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Journal of Nursing ›› 2023, Vol. 30 ›› Issue (12): 73-78.doi: 10.16460/j.issn1008-9969.2023.12.073

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Construction of risk prediction model for cognitive dysfunction in pregnant women with cesarean section

ZHANG Xiao-lan, SU Xiao-hua, ZHANG Jing   

  1. Dept. of Obstetrics and Gynecology, Second Affiliated Hospital of Air Force Military Medical University, Xi'an 710038, China
  • Received:2023-02-10 Online:2023-06-25 Published:2023-07-10

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Abstract: Objective To explore the influencing factors of cognitive dysfunction in pregnant women with cesarean section, and to construct a risk prediction model. Methods A total of 212 pregnant women who underwent cesarean section in the obstetrics and gynecology department of a tertiary grade-A hospital in Xi'an from September 2020 to December 2021 were enrolled and divided into cognitive dysfunction group (n=68) and non-cognitive dysfunction group (n=144). Univariate analysis and binary logistic regression were used to analyze the influencing factors of cognitive dysfunction in pregnant women with cesarean section, and a risk prediction model was constructed and verified internally. Result Postoperative analgesia time was a protective factor for cognitive dysfunction in pregnant woman with cesarean section (OR=0.164), and vaginal delivery to cesarean section (OR=2.827), intraoperative blood loss (OR=3.947), anxiety/depression (OR=5.272), gestational hypertension (OR=5.475), and gestational diabetes (OR=10.111) were risk factors. The risk prediction model had a good fit (Hosmer-Lemeshow test: χ2=13.961, P=0.083). The internal verification of the model showed that the area under the ROC curve was 0.800, which had a good degree of discrimination. The mean absolute error between the actual value and the predicted value of the calibration curve was 0.043, showing a good degree of calibration. When the risk threshold of the decision curve was greater than 0.130, the model provided significant net clinical benefit. Conclusion The risk prediction model of cognitive dysfunction in pregnant women with cesarean section is scientific and practical, which can help medical staff identify the risk of cognitive dysfunction in pregnant women with cesarean section.

Key words: pregnant women, cesarean section, cognitive dysfunction, influencing factor, nomogram, prediction model

CLC Number: 

  • R473.71
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