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Predictive models for IOPs measured with NCT, GAT, and ORA among patients undergoing SMILE

Purpose: To develop predictive models for the intraocular pressure (IOP) of patients undergoing small incision lenticule extraction (SMILE) procedures, measured with a noncontact tonometer (NCT), Goldmann applanation tonometry (GAT), and an ocular response analyzer (ORA). Methods: In this prospectiv...

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Detalles Bibliográficos
Autores principales: Han, Tian, Shi, Wanru, Chen, Yingjun, Shen, Yang, Xu, Ye, Zhou, Xingtao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751611/
https://www.ncbi.nlm.nih.gov/pubmed/36532578
http://dx.doi.org/10.3389/fbioe.2022.1030458
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author Han, Tian
Shi, Wanru
Chen, Yingjun
Shen, Yang
Xu, Ye
Zhou, Xingtao
author_facet Han, Tian
Shi, Wanru
Chen, Yingjun
Shen, Yang
Xu, Ye
Zhou, Xingtao
author_sort Han, Tian
collection PubMed
description Purpose: To develop predictive models for the intraocular pressure (IOP) of patients undergoing small incision lenticule extraction (SMILE) procedures, measured with a noncontact tonometer (NCT), Goldmann applanation tonometry (GAT), and an ocular response analyzer (ORA). Methods: In this prospective study, a total of 104 eyes (−6.23 ± 2.06 diopters) of 52 patients (24.38 ± 4.76 years) undergoing SMILE procedures were included. The intraocular pressure was measured (IOP(NCT) with NCT, IOP(GAT) with GAT, and IOPcc and IOPg with ORA) before surgery and at postoperative 6 months. Information on age, preoperative and attempted spherical equivalent (SE), ablation depth, preoperative values and postoperative changes in central corneal thickness (CCT), K1, K2, Km, corneal hysteresis (CH) and corneal resistance factor (CRF) values was collected in order to predict IOPs. Results: All surgeries were uneventful. At postoperative 6 months, the efficacy and safety index were 1.04 ± 0.15 and 1.08 ± 0.18, respectively. Significant decreases were detected in postoperative IOP(NCT), IOP(GAT), IOPcc, and IOPg compared to preoperative values (all p < 0.001). No relationship was found between any IOP and ablation depth, attempted SE, and preoperative SE, as well as CCT(difference) (all p > 0.05). Predictive models for IOPs were constructed to predict preoperative values, and R (2) values were 67.5% (IOP(NCT)), 64.5% (IOP(GAT)), 78.7% (IOPcc), and 82.0% (IOPg). The prediction band of IOP(NCT) and IOP(GAT) was 7.4–15.1 mmHg and 8–16 mmHg, respectively. Conclusion: Predictive models for IOP measurements after SMILE procedures can be helpful in clinical practice.
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spelling pubmed-97516112022-12-16 Predictive models for IOPs measured with NCT, GAT, and ORA among patients undergoing SMILE Han, Tian Shi, Wanru Chen, Yingjun Shen, Yang Xu, Ye Zhou, Xingtao Front Bioeng Biotechnol Bioengineering and Biotechnology Purpose: To develop predictive models for the intraocular pressure (IOP) of patients undergoing small incision lenticule extraction (SMILE) procedures, measured with a noncontact tonometer (NCT), Goldmann applanation tonometry (GAT), and an ocular response analyzer (ORA). Methods: In this prospective study, a total of 104 eyes (−6.23 ± 2.06 diopters) of 52 patients (24.38 ± 4.76 years) undergoing SMILE procedures were included. The intraocular pressure was measured (IOP(NCT) with NCT, IOP(GAT) with GAT, and IOPcc and IOPg with ORA) before surgery and at postoperative 6 months. Information on age, preoperative and attempted spherical equivalent (SE), ablation depth, preoperative values and postoperative changes in central corneal thickness (CCT), K1, K2, Km, corneal hysteresis (CH) and corneal resistance factor (CRF) values was collected in order to predict IOPs. Results: All surgeries were uneventful. At postoperative 6 months, the efficacy and safety index were 1.04 ± 0.15 and 1.08 ± 0.18, respectively. Significant decreases were detected in postoperative IOP(NCT), IOP(GAT), IOPcc, and IOPg compared to preoperative values (all p < 0.001). No relationship was found between any IOP and ablation depth, attempted SE, and preoperative SE, as well as CCT(difference) (all p > 0.05). Predictive models for IOPs were constructed to predict preoperative values, and R (2) values were 67.5% (IOP(NCT)), 64.5% (IOP(GAT)), 78.7% (IOPcc), and 82.0% (IOPg). The prediction band of IOP(NCT) and IOP(GAT) was 7.4–15.1 mmHg and 8–16 mmHg, respectively. Conclusion: Predictive models for IOP measurements after SMILE procedures can be helpful in clinical practice. Frontiers Media S.A. 2022-12-01 /pmc/articles/PMC9751611/ /pubmed/36532578 http://dx.doi.org/10.3389/fbioe.2022.1030458 Text en Copyright © 2022 Han, Shi, Chen, Shen, Xu and Zhou. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Han, Tian
Shi, Wanru
Chen, Yingjun
Shen, Yang
Xu, Ye
Zhou, Xingtao
Predictive models for IOPs measured with NCT, GAT, and ORA among patients undergoing SMILE
title Predictive models for IOPs measured with NCT, GAT, and ORA among patients undergoing SMILE
title_full Predictive models for IOPs measured with NCT, GAT, and ORA among patients undergoing SMILE
title_fullStr Predictive models for IOPs measured with NCT, GAT, and ORA among patients undergoing SMILE
title_full_unstemmed Predictive models for IOPs measured with NCT, GAT, and ORA among patients undergoing SMILE
title_short Predictive models for IOPs measured with NCT, GAT, and ORA among patients undergoing SMILE
title_sort predictive models for iops measured with nct, gat, and ora among patients undergoing smile
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751611/
https://www.ncbi.nlm.nih.gov/pubmed/36532578
http://dx.doi.org/10.3389/fbioe.2022.1030458
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