Evidence map›Paper›PMID 42170423›Full record

ArticleAmerican journal of translational research2026

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

Sha Li, Danli Yang, Gaili Chen, Juanling Sun

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Article in American journal of translational research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Sha LiDepartment of Ophthalmology, Xi'an People's Hospital (Xi'an Fourth Hospital) No. 21, Jiefang Road, Xincheng District, Xi'an 710004, Shaanxi, China.
Danli YangDepartment of Ophthalmology, Xi'an People's Hospital (Xi'an Fourth Hospital) No. 21, Jiefang Road, Xincheng District, Xi'an 710004, Shaanxi, China.
Gaili ChenDepartment of Ophthalmology, Xi'an People's Hospital (Xi'an Fourth Hospital) No. 21, Jiefang Road, Xincheng District, Xi'an 710004, Shaanxi, China.
Juanling SunDepartment of Ophthalmology, Xi'an People's Hospital (Xi'an Fourth Hospital) No. 21, Jiefang Road, Xincheng District, Xi'an 710004, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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

methodsA 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.

resultsPostoperative 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.

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

Indexed as

cataractDiabetes mellitusnomogramnursing interventionpostoperative dry eyerisk factorsrisk stratification

Identifiers

PMID42170423
PMCPMC13186756

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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.