| Literature DB >> 35232423 |
Fahimeh Alizadeh1, Malihe Mahmoudinia2, Masoumeh Mirteimoori3, Lila Pourali2, Shabnam Niroumand4.
Abstract
BACKGROUND: Preterm birth (PTB) remains a significant problem in obstetric care. Progesterone supplements are believed to reduce the rate of preterm labor, but formulation, type of administration, and dosage varies in different studies. This study was performed to compare oral Dydrogesterone with intramuscular 17α-hydroxyprogesterone caproate (17α-OHPC) administration in prevention of PTB.Entities:
Keywords: 17α-Hydroxyprogesterone caproate; Dydrogesterone; Preterm birth; Preterm labor
Mesh:
Substances:
Year: 2022 PMID: 35232423 PMCID: PMC8886932 DOI: 10.1186/s12884-022-04509-1
Source DB: PubMed Journal: BMC Pregnancy Childbirth ISSN: 1471-2393 Impact factor: 3.007
Fig. 1CONSORT flow diagram of the study
Baseline characteristics of participants
| Baseline Variable | Group 1 ( | Group 2 ( | Group 3 ( | |
|---|---|---|---|---|
| Maternal age (years) | 28.60 ± 4.04 | 26.53 ± 4.55 | 28.71 ± 3.98 | 0.017a |
| GA on admission (days) | 220.50 ± 13.30 | 219.88 ± 13.81 | 222.04 ± 12.84 | 0.707a |
| GA on admission (weeks) | 31.50 ± 1.90 | 31.41 ± 1.97 | 31.72 ± 1.83 | 0.69a |
| GA on admission categories (N (%)) | ||||
| 28 ≤ GA < 30 | 10 (20%) | 16 (32%) | 11 (22%) | 0.55b |
| 30 ≤ GA < 32 | 12 (24%) | 8 (16%) | 13 (26%) | |
| 32 ≤ GA < 35 | 28 (56%) | 26 (52%) | 26 (52%) | |
GA Gestational age
aOne-way ANOVA test
bChi-square test
Comparison of main outcomes between the study groups
| Outcome | Group 1 ( | Group 2 ( | Group 3 ( | ||
|---|---|---|---|---|---|
| 261.56 ± 14.90 | 249.32 ± 17.23 | 244.24 ± 18.08 | < 0.001a | ||
| 37.36 ± 2.12 | 35.61 ± 2.46 | 34.88 ± 2.59 | < 0.001a | ||
| 41.06 ± 17.29 | 29.44 ± 15.65 | 22.20 ± 14.51 | < 0.001a | ||
| Group1&2 | Group2&3 | Group1&3 | |||
| 11.62 ± 3.29 | 7.32 ± 3.02 | 18.94 ± 3.20 | |||
| 3042 ± 678 | 2424 ± 720 | 2341 ± 707 | < 0.001a | ||
| < 5% | 3 (6%) | 3 (6%) | 4 (8%) | < 0.001b | |
| 5–10% | 0 (0%) | 11 (22%) | 12 (24%) | ||
| 10–50% | 22 (44%) | 27 (54%) | 24 (48%) | ||
| 50–90% | 23 (46%) | 9 (18%) | 10 (20%) | ||
| > 90% | 2 (4%) | 0 (0%) | 0 (0%) | ||
| 10 (10–10) | 9.5 (8–10) | 8 (7–10) | < 0.001b | ||
| 11 (22%) | 20 (40%) | 22 (44%) | 0.050c | ||
| ND | 26 (52%) | 30 (60%) | 15 (30%) | 0.182c | |
| CS | 24 (48%) | 20 (40%) | 35 (70%) | ||
| 35 (70%) | 18 (36%) | 11 (22%) | < 0.001 | ||
| < 37 weeks | 15 (30%) | 32 (64%) | 39 (78%) | ||
GA Gestational age, NICU Neonatal intensive care unit, ND Natural delivery, CS Cesarean section
aOne-way ANOVA test
bKruskal-Wallis test
cChi-square test
Fig. 2GA at admission and delivery in each study groups
Regression on variables predicting the latency period and NICU admission
| Dependent variable | Independent variables | OR | 95% C.I | ||
|---|---|---|---|---|---|
| Latency period (days)a | First pregnancy age | -0.46 | -.065 | -.027 | < 0.001 |
| Mother age | -0.094 | -.056 | 0.37 | 0.69 | |
| Birth weight | 0.004 | 0.003 | 0.006 | < 0.001 | |
| NICU admissionb | First pregnancy age | 0.96 | 0.93 | 0.99 | 0.03 |
| End pregnancy age | 0.92 | 0.89 | 0.95 | < 0.001 | |
| Mother age | 1.04 | 0.96 | 1.13 | 0.29 | |
| Kind of delivery (CS) | 1.27 | 0.50 | 3.21 | 0.60 | |
aBased on Multiple stepwise linear regression
bBased on Binary logistic regression