Aleh Pazniak
Research Subjects
Aleh Pazniak has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
- Darya Smetanina
Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, United Arab Emirates
1 shared publication - Dmitriy Abelskyi
Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Belarus
1 shared publication - Elena Likhorad
Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
1 shared publication - Gillian Lylian Simiyu
Radiology Department, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, UAE
1 shared publication - Klaus Neidl-Van Gorkom
Radiology Department, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
1 shared publication - Mikalai Pazniak
Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Belarus
1 shared publication
Latest Publications
- Open Access
- 5 June 2024
- Published by MDPI AG in Preprints.org
Structural Outcomes of Corneal Cross-Linking for Keratoconus
Background: Studies have tried to identify predictors of functional markers of keratoconus progression, whereas structural outcomes of collagen cross-linking have not been properly investigated. Objective: find and set up a combination of diagnostic modalities and measurements to reliably reflect CXL efficiency. Material and methods: We retrospectively reviewed the medical histories of 107 KC patients (131 eyes) who underwent CXL in a medical center from January 2018 to December 2022. The dataset included preoperative examinations and follow-up results, which provided a total of 796 observations. The cases of other corneal diseases, repeated CXL, pregnancy, and observations without follow-up examinations were excluded. Results: The study findings revealed a significant drop in the central and corneal thickness during 14.01±9.98 months of observations. Linear and polynomial equations suggested different trends in pachymetry change after CXL. The linear model showed corneal thinning, and according to the polynomials, pachymetry findings return to baseline values two years after CXL. Conclusion: The most reliable prognosis of postoperative corneal thickness is achieved with the models trained on keratometry readings and topography indices. BAD indices are also reliable predictors of the corneal thickness after CXL. A combination of the aforementioned structural parameters and their derivatives can reliably predict CXL efficiency.
- 5 June 2024
- Published by MDPI AG in Preprints.org
Open AccessStructural Outcomes of Corneal Cross-Linking for Keratoconus
Background: Studies have tried to identify predictors of functional markers of keratoconus progression, whereas structural outcomes of collagen cross-linking have not been properly investigated. Objective: find and set up a combination of diagnostic modalities and measurements to reliably reflect CXL efficiency. Material and methods: We retrospectively reviewed the medical histories of 107 KC patients (131 eyes) who underwent CXL in a medical center from January 2018 to December 2022. The dataset included preoperative examinations and follow-up results, which provided a total of 796 observations. The cases of other corneal diseases, repeated CXL, pregnancy, and observations without follow-up examinations were excluded. Results: The study findings revealed a significant drop in the central and corneal thickness during 14.01±9.98 months of observations. Linear and polynomial equations suggested different trends in pachymetry change after CXL. The linear model showed corneal thinning, and according to the polynomials, pachymetry findings return to baseline values two years after CXL. Conclusion: The most reliable prognosis of postoperative corneal thickness is achieved with the models trained on keratometry readings and topography indices. BAD indices are also reliable predictors of the corneal thickness after CXL. A combination of the aforementioned structural parameters and their derivatives can reliably predict CXL efficiency.