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Validation of Novel Metrics from the Accommodative Dynamic Profile

机译:从适应性动态配置文件中验证新指标

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摘要

Objective and subjective methods of assessing time taken for accommodative change (ToAC) include accommodative dynamics (AD) and accommodative facility (AF). This study investigates the validity of novel metrics derived from the AD-profile and explores their relationship with AF. AD were assessed using a modified open-field autorefractor in 43 healthy adults. Non-linear regression curves were fitted to the data to derive: latency-of-accommodation (nLoA) and -disaccomodation (nLoD), Time-for-accommodation (ToA) and -disaccommodation (ToD), and objective-ToAC (oToAC). Latencies were also calculated through visual inspection of the AD data as in previous studies (pLoA and pLoD). AF was used to assess subjective-ToAC. Statistical analysis explored the relationships between the AD-metrics and AF. Subjects were assessed on three visits to examine intra- and inter-observer repeatability. nLoA and nLoD were greater than pLoA ( = 0.001) and pLoD ( = 0.004) respectively. nLoA and nLoD also demonstrated greater intra- and inter-observer repeatability than pLoA and pLoD. AF demonstrated a moderate, inverse correlation with ToA ( = 0.02), ToD ( = 0.007), and oToAC ( = 0.007). ToD was the single best accommodative predictor of AF ( = 0.011). The novel method for deriving latency was more repeatable, but not interchangeable with the techniques used in previous studies. ToD was the most repeatable metric with the greatest association with AF.
机译:评估适应性变化所需时间的主观和主观方法(ToAC)包括适应性动态(AD)和适应性设施(AF)。这项研究调查了从AD资料得出的新颖指标的有效性,并探讨了它们与AF的关系。使用改良的开放视野自动验光仪评估43位健康成年人的AD。将非线性回归曲线拟合到数据以得出:适应潜伏期(nLoA)和-适应不适应(nLoD),适应时间(ToA)和-适应不适应(ToD)以及客观-ToAC(oToAC) 。如以前的研究(pLoA和pLoD)一样,还通过目视检查AD数据来计算潜伏期。 AF用于评估主观ToAC。统计分析探讨了AD指标和AF之间的关系。在三次访问中对受试者进行评估,以检查观察者之间和观察者之间的重复性。 nLoA和nLoD分别大于pLoA(= 0.001)和pLoD(= 0.004)。 nLoA和nLoD还显示出比pLoA和pLoD更好的观察者内和观察者间重复性。 AF与ToA(= 0.02),ToD(= 0.007)和oToAC(= 0.007)呈中等程度的逆相关。 ToD是AF的最佳最佳适应性预测因子(= 0.011)。推导延迟的新方法更具可重复性,但不能与以前的研究中使用的技术互换。 ToD是与AF关联最大的可重复性最强的指标。

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