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Effect of evidence-based predictive nursing on postoperative infection and recovery outcomes in cesarean delivery: A
Sun Xuehua1, Zhang Yan1, Yu Huan2
1Department of Obstetrics and Gynecology, Shijiazhuang Obstetrics and Gynecology Hospital, Hebei, China.
Cesarean section (CS) is associated with a high risk of postoperative infection, which can compromise maternal recovery and increase the healthcare burden. Conventional nursing models often lack individualized risk assessment and proactive strategies. This study aimed to evaluate the effectiveness of evidence-based predictive nursing in reducing postoperative infection and improving recovery among women undergoing CS. A case-control study was conducted between March 2023 and June 2024, enrolling 240 women who underwent cesarean section. Participants were divided into 2 groups according to the nursing care received: the control group (routine nursing care, n = 120) and the intervention group (evidence-based predictive nursing, n = 120). The intervention involved preoperative risk assessment, individualized health education, intraoperative aseptic management, and postoperative monitoring of inflammatory markers (C-reactive protein, white blood cell). The primary outcome was postoperative infection within 7 days, with secondary outcomes comprising hospital stay, inflammatory marker trends, and patient satisfaction. The incidence of postoperative infection was significantly lower in the intervention group than in the control group (2.0% vs 8.0%, P = .015). Intervention patients had shorter hospital stays (5.3 ± 1.1 vs 6.4 ± 1.3 days, P < .001), faster normalization of C-reactive protein and white blood cell levels (interaction P < .05), and higher satisfaction scores (91.8 ± 4.7 vs 85.2 ± 6.1, P < .001). Multivariable analysis confirmed the intervention as an independent protective factor (OR = 0.35, 95% CI: 0.15-0.82). Incorporating evidence-based predictive nursing into risk models improved discrimination for infection (area under the curve 0.85 vs 0.71; P < .01). Evidence-based predictive nursing significantly reduces postoperative infection and enhances recovery in CS patients. This strategy is safe, effective, and holds potential for broader implementation. Future multicenter studies should validate these findings and assess cost-effectiveness.
Cesarean section (CS) is associated with a high risk of postoperative infection, which can compromise maternal recovery and increase the healthcare burden. Conventional nursing models often lack individualized risk assessment and proactive strategies. This study aimed to evaluate the effectiveness of evidence-based predictive nursing in reducing postoperative infection and improving recovery among women undergoing CS. A case-control study was conducted between March 2023 and June 2024, enrolling 240 women who underwent cesarean section. Participants were divided into 2 groups according to the nursing care received: the control group (routine nursing care, n = 120) and the intervention group (evidence-based predictive nursing, n = 120). The intervention involved preoperative risk assessment, individualized health education, intraoperative aseptic management, and postoperative monitoring of inflammatory markers (C-reactive protein, white blood cell). The primary outcome was postoperative infection within 7 days, with secondary outcomes comprising hospital stay, inflammatory marker trends, and patient satisfaction. The incidence of postoperative infection was significantly lower in the intervention group than in the control group (2.0% vs 8.0%, P = .015). Intervention patients had shorter hospital stays (5.3 ± 1.1 vs 6.4 ± 1.3 days, P < .001), faster normalization of C-reactive protein and white blood cell levels (interaction P < .05), and higher satisfaction scores (91.8 ± 4.7 vs 85.2 ± 6.1, P < .001). Multivariable analysis confirmed the intervention as an independent protective factor (OR = 0.35, 95% CI: 0.15-0.82). Incorporating evidence-based predictive nursing into risk models improved discrimination for infection (area under the curve 0.85 vs 0.71; P < .01). Evidence-based predictive nursing significantly reduces postoperative infection and enhances recovery in CS patients. This strategy is safe, effective, and holds potential for broader implementation. Future multicenter studies should validate these findings and assess cost-effectiveness.
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