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Segmental Inner Macular Layer Analysis with Spectral-domain Optical Coherence Tomography for Early Detection of Normal Tension Glaucoma.xlsx

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DataCite Commons2020-08-27 更新2024-07-27 收录
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https://figshare.com/articles/Segmental_Inner_Macular_Layer_Analysis_with_Spectral-domain_Optical_Coherence_Tomography_for_Early_Detection_of_Normal_Tension_Glaucoma_xlsx/7497128
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2: normal subjects; 3: PPG; 1: NTGSOMT: means total macular thickness at SOMSOMN: mRNFL at SOMSOMG: mGCL at SOMWe chose parameters at the superior and inferior quadrants for the statistical analysis, as they are commonly affected in glaucoma. The superior macular thickness was defined as the average thickness of the superior-outer macular (SOM) and superior-inner macular (SIM) sectors. The inferior macular thickness was defined as the average thickness of the inferior-outer macular (IOM) and inferior-inner macular (IIM) sectors. <br>The characteristics of the participants were assessed by one-way analysis of variance (ANOVA), and the χ<sup>2</sup> test was used to analyze the gender parameter. A post hoc test with Scheffe adjustment was used to determine significance between any two groups. One-way ANOVA was also conducted to assess differences in the thicknesses of the pRNFL, TML, mRNFL, and mGCL among the groups. The normal distribution was verified using a histogram test. Statistical associations among macular values, pRNFL, and visual function were evaluated by Pearson’s correlation coefficient. Areas under the receiver operating characteristic (AUROC) curves were used to assess the diagnostic capabilities of retinal layers. Significant differences between AUROCs were calculated using the DeLong test. A<i> p </i>value &lt;0.05 represents a significant difference. All statistical analyses were performed in SPSS statistical software (version 18.0; SPSS, Inc., Chicago, IL), except the DeLong test, which was performed in MedCalc-statistical-software (Version 16.8.4).
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figshare
创建时间:
2018-12-21
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