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Prediction of vulnerability to mental health symptoms in children with congenital ectopia lentis: development and validation of a prediction model

Eye volume 39, pages 2438–2443 (2025)Cite this article

Subjects

Abstract

Objective

To evaluate mental health among children with congenital ectopia lentis (CEL) and to develop an effective nomogram for predicting risk of mental health symptoms in CEL.

Methods

In total, 48 children with CEL and 50 control subjects aged 7–18 years old were enrolled in this study. Participants were required to complete the Children’s Depression Inventory (CDI) and the Screen for Child Anxiety Related Emotional Disorders (SCARED) questionnaire to screen depressive and anxiety symptoms. Three potential predictors were tested and chosen to build a prediction model using logistic regression.

Results

Compared with normal controls, CDI and SCARED scores were higher among children with CEL (P < 0.05). 35.4% of CEL children had varying degrees of depressive or anxiety symptoms. Child’s age (odds ratio [OR] = 1.815, 95% confidence interval [CI], 1.084-3.039), duration of disease (OR = 1.557, 95% CI, 1.009–2.403), and systemic abnormalities (OR = 19.894, 95% CI, 1.660–238.463) were identified as predictors of anxiety symptoms. The combination of the above predictors shows good predictive ability, as indicated by area under the curve of 0.924 (95% CI, 0.845–1.000). The calibration curves showed good agreement between the prediction of the nomogram and the actual observations. Additionally, decision curve analysis showed that the nomogram was clinically useful and had better discriminatory power in identifying patients with significant anxiety symptoms.

Conclusions

Children with CEL experience higher level of depressive and anxiety symptoms. Child’s age, duration of disease and systemic abnormalities are associated factors and can serve as useful indexes in predicting mental illness among CEL children.

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Fig. 1: Nomogram for probability of anxiety symptoms using demographic and clinical factors.
Fig. 2: The calibration plot that compares the predicted and actual identification probabilities.
Fig. 3

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Data availability

Data are available upon reasonable request. Requests can be submitted to the corresponding author.

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Acknowledgements

We thank the participation of all children in the cohorts and their families.

Funding

This study was supported by the National Natural Science Foundation of China (81873673, 81900841), and Guangdong Basic and Applied Basic Research Foundation (2021A1515011673; 2022A1515011181).

Author information

Author notes

  1. These authors contributed equally: Xiaolin Liang, Xinyu Zhang.

Authors and Affiliations

  1. State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China

    Xiaolin Liang, Xinyu Zhang, Siyuan Liu, Ling Jin, Yiyuan Ma, Ming Zhou, Danying Zheng & Guangming Jin

  2. Jiangmen Central Hospital, Jiangmen, Guangdong, China

    Xiaolin Liang

  3. Albany Medical College, 49 New Scotland Ave Albany, New York, NY, USA

    Charlotte Aimee Young

Authors
  1. Xiaolin Liang
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  4. Ling Jin
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Contributions

XL, XZ, DZ and GJ contributed to the study conception and study design. Data collection, analysis and interpretation were undertaken by XL, SY, LJ, YM and MZ. The first draft of the manuscript was written by XL and CAY. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. DZ and GJ act as guarantors for this manuscript.

Corresponding authors

Correspondence to Danying Zheng or Guangming Jin.

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Competing interests

The authors declare no competing interests.

Ethics approval

This study was conducted in accordance with the principles of the Declaration of Helsinki and approved by the Institutional Review Board of Zhongshan Ophthalmic Center (2022KYPJ207). Informed consent was obtained from one of parents or legal guardians of the children before enrolling.

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Liang, X., Zhang, X., Liu, S. et al. Prediction of vulnerability to mental health symptoms in children with congenital ectopia lentis: development and validation of a prediction model. Eye 39, 2438–2443 (2025). https://doi.org/10.1038/s41433-025-03877-0

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