Objective
Predicting women at risk for spontaneous pre-term birth (sPTB) has been medically
challenging because of the lack of signs and symptoms of pre-term birth until interventions
are too late. We hypothesized that prediction of the sPTB risk level is enhanced when
using both historical clinical (HC) data and quantitative ultrasound (QUS) data compared
with using only HC data. HC data defined herein included birth history prior to that
of the current pregnancy as well as, from the current pregnancy, a clinical cervical
length assessment and physical examination data.
Methods
The study population included 248 full-term births (FTBs) and 26 sPTBs. QUS scans
(Siemens S2000 and MC9-4) were performed by registered diagnostic medical sonographers
using a standard cervical length approach. Two cervical QUS scans were conducted at
20 ± 2 and 24 ± 2 wk of gestation. Multiple QUS features were evaluated from calibrated
raw radiofrequency backscattered ultrasonic signals. Two statistical models designed
to determine sPTB risk were compared: (i) HC data alone and (ii) combined HC and QUS
data. Model comparisons included a likelihood ratio test, cross-validated receiver
operating characteristic area under the curve, sensitivity and specificity. The study's
birth outcomes were only FTBs and sPTBs; medically induced pre-term births were not
included.
Discussion
Combined HC and QUS data identified women at risk of sPTB with better AUC (0.68, 95%
confidence interval [CI]: 0.57–0.78) compared with HC data alone (0.53, 95% CI: 0.40–0.66)
and HC data + cervical length at 18–20 wk of gestation (average AUC = 0.51, 95% CI:
0.38–0.64). A likelihood ratio test for significance of QUS features in the classification
model was highly statistically significant (p < 0.01).
Conclusion
Even with only 26 sPTBs among 274 births, value was added in predicting sPTB when
QUS data were included with HC data.
Keywords
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Article info
Publication history
Published online: February 03, 2023
Accepted:
December 26,
2022
Received in revised form:
December 13,
2022
Received:
October 5,
2022
Identification
Copyright
© 2023 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
