28 resultados para CORNEAL TRANSPLANTATION


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Purpose: To evaluate the correlation of the magnitude of corneal toricity and power vector components of both corneal surfaces measured with a Scheimpflug photography-based system. Methods: A total of 117 healthy normal eyes of 117 subjects selected randomly with ages ranging from 7 to 80 years were included. All eyes received an anterior segment and corneal analysis with the Sirius system (CSO) evaluating the anterior and posterior mean toricity for 3 and 7 mm (aAST and pAST). The vector components J0 and J45 as well as the overall strength blur (B) were calculated for each keratometric measurement using the procedure defined by Thibos and Horner. Results: The coefficient of correlation between aAST and pAST was 0.52 and 0.62 and the mean anteroposterior ratio for toricity was 0.46 ± 0.39 and 0.57 ± 0.75 for 3 and 7 mm, respectively. These ratios correlated significantly with aAST, anterior corneal J0, and manifest refraction J0 (r ≥ 0.39, P < 0.01). The coefficient of correlation was 0.69 and 0.81 between anterior and posterior J0 for 3 and 7 mm, respectively. For J45, the coefficients were 0.62 and 0.71, respectively. The linear regression analysis revealed that the pAST and power vectors could be predicted from the anterior corneal data (R2 ≥ 0.40, P < 0.01). Conclusions: The toricity and astigmatic power vector components of the posterior corneal surface in the human healthy eye are related to those of the anterior and therefore can be predicted consistently from the anterior toricity and astigmatic power vectors.

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Purpose: To evaluate the correlation of the mean curvature and shape factors of both corneal surfaces for different corneal diameters measured with the Scheimpflug photography–based system in keratoconus eyes. Methods: A total of 61 keratoconus eyes of 61 subjects, aged 14 to 64 years, were included in this study. All eyes received a comprehensive ophthalmologic examination including anterior segment and corneal analysis with the Sirius system (CSO): anterior and posterior mean corneal radius for 3, 5, and 7 mm (aKM, pKM), anterior and posterior mean shape factor for 4.5 and 8 mm (ap, pp), central and minimal corneal thickness, and anterior chamber depth. Results: Mean aKM/pKM ratio around 1.20 (range, 0.95–1.48) was found for all corneal diameters (P = 0.24). Weak but significant correlations of this ratio with pachymetric parameters were found (r between −0.28 and −0.34, P < 0.04). The correlation coefficient between aKM and pKM was ≥0.92 for all corneal diameters. A strong and significant correlation was also found between ap and pp (r ≥ 0.86, P < 0.01). The multiple regression analysis revealed that central pKM was significantly correlated with aKM, central corneal thickness, anterior chamber depth, and spherical equivalent (R2 ≥ 0.88, P < 0.01) and that 8 mm pp was significantly correlated with 8 mm ap and age (R2 = 0.89, P < 0.01). Conclusions: Central posterior corneal curvature and shape factor in the keratoconus eye can be consistently predicted from the anterior corneal curvature and shape factor, respectively, in combination with other anatomical and ocular parameters.

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Biomechanics is often defined as ‘mechanics applied to biology’. Due to the variety and complexity of the behaviour of biological structures and materials, biomechanics is better defined as the development, extension and application of mechanics for a better understanding of physiology and physiopathology and consequently for a better diagnosis and treatment of disease and injury. Different methods for the characterisation of corneal biomechanics are reviewed in detail, including those that are currently commercially available (Ocular Response Analyzer and CorVis ST). The clinical applicability of the parameters provided by these devices are discussed, especially in the fields of glaucoma, detection of ectatic disorders and orthokeratology. Likewise, other methods are also reviewed, such as Brillouin microscopy or dynamic optical coherence tomography and others with potential application to clinical practice but not validated for in vivo measurements, such as ultrasonic elastography. Advantages and disadvantages of all these techniques are described. Finally, the concept of biomechanical modelling is revised as well as the requirements for developing biomechanical models, with special emphasis on finite element modelling.

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Purpose: To evaluate the possible associations between corneal biomechanical parameters, optic disc morphology, and retinal nerve fiber layer (RNFL) thickness in healthy white Spanish children. Methods: This cross-sectional study included 100 myopic children and 99 emmetropic children as a control group, ranging in age from 6 to 17 years. The Ocular Response Analyzer was used to measure corneal hysteresis (CH) and corneal resistance factor. The optic disc morphology and RNFL thickness were assessed using posterior segment optical coherence tomography (Cirrus HD-OCT). The axial length was measured using an IOLMaster, whereas the central corneal thickness was measured by anterior segment optical coherence tomography (Visante OCT). Results: The mean (±SD) age and spherical equivalent were 12.11 (±2.76) years and −3.32 (±2.32) diopters for the myopic group and 11.88 (±2.97) years and +0.34 (±0.41) diopters for the emmetropic group. In a multivariable mixed-model analysis in myopic children, the average RNFL thickness and rim area correlated positively with CH (p = 0.007 and p = 0.001, respectively), whereas the average cup-to-disc area ratio correlated negatively with CH (p = 0.01). We did not observe correlation between RNFL thickness and axial length (p = 0.05). Corneal resistance factor was only positively correlated with the rim area (p = 0.001). The central corneal thickness did not correlate with the optic nerve parameters or with RNFL thickness. These associations were not found in the emmetropic group (p > 0.05 for all). Conclusions: The corneal biomechanics characterized with the Ocular Response Analyzer system are correlated with the optic disc profile and RNFL thickness in myopic children. Low CH values may indicate a reduction in the viscous dampening properties of the cornea and the sclera, especially in myopic children.

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Purpose: To evaluate the relationship between different ocular and corneal biomechanical parameters in emmetropic and ametropic healthy white children. Methods: This study included 293 eyes of 293 healthy Spanish children (135 boys and 158 girls), ranging in age from 6 to 17 years. Subjects were divided according to the refractive error: control (emmetropia, 99 children), myopia (100 children), and hyperopia (94 children) groups. In all cases, corneal hysteresis (CH) and corneal resistance factor (CRF) were evaluated with the Ocular Response Analyzer system. Axial length (AL) and mean corneal power were also measured by partial coherence interferometry (IOLMaster), and central corneal thickness (CCT) and anterior chamber depth were measured by anterior segment optical coherence tomography (Visante). Results: Mean (±SD) CH and CRF were 12.12 (±1.71) and 12.30 (±1.89) mm Hg, respectively. Mean (±SD) CCT was 542.68 (±37.20) μm and mean (±SD) spherical equivalent was +0.14 (±3.41) diopters. A positive correlation was found between CH and CRF (p < 0.001), and both correlated as well with CCT (p < 0.0001). Corneal resistance factor was found to decrease with increasing age (p = 0.01). Lower levels of CH were associated with longer AL and more myopia (p < 0.001 and p = 0.001, respectively). Higher values of CH were associated with increasing hyperopia. Significant differences in CH were found between emmetropic and myopic groups (p < 0.001) and between myopic and hyperopic groups (p = 0.011). There were also significant differences in CRF between emmetropic and myopic groups (p = 0.02). Multiple linear regression analysis showed that lower CH and CRF significantly associated with thinner CCT, longer AL, and flatter corneal curvature. Conclusions: The Ocular Response Analyzer corneal biomechanical properties seem to be compromised in myopia from an early age, especially in high myopia.

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The aim of this study was to obtain the exact value of the keratometric index (nkexact) and to clinically validate a variable keratometric index (nkadj) that minimizes this error. Methods: The nkexact value was determined by obtaining differences (DPc) between keratometric corneal power (Pk) and Gaussian corneal power (PGauss c ) equal to 0. The nkexact was defined as the value associated with an equivalent difference in the magnitude of DPc for extreme values of posterior corneal radius (r2c) for each anterior corneal radius value (r1c). This nkadj was considered for the calculation of the adjusted corneal power (Pkadj). Values of r1c ∈ (4.2, 8.5) mm and r2c ∈ (3.1, 8.2) mm were considered. Differences of True Net Power with PGauss c , Pkadj, and Pk(1.3375) were calculated in a clinical sample of 44 eyes with keratoconus. Results: nkexact ranged from 1.3153 to 1.3396 and nkadj from 1.3190 to 1.3339 depending on the eye model analyzed. All the nkadj values adjusted perfectly to 8 linear algorithms. Differences between Pkadj and PGauss c did not exceed 60.7 D (Diopter). Clinically, nk = 1.3375 was not valid in any case. Pkadj and True Net Power and Pk(1.3375) and Pkadj were statistically different (P , 0.01), whereas no differences were found between PGauss c and Pkadj (P . 0.01). Conclusions: The use of a single value of nk for the calculation of the total corneal power in keratoconus has been shown to be imprecise, leading to inaccuracies in the detection and classification of this corneal condition. Furthermore, our study shows the relevance of corneal thickness in corneal power calculations in keratoconus.

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Purpose: The aim of this study was to analyze theoretically the errors in the central corneal power calculation in eyes with keratoconus when a keratometric index (nk) is used and to clinically confirm the errors induced by this approach. Methods: Differences (DPc) between central corneal power estimation with the classical nk (Pk) and with the Gaussian equation (PGauss c ) in eyes with keratoconus were simulated and evaluated theoretically, considering the potential range of variation of the central radius of curvature of the anterior (r1c) and posterior (r2c) corneal surfaces. Further, these differences were also studied in a clinical sample including 44 keratoconic eyes (27 patients, age range: 14–73 years). The clinical agreement between Pk and PGauss c (true net power) obtained with a Scheimpflug photography–based topographer was evaluated in such eyes. Results: For nk = 1.3375, an overestimation was observed in most cases in the theoretical simulations, with DPc ranging from an underestimation of 20.1 diopters (D) (r1c = 7.9 mm and r2c = 8.2 mm) to an overestimation of 4.3 D (r1c = 4.7 mm and r2c = 3.1 mm). Clinically, Pk always overestimated the PGauss c given by the topography system in a range between 0.5 and 2.5 D (P , 0.01). The mean clinical DPc was 1.48 D, with limits of agreement of 0.71 and 2.25 D. A very strong statistically significant correlation was found between DPc and r2c (r = 20.93, P , 0.01). Conclusions: The use of a single value for nk for the calculation of corneal power is imprecise in keratoconus and can lead to significant clinical errors.

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Purpose: To evaluate the influence of the difference between preoperative corneal and refractive astigmatism [ocular residual astigmatism (ORA)] on outcomes obtained after laser in situ keratomileusis (LASIK) surgery for correction of myopic astigmatism using the solid-state laser technology. Methods: One hundred one consecutive eyes with myopia or myopic astigmatism of 55 patients undergoing LASIK surgery using the Pulzar Z1 solid-state laser (CustomVis Laser Pty Ltd, currently CV Laser) were included. Visual and refractive changes at 6 months postoperatively and changes in ORA and anterior corneal astigmatism and posterior corneal astigmatism (PCA) were analyzed. Results: Postoperatively, uncorrected distance visual acuity improved significantly (P < 0.01). Likewise, refractive cylinder magnitude and spherical equivalent were reduced significantly (P < 0.01). In contrast, no significant changes were observed in ORA magnitude (P = 0.81) and anterior corneal astigmatism (P = 0.12). The mean overall efficacy and safety indices were 0.96 and 1.01, respectively. These indices were not correlated with preoperative ORA (r = −0.15, P = 0.15). Furthermore, a significant correlation was found between ORA (r = 0.81, P < 0.01) and PCA postoperatively, but not preoperatively (r = 0.12, P = 0.25). Likewise, a significant correlation of ORA with manifest refraction was only found postoperatively (r = −0.38, P < 0.01). Conclusions: The magnitude of ORA does not seem to be a predictive factor of efficacy and safety of myopic LASIK using a solid-state laser platform. The higher relevance of PCA after surgery in some cases may explain the presence of unexpected astigmatic residual refractive errors.

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AIM: To evaluate the prediction error in intraocular lens (IOL) power calculation for a rotationally asymmetric refractive multifocal IOL and the impact on this error of the optimization of the keratometric estimation of the corneal power and the prediction of the effective lens position (ELP). METHODS: Retrospective study including a total of 25 eyes of 13 patients (age, 50 to 83y) with previous cataract surgery with implantation of the Lentis Mplus LS-312 IOL (Oculentis GmbH, Germany). In all cases, an adjusted IOL power (PIOLadj) was calculated based on Gaussian optics using a variable keratometric index value (nkadj) for the estimation of the corneal power (Pkadj) and on a new value for ELP (ELPadj) obtained by multiple regression analysis. This PIOLadj was compared with the IOL power implanted (PIOLReal) and the value proposed by three conventional formulas (Haigis, Hoffer Q and Holladay). RESULTS: PIOLReal was not significantly different than PIOLadj and Holladay IOL power (P>0.05). In the Bland and Altman analysis, PIOLadj showed lower mean difference (-0.07 D) and limits of agreement (of 1.47 and -1.61 D) when compared to PIOLReal than the IOL power value obtained with the Holladay formula. Furthermore, ELPadj was significantly lower than ELP calculated with other conventional formulas (P<0.01) and was found to be dependent on axial length, anterior chamber depth and Pkadj. CONCLUSION: Refractive outcomes after cataract surgery with implantation of the multifocal IOL Lentis Mplus LS-312 can be optimized by minimizing the keratometric error and by estimating ELP using a mathematical expression dependent on anatomical factors.

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Purpose: To analyze and define the possible errors that may be introduced in keratoconus classification when the keratometric corneal power is used in such classification. Materials and methods: Retrospective study including a total of 44 keratoconus eyes. A comprehensive ophthalmologic examination was performed in all cases, which included a corneal analysis with the Pentacam system (Oculus). Classical keratometric corneal power (Pk), Gaussian corneal power (Pc Gauss), True Net Power (TNP) (Gaussian power neglecting the corneal thickness effect), and an adjusted keratometric corneal power (Pkadj) (keratometric power considering a variable keratometric index) were calculated. All cases included in the study were classified according to five different classification systems: Alió-Shabayek, Amsler-Krumeich, Rabinowitz-McDonnell, collaborative longitudinal evaluation of keratoconus (CLEK), and McMahon. Results: When Pk and Pkadj were compared, differences in the type of grading of keratoconus cases was found in 13.6% of eyes when the Alió-Shabayek or the Amsler-Krumeich systems were used. Likewise, grading differences were observed in 22.7% of eyes with the Rabinowitz-McDonnell and McMahon classification systems and in 31.8% of eyes with the CLEK classification system. All reclassified cases using Pkadj were done in a less severe stage, indicating that the use of Pk may lead to the classification of a cornea as keratoconus, being normal. In general, the results obtained using Pkadj, Pc Gauss or the TNP were equivalent. Differences between Pkadj and Pc Gauss were within ± 0.7D. Conclusion: The use of classical keratometric corneal power may lead to incorrect grading of the severity of keratoconus, with a trend to a more severe grading.

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Purpose. To validate clinically a new method for estimating the corneal power (P,) using a variable keratometric index (nkadj) in eyes with previous laser refractive surgery. Setting. University of Alicante and Medimar International Hospital (Oftalmar), Alicante, (Spain). Design. Retrospective case series. Methods. This retrospective study comprised 62 eyes of 62 patients that had undergone myopic LASIK surgery. An algorithm for the calculation of 11kadj was used for the estimation of the adjusted keratometric corneal power (Pkadj). This value was compared with the classical keratometric corneal power (Pk), the True Net Power (TNP), and the Gaussian corneal power (PcGauss). Likewise, Pkadj was compared with other previously described methods. Results. Differences between PcGauss and P, values obtained with all methods evaluated were statistically significant (p < 0.01). Differences between Pkadj and PcGauss were in the limit of clinical significance (p < 0.01, loA [ - 0.33,0.60] D). Differences between Pkadj and TNP were not statistically and clinically significant (p = 0.319, loA [- 0.50,0.44] D). Differences between Pkadj and previously described methods were statistically significant (p < 0.01), except with PcHaigisL (p = 0.09, loA [ - 0.37,0.29] D). Conclusion. The use of the adjusted keratometric index (nkadj) is a valid method to estimate the central corneal power in corneas with previous myopic laser refractive surgery, providing results comparable to PcHaigisL.

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Diurnal changes in corneal geometry, pachymetry, and intraocular pressure (IOP) in a healthy eye were recorded. The deformation response to an air puff was simulated using 3 levels of corneal stiffness. The response was dependent on IOP and pachymetry and not only on the biomechanical properties of the cornea. Similarly, the maximum variability due to the diurnal changes in pachymetry and IOP in the corneal displacement generated by the air puff was found to reach 5%. Therefore, diurnal changes in IOP and corneal thickness were able to induce some variability in the air puff–based corneal deformation response. This potential variability should be considered when the biomechanical properties of the cornea are analyzed with air-puff devices.

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Purpose: To evaluate the predictability of the refractive correction achieved with a positional accommodating intraocular lenses (IOL) and to develop a potential optimization of it by minimizing the error associated with the keratometric estimation of the corneal power and by developing a predictive formula for the effective lens position (ELP). Materials and Methods: Clinical data from 25 eyes of 14 patients (age range, 52–77 years) and undergoing cataract surgery with implantation of the accommodating IOL Crystalens HD (Bausch and Lomb) were retrospectively reviewed. In all cases, the calculation of an adjusted IOL power (PIOLadj) based on Gaussian optics considering the residual refractive error was done using a variable keratometric index value (nkadj) for corneal power estimation with and without using an estimation algorithm for ELP obtained by multiple regression analysis (ELPadj). PIOLadj was compared to the real IOL power implanted (PIOLReal, calculated with the SRK-T formula) and also to the values estimated by the Haigis, HofferQ, and Holladay I formulas. Results: No statistically significant differences were found between PIOLReal and PIOLadj when ELPadj was used (P = 0.10), with a range of agreement between calculations of 1.23 D. In contrast, PIOLReal was significantly higher when compared to PIOLadj without using ELPadj and also compared to the values estimated by the other formulas. Conclusions: Predictable refractive outcomes can be obtained with the accommodating IOL Crystalens HD using a variable keratometric index for corneal power estimation and by estimating ELP with an algorithm dependent on anatomical factors and age.