Purpose: We aimed to develop a self-designed software programmed with a mathematical method that analyzes the refractive outcome after toric intraocular lens (IOL) implantation, taking the axis misalignment of the toric IOL into consideration.
Methods: A mathematical method that can analyze the refractive outcome after toric IOL implantation was devised. Compared with the conventional method, which performs the analysis based on precise alignment of the IOL, optional meridian orientations of the toric IOL were taken into account in this method. Self-designed computer software was developed using the mathematical method.
Results: Relatively high accordance was achieved between the mathematical analysis and the actual postoperative outcome. The mean predicted spherical power was 0.37 ± 0.74 dpt, and the mean measured spherical power was 0.37 ± 0.71 dpt (paired t test, p = 0.98). The mean predicted cylindrical power was -1.35 ± 0.86 dpt, and the mean measured cylindrical power was -1.42 ± 0.85 dpt (p = 0.27). The mean predicted change in the astigmatic axis was 33.7 ± 11.8°, and the mean measured parameter was 32.5 ± 15.4° (p = 0.49).
Conclusions: The advantage of the present mathematical method is that the postoperative refractive outcome can be analyzed under IOL misalignment.
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http://dx.doi.org/10.1159/000443509 | DOI Listing |
J Neurosurg
January 2025
2Department of Radiology, Service of Interventional Neuroradiology, Centre hospitalier de l'Université de Montréal (CHUM), Montréal.
Objective: Many patients with ruptured intracranial aneurysms (RIAs) underrepresented or excluded from previous randomized controlled trials (RCTs) comparing surgery with endovascular treatment (EVT) are still considered for surgical clipping, but the best management of these patients remains unknown.
Methods: The International Subarachnoid Aneurysm Trial-2 was a randomized trial comparing surgical versus EVT of RIAs considered for surgical clipping, despite the results of previous RCTs, and also eligible for EVT. The primary endpoint was death or dependency according to the modified Rankin Scale score (mRS score > 2) at 1 year.
PLoS One
January 2025
Division of Gastroenterology & Hepatology, University of Toronto, Toronto, ON, Canada.
Survival analysis is critical in many fields, particularly in healthcare where it can guide medical decisions. Conventional survival analysis methods like Kaplan-Meier and Cox proportional hazards models to generate survival curves indicating probability of survival v. time have limitations, especially for long-term prediction, due to assumptions that all instances follow a general population-level survival curve.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Mathematics, Aswan University, Faculty of Science, Aswan, Egypt.
In this work, bridge network model with Rayleigh distribution lifetimes is used. Two main techniques are calculated to upgrade this model: reduction and redundancy techniques. In order to compare the effectiveness of the various approaches, the survival function, the mean time to failure and gamma-fractiles for the original and upgraded model are calculated.
View Article and Find Full Text PDFDiabetes Obes Metab
January 2025
Department of Clinical Neuropsychology, Faculty of Health Sciences, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Toruń, Poland.
Background: Metabolic-bariatric surgery (MBS) transcends weight loss and offers wide-ranging health benefits, including positive effects on brain function. However, the mechanisms behind these effects remain unclear, particularly in the context of significant postoperative changes in the inflammatory profile characteristic of MBS. Understanding how inflammation influences postoperative brain function can enhance our decision-making on patient eligibility for MBS and create new opportunities to improve the outcomes of this popular treatment.
View Article and Find Full Text PDFPeerJ
January 2025
School of Mathematics and Computer Science, Gannan Normal University, Ganzhou, China.
Background: Convolutional neural networks have excellent modeling abilities to complex large-scale datasets and have been applied to genomics. It requires converting genotype data to image format when employing convolutional neural networks to genome-wide association studies. Existing studies converting the data into grayscale images have shown promising.
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