Contact lens & anterior eye : the journal of the British Contact Lens Association · 2025
Predicting contact lens discomfort from meibomian gland morphology and function.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Iqbal Fatima, Papas Eric B, Stapleton Fiona, Alghamdi Waleed M, Ruan Amy, Darvesh Karuna, Nguyen Lucy, Tan Jacqueline
Аннотация
PURPOSE: To develop and validate a model to predict contact lens discomfort (CLD) using features of the meibomian glands (MG).
METHODS: This study consisted of three parts: (i) 50 meibography images from contact lens wearers and non-wearers were assessed to distinguish features of interest between the groups to develop an automated algorithm which was tested on 154 images from CLD participants (ii) A multivariable model was constructed with a separate population of 84 lens wearers using imaging features and ocular surface signs to predict Contact Lens Dry Eye Questionnaire-8 (CLDEQ-8) score (iii) The model was validated on two independent sets of images using Bland-Altman comparisons between actual and predicted CLDEQ-8 scores.
RESULTS: Part I: Intergland distance and width of the gland at the lid margin, centre and distal end were identified as features distinguishing between lens wearers and non-wearers. Part II: In univariate analysis, CLDEQ-8 scores were negatively associated with gland width at the lid margin (r = -0.52, p = 0.01) and lipid layer thickness (r = -0.40, p < 0.05) and positively associated with tear break-up time (r = 0.51, p < 0.001), MG expressibility (r = 0.35, p = 0.01), and intergland distance at the lid margin (r = 0.73, p = 0.02). The multivariable regression model accounted for 68 % (R2 = 0.68, p < 0.05) of the variance in CLDEQ-8 scores. Part III: The mean difference (bias) between the predicted and actual CLDEQ-8 score was -0.1 with limits of agreement of ± 2.8 units.
CONCLUSION: Morphometric features of MG can predict CLDEQ-8 score in lens wearers with reasonable accuracy. This approach may be a suitable screening tool in early detection and to understand the natural history of CLD.
METHODS: This study consisted of three parts: (i) 50 meibography images from contact lens wearers and non-wearers were assessed to distinguish features of interest between the groups to develop an automated algorithm which was tested on 154 images from CLD participants (ii) A multivariable model was constructed with a separate population of 84 lens wearers using imaging features and ocular surface signs to predict Contact Lens Dry Eye Questionnaire-8 (CLDEQ-8) score (iii) The model was validated on two independent sets of images using Bland-Altman comparisons between actual and predicted CLDEQ-8 scores.
RESULTS: Part I: Intergland distance and width of the gland at the lid margin, centre and distal end were identified as features distinguishing between lens wearers and non-wearers. Part II: In univariate analysis, CLDEQ-8 scores were negatively associated with gland width at the lid margin (r = -0.52, p = 0.01) and lipid layer thickness (r = -0.40, p < 0.05) and positively associated with tear break-up time (r = 0.51, p < 0.001), MG expressibility (r = 0.35, p = 0.01), and intergland distance at the lid margin (r = 0.73, p = 0.02). The multivariable regression model accounted for 68 % (R2 = 0.68, p < 0.05) of the variance in CLDEQ-8 scores. Part III: The mean difference (bias) between the predicted and actual CLDEQ-8 score was -0.1 with limits of agreement of ± 2.8 units.
CONCLUSION: Morphometric features of MG can predict CLDEQ-8 score in lens wearers with reasonable accuracy. This approach may be a suitable screening tool in early detection and to understand the natural history of CLD.