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Comparative study of placental α‐microglobulin‐1, insulin‐like growth factor binding protein‐1 and nitrazine test to diagnose premature rupture of membranes: A randomized controlled trial
Author(s) -
Liang Deku,
Qi Hongbo,
Luo Xin,
Xiao Xiaoqiu,
Jia Xiaoyan
Publication year - 2014
Publication title -
journal of obstetrics and gynaecology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 50
eISSN - 1447-0756
pISSN - 1341-8076
DOI - 10.1111/jog.12381
Subject(s) - medicine , predictive value , rupture of membranes , beta 2 microglobulin , preterm delivery , positive predicative value , premature rupture of membranes , kappa , obstetrics , gastroenterology , pregnancy , fetus , biology , linguistics , philosophy , genetics
Aim The aim of this study was to compare the accuracy of placental α‐microglobulin‐1 ( PAMG ‐1), insulin‐like growth factor binding protein‐1 ( IGFBP ‐1) and nitrazine test to diagnose premature rupture of membranes. Material and Methods A total of 120 pregnant women between 11 and 42 weeks with signs/symptoms of membrane rupture were eligible for our study. These women were evaluated with the PAMG ‐1, IGFBP ‐1, and nitrazine tests. Results In the 120 women, the sensitivity, specificity, positive predictive value, and negative predictive value of PAMG‐1, IGFBP‐1 and nitrazine test were 100%, 100%, 100%, and 100%, 93.33%, 98.89%, 96.55% and 97.80%, and 93.33%, 94.44%, 84.85%, and 97.7%, respectively. In a comparison of the PAMG ‐1 test and the nitrazine test, positive coincidence rate was 84.85%, negative coincidence rate was 97.70%, total coincidence rate was 94.17%, and kappa value was 0.85. In a comparison of the PAMG ‐1 test and the IGFBP ‐1 test, the positive coincidence rate, negative coincidence rate and total coincidence rate were 96.55%, 97.80%, and 97.50%, and kappa value was 0.93. Conclusion PAMG ‐1 assay was the most accurate method to diagnose premature rupture of membranes with the highest sensitivity, specificity, positive predictive value and negative predictive value.