Measured Corneal Astigmatism Versus Pseudophakic Predicted Refractive Astigmatism in Cataract Surgery Candidates

PURPOSE: To compare standard and total corneal astigmatism measurements to the predicted pseudophakic (nontoric) refractive astigmatism in candidates for cataract surgery. DESIGN: A retrospective, cross-sectional study. METHODS: A single-center analysis of consecutive eyes measured with a swept-source optical coherence tomography biometer at a large tertiary medical center between February 2018 and June 2020. Corneal astigmatism was calculated based on standard keratometry astigmatism (KA), total corneal astigmatism (TCA), and predicted refractive astigmatism (PRA) for a monofocal nontoric intraocular lens (IOL) implantation calculated by the Barrett toric calculator using the predicted posterior corneal astigmatism (PRA(Predicted-PCA)) and the measured posterior corneal astigmatism (PRA(Measured-PCA)) options. Separate analyses were performed for each eye. SETTING: Ophthalmology Department, Shaare Zedek Medical Center, Jerusalem, Israel. RESULTS: In total, 8152 eyes of 5320 patients (4221 right eyes [OD] and 3931 left eyes [OS], mean age 70.6±12.2 years, 54.2% females) were included in the study. The mean vector values (centroid) for KA, TCA, PRA(Predicted-PCA), and PRA(Measured-PCA) were 0.07 diopters [D] at 19.5°, 0.27 D at 7.5°, 0.44 D at 2.9°, and 0.43 D at 179.3°, respectively (P 0.5 D. CONCLUSIONS: Standard and total corneal astigmatism measurements differ significantly from the PRA by the Barrett toric calculator. The PRA, rather than the KA or TCA, should be used as the reference guide for astigmatism correction with toric IOL implantation

Measured Corneal Astigmatism Versus Pseudophakic Predicted Refractive Astigmatism in Cataract Surgery Candidates

PURPOSE: To compare standard and total corneal astigmatism measurements to the predicted pseudophakic (nontoric) refractive astigmatism in candidates for cataract surgery. DESIGN: A retrospective, cross-sectional study. METHODS: A single-center analysis of consecutive eyes measured with a swept-source optical coherence tomography biometer at a large tertiary medical center between February 2018 and June 2020. Corneal astigmatism was calculated based on standard keratometry astigmatism (KA), total corneal astigmatism (TCA), and predicted refractive astigmatism (PRA) for a monofocal nontoric intraocular lens (IOL) implantation calculated by the Barrett toric calculator using the predicted posterior corneal astigmatism (PRA(Predicted-PCA)) and the measured posterior corneal astigmatism (PRA(Measured-PCA)) options. Separate analyses were performed for each eye. SETTING: Ophthalmology Department, Shaare Zedek Medical Center, Jerusalem, Israel. RESULTS: In total, 8152 eyes of 5320 patients (4221 right eyes [OD] and 3931 left eyes [OS], mean age 70.6±12.2 years, 54.2% females) were included in the study. The mean vector values (centroid) for KA, TCA, PRA(Predicted-PCA), and PRA(Measured-PCA) were 0.07 diopters [D] at 19.5°, 0.27 D at 7.5°, 0.44 D at 2.9°, and 0.43 D at 179.3°, respectively (P 0.5 D. CONCLUSIONS: Standard and total corneal astigmatism measurements differ significantly from the PRA by the Barrett toric calculator. The PRA, rather than the KA or TCA, should be used as the reference guide for astigmatism correction with toric IOL implantation

When Every Second Counts: Novel Device to Shorten Chest Tube Insertion Time in a Pre-hospital Setting

<p><b>Article full text</b></p> <p><br></p> <p>The full text of this article can be found here<b>. </b><a href="https://link.springer.com/article/10.1007/s41030-016-0020-4">https://link.springer.com/article/10.1007/s41030-016-0020-4</a></p><p></p> <p><br></p> <p><b>Provide enhanced content for this article</b></p> <p><br></p> <p>If you are an author of this publication and would like to provide additional enhanced content for your article then please contact <a href="http://www.medengine.com/Redeem/”mailto:[email protected]”"><b>[email protected]</b></a>.</p> <p><br></p> <p>The journal offers a range of additional features designed to increase visibility and readership. All features will be thoroughly peer reviewed to ensure the content is of the highest scientific standard and all features are marked as ‘peer reviewed’ to ensure readers are aware that the content has been reviewed to the same level as the articles they are being presented alongside. Moreover, all sponsorship and disclosure information is included to provide complete transparency and adherence to good publication practices. This ensures that however the content is reached the reader has a full understanding of its origin. No fees are charged for hosting additional open access content.</p> <p><br></p> <p>Other enhanced features include, but are not limited to:</p> <p><br></p> <p>• Slide decks</p> <p>• Videos and animations</p> <p>• Audio abstracts</p> <p>• Audio slides</p

Automated Evaluation of Human Embryo Blastulation and Implantation Potential using Deep‐Learning

In in vitro fertilization (IVF) treatments, early identification of embryos with high implantation potential is required for shortening time to pregnancy while avoiding clinical complications to the newborn and the mother caused by multiple pregnancies. Current classification tools are based on morphological and morphokinetic parameters that are manually annotated using time‐lapse video files. However, manual annotation introduces interobserver and intraobserver variability and provides a discrete representation of preimplantation development while ignoring dynamic features that are associated with embryo quality. A fully automated and standardized classifiers are developed by training deep neural networks directly on the raw video files of >6200 blastulation‐labeled and >5500 implantation‐labeled embryos. Prediction of embryo implantation is more accurate than the current state‐of‐the‐art morphokientic classifier. Embryo classification improves with video length where the most predictive images show only partial association with morphological features. Deep learning substitute to human evaluation of embryo developmental competence thus contributes to implementing single embryo transfer methodology