PURPOSE: To develop a model for establishing indications for cataract surgery that incorporates clinical and questionnaire data on a single linear scale using Rasch analysis. METHODS: In this prospective study, 293 preoperative cataract surgery patients (mean age, 72.8±10 years; age range, 33-98 years; 174 female, 119 male; 49% with ocular comorbidity) completed two questionnaires, and visual acuity was measured in each eye. A cataract impact model was developed using Rasch analysis incorporating questionnaire scores and visual acuity. Participants were ranked from 1 to 293 based on the order in which they presented (first in first out [FIFO]) and then were ranked based on the cataract impact model. The main outcome measure was the number of participants moving 49 (16.7% change) rank positions, which represented a likelihood to change priority category. RESULTS: The cataract impact model was unidimensional (fit statistics within 0.66-1.68) and had adequate precision (person separation of 2.58), and the components were well targeted to the population (0.05 logits between the mean item difficulty and person ability). Two hundred twenty-seven (77.5%) patients moved by at least 49 rank positions. CONCLUSIONS: It is possible to combine clinical and questionnaire data and rank patients on a single linear scale. This approach modifies the ranking that occurs with the FIFO model and can be used for prioritizing patients for surgical intervention. More sophisticated models incorporating more clinical information may provide a better measure of the cataract impact latent trait.
PURPOSE: To develop a model for establishing indications for cataract surgery that incorporates clinical and questionnaire data on a single linear scale using Rasch analysis. METHODS: In this prospective study, 293 preoperative cataract surgery patients (mean age, 72.8±10 years; age range, 33-98 years; 174 female, 119 male; 49% with ocular comorbidity) completed two questionnaires, and visual acuity was measured in each eye. A cataract impact model was developed using Rasch analysis incorporating questionnaire scores and visual acuity. Participants were ranked from 1 to 293 based on the order in which they presented (first in first out [FIFO]) and then were ranked based on the cataract impact model. The main outcome measure was the number of participants moving 49 (16.7% change) rank positions, which represented a likelihood to change priority category. RESULTS: The cataract impact model was unidimensional (fit statistics within 0.66-1.68) and had adequate precision (person separation of 2.58), and the components were well targeted to the population (0.05 logits between the mean item difficulty and person ability). Two hundred twenty-seven (77.5%) patients moved by at least 49 rank positions. CONCLUSIONS: It is possible to combine clinical and questionnaire data and rank patients on a single linear scale. This approach modifies the ranking that occurs with the FIFO model and can be used for prioritizing patients for surgical intervention. More sophisticated models incorporating more clinical information may provide a better measure of the cataract impact latent trait.
Authors: Matthew B Schlenker; Saba Samet; Morgan Lim; Chelsea D'Silva; Robert J Reid; Iqbal Ike K Ahmed Journal: PLoS One Date: 2021-06-25 Impact factor: 3.240
Authors: Rachel L Z Goh; Yu Xiang George Kong; Colm McAlinden; John Liu; Jonathan G Crowston; Simon E Skalicky Journal: Transl Vis Sci Technol Date: 2018-01-23 Impact factor: 3.283