Journal of cardiothoracic surgery · 2024
Clinical investigation into risk factors for delirium post-cardiac surgery and its implications for nursing intervention guided by behavior change theory.
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Zhao Youwei, Guo Shichao, Wang Zhiyuan, Dong Yanbo, Wei Wei, Su Zhenyu
Аннотация
BACKGROUND: This study explores the factors contributing to the occurrence of delirium following cardiac surgery and devises nursing strategies rooted in behavior change theory.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.