Department of Cardiac Surgery, The First Hospital of Hebei Medical University, No. 89 Donggang Road, Yuhua District, Shijiazhuang, 050000, Hebei, China.
J Cardiothorac Surg. 2024 Oct 17;19(1):608. doi: 10.1186/s13019-024-03021-1.
This study explores the factors contributing to the occurrence of delirium following cardiac surgery and devises nursing strategies rooted in behavior change theory.
A cohort of 320 cardiac surgery patients was selected, categorized into two groups: 93 cases where postoperative delirium (POD) was anticipated, and 227 cases where it was not. Preoperative, intraoperative, and postoperative factors of POD were scrutinized using single-factor analysis, while binary logistic regression analysis was employed to pinpoint risk factors.
Among the 320 patients, 93 displayed POD symptoms post-surgery, yielding an incidence of 29.06%. Preoperative univariate analysis disclosed significant differences in gender, age, smoking, hypertension, and diabetes (P < 0.05). Intraoperatively, significant differences were noted in the American Society of Anesthesiologists (ASA) anesthesia grade (II, III, and IV), surgery time, cardiopulmonary bypass duration, and aortic occlusion duration (P < 0.05). Post-surgery, significant differences were observed in the duration of Intensive Care Unit (ICU) stay, mechanical ventilation time, and visual analogue scale (VAS) scores (P < 0.05). Multivariate Logistic regression identified surgery time (OR = 2.334, P < 0.001), ICU admission duration (OR = 1.457, P < 0.001), mechanical ventilation time (OR = 1.235, P = 0.004), and VAS scores (OR = 2.986, P < 0.001) as independent risk factors for POD. ROC curve analysis indicated higher sensitivity and specificity in predicting POD with surgery time, ICU stay duration, mechanical ventilation time, and VAS scores.
Irrespective of the surgical intervention type, surgery time, ICU stay duration, mechanical ventilation time, and VAS scores are recognized as risk factors for POD in cardiac surgery patients. Hence, continuous patient monitoring and early intervention tailored to specific risk factors are essential in clinical practice to mitigate POD incidence.
本研究旨在探讨心脏手术后发生谵妄的相关因素，并制定基于行为改变理论的护理策略。
选取 320 例心脏手术患者，分为术后预计发生谵妄（POD）组 93 例和术后未发生 POD 组 227 例。采用单因素分析比较 POD 组和非 POD 组患者术前、术中和术后的因素，采用二项逻辑回归分析确定危险因素。
320 例患者中，术后发生 POD93 例，发生率为 29.06%。术前单因素分析显示，性别、年龄、吸烟、高血压和糖尿病差异有统计学意义（P<0.05）。术中 ASA 麻醉分级（Ⅱ、Ⅲ、Ⅳ级）、手术时间、体外循环时间、主动脉阻断时间差异有统计学意义（P<0.05）。术后 ICU 入住时间、机械通气时间、视觉模拟评分（VAS）差异有统计学意义（P<0.05）。多因素 Logistic 回归分析显示，手术时间（OR=2.334，P<0.001）、ICU 入住时间（OR=1.457，P<0.001）、机械通气时间（OR=1.235，P=0.004）、VAS 评分（OR=2.986，P<0.001）是 POD 的独立危险因素。ROC 曲线分析显示，手术时间、ICU 入住时间、机械通气时间和 VAS 评分预测 POD 的敏感性和特异性较高。
无论手术干预类型如何，手术时间、ICU 入住时间、机械通气时间和 VAS 评分均被认为是心脏手术患者发生 POD 的危险因素。因此，在临床实践中，持续监测患者并针对特定危险因素进行早期干预对于降低 POD 的发生率至关重要。
