Objective To observe the characteristics of fundus fluorescein angiography (FFA) in different types of pathologic myopic maculopathy and evaluate the influence factor.Methods The clinical data of 251 patients (451 eyes) with pathologic myopic maculopathy were retrospectively analyzed. The patients were divided into 6 groups according to FFA characteristics: (1) lacquer cracks (LC); (2) choroidal neovascularization (CNV); (3) macular hemorrhage with LCs; (4) Fuchs spots; (5) macular atrophy; (6) macular hole. Their relationship with age, gender, refraction and (BCVA) were analyzed.Results Older age was significantly associated with CNV and macular atrophy (OR=1.034,CI=1.019-1.049,P＜0.001;OR=1.054,CI=1.031-1.076,P＜0.001; respectively);younger age was associated with hemorrhage with LC (OR=0.906,CI=0.876-0.937,P＜0.001). Higher myopic refractive error was associated with macular atrophy (OR=0.762,CI=0.705-0.824,P＜0.001), whereas lower myopic refractive error was associated with CNV and macular hole(OR=1.233,CI=1.136-1.338,P＜0.001;OR=1.554,CI=1.185-2.038,P＜0.001; respectively). A worse visual acuity was associated with CNV (OR=1.835,CI=1.180 -2.854,P=0.007), while better visual acuity was associated with LC (OR=0.506,CI=0.328 - 0.782,P=0.002). There was no gender difference in distribution of high myopic maculopathy types. Conclusions Pathologic myopic maculopathy can be divided into six types. With increasing age, the incidence rates of CNV and macular atrophy increases, hemorrhage with LC but decreases. With the rise of myopic refractive, the incidence rates of CNV and macular hole decreases, macular atrophy but increases.
Early detection of vascular function plays an important role in the prevention and treatment of cardiovascular diseases (CVDs). This paper reports the main studies of the effectiveness of fingertip temperature curve in digital thermal monitoring (DTM) for predicting CVDs, as well as the relationship between parameters from DTM and pulse wave velocity (PWV) detection. A total of 112 subjects [age (42.18±12.28) years, 50% male, 37 with known CVDs] underwent DTM and PWV detection. Results showed that most of parameters related to CVDs were from the declining stage of the digital thermal signal. Binary Logistic regression models were built, and the best one was chosen by ten-fold validation to predict CVDs. Consistency was great between the detection result of PWV and that of the Logistic model of DTM parameters. Parameters from DTM also contained information for early detecting of vascular stiffness. This study indicates that the fingertip temperature curve in DTM has a potential application for predication of CVDs, and it would be used to access vascular function in the initial stage of CVDs.