Construction of nomogram prediction model using heart rate and pulse perfusion variability index as predictors for hypotension in cervical cancer patients with spinal epidural anesthesia.

The prevention and treatment strategies for cervical cancer patients undergoing spinal epidural anesthesia have increasingly focused on early screening for high-risk factors associated with potential hypotension. We analyze the general conditions and preoperative examination results of 312 cervical cancer patients who received spinal epidural anesthesia, in order to identify independent risk factors for hypotension, assess their predictive efficacy, and construct a nomogram. 312 patients with cervical cancer received spinal epidural anesthesia were included in this study. Among them, 164 patients with hypotension after hysterectomy with spinal epidural anesthesia were in a hypotension group. Important risk predictors of hypotension after hysterectomy with spinal epidural anesthesia were identified using univariate and multivariate analyses, then a clinical nomogram was constructed. The predictive accuracy was assessed by unadjusted concordance index (C-index) and calibration plot. Univariate and multivariate regression analysis identified basal HR (≥95) (95% CI 0.831-0.900; P = 0.000) and basal PVI (95% CI 0.679-0.877; P = 0.000) were the independent risk factors for hypotension in cervical cancer patients with spinal epidural anesthesia. Those risk factors were used to construct a clinical predictive nomogram. The regression equation model based on the above factors was logit (P) = -6.820 + 0.216 * basal HR + basic PVI * 0.312. The calibration curves for hypotension risk revealed excellent accuracy of the predictive nomogram model. Decision curve analysis showed that the predictive model could be applied clinically when the threshold probability was 20 to 75%. We surmised that the basal HR values and PVI values are the independent risk factors for hypotension in cervical cancer patients with spinal epidural anesthesia. The construction of nomograms is beneficial in predicting the risk of hypotension in these patients.