Scheimpflug-Based Corneal Biomechanical Analysis As A Predictor of Glaucoma in Eyes With High Myopia

Pedro ML Baptista,1,2 André S Ferreira,1,3 Nisa P Silva,1 Ana RM Figueiredo,1 Isabel C Sampaio,1 Rita VF Reis,1 Renato Ambrósio Jr,4– 8 Pedro M A M Menéres,1,2 João N M Beirão,1,2 Maria J F S Menéres1,2 1Ophthalmology Department, Centro Hospitalar Universitário do Porto, Porto, Portugal; 2Instituto de Ciências Biomédicas Abel Salazar, Universidade do Porto, Porto, Portugal; 3Faculdade de Medicina da Universidade do Porto, Universidade do Porto, Porto, Portugal; 4Rio de Janeiro Corneal Tomography and Biomechanics Study Group, Rio de Janeiro, RJ, Brazil; 5Department of Cornea and Refractive Surgery, Instituto de Olhos Renato Ambrósio, Rio de Janeiro, Brazil; 6Department of Ophthalmology, Federal University of the State of Rio de Janeiro (UNIRIO), Rio de Janeiro, Brazil; 7Federal University of São Paulo (UNIFESP), São Paulo, Brazil; 8Brazilian Study Group of Artificial Intelligence and Corneal Analysis - BrAIN, Rio de Janeiro & Maceió, BrazilCorrespondence: Pedro ML Baptista, Centro Hospitalar Universitário do Porto, Largo Prof. Abel Salazar 4099-001 Porto, Portugal, Email [email protected]: To address if corneal biomechanical behavior has a predictive value for the presence of glaucomatous optical neuropathy in eyes with high myopia.Patients and Methods: This observational cross-sectional study included 209 eyes from 108 consecutive patients, divided into four groups: high myopia and primary open-angle glaucoma (POAG) – HMG, n = 53; high myopia without POAG – HMNG, n = 53; non-myopic with POAG – POAG, n = 50; non-myopic and non-POAG– NMNG, n = 53. Biomechanical assessment was made through a Scheimpflug-camera-based technology. Receiver operating characteristic curves were made for the discrimination between groups. Multivariable logistic regression models were performed to address the predictive value of corneal biomechanics for the presence of glaucoma.Results: Areas Under the Receiver Operating Characteristic (AUROCs) above 0.6 were found in 6 parameters applied to discriminate between HMG and HMNG and six parameters to discriminate between POAG and NMNG. The biomechanical models with the highest power of prediction for the presence of glaucoma included 5 parameters with an AUROC of 0.947 for eyes with high myopia and 6 parameters with an AUROC of 0.857 for non-myopic eyes. In the final model, including all eyes, and adjusted for the presence of high myopia, the highest power of prediction for the presence of glaucoma was achieved including eight biomechanical parameters, with an AUROC of 0.917.Conclusion: Corneal biomechanics demonstrated differences in eyes with glaucoma and mainly in myopic eyes. A biomechanical model based on multivariable logistic regression analysis and adjusted for high myopia was built, with an overall probability of 91.7% for the correct prediction of glaucomatous damage.Plain Language Summary: High myopia and glaucoma are two entities with a worldwide growing prevalence and with a great visual, social and economic impact. High myopic eyes have a greater risk of glaucomatous damage, but early diagnosis is difficult due to the particularities of the eyes. This study asks if corneal biomechanics assessment can have a role in the risk prediction of glaucomatous damage in eyes with high myopia. As a strong biomechanical model for the correct prediction of glaucomatous damage was built, corneal biomechanics study can be a useful tool in the management of high myopic eyes with suspected glaucoma.Keywords: corneal biomechanics, corvis, glaucoma, high myopia, intraocular pressure, Scheimpflug camer

Pattern and process in Amazon tree turnover, 1976-2001.

Previous work has shown that tree turnover, tree biomass and large liana densities have increased in mature tropical forest plots in the late twentieth century. These results point to a concerted shift in forest ecological processes that may already be having significant impacts on terrestrial carbon stocks, fluxes and biodiversity. However, the findings have proved controversial, partly because a rather limited number of permanent plots have been monitored for rather short periods. The aim of this paper is to characterize regional-scale patterns of 'tree turnover' (the rate with which trees die and recruit into a population) by using improved datasets now available for Amazonia that span the past 25 years. Specifically, we assess whether concerted changes in turnover are occurring, and if so whether they are general throughout the Amazon or restricted to one region or environmental zone. In addition, we ask whether they are driven by changes in recruitment, mortality or both. We find that: (i) trees 10 cm or more in diameter recruit and die twice as fast on the richer soils of southern and western Amazonia than on the poorer soils of eastern and central Amazonia; (ii) turnover rates have increased throughout Amazonia over the past two decades; (iii) mortality and recruitment rates have both increased significantly in every region and environmental zone, with the exception of mortality in eastern Amazonia; (iv) recruitment rates have consistently exceeded mortality rates; (v) absolute increases in recruitment and mortality rates are greatest in western Amazonian sites; and (vi) mortality appears to be lagging recruitment at regional scales. These spatial patterns and temporal trends are not caused by obvious artefacts in the data or the analyses. The trends cannot be directly driven by a mortality driver (such as increased drought or fragmentation-related death) because the biomass in these forests has simultaneously increased. Our findings therefore indicate that long-acting and widespread environmental changes are stimulating the growth and productivity of Amazon forests