{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T22:07:19Z","timestamp":1788386839320,"version":"build-2803163510"},"reference-count":28,"publisher":"Public Library of Science (PLoS)","issue":"2","license":[{"start":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T00:00:00Z","timestamp":1707177600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"\n Objectives<\/jats:title>\n To identify predictive factors and to construct predictive models using epidemiological and clinical preoperative factors for the visual acuity change after intracorneal ring segment (ICRS) implantation in patients with keratoconus.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n The medical records of 287 keratoconic eyes of 230 patients implanted with ICRS at Chula Refractive Surgery Center of a tertiary university hospital (Bangkok, Thailand) between January 2012 and March 2022 were retrospectively reviewed for epidemiological and clinical preoperative variables, including those derived from Scheimpflug tomography. After randomly excluding one eye for each bilateral case, the remaining 230 eyes were randomized into two groups: a training group (184 eyes) and a validation group (46 eyes). In the training group, the correlation between the interesting variables and postoperative uncorrected and corrected distance visual acuity change (\u0394UDVA and \u0394CDVA; logMAR scale) at 6 months was explored, and then the multiple linear regression analysis was used to develop the predictive models. The obtained models were tested using the validation group.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n There were 5 and 14 preoperative variables that statistically correlated with \u0394UDVA and \u0394CDVA respectively. Only the preoperative corrected distance visual acuity (CDVAp) strongly correlated with \u0394CDVA (Beta = -0.746). Using multiple regression, the preoperative uncorrected distance visual acuity (UDVAp) and front mean keratometry were selected in the proposed model for \u0394UDVA (adjusted R\n 2<\/jats:sup>\n = 38.8%), while the CDVAp and index of surface variance (ISV) were selected in the model\n \n \n \n \n \n \u0394<\/mml:mi>\n CDVA<\/mml:mi>\n =<\/mml:mo>\n \u2212<\/mml:mo>\n 0.043<\/mml:mn>\n \u2212<\/mml:mo>\n 0.613<\/mml:mn>\n \u00d7<\/mml:mo>\n CDVAp<\/mml:mi>\n +<\/mml:mo>\n 0.002<\/mml:mn>\n \u00d7<\/mml:mo>\n ISV<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:alternatives>\n <\/jats:inline-formula>\n (adjusted R\n 2<\/jats:sup>\n = 48.9%). The \u0394UDVA and \u0394CDVA models were correct in 47.83% and 63.4% of the validation group within 0.20 logMAR, respectively.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Potential predictive factors and models for ICRS-induced changes in visual acuity are proposed as adjunctive tools for clinicians. Such tools could be used for case selection and during counselling before ICRS implantation to maximize surgical outcomes.<\/jats:p>\n <\/jats:sec>","DOI":"10.1371\/journal.pone.0288181","type":"journal-article","created":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T13:37:49Z","timestamp":1707226669000},"page":"e0288181","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":4,"title":["Factors predicting the visual outcome of intracorneal ring segment for 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