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Abstract：
OBJECTIVE: With the improvement of medical level, the number of elderly patients is increasing, and the postoperative outcome of the patients cannot be ignored. However, there have been no studies on the relationship between preoperative heart rate variability (HRV) and Perioperative Neurocognitive Disorders (PND). The purpose of this study was to explore the correlation between (HRV) and (PND), postoperative intensive care unit (ICU), and hospital stay in patients undergoing non-cardiac surgery.
METHODS: This retrospective analysis included 687 inpatients who underwent 24-hour dynamic electrocardiogram examination in our six departments from January 2021 to January 2022. Patients were divided into two groups based on heart rate variability (HRV): high and low. Possible risk factors of perioperative outcomes were screened using univariate analysis, and risk factors were included in multivariate logistic regression to screen for independent risk factors. The subgroup analysis was carried out to evaluate the robustness of the results. The nomogram of PND multi-factor logistic prediction model was constructed. The receiver operating characteristic (ROC) curve was drawn, and the calibration curve was drawn by bootstrap resampling 1000 times for internal verification to evaluate the prediction ability of nomogram.
RESULTS: A total of 687 eligible patients were included. The incidence of low HRV was 36.7% and the incidence of PND was 7.6%. The incidence of PND in the low HRV group was higher than that in the high HRV group (11.8% vs 5.2%), the postoperative ICU transfer rate was higher (15.9% than 9.3%P = 0.009), and the hospital stay was longer [15 (11, 19) vs (13), 0.015]. The multivariable logistic regression analysis showed that after adjusting for other factors, decreased low HRV was identified as an independent risk factor for the occurrence of PND (Adjusted Odds Ratio = 2.095; 95% Confidence Interval: 1.160-3.784; P = 0.014) and postoperative ICU admission (Adjusted Odds Ratio = 1.925; 95% Confidence Interval: 1.128-3.286; P = 0.016). This study drew a nomogram column chart for a multivariate logistic regression model, incorporating age and HRV. The calibration curve shows that the predicted value of the model for the occurrence of cardio-cerebrovascular events is in good agreement with the actual observed value, with C-index of 0.696 (95% CI: 0.626 ~ 0.766). Subgroup analysis showed that low HRV was an independent risk factor for PND in patients with gastrointestinal surgery and ASA Ⅲ, aged ≥ 65 years.
CONCLUSIONS: In patients undergoing non-cardiac surgery, the low HRV was an independent risk factor for PND and postoperative transfer to the ICU, and the hospitalization time of patients with low HRV was prolonged. Through establishing a risk prediction model for the occurrence of PND, high-risk patients can be identified during the perioperative period for early intervention.
METHODS: This retrospective analysis included 687 inpatients who underwent 24-hour dynamic electrocardiogram examination in our six departments from January 2021 to January 2022. Patients were divided into two groups based on heart rate variability (HRV): high and low. Possible risk factors of perioperative outcomes were screened using univariate analysis, and risk factors were included in multivariate logistic regression to screen for independent risk factors. The subgroup analysis was carried out to evaluate the robustness of the results. The nomogram of PND multi-factor logistic prediction model was constructed. The receiver operating characteristic (ROC) curve was drawn, and the calibration curve was drawn by bootstrap resampling 1000 times for internal verification to evaluate the prediction ability of nomogram.
RESULTS: A total of 687 eligible patients were included. The incidence of low HRV was 36.7% and the incidence of PND was 7.6%. The incidence of PND in the low HRV group was higher than that in the high HRV group (11.8% vs 5.2%), the postoperative ICU transfer rate was higher (15.9% than 9.3%P = 0.009), and the hospital stay was longer [15 (11, 19) vs (13), 0.015]. The multivariable logistic regression analysis showed that after adjusting for other factors, decreased low HRV was identified as an independent risk factor for the occurrence of PND (Adjusted Odds Ratio = 2.095; 95% Confidence Interval: 1.160-3.784; P = 0.014) and postoperative ICU admission (Adjusted Odds Ratio = 1.925; 95% Confidence Interval: 1.128-3.286; P = 0.016). This study drew a nomogram column chart for a multivariate logistic regression model, incorporating age and HRV. The calibration curve shows that the predicted value of the model for the occurrence of cardio-cerebrovascular events is in good agreement with the actual observed value, with C-index of 0.696 (95% CI: 0.626 ~ 0.766). Subgroup analysis showed that low HRV was an independent risk factor for PND in patients with gastrointestinal surgery and ASA Ⅲ, aged ≥ 65 years.
CONCLUSIONS: In patients undergoing non-cardiac surgery, the low HRV was an independent risk factor for PND and postoperative transfer to the ICU, and the hospitalization time of patients with low HRV was prolonged. Through establishing a risk prediction model for the occurrence of PND, high-risk patients can be identified during the perioperative period for early intervention.
摘要：
目的：随着医疗水平的提高，老年患者的数量正在增加，患者的术后结局不容忽视。然而,术前心率变异性(HRV)与围手术期神经认知障碍(PND)之间的关系尚未有研究.本研究的目的是探讨(HRV)和(PND)之间的相关性。术后重症监护病房(ICU),非心脏手术患者的住院时间。
方法：这项回顾性分析包括2021年1月至2022年1月在我们六个科室接受24小时动态心电图检查的687名住院患者。根据心率变异性（HRV）将患者分为两组：高和低。使用单因素分析筛选围手术期结局的可能危险因素,并将危险因素纳入多因素logistic回归，筛选独立危险因素。进行亚组分析以评估结果的稳健性。构建了PND多因素Logistic预测模型的列线图。绘制受试者工作特性(ROC)曲线,并通过自举重新采样1000次绘制校准曲线进行内部验证，以评估列线图的预测能力。
结果：共纳入687例符合条件的患者。低HRV发生率为36.7%,PND发生率为7.6%。低HRV组PND发生率高于高HRV组(11.8%vs5.2%),术后ICU转移率较高(15.9%比9.3%P=0.009),住院时间更长[15（11，19）vs（13），0.015].多变量logistic回归分析显示，在调整其他因素后，低HRV降低被确定为PND发生的独立危险因素(调整后赔率=2.095;95%置信区间:1.160-3.784;P=0.014)和术后ICU入住(调整后赔率=1.925;95%置信区间:1.128-3.286;P=0.016).本研究绘制了多元逻辑回归模型的列线图，纳入年龄和HRV。校正曲线表明,模型对心脑血管事件发生的预测值与实际观测值吻合较好,C指数为0.696(95%CI:0.626~0.766)。亚组分析显示,低HRV是胃肠道手术患者发生PND的独立危险因素,年龄≥65岁。
结论：在接受非心脏手术的患者中，低HRV是PND及术后转ICU的独立危险因素,低HRV患者的住院时间延长。通过建立PND发生的风险预测模型,围手术期可以识别高危患者进行早期干预。
方法：这项回顾性分析包括2021年1月至2022年1月在我们六个科室接受24小时动态心电图检查的687名住院患者。根据心率变异性（HRV）将患者分为两组：高和低。使用单因素分析筛选围手术期结局的可能危险因素,并将危险因素纳入多因素logistic回归，筛选独立危险因素。进行亚组分析以评估结果的稳健性。构建了PND多因素Logistic预测模型的列线图。绘制受试者工作特性(ROC)曲线,并通过自举重新采样1000次绘制校准曲线进行内部验证，以评估列线图的预测能力。
结果：共纳入687例符合条件的患者。低HRV发生率为36.7%,PND发生率为7.6%。低HRV组PND发生率高于高HRV组(11.8%vs5.2%),术后ICU转移率较高(15.9%比9.3%P=0.009),住院时间更长[15（11，19）vs（13），0.015].多变量logistic回归分析显示，在调整其他因素后，低HRV降低被确定为PND发生的独立危险因素(调整后赔率=2.095;95%置信区间:1.160-3.784;P=0.014)和术后ICU入住(调整后赔率=1.925;95%置信区间:1.128-3.286;P=0.016).本研究绘制了多元逻辑回归模型的列线图，纳入年龄和HRV。校正曲线表明,模型对心脑血管事件发生的预测值与实际观测值吻合较好,C指数为0.696(95%CI:0.626~0.766)。亚组分析显示,低HRV是胃肠道手术患者发生PND的独立危险因素,年龄≥65岁。
结论：在接受非心脏手术的患者中，低HRV是PND及术后转ICU的独立危险因素,低HRV患者的住院时间延长。通过建立PND发生的风险预测模型,围手术期可以识别高危患者进行早期干预。
