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<p>This study conducted a single-center cross-sectional analysis of 120 patients undergoing corneal transplantation to explore preoperative visual function expectations and contributing factors. Utilizing self-designed questionnaires and validated scales, significant item score variations were observed, highlighting higher expectations for independent daily activities and near-vision tasks. Multivariate analysis identified educational level, ophthalmic history, and neuroticism as independent influencers. A binary logistic regression model exhibited strong discrimination (AUC 0.858) and good calibration, validated through internal methods. Decision curve analysis favored the model, and ROC analysis pinpointed 0.293 as the optimal threshold for identifying high expectations. In the outpatient setting, thresholds of 0.20–0.30 are recommended for screening and trigger purposes, while 0.40 is suggested for referrals and resource allocation. Overall, patients displayed varied preoperative expectations, with educational level, prior ophthalmic history, and neuroticism notably impacting these expectations. The predictive model, in conjunction with decision curve and ROC-based optimization, provides actionable thresholds for enhancing preoperative communication and management. Multicenter validation and longitudinal studies are advised for further model refinement and evaluating long-term outcomes.</p>

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Factors influencing high expectations in patients undergoing corneal transplantation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月14日

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  • Ayixianmuguli Wufuer,
  • Xiaodi Liu,
  • Jiamei Ma,
  • Suling Tan,
  • Qi Zhou

摘要

This study conducted a single-center cross-sectional analysis of 120 patients undergoing corneal transplantation to explore preoperative visual function expectations and contributing factors. Utilizing self-designed questionnaires and validated scales, significant item score variations were observed, highlighting higher expectations for independent daily activities and near-vision tasks. Multivariate analysis identified educational level, ophthalmic history, and neuroticism as independent influencers. A binary logistic regression model exhibited strong discrimination (AUC 0.858) and good calibration, validated through internal methods. Decision curve analysis favored the model, and ROC analysis pinpointed 0.293 as the optimal threshold for identifying high expectations. In the outpatient setting, thresholds of 0.20–0.30 are recommended for screening and trigger purposes, while 0.40 is suggested for referrals and resource allocation. Overall, patients displayed varied preoperative expectations, with educational level, prior ophthalmic history, and neuroticism notably impacting these expectations. The predictive model, in conjunction with decision curve and ROC-based optimization, provides actionable thresholds for enhancing preoperative communication and management. Multicenter validation and longitudinal studies are advised for further model refinement and evaluating long-term outcomes.