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| The role of decision tree model and Logistic regression model in postpartum urinary retention influencing factors analysis |
| GUO Xueqi YAN Guizhen ZHANG Caixia CHEN Jingjuan |
| Department of Obstetrics, Lishui People′s Hospital, Zhejiang Province, Lishui 323000, China |
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Abstract 0bjective To investigate the role of decision tree model and Logistic regression model in postpartum urinary retention (PUR) influencing factors analysis. Methods From January 1, 2014 to December 31, 2017, 180 puerpera with PUR after vaginal delivery in Lishui People′s Hospital of Zhejiang Province ("our hospital" for short) were selected as case group, and 200 puerpera who without PUR in our hospital at the same period were selected randomly as control group. Decision tree model and Logistic regression model were used to determine influential factors for PUR. Results Decision tree model and Logistic regression model indicated that delivery analgesia (P = 0.047), forceps delivery (P = 0.001) and episiotomy (P < 0.001) were independent risk factors of PUR, and fetal macrosomia (P = 0.023) was also the influencing factor in the Logistic regression model, but the decision tree model did not indicate its influence. Conclusion There are many factors influencing PUR. Decision tree model and Logistic regression model are complementary to each other, which can describe the factors from different aspects, and provide basis and reference for the further formulation of preventive measures.
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