Figures & data
Table 1. Statistically significant risk factors for AHD between the two groups.
Figure 1. The 22 risk factors screened out by LASSO regression with significant differences between the patients with and without additional hospital days.
Figure 2. The importance of the top ten variables in the Random Forest (RF) model. BMI: body mass index; MRI T2WIHS: magnetic resonance imaging T2-weighted imaging high signal; ASIA: American Spinal Injury Association.
Table 2. The final selection of random forest (RF) regression.
Figure 3. Selection of 19 factors by the support vector machine recursive feature elimination (SVM-RFE).
Figure 4. The intersection of nine factors screened using Lasso regression, random forest (RF), support vector machine recursive feature elimination (SVM-RFE).
Figure 5. The nomogram model to predict AHD in patients undergoing cervical spine surgery. AHD: additional hospital day; BMI: body mass index; MRI T2WIHS: magnetic resonance imaging T2-weighted imaging high signal; ASIA: American Spinal Injury Association.
Figure 6. Receiver operating characteristic curve analysis (A), calibration curves (B), and decision curve analysis (C) of the nomogram prediction in the training cohort. AUC: area under the curve; AHD: additional hospital day.
Figure 7. Receiver operating characteristic curve analysis (A) and decision curve analysis (B) of the nomogram prediction in the validation cohort. AUC: area under the curve; AHD: additional hospital day.
