BMC Pregnancy and Childbirth (Jul 2021)

Self-reported pain scores as a predictor of preterm birth in symptomatic twin pregnancy: a retrospective study

  • Ji Hoi Kim,
  • Seung Mi Lee,
  • Sungyoung Lee,
  • So Yeon Kim,
  • Hye Jeong Hue,
  • Chan-Wook Park,
  • Joong Shin Park,
  • Jong Kwan Jun

DOI
https://doi.org/10.1186/s12884-021-03931-1
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 8

Abstract

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Abstract Background To evaluate the self-reported pain scores as a predictor of preterm birth (PTB) in symptomatic twin pregnancy and to develop a nomogram for the prediction model. Methods We conducted a retrospective study of 148 cases of symptomatic twin pregnancies before 34 weeks of gestation visited at Seoul national university hospital from 2013 to 2018. With other clinical factors, self-reported pain score was evaluated by the numerical rating scale (NRS) pain scores for pain intensity. By multivariate analyses and logistic regression, we developed a prediction model for PTB within 7 days. Using the Cox proportional hazards model, the curves were plotted to show the predictability of the PTB according to NRS pain score, while adjusting the other covariates. Results Twenty-three patients (15.5 %) delivered preterm within 7 days. By a logistic regression analysis, higher NRS pain score (OR 1.558, 95 % CI 1.093–2.221, P < 0.05), shorter cervical length (OR 3.164, 95 % CI 1.262–7.936, P < 0.05) and positive fibronectin results (OR 8.799, 95 % CI 1.101–70.330, P < 0.05) affect PTB within 7 days. Using the variables, the area under the receiver operating characteristic curve (AUROC) of the prediction model was 0.917. In addition, we developed a nomogram for the prediction of PTB within 7 days. Conclusions Self-reported pain scores combined with cervical length and fetal fibronectin are useful in predicting impending PTB in symptomatic twin pregnancy.

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