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Predictive Value of Single Serum Progesterone Level for Viability in Threatened Miscarriage
Vijay K Kadam1, Shivani Agrawal1, Pinkee Saxena1
1Department of Obstetrics and Gynaecology, Deen Dayal Upadhyay Hospital, Hari Nagar, New Delhi, 110064 India.
Background:
Bleeding is commonly seen during early pregnancy, and predicting the outcome of pregnancy in such cases is a difficult task. The aim of our study was to evaluate the predictive value of single serum progesterone level for finding the viability in threatened miscarriage and to determine the cut-off value for a viable ongoing pregnancy.
Methods:
This was a prospective study in which patients attending the OPD with early pregnancy and bleeding were recruited. Inclusion criteria were period of amenorrhoea less than 12 weeks, complaints of bleeding per vaginum with or without lower abdominal pain and positive urine pregnancy test or serum beta HCG. Multiple pregnancies, inevitable miscarriage, ectopic pregnancy, molar pregnancy and pregnancy achieved by artificial reproductive techniques were excluded from this study. A detailed clinical examination was done, and routine investigations along with serum progesterone were done. Patients were followed up by serial ultrasound for viability, and their outcome was recorded.
Result:
A total of 150 patients with early pregnancy threatened miscarriage were enrolled for this study. Of the patients studied, 105 (70%) had a viable pregnancy and 45 (30%) had non-viable pregnancies. The mean serum progesterone was higher in the viable pregnancy, 17.97 ± 7.75 ng/ml, compared to non-viable group, 6.21 ± 2.86 ng/ml. The area under curve was calculated, and a cut-off value of 10.08 ng/ml was obtained. 83.8% of viable pregnancies had serum progesterone more than or equal to 10.08 ng/ml which was statistically significant.
Conclusion:
A single value of progesterone is useful in predicting the viability of the ongoing threatened pregnancy. Serum progesterone with a cut-off value of 10.8 ng/ml was found to have a positive predictive value of 95.7% and negative predictive value of 70.7% with an accuracy of 86%.
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P-value
P-value stands for the probability value. P-value is the probability that, if the null hypothesis is true, the results from another randomly selected sample will be as extreme or more extreme as the results obtained from the given sample.
A large P-value calculated from the data indicates to not reject the null hypothesis. But a higher P-value does not mean that the null hypothesis is true. The smaller the P-value, the more...