scholarly journals Does Every Calculation Formula Fit for All Types of Intraocular Lenses? Optimization of Constants for Tecnis ZA9003 and ZCB00 Is Necessary

Medicina ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 319
Author(s):  
Ivajlo Popov ◽  
Veronika Popova ◽  
Juraj Sekac ◽  
Vladimir Krasnik
Keyword(s):  
Prediction Error ◽  
Poor Performance ◽  
Intraocular Lenses ◽  
Power Calculation ◽  
Universal Formula ◽  
Aspheric Iol ◽  
Different Types ◽  
The Mean ◽  
Clinically Significant ◽  
Mean Prediction Error

Background and Objectives: To evaluate the performance of intraocular lenses (IOLs) using power calculation formulas on different types of IOL. Materials and Methods: 120 eyes and four IOL types (BioLine Yellow Accurate Aspheric IOL (i-Medical), TECNIS ZCB00, TECNIS ZA9003 (Johnson & Johnson) (3-piece IOL) and Softec HD (Lenstec)) were analyzed. The performance of Haigis, Barret Universal II and SKR-II formulas were compared between IOL types. The mean prediction error (ME) and mean absolute prediction error (MAE) were analyzed. Results: The overall percentage of eyes predicted within ±0.25 diopters (D) was 40.8% for Barret; 39.2% Haigis and 31.7% for SRK-II. Barret and Haigis had a significantly lower MAE than SRK-II (p < 0.05). The results differed among IOL types. The largest portion of eyes predicted within ±0.25 D was with the Barret formula in ZCB00 (33.3%) and ZA9003 (43.3%). Haigis was the most accurate in Softec HD (50%) and SRK-II in Biolline Yellow IOL (50%). ZCB00 showed a clinically significant hypermetropic ME compared to other IOLs. Conclusions: In general, Barret formulas had the best performance as a universal formula. However, the formula should be chosen according to the type of IOL in order to obtain the best results. Constant optimizations are necessary for the Tecnis IOL ZCB00 and ZA9003, as all of the analyzed formulas achieved a clinically significant poor performance in this type of IOL. ZCB00 also showed a hypermetropic shift in ME in all the formulas.

Intraocular lenses optic power calculation with seven formulas in short eyes

2021 ◽  
pp. 57-61
Author(s):  
K.B. Pershin ◽  
◽  
N.F. Pashinova ◽  
I.A. Likh ◽  
А.Y. Tsygankov ◽  
...  
Keyword(s):  
Axial Length ◽  
Mean Absolute Error ◽  
Optical Power ◽  
Absolute Error ◽  
Intraocular Lenses ◽  
Power Calculation ◽  
Retrospective Comparison ◽  
Monofocal Iol ◽  
The Mean ◽  
Axial Eye Length

Purpose. The choice of the optimal formula for calculating the IOL optical power in patients with an axial eye length of less than 20 mm. Material and methods. A total of 78 patients (118 eyes) were included in the prospective study. 1st group included 30 patients (52 eyes) with short eyes (average axial eye length of 19.60±0.42 (18.54–20.0) mm), 2nd group consisted of 48 patients (66 eyes) with a axial length 22.75±0.46 (22.0–23.77) mm. Various monofocal IOL models were used. The average follow-up period was 13 months. IOL optical power was calculated using the SRK/T formula, retrospective comparison – according to the formulas Hoffer-Q, Holladay II, Olsen, Haigis, Barrett Universal II and Kane. Results. In 1st group, the mean absolute error was determined for the formulas Haigis, Olsen, Barrett Universal II, Kane, SRK/T, Holladay II and Hoffer-Q (0.85, 0.78, 0.21, 0.17, 0.79, 0.73, 0.19 respectively). When comparing the formulas, significant differences were found for the formulas Hoffer-Q, Barrett Universal II and Kane in comparison with the formulas Haigis, Olsen, SRK/T and Holladay II (p<0.05) in all cases, respectively. In 2nd group, the mean absolute error was determined for the formulas Haigis, Olsen, Barrett Universal II, Kane, SRK/T, Holladay II and Hoffer-Q (0.15, 0.16, 0.23, 0.10, 0.19, 0.23, 0,29 respectively). In 2nd group, there were no significant differences between the studied formulas (p>0.05). Conclusion. This paper presents an analysis of data on the effectiveness of seven formulas for calculating the IOL optical power in short (less than 20 mm) eyes in comparison with the normal axial length. The advantage of the Hoffer-Q, Barrett Universal II and Kane formulas over Haigis, Holladay II, Olsen, and SRK/T is shown. Key words: cataract, hypermetropia, short eyes, calculation of the IOL optical power.

Accuracy of predicting the vancomycin concentration in Japanese cancer patients by the Sawchuk–Zaske method or Bayesian method

2019 ◽  
Vol 26 (3) ◽  
pp. 543-548
Author(s):  
Toshihisa Nakashima ◽  
Takayuki Ohno ◽  
Keiichi Koido ◽  
Hironobu Hashimoto ◽  
Hiroyuki Terakado
Keyword(s):  
Cancer Patients ◽  
Prediction Error ◽  
Bayesian Method ◽  
Predictive Accuracy ◽  
Pharmacokinetic Parameters ◽  
Population Pharmacokinetic ◽  
Squared Prediction Error ◽  
Trough Concentrations ◽  
The Mean ◽  
Mean Prediction Error

Background In cancer patients treated with vancomycin, therapeutic drug monitoring is currently performed by the Bayesian method that involves estimating individual pharmacokinetics from population pharmacokinetic parameters and trough concentrations rather than the Sawchuk–Zaske method using peak and trough concentrations. Although the presence of malignancy influences the pharmacokinetic parameters of vancomycin, it is unclear whether cancer patients were included in the Japanese patient populations employed to estimate population pharmacokinetic parameters for this drug. The difference of predictive accuracy between the Sawchuk–Zaske and Bayesian methods in Japanese cancer patients is not completely understood. Objective To retrospectively compare the accuracy of predicting vancomycin concentrations between the Sawchuk–Zaske method and the Bayesian method in Japanese cancer patients. Methods Using data from 48 patients with various malignancies, the predictive accuracy (bias) and precision of the two methods were assessed by calculating the mean prediction error, the mean absolute prediction error, and the root mean squared prediction error. Results Prediction of the trough and peak vancomycin concentrations by the Sawchuk–Zaske method and the peak concentration by the Bayesian method showed a bias toward low values according to the mean prediction error. However, there were no significant differences between the two methods with regard to the changes of the mean prediction error, mean absolute prediction error, and root mean squared prediction error. Conclusion The Sawchuk–Zaske method and Bayesian method showed similar accuracy for predicting vancomycin concentrations in Japanese cancer patients.

scholarly journals External Validation of the Dutch SOURCE Survival Prediction Model in Belgian Metastatic Oesophageal and Gastric Cancer Patients

Cancers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 834
Author(s):  
J.J. van Kleef ◽  
H.G. van den Boorn ◽  
R.H.A. Verhoeven ◽  
K. Vanschoenbeek ◽  
A. Abu-Hanna ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Prediction Model ◽  
Oesophageal Cancer ◽  
Prediction Error ◽  
Prediction Models ◽  
Mean Difference ◽  
Survival Prediction ◽  
Cancer Model ◽  
The Mean ◽  
Mean Prediction Error

The SOURCE prediction model predicts individualised survival conditional on various treatments for patients with metastatic oesophageal or gastric cancer. The aim of this study was to validate SOURCE in an external cohort from the Belgian Cancer Registry. Data of Belgian patients diagnosed with metastatic disease between 2004 and 2014 were extracted (n = 4097). Model calibration and discrimination (c-indices) were determined. A total of 2514 patients with oesophageal cancer and 1583 patients with gastric cancer with a median survival of 7.7 and 5.4 months, respectively, were included. The oesophageal cancer model showed poor calibration (intercept: 0.30, slope: 0.42) with an absolute mean prediction error of 14.6%. The mean difference between predicted and observed survival was −2.6%. The concordance index (c-index) of the oesophageal model was 0.64. The gastric cancer model showed good calibration (intercept: 0.02, slope: 0.91) with an absolute mean prediction error of 2.5%. The mean difference between predicted and observed survival was 2.0%. The c-index of the gastric cancer model was 0.66. The SOURCE gastric cancer model was well calibrated and had a similar performance in the Belgian cohort compared with the Dutch internal validation. However, the oesophageal cancer model had not. Our findings underscore the importance of evaluating the performance of prediction models in other populations.

scholarly journals Comparison of Predictability Using Barrett Universal II and SRK/T Formulas according to Keratometry

2020 ◽  
Vol 2020 ◽  
pp. 1-5
Author(s):  
Kei Iijima ◽  
Kazutaka Kamiya ◽  
Yoshihiko Iida ◽  
Nobuyuki Shoji
Keyword(s):  
Prediction Error ◽  
Pearson Correlation ◽  
Absolute Error ◽  
Power Calculation ◽  
Universal Formula ◽  
Iol Power Calculation ◽  
Iol Power ◽  
The Absolute ◽  
Relationship Of ◽  
The Relationship

Purpose. To compare the predictability of intraocular lens (IOL) power calculation using the Barrett Universal II and the SRK/T formulas, according to the keratometry. Methods. We retrospectively reviewed the clinical charts of 335 consecutive eyes undergoing standard cataract surgery. IOL power calculations were performed using the Barrett Universal II and the SRK/T formulas. We compared the prediction error, the absolute error, and the percentages within ±0.25, ±0.5, and ±1.0 D of the targeted refraction, 1 month postoperatively, and also investigated the relationship of these outcomes with the keratometric readings, using the two formulas. Results. The prediction error using the SRK/T formula was significantly more myopic than that using the Barrett Universal II formula (the paired t-test, p<0.001). The absolute error using the SRK/T formula was significantly larger than that using the Barrett Universal II formula (p=0.006). We found a significant correlation between the prediction error and the keratometric readings using the SRK/T formula (Pearson correlation coefficient, r = −0.522, p<0.001), but there was no significant correlation between them using the Barrett Universal II formula (r = −0.031, p=0.576). Conclusions. The Barrett Universal II formula provides a better predictability of IOL power calculation and is less susceptible to the effect of the corneal shape, than the SRK/T formula. The Barrett Universal formula, instead of the SRK/T formula, may be clinically helpful for improving the refractive accuracy, especially in eyes with steep or flat corneas.

Anterior chamber depth, lens thickness and intraocular lens calculation formula accuracy: nine formulas comparison

2020 ◽  
pp. bjophthalmol-2020-317822
Author(s):  
Diogo Hipólito-Fernandes ◽  
Maria Elisa Luís ◽  
Rita Serras-Pereira ◽  
Pedro Gil ◽  
Vitor Maduro ◽  
...  
Keyword(s):  
Anterior Chamber ◽  
Intraocular Lens ◽  
Prediction Error ◽  
Anterior Chamber Depth ◽  
Case Series ◽  
Absolute Error ◽  
Power Calculation ◽  
Retrospective Case ◽  
Lens Thickness ◽  
Mean Prediction Error

Background/AimsTo investigate the influence of anterior chamber depth (ACD) and lens thickness (LT) on 9 intraocular lens (IOL) power calculation formulas accuracy, in patients with normal axial lengths.MethodsRetrospective case series, including patients having uncomplicated cataract surgery with insertion of a single IOL model, divided into three groups according to preoperative ACD. Each group was further subdivided into three subgroups, according to the LT. Using optimised constants, refraction prediction error was calculated for Barrett Universal II, Emmetropia Verifying Optical (EVO) V.2.0, Haigis, Hill-RBF V.2.0, Hoffer Q, Holladay 1, Kane, PEARL-DGS and SRK/T formulas. Mean prediction error, mean and median absolute error (MedAE) and the percentage of eyes within ±0.25D, ±0.50D and ±1.00D were also calculated.ResultsThe study included 695 eyes from 695 patients. For ACD ≤3.0 mm and ≥3.5 mm, mean prediction error of SRK/T, Hoffer Q and Holladay 1 was significantly different from 0 (p<0.05). PEARL-DGS, Kane, EVO V.2.0 and Barrett Universal II were more accurate than the Hoffer Q in ACD ≤3.0 mm (p<0.05). Kane, PEARL-DGS, EVO V.2.0 and Barrett Universal II revealed the lowest variance of mean and MedAE by ACD and LT subgroup. Haigis and Hill-RBF V.2.0 were significantly influenced by LT, independently of the ACD, with a myopic shift with thin lenses and a hyperopic shift with thick lenses (p<0.05).ConclusionNew generation formulas, particularly Kane, PEARL-DGS and EVO V.2.0, seem to be more reliable and stable even in eyes with extreme ACD-LT combinations.

Intraocular lenses optic power calculation with seven formulas in short eyes

2021 ◽  
pp. 37-40
Author(s):  
K.B. Pershin ◽  
◽  
N.F. Pashinova ◽  
I.A. Likh ◽  
А.I. Tsygankov ◽  
...  
Keyword(s):  
Axial Length ◽  
Mean Absolute Error ◽  
Optical Power ◽  
Absolute Error ◽  
Intraocular Lenses ◽  
Power Calculation ◽  
Group I ◽  
The Mean ◽  
Group Ii ◽  
Axial Eye Length

Purpose. The choice of the optimal formula for calculating the IOL optical power in patients with an axial eye length of less than 20 mm. Material and methods.A total of 78 patients (118 eyes) were included in theprospective study. Group I included 30 patients (52 eyes) with short eyes (average axial eye length of 19.60 ± 0.42 (18.54-20.0) mm), group II consisted of 48 patients (66 eyes) with a axial length (22.75 ± 0.46 (22.0-23.77) mm. Various monofocal IOL models were used. The average follow-up period was 13 months. IOL optical power was calculated using the SRK/T formula, retrospective comparison - according to the formulas Hoffer-Q, Holladay II, Olsen, Haigis, Barrett Universal II and Kane. Results. In group I, the mean absolute error was determined for the formulas Haigis, Olsen, Barrett Universal II, Kane, SRK / T, Holladay 2 and Hoffer-Q (0.85; 0.78; 0.21; 0.17; 0.79; 0.73; 0.19 respectively). When comparing the formulas, significant differences were found for the formulas Hoffer-Q, Barrett Universal II and Kane in comparison with the formulas Haigis, Olsen, SRK / T and Holladay II (p <0.05) in all cases, respectively. In group I, the mean absolute error was determined for the formulas Haigis, Olsen, Barrett Universal II, Kane, SRK / T, Holladay 2 and Hoffer-Q (0.15; 0.16; 0.23; 0.10; 0.19; 0.23; 0.29 respectively) In group II, there were no significant differences between the studied formulas (p> 0.05). Conclusion. This paper presents an analysis of data on the effectiveness of seven formulas for calculating the IOL optical power in short (less than 20 mm) eyes in comparison with the normal axial length. The advantage of the Hoffer-Q, Barrett Universal II and Kane formulas over Haigis, Holladay 2, Olsen, and SRK / T is shown. Key words: cataract; hypermetropia; short eyes; calculation of the IOL optical power.

scholarly journals A Wavelet-Based Robust Relevance Vector Machine Based on Sensor Data Scheduling Control for Modeling Mine Gas Gushing Forecasting on Virtual Environment

2013 ◽  
Vol 2013 ◽  
pp. 1-4 ◽  
Author(s):  
Wang Ting ◽  
Cai Lin-qin ◽  
Fu Yao ◽  
Zhu Tingcheng
Keyword(s):  
Prediction Error ◽  
Relevance Vector Machine ◽  
Wavelet Function ◽  
Sensor Data ◽  
Percentage Error ◽  
Data Scheduling ◽  
The Mean ◽  
Mine Gas ◽  
Mean Prediction Error ◽  
Better Than

It is wellknown that mine gas gushing forecasting is very significant to ensure the safety of mining. A wavelet-based robust relevance vector machine based on sensor data scheduling control for modeling mine gas gushing forecasting is presented in the paper. Morlet wavelet function can be used as the kernel function of robust relevance vector machine. Mean percentage error has been used to measure the performance of the proposed method in this study. As the mean prediction error of mine gas gushing of the WRRVM model is less than 1.5%, and the mean prediction error of mine gas gushing of the RVM model is more than 2.5%, it can be seen that the prediction accuracy for mine gas gushing of the WRRVM model is better than that of the RVM model.

scholarly journals In-vitro glistening formation in six different foldable hydrophobic intraocular lenses

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Tamer Tandogan ◽  
Gerd U. Auffarth ◽  
Hyeck-Soo Son ◽  
Patrick Merz ◽  
Chul Young Choi ◽  
...  
Keyword(s):  
Image Analysis ◽  
Laboratory Method ◽  
Intraocular Lenses ◽  
Analysis Program ◽  
Quality Of Vision ◽  
Different Types ◽  
The Mean ◽  
Hydrophobic Acrylic

Abstract Background Glistenings describe small, refractile microvacuoles that may arise within the intraocular lens (IOL) material and reduce the patients’ quality of vision. Lenses composed of hydrophobic acrylic material are particularly affected by glistening formation. In this study, we compared the tendency of glistening formation in six different types of hydrophobic acrylic intraocular lenses (IOLs). Methods We used a well-established accelerated laboratory method to develop glistenings in the following IOLs: Vivinex XY1 (Hoya), AcrySof SN60WF (Alcon), Tecnis ZCB00 (AMO), Avansee PN6A (Kowa), Aktis SP NS-60YG (Nidek), and CT Lucia 601P (Zeiss). IOLs were first immersed in saline at 45 °C for 24 h and then at 37 °C for 2.5 h in a water bath. Microvacuole (MV) density and size (Miyata grading) were documented and calculated using an image analysis program. Results The mean glistening density [MV/mm2] and mean Miyata grading (in brackets) were: Vivinex: 11.6 ± 5.7 (0), SN60WF: 264.4 ± 110.3 (2.6), Tecnis: 6.0 ± 2.8 (0), Avansee: 2.2 ± 0.7 (0), Aktis: 851.4 ± 59.4 (3+) and CT Lucia: 71.0 ± 71.6 (1). Conclusions While all tested IOLs showed glistenings with the accelerated laboratory method, the Aktis and SN60WF showed the highest microvacuole density, followed by the CT Lucia. In comparison, the Vivinex, Tecnis, and Avansee IOLs showed far fewer number of glistenings.

Rainfall patterns in a major wheat-growing region of Australia

1993 ◽  
Vol 44 (4) ◽  
pp. 609 ◽  
Author(s):  
R Boer ◽  
DJ Fletcher ◽  
LC Campbell
Keyword(s):  
Prediction Error ◽  
Summer Rainfall ◽  
Important Variable ◽  
Regression Equations ◽  
Winter Rainfall ◽  
Rainfall Prediction ◽  
The Mean ◽  
Production Areas ◽  
Growing Region ◽  
Mean Prediction Error

Rainfall is an important variable in the wheat production areas of Australia. This analysis examines, firstly, the pattern of rainfall over 2.3 million ha of a high-quality wheat-producing region, and secondly, develops regression equations for rainfall prediction over this region. Most of the variation in rainfall pattern across the region is accounted for by differences in October-to-March (summer) rainfall and in April-to-September (winter) rainfall. The summer rainfall differences account for over two thirds of the variation. Based on these two rainfall periods, a partitioning of the study area reveals five distinct regions. The second part of the analysis uses multiple regression to provide a set of equations for rainfall prediction at any location in the region, for a number of rainfall periods. These equations use altitude, longitude and latitude as predictors. Nearly all of the equations explain between 80% and 94% of the variation in rainfall. Differences between regions are accounted for in the analysis, making the equations widely applicable. The validity of the mean rainfall equations was tested on three further sites: the mean prediction error was 6.9%. This approach may be applicable where large land masses with similar geographical features occur.

Increasing Hemoglobin Levels with Epoetin Alfa in Anemic Hematologic Cancer Patients Receiving Chemotherapy Correlates Significantly with Improved Quality of Life.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2213-2213
Author(s):  
Jean-Luc Harousseau ◽  
Pierre Fumoleau ◽  
Winand Lange ◽  
Manfred Welslau
Keyword(s):  
Quality Of Life ◽  
Total Population ◽  
Poor Performance ◽  
Epoetin Alfa ◽  
Analog Scale ◽  
Open Label ◽  
Linear Analog ◽  
The Mean ◽  
Clinically Significant

Abstract The majority of patients (pts) with hematologic malignancies (HM) are anemic and often have poor performance scores (Ludwig H et al. Blood.2002;100:234a). The correlation between increases in hemoglobin (Hb) with epoetin alfa and improvements in quality of life (QOL) was evaluated in this open-label, multicenter study that enrolled 736 adult pts with various solid tumors and HM (n = 122) who were receiving cytotoxic chemotherapy and had Hb levels <12 g/dL. Epoetin alfa was administered 150 IU/kg or 10,000 IU 3 times weekly (TIW) for a maximum 28 weeks (wks); dose was increased to 300 IU/kg or 20,000 IU TIW if Hb was not increased >1 g/dL above baseline within 4 wks. Results for pts with HM are compared to results from a similar 16-wk trial that included pts with HM (n = 488) and used the 40,000 IU once-weekly (QW) dose, increased to 60,000 IU QW if Hb did not increase ≥1 g/dL within 4 wks (Gabrilove J et al. Int J Hematol.2000;72:55). In the TIW study, the primary efficacy endpoint was change in QOL as measured by the Functional Assessment of Cancer Therapy-General (FACT-G), including subscales for anemia (FACT-An) and fatigue; the FACT was administered at study entry, at 8–9 wks, and at 12 wks. QOL was additionally measured by the Cancer Linear Analog Scale (CLAS; also known as the Linear Analog Scale Assessment [LASA]) administered at every study visit. Dose increases were similar in both studies (33.6% of pts in the TIW study; 36.7% of pts in the QW study). In the TIW study, mean baseline Hb was 9.6 g/dL; mean Hb increased at 4–6 wks (1.35 g/dL), 8–9 wks (2.09 g/dL) and 12 wks (2.46 g/dL) to a mean Hb of 12.0 g/dL. Almost half the HM patients in the TIW study (48.1%) had a complete response (Hb increase ≥2 g/dL without blood transfusion). Hematologic results are similar to those reported in the QW study where mean Hb increased 1.96 g/dL by end of study (P = .0001). QOL improvements were also similar between studies. Mean FACT-An scores for the total population in the TIW study increased 6.7 points after 12 wks, which is clinically significant (Patrick DL et al. Eur J Cancer.2003;39:335–345). The mean increase for overall FACT-G correlated significantly with increased Hb at 12 wks (P <.0001; r = .262). Mean CLAS scores for the total population increased steadily throughout the study. At 12 wks mean increases (based on the 100-mm scale) were clinically significant (Patrick et al): 10.9 mm for Energy, 11.2 mm for Daily Activity, and 10.3 mm for Overall QOL. Mean change for FACT-An for patients from the total population in the QW study (n = 2,230) was 6.0 points (P <.001), which is comparable to the mean changes in the TIW study and the HM population of the QW study (6.59 points, P <.0001). No unexpected adverse events were reported. Epoetin alfa TIW or QW was shown to steadily increase Hb, which significantly correlated with clinically significant improvements in QOL.

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