adults with high myopia (18-60 years). We evaluated the predictive performance of nine candidate variables for rapid axial elongation, defined as a 2-year axial elongation of at least 0.10 mm. Predictors were selected using bidirectional stepwise regression. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC), and the incremental value of the new model was quantified using integrated discrimination improvement (IDI).
resultsThe mean annual axial elongation rate was 0.020 ± 0.051 mm/year, and 24.78% of eyes developed rapid axial elongation. Stepwise regression constructed a full model (AUC = 0.811) including six predictors-age, sex, axial length, best-corrected visual acuity, choroidal thickness (ChT), and vascularity index. ChT showed the highest individual discriminative ability (AUC = 0.728), followed by age (AUC = 0.666). Removing age or ChT from the full model reduced the AUCs to 0.735 and 0.753, respectively (both P < 0.001), with IDIs of - 0.116 and - 0.095 (both P < 0.001). In contrast, excluding sex only resulted in an IDI of - 0.008 (P = 0.032). Simplified models combining age and ChT, with or without sex, showed discrimination comparable to that of the full model, with only modest reductions in predictive performance (IDIs: - 0.028 and - 0.033, respectively; both P < 0.05). In the bivariate model, the predictive cut-off of ChT decreased progressively with age, ranging from 187 µm at age 20 to 29 µm at age 60. The results remained consistent in sensitivity analyses using alternative axial elongation definitions (0.05 mm and 0.15 mm). Nonlinear relationship analyses revealed that thinner choroids were associated with faster axial elongation rate only below an inflection point.
conclusionsChT and age are the optimal predictors for axial elongation in adults with high myopia. These findings establish their dominant role in personalized management and support further investigation into choroidal architecture to guide proactive, choroid-centered strategies.
trial registrationThis study was registered with the Chinese Clinical Trial Registry (ChiCTR2100047424).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.