vector analysis
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2022 ◽  
Vol 68 ◽  
pp. 89-95
Author(s):  
Paolo Formenti ◽  
Silvia Coppola ◽  
Michele Umbrello ◽  
Sara Froio ◽  
Alessio Cacioppola ◽  
...  

Author(s):  
Brent J. Lewis ◽  
E. Nihan Onder ◽  
Andrew A. Prudil

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Colm McAlinden ◽  
David Janicek

Aims/Background. To assess astigmatic outcomes with the use of toric intraocular lenses (IOLs) for patients with significant amounts of corneal astigmatism undergoing cataract surgery. Methods. This audit was conducted in a UK ophthalmology department and included 48 eyes of 42 patients. Surgery was performed during 2019 in patients with 2.50 diopters (D) or more corneal astigmatism. Anterior keratometry readings were used to determine the toric IOL power. Vector analysis using the Alpins method was used to assess changes in astigmatism pre to postoperatively. Results. There were 18 right and 26 left eyes included. In terms of gender, 61% of patients were female and 39% were male. The mean (±standard deviation (SD)) age was 70 (±11) years. The mean (±SD) axial length, K1, K2, and delta K was 23.55 (±1.4) mm, 42.71 (±1.39) D, 45.78 (±1.60) D, and 3.01 (±0.89) D, respectively. Postoperatively, the median spherical, cylinder, and spherical equivalent refraction was 0.00 D, −1.00 D, and 0.00 D, respectively. Postoperatively, 41% of the eyes had ≤0.50 D of spectacle astigmatism and 80% had ≤1.00 D. No patient required a secondary procedure to reposition the IOL from rotation. In vector analysis with the use of polar diagrams, there was a tendency for overcorrection of with-the-rule astigmatism and undercorrection of against-the-rule astigmatism. Conclusions. Significant reductions in astigmatism can be achieved with the use of toric IOLs in patients undergoing cataract surgery. Further improvements may be possible with surgeon-specific determination of their surgically induced astigmatism and flattening effect from the main corneal incision. Furthermore, the use of an optical biometer that directly measures the posterior corneal curvature and permits automatic toric IOL power determination with modern formulas avoiding the need for manual data entry may reduce the risk of human error and improve visual and refractive outcomes.


Author(s):  
Andrea Di Credico ◽  
Giulia Gaggi ◽  
Anastasios Vamvakis ◽  
Sofia Serafini ◽  
Barbara Ghinassi ◽  
...  

Team handball is a highly dynamic sport where physical demands differ between categories and roles. Thus, physical characteristics are fundamental for the final performance. This study aims to (a) characterize a sample of young male and female elite team handball players with a non-athletic reference population; (b) to generate their 50%, 75%, and 95% percentiles of the bioelectrical variables. The study included 55 young elite team handball players (Males, n = 37, age = 17.0 ± 1.2 yrs, height = 185.8 ± 7.3 cm, weight = 82.0 ± 11.0 kg, body mass index (BMI) = 23.7 ± 2.5; Females, n = 18, age = 17.8 ± 0.9 yrs, height = 171.2 ± 6.4 cm, weight = 67.4 ± 7.2 kg, BMI = 23.0 ± 2.0). Height and bioelectrical variables were assessed in a state of euhydration and standard conditions. Bioelectrical impedance vector analysis (BIVA) was used to characterize the bioelectrical vector (BIA vector) distribution pattern for each group. Compared to the reference values, BIA vector showed statistically significant differences in males U17 (n = 19, T2 = 51.0, p < 0.0001), males U19 (n = 18, T2 = 82.0, p < 0.0001) and females U19 (n = 18, T2 = 85.8, p < 0.0001). Male groups were also bioelectrically different (T2 = 13.7, p = 0.0036). BIVA showed specific bioelectrical characteristics in young male and female elite handball players. This study provides an original data set of bioelectrical impedance reference values of young male and female elite team handball players. Our result might help to interpret individual bioimpedance vectors and define target regions for young handball players.


2021 ◽  
Vol 59 (9) ◽  
pp. 720-723
Author(s):  
Erica Farnsworth ◽  
Mark A. Milanick
Keyword(s):  

Author(s):  
Pengfeng Xiao ◽  
Guangwei Sheng ◽  
Xueliang Zhang ◽  
Hao Liu ◽  
Rui Guo

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