# Prediction of Post-Intubation Tachycardia Using Machine-Learning Models
## 3 Results  
Among the 257 patients, there were positive patients that had the post-intubation tachycardia, where the number of positive patients \(|\mathbf{D_{pos}}|\) = 50. To avoid such imbalance, we randomly divided the remaining 207 \begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **All Cases** & **No Tachycardia** & **Tachycardia** & \(p\)**Value** \\  & **(n = 257)** & **(n = 207)** & **(n = 50)** & \\ \hline Mechanical ventilation data & & & & \\ Tidal volume—mL & 239.4 (86.0) & 237.1 (85.7) & 248.8 (87.4) & 0.39 \\ Minute ventilation—L/min & 3.8 (1.5) & 3.8 (1.5) & 4.1 (1.5) & 0.131 \\ Respiratory rate—/min & 15.9 (5.8) & 15.6 (5.8) & 16.9 (5.6) & 0.169 \\ Mean positive airway pressure—cmH2O & 6.8 (1.9) & 6.8 (1.9) & 6.9 (1.8) & 0.645 \\ Peak inspiratory pressure—cmH2O & 14.8 (4.3) & 14.8 (4.2) & 14.6 (4.4) & 0.783 \\ End-tidal CO2 partial pressure—\% & 22.8 (0.7) & 2.8 (0.7) & 2.8 (0.5) & 0.567 \\ Carbon dioxide—\% & 1.1 (0.4) & 1.1 (0.4) & 1.1 (0.3) & 0.977 \\ Saturation of partial pressure of oxygen—\% & 99.1 (1.2) & 99.0 (1.2) & 99.1 (1.0) & 0.635 \\ Positive endeepiratory pressure—cmH2O & 2.7 (1.1) & 2.7 (1.1) & 2.8 (1.2) & 0.334 \\ \hline Neuromuscular transmission & & & & \\ train-of-four count & 1.5 (0.6) & 1.5 (0.6) & 1.5 (0.7) & 0.838 \\ \hline Bispectral Index & & & & \\ Spectral frequency—Hz & 17.5 (2.6) & 17.4 (2.5) & 18.0 (2.9) & 0.195 \\ Signal quality index—Hz & 81.0 (12.0) & 81.0 (12.0) & 81.2 (12.1) & 0.902 \\ Electromyography—Hz & 35.4 (4.2) & 35.3 (4.2) & 35.9 (4.0) & 0.331 \\ Total power & 63.9 (2.9) & 63.8 (2.7) & 64.2 (3.4) & 0.479 \\ Bispectral index value & 63.2 (10.9) & 62.8 (10.6) & 65.0 (12.1) & 0.185 \\ \hline Anesthetic drug & & & & \\ Volume & 112.7 (31.3) & 112.6 (30.8) & 113.2 (33.2) & 0.909 \\ Remifentanil—\(\mu\) g & 32.7 (15.7) & 34.0 (16.3) & 27.4 (11.8) & 0.001\({}^{***}\) \\ Rate - mL/hr & & & & \\ Propofol & 200.3 (184.5) & 208.9 (194.0) & 164.8 (134.8) & 0.062 \\ Remifentanil & 44.0 (81.2) & 44.4 (84.0) & 42.0 (69.1) & 0.852 \\ Plasma concentration & & & & \\ Propofol—mcg/mL & 6.0 (1.6) & 6.0 (1.7) & 6.0 (1.3) & 0.947 \\ Remifentanil—mg/mL & 2.7 (1.6) & 2.8 (1.7) & 2.2 (1.2) & 0.017\({}^{*}\) \\ Effect-site concentration & & & & \\ Propofol—mcg/mL & 4.2 (0.8) & 4.2 (0.8) & 4.3 (0.7) & 0.471 \\ Remifentanil—mg/mL & 1.5 (0.7) & 1.5 (0.7) & 1.3 (0.6) & 0.04\({}^{*}\) \\ Target concentration & & & & \\ Propofol—mcg/mL & 4.9 (0.8) & 4.8 (0.8) & 5.0 (0.8) & 0.275 \\ Remifentanil—mg/mL & 1.8 (0.9) & 1.9 (0.9) & 1.6 (0.8) & 0.035 \({}^{*}\) \\ \hline Vasoactive drug administration - no. & & & & \\ Ephedrine & 3 (1.2\%) & 3 (1.4\%) & 0 (0.0\%) & 0.521 \\ Phenylephrine & 3 (1.2\%) & 3 (1.4\%) & 0 (0.0\%) & 0.521 \\ Esmolol & 2 (0.8\%) & 1 (0.5\%) & 1 (2.0\%) & 0.352 \\ Nicardipine & 1 (0.4\%) & 1 (0.5\%) & 0 (0.0\%) & 0.805 \\ Dexamethasone & 68 (26.5\%) & 57 (27.5\%) & 11 (22.0\%) & 0.426 \\ \hline Muscle relaxant & & & & \\ Rocuronium—mg & 46.2 (11.9) & 45.8 (12.4) & 48.0 (9.3) & 0.239 \\ \hline \hline \end{tabular}  
* Continuous variable are expressed as mean and standard deviation. T-test or Wilcox test was performed appropriately. For categorical variables, numbers and ratios are displayed, and chi-square tests or Fisher’s tests performed appropriately.
* 0.05, **  
\end{table} 
Table 3: _Cont._negative patients \(D_{neg}\) into four disjoint subsets, where \(|D_{neg}|=52\), \(|D_{neg}|=52\), \(|D_{neg}|=52\), and \(|D_{neg}|=51\). We conducted four independent experiments with every pair of \(D_{pos}\) and \(\{|D_{neg}|\), \(D_{neg}^{2}\), \(D_{neg}^{3}\), \(D_{neg}^{4}\)}; the total amount of datasets for the four experiments was 102, 102, 102, and 101, respectively. All experimental results were averaged values of 10-fold cross-validation. The performance of different models was compared by accuracy, precision, recall, and F1 score [23]. We also utilized an area under the receiver operating characteristic curve (AUC) to compare the models; larger AUC values implied better models. We applied our five feature sets to six machine learning models.