A large retrospective database analysis comparing outcomes of intraoperative aberrometry with conventional preoperative planning.

J Cataract Refract Surg

From The Eye Institute of Utah (Cionni), Salt Lake City, Utah, and Alcon Laboratories Inc. (Dimalanta, Breen, Hamilton), Fort Worth, Texas, USA.

Published: October 2018

Purpose: To evaluate differences between the absolute prediction error using an intraoperative aberrometry (IA) device for intraocular lens (IOL) power determination versus the error that would have resulted if the surgeon's preoperative plan had been followed.

Setting: Multiple centers in the United States.

Design: Retrospective analysis of data collected using an IA device.

Methods: The database information was limited according to predetermined inclusion/exclusion criteria. Primary endpoints included the difference between mean and median absolute prediction error with IA use versus preoperative calculation, and the percentage of cases were compared when the prediction error was 0.5 diopters (D) or less.

Results: A total of 32 189 eyes were analyzed. The IA mean absolute prediction error was lower than the preoperative calculation, 0.30 D ± 0.26 (SD) versus 0.36 ± 0.32 D (P < .0001). The aberrometry absolute median prediction error was lower than the preoperative calculation, 0.24 D versus 0.29 D (P < .0001). There was a significantly greater percentage of eyes with an aberrometry absolute prediction error of 0.5 D or less than eyes with a preoperative absolute prediction error of 0.5 D or less (26 357 [81.9%] of 32 189 vs. 24 437 [75.9%] of 32 189, P < .0001). In addition, in those cases in which power of the IOL implanted was different than the preoperatively planned IOL power, significantly more eyes had an aberrometry absolute prediction error of 0.5 D or less (10 385 [81.3%] of 12 779 vs. 8794 [68.8%] of 12 779, P < .0001).

Conclusions: In a database of more than 30 000 eyes, calculations incorporating IA outperformed preoperative calculations. The difference was more pronounced in those cases in which the preoperatively planned IOL power was different than the power of the IOL implanted.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jcrs.2018.07.016DOI Listing

Publication Analysis

Top Keywords

prediction error
16
absolute prediction
12
intraoperative aberrometry
8
preoperative calculation
8
error
5
large retrospective
4
retrospective database
4
database analysis
4
analysis comparing
4
comparing outcomes
4

Similar Publications

Background: Despite improved survival rates in rectal cancer treatment, many patients experience low anterior resection syndrome (LARS). The preoperative LARS score (POLARS) aims to address the limitations of LARS assessment by predicting outcomes preoperatively to enhance surgical planning.

Aim: To investigate the predictive accuracy of POLARS in assessing the occurrence of LARS.

View Article and Find Full Text PDF

In neuro-oncology, MR imaging is crucial for obtaining detailed brain images to identify neoplasms, plan treatment, guide surgical intervention, and monitor the tumor's response. Recent AI advances in neuroimaging have promising applications in neuro-oncology, including guiding clinical decisions and improving patient management. However, the lack of clarity on how AI arrives at predictions has hindered its clinical translation.

View Article and Find Full Text PDF

Background: In the realm of Evidence-Based Medicine, introduced by Gordon Guyatt in the early 1990s, the integration of machine learning technologies marks a significant advancement towards more objective, evidence-driven healthcare. Evidence-Based Medicine principles focus on using the best available scientific evidence for clinical decision-making, enhancing healthcare quality and consistency by integrating this evidence with clinician expertise and patient values. Patient-Reported Outcome Measures (PROMs) and Patient-Reported Experience Measures (PREMs) have become essential in evaluating the broader impacts of treatments, especially for chronic conditions like HIV, reflecting patient health and well-being comprehensively.

View Article and Find Full Text PDF

To analyze the refractive accuracy of a novel swept-source optical coherence biometer (SS-OCT), that uses individual refractive indices to measure axial length, in short and long eyes implanted with monofocal intraocular lenses (IOLs). This retrospective comparative study considered eyes with short axial length (AL) (< 22.5 mm) or long AL (> 26 mm) bilaterally implanted with the Acrysof IQ monofocal IOL.

View Article and Find Full Text PDF

scHiGex: predicting single-cell gene expression based on single-cell Hi-C data.

NAR Genom Bioinform

March 2025

Department of Computer Science, University of Miami, Coral Gables, FL 33146, United States.

A novel biochemistry experiment named HiRES has been developed to capture both the chromosomal conformations and gene expression levels of individual single cells simultaneously. Nevertheless, when compared to the extensive volume of single-cell Hi-C data generated from individual cells, the number of datasets produced from this experiment remains limited in the scientific community. Hence, there is a requirement for a computational tool that can forecast the levels of gene expression in individual cells using single-cell Hi-C data from the same cells.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!