## 3 Results
### Determinant of Salivary Conductivity from Clinical Parameters  
We further used multiple linear regression analysis to determine the correlations between salivary conductivity and continuous parameters. Because osmolality is composed of serum sodium, glucose, and blood urea nitrogen, we only input age, serum creatinine, osmolality, potassium, and the Third intensity scale (VAS) into the analysis model. We found older age (\(\beta\) = 0.309 \(\pm\) 0.000, \(p\) < 0.001) and higher serum osmolality (\(\beta\) = 0.192 \(\pm\) 0.000, \(p\) = 0.023) were positively correlated with salivary conductivity values (R2 = 0.35, Table 3). Figure 5 is a three-dimensional scatter plot, prepared for salivary conductivity, serum osmolality, and age, to identify the data behavior. The z-axis was salivary conductivity, and the x- and y-axis were age and serum osmolality, respectively. The positive trend between salivary conductivity and serum osmolality was more obvious especially in  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Model 1** & \multicolumn{3}{c}{**Cardiothoracic Ratio**} \\ \hline \hline  & \multicolumn{2}{c}{**Standardized**} & \\  & **Beta Coefficient** & **t** & **Significance** \\  & **(Standard Error)** & & \\ \hline Age, per year & 0.200 (0.000) & 2.121 & 0.036 * \\ Salivary conductivity, \(\mu\)s/cm & \(-\)0.203 (0.000) & \(-\)2.230 & 0.028 * \\ Serum sodium, mEq/L & \(-\)0.130 (0.001) & \(-\)1.486 & 0.140 \\ Serum potassium, mEq/L & 0.122 (0.007) & 1.368 & 0.174 \\ R2 = 0.30 & & & \\ \hline
**Model 2** & \multicolumn{3}{c}{**Cardiothoracic Ratio**} \\ \hline  & \multicolumn{2}{c}{**Standardized**} & \\  & **Beta Coefficient** & **t** & **Significance** \\  & **(Standard Error)** & & \\ \hline Serum sodium, mEq/L & \(-\)0.178 (0.001) & \(-\)1.486 & 0.044 * \\ R2 = 0.18 & & & \\ \hline \hline \end{tabular} Parameters included in model 1: age, blood urea nitrogen, creatinine, salivary conductivity, glucose, and serum sodium and potassium levels. Parameters included in model 2: age, blood urea nitrogen, creatinine, glucose, and serum sodium and potassium levels. Abbreviations: BUN/Cr ratio, blood urea nitrogen to creatinine ratio. Note: *\(p\) \(\leq\) 0.05.  
\end{table}
Table 2: Prediction of the cardiothoracic ratio from clinical data and salivary conductivity by multiple linear regression analysis.  
older age (\(>\)60 years old), which explained that age was the most significant independent variable (Table 3).  
Figure 4: The receiver operating characteristic curve analysis. The receiver operating characteristic curves were built from four prediction models for the diagnosis of cardiomegaly. The area under the ROC curve (AUROC) was equal to 0.626 (95% CI: 0.521–0.730, \(p=0.02\)) when salivary conductivity was the predicting factor. The combination of salivary conductivity, serum sodium, and history of diabetes mellitus showed a significant increase in AUROC (0.782, 95% CI: 0.696–0.868). Abbreviations: AUC, area under the curve; DM, diabetes mellitus; Na, serum sodium; Osm, serum osmolality.  
Figure 3: Distribution of cardiomegaly from low to high salivary conductivity groups. Patients were divided into low, middle, and high salivary conductivity groups according to the tertials of conductivity levels (range values: Low \(\leq\) 6273.23 \(\upmu\)s/cm; 6273.23 \(<\) Middle \(\leq\) 8131.59 \(\upmu\)s/cm; High \(>\) 8131.59 \(\upmu\)s/cm). The number and percentage of patients with cardiomegaly were demonstrated in the bar chart (Chi-square = 5.296, \(p\) for trend: 0.021 *). Note: * \(p\leq 0.05\).