Nomogram-based risk stratification for postoperative dry eye in diabetic cataract patients and its application in tiered nursing care.

OBJECTIVE

To identify risk factors for postoperative dry eye in diabetic cataract patients, develop a nomogram prediction model, and establish a tiered nursing intervention protocol.

METHODS

A retrospective cohort study was conducted involving 678 diabetic patients who underwent phacoemulsification with intraocular lens implantation between January 2024 and January 2025. Patients were divided into a dry eye group (n=132) and a non-dry eye group (n=546). Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to identify independent risk factors. A nomogram was constructed, and patients were stratified into low-, moderate-, and high-risk groups based on tertile cutoffs. Model performance was validated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis.

RESULTS

Postoperative dry eye occurred in 19.5% (132/678) of patients. Independent risk factors included: preoperative tear break-up time (odds ratio [OR]=0.715), Schirmer test value (OR=0.868), age ≥65 years (OR=1.975), diabetes duration ≥10 years (OR=8.511), glycated hemoglobin (HbA1c) ≥7% (OR=1.907), diabetic retinopathy (OR=0.090), glaucoma (OR=2.530), corneal comorbidities (OR=4.074), operative time ≥20 minutes (OR=2.327), and preservative-free artificial tear use (OR=0.407). The model demonstrated good discrimination (area under the curve [AUC]=0.877), calibration (Brier score = 0.1035), and clinical utility.

CONCLUSION

The nomogram effectively identifies high-risk patients. Risk stratification combined with tiered nursing enables rational resource allocation and targeted intervention for diabetic cataract patients.