RESUMEN
BACKGROUND: Cataract waiting lists are growing globally. Pragmatic, cost-effective methods are required to prioritise the most urgent cases. Here we investigate the feasibility of using a third-party pen-and-paper contrast sensitivity, CS, test (SpotChecksTM), delivered by mail, and performed by patients at home unsupervised, to flag eyes requiring surgery. METHODS: Pen-and-paper CS tests were mailed to 233 people waiting for a cataract assessment, along with a prepaid return envelope (cross-sectional study). Response rates were tabulated (stratified by age, sex and socioeconomic status), and test scores analysed to see how well the home tests predicted which eyes were listed subsequently for surgery. A subset of patients (N = 39) also underwent in-person follow-up testing, to confirm the accuracy of the home data. RESULTS: Forty-six percent of patients responded (216 eyes). No gross differences were observed between respondents and non-respondents, either in terms of age, sex, socioeconomic status, or geographic location (all P > 0.05). The home-test CS scores predicted which eyes were subsequently listed for surgery, with an AUROC {±CI95%} of 0.69 {0.61-0.76}. Predictive performance was further-improved when machine learning was used to combine CS scores with letter acuity, extracted from patients' medical records (AUROC {±CI95%} = 0.77 {0.70-0.83}). Among 39 patients who underwent follow-up testing, home CS scores were correlated with various measures made in clinic: biometry signal-to-noise (P = 0.032), LogMAR acuity, Pelli-Robson CS and SpotChecks CS (all P < 0.001). CONCLUSIONS: Mailing patients pen-and-paper CS tests may be a feasible, 'low-tech' way of prioritising patients on cataract waiting lists.
