## 3 Results  
Through the above-mentioned search criteria, 241 research publications were retrieved within the 20 years period (2000-2019). Of these, 85.89% (\(n=207\)) were Original articles, while the others, 14.11%, correspond to Reviews, Letters, Conference Papers, Notes, Book chapters, Editorials, and Short Surveys respectively (Figure 1). Figure 2 shows the increase in the number of documents in the area on retinal nerve fiber thickness research over time. After applying the mathematical adjustments to a linear curve, we have obtained a correlation coefficient of 0.885, which indicates 11.50% of variability unexplained by this adjustment, and a correlation coefficient of 0.869 after performing an exponential adjustment (13.1% of variability unexplained). These data allow us to confirm that the analyzed sample fits the linear model more than the exponential model, therefore, it does not comply with the postulates of the Price law. Figure 1: Literature contribution of different types of papers. The distribution in 5-year periods shows that the time frame 2019-2015 contains the most documents, with more than 50% of the total, as displayed in Figure 3. It also reflects a 34.78% increase with respect to the previous period, and an average of 42.32% in the last 4 five years, illustrating the great interest that this topic has lately generated. Table 1 shows the parameters and values obtained from the application of the exponential model by the non-linear regression method. The value of c is 3.018 and that of g 1.131. With these values, the [PERSON] and Ravichandra [PERSON] equation can be established, and thus, predict the growth of the published literature on retinal nerve fiber thickness:  
\[C(t)=3.018\,*\,1.131^{t} \tag{6}\]  
From this method, it is inferred that the literature on detection of NDD based on decreased retinal thickness has grown at a rate of 13.1% per year with a production that doubles its size every 5.6 years. We have obtained that the model is explained at 89.3%. Figure 3: Literature distribution by 5-year periods. Figure 2: Chronological distribution of scientific Production. Linear adjustment (blue): \(y=1.5015x\) – \(3005.2\) (\(r=0.8856\)). Exponential adjustment (red): \(y=8E\)-\(142e^{0.1627x}\) (\(r=0.8695\)). Figure 4 shows the geographical distribution of the documents analyzed, while Figure 5 shows the most important institutions in scientific production in this field. From this analysis, it should be noted that four countries account for about 50% of total production. The United States was the most productive (\(n=69\)), whose Participation Index (PI) is 28.63, followed by South Korea (\(n=26\); PI = 10.79) and Japan (\(n=21\); PI = 8.71). As for the most productive institutions, they are University of California San Diego, Seoul National University Bundang Hospital and Seoul National University College of Medicine (Figure 5). The authors' productivity level (PL) is shown in Table 2. It can be seen that the most important group of authors (almost 90%) is responsible for a single publication (PI = 0). This is the so-called \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{3}{c}{**Parameter Estimates**} \\ \hline
**Parameter** & **Estimate** & **Std. Error** & \multicolumn{2}{c}{**95\% Confidence Interval**} \\ \cline{2-5}  & & **Lower Bound** & **Upper Bound** \\ \hline c & 3.018 & 0.626 & 1.702 & 4.334 \\ g & 1.131 & 0.015 & 1.100 & 1.162 \\ \hline \multicolumn{5}{c}{**ANOVA a**} \\ \hline Source & Sum of Squares & df & Mean Squares \\ \hline Regression & 4415.942 & 2 & 2207.971 \\ \hline Residual & 181.058 & 18 & 10.059 \\ Uncorrected Total & 4597.000 & 20 & \\ Corrected Total & 1692.950 & 19 & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Values of the parameters obtained with the exponential model. Figure 4: More productive countries in the generation of scientific literature on retinal nerve fiber thickness. Figure 5: More productive institutions in the generation of scientific literature on retinal nerve fiber thickness. Price transient index.