David L. Cooke

Difluprednate ophthalmic emulsion 0.05% for postoperative inflammation and pain

PURPOSE: To assess the efficacy and safety of difluprednate ophthalmic emulsion 0.05% (Durezol) 2 or 4 times a day compared with those of a placebo in the treatment of inflammation and pain associated with ocular surgery. SETTING: Twenty‐six clinics in the United States. METHODS: One day after unilateral ocular surgery, patients who had an anterior chamber cell grade of 2 or higher (>10 cells) were treated with 1 drop of difluprednate 2 times or 4 times a day or with a placebo (vehicle) 2 times or 4 times a day in the study eye for 14 days. This was followed by a 14‐day tapering period and a 7‐day safety evaluation. Outcome measures included cleared anterior chamber inflammation (grade 0, ≤1 cell), absence of pain, and analysis of ocular adverse events. RESULTS: Of the 438 patients, 111 received difluprednate 2 times a day, 107 received difluprednate 4 times a day, and 220 received a placebo 2 or 4 times a day. Both difluprednate dosage regimens reduced postoperative ocular inflammation and pain safely and effectively compared with the placebo. A greater proportion of difluprednate‐treated patients had a reduction in inflammation and pain at 8 days and 15 days. Three percent of patients in both difluprednate groups had a clinically significant IOP rise (≥10 mm Hg and ≥21 mm Hg from baseline, respectively) versus 1% in the placebo group. CONCLUSIONS: Difluprednate given 2 or 4 times a day cleared postoperative inflammation and reduced pain rapidly and effectively. There were no serious ocular adverse events. Fewer adverse events were reported in the difluprednate‐treated groups than in the placebo group.

Improving the prediction accuracy of the SRK/T formula: the T2 formula.

PURPOSE: To investigate the causes of nonphysiologic behavior of the SRK/T formula, assess their clinical significance, and develop and evaluate solutions. SETTING: Two NHS ophthalmology departments, United Kingdom, and a private practice, United States. DESIGN: Evaluation of technology. METHODS: The individual steps of the SRK/T formula were examined for nonphysiologic behavior, and the clinical significance of behaviors was assessed with reference to a database of biometry and refractive outcomes in 11 189 eyes. The full data set was divided into 2 subsets, the first to develop solutions to nonphysiologic behavior of the SRK/T formula and the second to evaluate their performance. RESULTS: The SRK/T formula showed nonphysiologic behavior in the calculation of corrected axial length and corneal height. Although the former is of little clinical significance, the latter showed a systematic error that contributes to inaccurate intraocular lens (IOL) power prediction. The T2 formula was developed using a regression formula for corneal height derived from the development subset. Comparison of the performance of the T2 and SRK/T formulas using the evaluation subset showed significant improvement in the mean absolute error with the T2 formula (0.3064 diopter [D] versus 0.3229 D; P<.0001). On average, the prediction error with the T2 formula was 9.7% less than with the SRK/T formula, with significantly higher proportions of eyes within ±0.50 D of target (P<.0001). CONCLUSIONS: The SRK/T formula has nonphysiologic behavior that contributes to IOL power prediction errors. A modification to the formula algorithm, the T2 formula, can be directly substituted for SRK/T, resulting in significantly improved prediction accuracy. Financial Disclosure: No author has a financial or proprietary interest in any material or method mentioned.

Comparison of 9 intraocular lens power calculation formulas

Purpose To evaluate the accuracy of 9 intraocular lens (IOL) calculation formulas using 2 optical biometers. Setting Private practice, Saint Joseph, Michigan, USA. Design Retrospective consecutive case series. Methods Nine IOL power formula predictions with observed refractions after cataract surgery were compared using 1 IOL platform. The performance of each formula was ranked for accuracy by machine and by axial length (AL). The Olsen was further divided by a preinstalled version (OlsenOLCR) and a purchased version (OlsenStandalone). The Holladay 2 was divided by whether a refraction was entered (Holladay 2PreSurgRef) or not (Holladay 2NoRef). The OLCR device used in the study was the Lenstar L5 900 and the PCI device, the IOLMaster. Results The formulas were ranked by the standard deviation of the prediction error (optical low‐coherence reflectometry [OLCR], partial coherence interferometry [PCI]) as follows: OlsenStandalone (0.361, 0.446), Barrett Universal II (0.365, 0.387), OlsenOLCR (0.378, not applicable), Haigis (0.393, 0.401), T2 (0.397, 0.404), Super Formula (0.403, 0.410), Holladay 2NoRef (0.404, 0.417), Holladay 1 (0.408, 0.414), Holladay 2PreSurgRef (0.423, 0.432), Hoffer Q (0.428, 0.432), and SRK/T (0.433, 0.44). Conclusions The formulas gave different results depending on which machine measurements were used. The Olsen formula was the most accurate with OLCR measurements, significantly better than the best formula with PCI measurements. The Olsen was better, regardless of AL. If only PCI measurements (without lens thickness) were available, the Barrett Universal II performed the best and the Olsen formula performed the worst. The preinstalled version of Olsen was not as good as the standalone version. The Holladay 2 formula performed better when the preoperative refraction was excluded. Financial Disclosure Neither author has a financial or proprietary interest in any material or method mentioned.

Resolution of negative dysphotopsia after laser anterior capsulotomy.

UNLABELLED It has been suggested that a clear anterior nasal capsule contributes to negative dysphotopsia and that symptoms may resolve with opacification of the capsule. We describe a case in which negative dysphotopsia occurred despite a translucent anterior peripheral capsule and resolved following laser removal of the anterior nasal capsule. FINANCIAL DISCLOSURE No author has a financial or proprietary interest in any material or method mentioned.

Negative dysphotopsia after temporal corneal incisions.

Temporal incisions made during cataract extraction have been purported to cause negative dysphotopsia. A case in which negative dysphotopsia occurred after superior scleral tunnel incisions is described. The dystopsia symptoms resolved immediately after intraocular lens exchange using temporal corneal incisions.

Simulation of toric intraocular lens results: Manual keratometry versus dual-zone automated keratometry from an integrated biometer

PURPOSE: To evaluate simulated clinical outcomes in patients with toric intraocular lenses (IOLs) calculated on the basis of dual‐zone automated keratometry from an integrated optical biometer, relative to manual keratometry. SETTING: Private practice, Mesa, Arizona, USA. DESIGN: Comparative case series. METHODS: Patient records at 4 clinical sites were reviewed to identify patients who had manual keratometry and biometry with the Lenstar LS 900 recorded before toric IOL implantation and refractive follow‐up data after implantation. Preoperative and operative data were extracted from patient charts. Simulated refractive outcomes were calculated based on mathematically removing the actual IOL implanted and then mathematically inserting the IOLs as determined by manual or automated keratometry from the biometry device. RESULTS: Data for 128 patients were available for analysis. The actual residual astigmatism was comparable between manual keratometry and automated keratometry from the biometry system. Although simulated residual refractive astigmatism was similar between the 2 devices on average, there was variability in results by patient. Simulated residual refractive astigmatism was lower for the biometer when the standard deviation of the angle of astigmatism was low. Site‐to‐site variability was lower with the biometer than with manual keratometry. CONCLUSIONS: Simulated outcomes suggest that overall results for a group of patients whose toric IOL surgery planning is performed with the dual‐zone automated keratometry data from the biometer will be equivalent to those when manual keratometry is used. The reduced site‐to‐site variability with the biometer suggests an operational advantage. Financial Disclosure: No author has a financial or proprietary interest in any material or method mentioned.

Accuracy and precision of a new system for measuring toric intraocular lens axis rotation

&NA; We determined the accuracy and precision of a new system for measuring postoperative toric intraocular lens (IOL) axis rotation. The system performs high‐resolution retroillumination photography to identify toric IOL axis markings and then takes a photograph of the iris and conjunctival/scleral vessels. Built‐in software measures the toric axis to within 0.2 degree. If performed twice on the same eye, the system will correct the 2 toric axis measurements for cyclorotation/head tilt using iris/vessel registration. Testing in 37 eyes showed that using iris/vessel registration correction reduced the mean absolute toric IOL axis rotation by a factor of 4.5. We conclude that this system seems to be both accurate and precise for measuring postoperative toric IOL axis rotation. Financial Disclosure Dr. Sanders and Dr. Sarver have a financial interest in the imaging/measurement system. Dr. Cooke has no financial or proprietary interest in any material or method mentioned.

Prediction accuracy of preinstalled formulas on 2 optical biometers.

Purpose To evaluate how well partial coherence interferometry (PCI) (IOLMaster) and optical low‐coherence reflectometry (OLCR) (Lenstar LS 900) predict postoperative refractions using only the formulas that come preinstalled on the machines. Setting Private practice, Saint Joseph, Michigan, USA. Design Retrospective consecutive case series. Methods Eyes were measured with 2 biometers before cataract surgery. Six formulas were ranked by machine. Formulas were also ranked for extremely long and short eyes by averaging the ranks of 6 statistics (mean error, mean absolute error, standard deviation [SD], maximum error, and percentage of eyes within ±0.5 diopter [D] and ±1.0 D of prediction). Results Formulas were ranked by the SD of the prediction errors. The OLCR device outperformed the PCI device using the preinstalled formulas. The Olsen formula performed the best (0.378) but was preinstalled on the OLCR device only. Other formulas had the following SDs (OLCR device first, PCI device second): Haigis (0.393, 0.401), Holladay 1 (0.408, 0.414), Hoffer Q (0.428, 0.432), SRK/T (0.433, 0.440), and SRK II (0.623, 0.633). Rankings for long eye were (first to last) were Olsen, Haigis, SRK/T, Hoffer Q, and Holladay 1. Rankings for short eyes were Olsen, Haigis, Holladay 1, SRK/T, and Hoffer Q. Conclusions The OLCR device outperformed the PCI device using the Olsen formula. The Olsen formula also ranked first for short eyes and long eyes. Other formulas performed about the same on both machines. The SRK II formula should be avoided. Financial Disclosure Neither author has a financial or proprietary interest in any material or method mentioned.

Effect of altering lens constants

Figure 1.Mean prediction change versus lens constant change. Formulas that used an A-constant were evaluated separately. The change in the mean predicted refraction for our entire database was 1.3357 the change in lens constant. Although all intraocular lenses (IOLs) come with a lens constant on the box, optimized lens constants are not always known. One might consider using a lens constant from a journal article or from the User Group for Laser Interference Biometry (ULIB). The ULIB periodically updates its values, but some of the changes seem quite small. We wondered when it is worthwhile to update our IOL constants. How much does a prediction change when a lens constant is changed? We recently evaluated a database that comprised 1079 eyes that had cataract extraction by small-incision phacoemulsification and implantation of an Acrysof SN60WF IOL (Alcon Laboratories, Inc.). The lens constants for the entire database were optimized for 8 IOL formulas, which reduced the mean prediction errors to zero. In this current study, the lens constants were altered by 7 amounts ranging from 0.15 to C0.50. The prediction changes are shown Table 1. Three lens constants were used for Haigis: a0, a1, and a2. Note that of these, only a0 was altered. All formulas behaved almost identically except the 2 that used an A-constant. For this reason, the 2 formulas that used an A-constant are listed at the bottom of the table. The data in each cell of Table 1 represent a formula’s mean refractive change for the entire dataset of 1079 eyes after a lens constant change was applied. The mean change in predicted refraction of the entire dataset that was induced by a change in the lens constant value was highly consistent between formulas. Individual eyes will not always respond as the table indicates. (The same change in lens constant alters predictions more for short eyes than for long eyes.) The results of the mean of the top 6 formulas in Table 1 are shown in Figure 1. Holladay 1 uses a surgeon factor, and Holladay 2 uses an anterior chamber depth, which is often 3 to 4 times in magnitude. It was surprising that all formula predictions changed the same amount for a given change in their respective lens constants. When 0.15 was added to each lens constant, even if 2 lens constants were markedly

Correlation between preoperative refraction and other variables

of scores is not presented anywhere in the paper, the standard deviations are expressed as bars in Figure 1 in the article. Note that neither a 16 nor a 2 are represented in the standard deviation bars. Furthermore, the bars demonstrate the large variability in these scores, again calling into question the statistical analysis provided and the selection of these 2 representative photographs. The authors performed statistical analysis using the chi-square test with P values obtained via the Fischer exact test. This test is appropriate for comparison of 2 groups. However, this study uses a 4-treatment, 2vehicle design. In the Wilcoxon rank sum test used for post-comparison analysis, the authors appropriately adjusted for the multiple comparisons using the Bonferroni correction, obtaining a critical value of P%0.0083 for significance. This correction should also have been applied in Table 2 in the article, where none of the P values were less than 0.0083 and, therefore, the differences between the treatment groups were not statistically significant. The authors were incorrect in stating that the difference in clinical scores between the collagen shield treatments was statistically significant. Their own post-comparison analysis demonstrates this lack of a meaningful difference between the gatifloxacin and moxifloxacin groups. In light of the above concerns, the conclusion that ‘‘gatifloxacin.was statistically superior to placebo in treating or preventing endophthalmitis and that moxifloxacinwas not superior’’ is misleading due to lack of laboratory data and statistical evidence.