Probability model of the inaccuracy of residual stromal thickness prediction to reduce the risk of ectasia after LASIK part II: quantifying population risk
PURPOSE: To derive a statistical model to estimate the rate of excessive keratectomy depth below a selected cut-off residual stromal thickness (RST) gven a minimum target RST and specific Clinical Protocol; apply the model to estimate the RST below which ectasia appears likely to occur and back-calc...
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th-mahidol.235262018-08-20T14:09:03Z Probability model of the inaccuracy of residual stromal thickness prediction to reduce the risk of ectasia after LASIK part II: quantifying population risk Dan Z. Reinstein Sabong Srivannaboon Timothy J. Archer Ronald H. Silverman Hugo Sutton D. Jackson Coleman London Vision Clinic The University of British Columbia Weill Cornell Medical College King's College London Centre Hospitalier National d`Ophtalmologie des Quinze-Vingts Mahidol University Medicine PURPOSE: To derive a statistical model to estimate the rate of excessive keratectomy depth below a selected cut-off residual stromal thickness (RST) gven a minimum target RST and specific Clinical Protocol; apply the model to estimate the RST below which ectasia appears likely to occur and back-calculate the safe minimum target RST that should be used given a specific Clinical Protocol. METHODS: Myopia and corneal thickness distribution were modeled for a population of 5212 eyes that underwent LASIK. The probability distribution of predicted target RST error (Part I) was used to calculate the rate of excessive keratectomy depth for this series. All treatments were performed using the same Clinical Protocol; one surgeon, Moria LSK-One microkeratome, NIDEK EC-5000 excimer laser, Orbscan pachymetry, and a minimum target RST of 250 μm-the Vancouver Clinical Protocol. The model estimated the RST below which ectasia appears likely to occur and back-calculated the safe minimum target RST. These values were recalculated for a series of microkeratomes using published flap thickness statistics as well as for the Clinical Protocol of one of the authors-the London Clinical Protocol. RESULTS: In the series of 5212 eyes, 6 (0.12%) cases of ectasia occurred. The model predicted an RST of 191 μm for ectasia to occur and that a minimum target RST of 329 μm would have reduced the rate of ectasia to 1:1,000,000 for the Vancouver Clinical Protocol. The model predicted that the choice of microkeratome varied the rate of ectasia between 0.01 and 11,623 eyes per million and the safe minimum target RST between 220 and 361 μm. The model predicted the rate of ectasia would have been 0.000003:1,000,000 had the London Clinical Protocol been used for the Vancouver case series. CONCLUSIONS: There appears to be no universally safe minimum target RST to assess suitability for LASIK largely due to the disparity in accuracy and reproducibility of microkeratome flap thickness. This model may be used as a tool to evaluate the risk of ectasia due to excessive keratectomy depth and help determine the minimum target RST given a particular Clinical Protocol. 2018-08-20T07:09:03Z 2018-08-20T07:09:03Z 2006-11-01 Article Journal of Refractive Surgery. Vol.22, No.9 (2006), 861-870 1081597X 2-s2.0-33751082708 https://repository.li.mahidol.ac.th/handle/123456789/23526 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=33751082708&origin=inward |
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Medicine Dan Z. Reinstein Sabong Srivannaboon Timothy J. Archer Ronald H. Silverman Hugo Sutton D. Jackson Coleman Probability model of the inaccuracy of residual stromal thickness prediction to reduce the risk of ectasia after LASIK part II: quantifying population risk |
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PURPOSE: To derive a statistical model to estimate the rate of excessive keratectomy depth below a selected cut-off residual stromal thickness (RST) gven a minimum target RST and specific Clinical Protocol; apply the model to estimate the RST below which ectasia appears likely to occur and back-calculate the safe minimum target RST that should be used given a specific Clinical Protocol. METHODS: Myopia and corneal thickness distribution were modeled for a population of 5212 eyes that underwent LASIK. The probability distribution of predicted target RST error (Part I) was used to calculate the rate of excessive keratectomy depth for this series. All treatments were performed using the same Clinical Protocol; one surgeon, Moria LSK-One microkeratome, NIDEK EC-5000 excimer laser, Orbscan pachymetry, and a minimum target RST of 250 μm-the Vancouver Clinical Protocol. The model estimated the RST below which ectasia appears likely to occur and back-calculated the safe minimum target RST. These values were recalculated for a series of microkeratomes using published flap thickness statistics as well as for the Clinical Protocol of one of the authors-the London Clinical Protocol. RESULTS: In the series of 5212 eyes, 6 (0.12%) cases of ectasia occurred. The model predicted an RST of 191 μm for ectasia to occur and that a minimum target RST of 329 μm would have reduced the rate of ectasia to 1:1,000,000 for the Vancouver Clinical Protocol. The model predicted that the choice of microkeratome varied the rate of ectasia between 0.01 and 11,623 eyes per million and the safe minimum target RST between 220 and 361 μm. The model predicted the rate of ectasia would have been 0.000003:1,000,000 had the London Clinical Protocol been used for the Vancouver case series. CONCLUSIONS: There appears to be no universally safe minimum target RST to assess suitability for LASIK largely due to the disparity in accuracy and reproducibility of microkeratome flap thickness. This model may be used as a tool to evaluate the risk of ectasia due to excessive keratectomy depth and help determine the minimum target RST given a particular Clinical Protocol. |
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London Vision Clinic |
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London Vision Clinic Dan Z. Reinstein Sabong Srivannaboon Timothy J. Archer Ronald H. Silverman Hugo Sutton D. Jackson Coleman |
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Article |
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Dan Z. Reinstein Sabong Srivannaboon Timothy J. Archer Ronald H. Silverman Hugo Sutton D. Jackson Coleman |
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Dan Z. Reinstein |
title |
Probability model of the inaccuracy of residual stromal thickness prediction to reduce the risk of ectasia after LASIK part II: quantifying population risk |
title_short |
Probability model of the inaccuracy of residual stromal thickness prediction to reduce the risk of ectasia after LASIK part II: quantifying population risk |
title_full |
Probability model of the inaccuracy of residual stromal thickness prediction to reduce the risk of ectasia after LASIK part II: quantifying population risk |
title_fullStr |
Probability model of the inaccuracy of residual stromal thickness prediction to reduce the risk of ectasia after LASIK part II: quantifying population risk |
title_full_unstemmed |
Probability model of the inaccuracy of residual stromal thickness prediction to reduce the risk of ectasia after LASIK part II: quantifying population risk |
title_sort |
probability model of the inaccuracy of residual stromal thickness prediction to reduce the risk of ectasia after lasik part ii: quantifying population risk |
publishDate |
2018 |
url |
https://repository.li.mahidol.ac.th/handle/123456789/23526 |
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1763498088395177984 |