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1.
J Ophthalmol ; 2022: 9355206, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-35942064

RESUMEN

Purpose: The aim is to evaluate the effect of amniotic membrane transplantation (AMT) on trabeculectomy with mitomycin C in patients with pseudoexfoliation glaucoma (PXG). Methods: This retrospective cohort study included 85 eyes of PXG who underwent trabeculectomy with or without AMT (52/33 eyes in the AMT/control group). Surgical success was defined by these criteria: (1) intraocular pressure (IOP) ≤18 mmHg and IOP reduction ≥20% and (2) IOP ≤15 mmHg and IOP reduction ≥25%. Criteria A and B defined complete success rates as patients who met these criteria without medication, respectively. Criteria C and D defined qualified success rates as patients who met these criteria with medication, respectively. Cumulative probabilities of success were compared using the Kaplan-Meier survival analysis. Cox proportional hazard models were used to evaluate the influence of AMT on surgical success accounting for confounding variables. Results: For the AMT group, compared with the control group, the complete success rates at 12 months for criterion A were 86.5% and 63.6%, respectively (P = 0.017) and for criterion B, 86.4% and 63.6% (P = 0.005). The qualified success rates at 12 months for criterion C were 92.1% and 75.1%, respectively (P = 0.047) and for criterion D, 92.1% and 72.1% (P = 0.021). On multivariable Cox regression analyses, AMT was associated with a lower failure rate on criteria A, B, and D (all P ≤ 0.047). Incidence of avascular bleb was higher in the control group than in the AMT group (7 vs 0 eyes; P = 0.004). Conclusions: In patients with PXG, trabeculectomy with AMT was associated with higher success rates and a lower incidence of avascular bleb compared with conventional trabeculectomy. Research Registration. This retrospective cohort study was registered at the Clinical Trial Registry of Korea (https://cris.nih.go.kr/cris/index/index.do, KCT0007228).

2.
Eur J Ophthalmol ; 31(5): 2738-2745, 2021 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-32757633

RESUMEN

PURPOSE: To evaluate the peripapillary retinal nerve fiber layer (RNFL) and macular ganglion cell-inner plexiform layer (GCIPL) measurements using spectral domain optical coherence tomography (SD-OCT) in patients with chiasmal compression and analyze the diagnostic value of a neural network model. METHODS: Forty-seven patients with chiasmal compressive disorder were recruited and divided into two groups depending on the visual field defect (perimetric; group 1 and preperimetric; group 2). Fifty-seven normal subjects were also recruited (group 3). Peripapillary RNFL and macular GCIPL were analyzed in each group. A multilayer perceptron was trained using a training dataset and derived a neural network model. The diagnostic performances were compared using the area under the receiver operating curve (AUROC) between each parameters and neural network model. RESULTS: All macular GCIPL parameters, except inferotemporal GCIPL thickness, were thinner in group 1 than in group 2 and group 3, with barely any difference between group 2 and group 3 parameter values. The diagnostic power of the neural network model, minimum GCIPL, and inferonasal GCIPL were superior when compared with other parameters; the diagnostic values of these three parameters are not significantly different in discriminating the patients and normal control. However, the neural network exhibited the best diagnostic power in distinguishing group 2 and group 3. CONCLUSION: Macular GCIPL was reduced in chiasmal compression patients with visual field defect which was not evident in the preperimetric state. Neural network model showed superior diagnostic value in discriminating the preperimetric patients from normal control. The results suggest that neural networks may be helpful in the early diagnosis of chiasmal compression.


Asunto(s)
Tomografía de Coherencia Óptica , Campos Visuales , Humanos , Presión Intraocular , Redes Neurales de la Computación , Células Ganglionares de la Retina , Pruebas del Campo Visual
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