Jorge Burgos

Background and Objectives: Risk stratification in symptomatic threatened preterm labor (TPTL) remains challenging, particularly for clinically actionable time horizons. We evaluated whether quantitative cervical stiffness measured with the Cervisense Intravaginal Probe discriminates between women who will and will not deliver within 7, 10, or 14 days after presentation and assessed its discriminative performance alone and in combination with transvaginal cervical length. Materials and Methods: We conducted a multicenter, non-interventional study across 10 obstetric emergency units in Spain. Eligible participants were women aged ≥ 18 years with a live singleton pregnancy at 28⁺⁰ to 36⁺⁶ weeks, regular uterine contractions, intact membranes, and cervical dilatation < 2 cm on speculum examination. Cervical stiffness was measured at presentation using torsional wave elastography with the Cervisense Intravaginal Probe. Cervical length was measured by transvaginal ultrasonography following international standards. Outcomes were delivery within 7, 10, and 14 days after presentation. Discrimination was quantified using the area under the receiver operating characteristic curve (AUC). An explanatory multivariable logistic regression model for delivery within 14 days included cervical stiffness, cervical length, and covariates selected as potential confounders. Results: Among 305 participants, 17 (5.6%) delivered within 7 days, 19 (6.2%) within 10 days, and 24 (7.9%) within 14 days. Mean cervical stiffness was lower among women who delivered within 14 days than among those who did not (8.63 vs. 14.82 kPa; p = 0.048). Cervical length was shorter among women who delivered within 7, 10, and 14 days (all p < 0.001). Discrimination for cervical stiffness was moderate (AUC, 0.66, 0.64, and 0.73 for ≤7, ≤10, and ≤14 days) and higher for cervical length (AUC, 0.80, 0.77, and 0.78). The combined model achieved the highest discrimination (AUC, 0.85, 0.85, and 0.86). In the ≤14-day explanatory model, higher log-transformed cervical stiffness was associated with lower odds of delivery (OR, 0.907; 95% CI, 0.828 to 0.995; p = 0.039), as was longer cervical length (OR per 1 mm, 0.910; 95% CI, 0.876 to 0.946; p < 0.001). Conclusions: In symptomatic TPTL, Cervisense-derived cervical stiffness showed moderate discrimination for short-term delivery and provided complementary information to cervical length, with improved discrimination when both measures were combined. These findings support future studies developing multivariable prediction models that incorporate quantitative cervical consistency.

This paper presents a novel approach for screening women in their first trimester of pregnancy to identify those at high risk of having a child with Down syndrome (DS), using machine learning algorithms. Various machine learning models, including statistical, linear, and ensemble models, were trained using a pseudo-anonymized dataset of 90,532 screening patients. This dataset, containing less than 1% positive cases, was obtained from Cruces University Hospital, a public health hospital (Osakidetza) in Baracaldo, Basque Country, Spain. The models incorporate a set of input variables, including demographic variables such as maternal age, weight, ethnicity, smoking status, and diabetes status, as well as laboratory variables like nuchal translucency (NT), pregnancy-associated plasma protein-A (PAPP-A), and beta-human chorionic gonadotropin hormone (B-HCG) levels. The trained classification algorithms achieved ROC-AUC values between 0.970 and 0.982, with sensitivity and specificity of 0.94. The results indicate that machine learning techniques can effectively predict Down syndrome risk in first-trimester screening programs.

Preeclampsia is a multisystem progressive disorder characterized by the new onset of hypertension and proteinuria in the last half of pregnancy or postpartum. Due to the high risk for the mother and also the child it would be really useful to detect as early as possible if a woman is at high risk...

Objectives: To evaluate the reproducibility of lower uterine segment (LUS) thickness measurement before induction of labor (IOL), and to assess the relationship between LUS thickness and IOL outcomes.Methods: This was a prospective cohort study of pregnant women undergoing IOL at term, conducted in a single tertiary hospital between July 2014 and February 2017. Women with a singleton pregnancy at ≥ 37 weeks' gestation, with a live fetus in cephalic presentation and a Bishop score of ≤ 6, were eligible for inclusion. Both nulliparous and parous women, and those with a previous Cesarean section (CS), were eligible. All women underwent transvaginal ultrasound assessment before IOL admission, and cervical length and LUS thickness were measured offline after delivery. Maternal and obstetric characteristics and Bishop score were recorded. The main outcome was the overall rate of CS after IOL, and secondary outcomes were CS for either failure to progress in the active phase of labor or failed IOL, and CS for failed IOL only. Interobserver agreement for measurement of LUS thickness between two operators was assessed using the intraclass correlation coefficient (ICC) and Bland–Altman analysis with the ANOVA test to evaluate systematic bias. Univariable and multivariable analysis were employed to evaluate the relationship between clinical and sonographic characteristics and IOL outcomes.Results: Of 265 women included in the analysis, 195 (73.6%) had a vaginal delivery and 70 (26.4%) required a CS after IOL. Reproducibility analysis showed excellent interobserver agreement for the measurement of LUS thickness (ICC, 0.96 (95% CI, 0.93–0.98)). On Bland–Altman analysis, the mean difference in LUS thickness between the two operators was 0.15 mm (95% limits of agreement, –1.84 to 2.14 mm), and there was no evidence of systematic bias (ANOVA test, P = 0.46). Univariable analysis showed that LUS thickness was associated significantly with overall CS (P = 0.002), CS for failure to progress in the active phase of labor or failed IOL (P = 0.03) and CS for failed IOL (P = 0.037). On multivariable logistic regression analysis, LUS thickness was an independent predictive factor for overall CS (odds ratio (OR), 1.149 (95% CI, 1.031–1.281)) and CS for failure to progress in the active phase of labor or failed IOL (OR, 1.226 (95% CI, 1.039–1.445)).Conclusions: In women undergoing IOL at term, measurement of LUS thickness is feasible and reproducible, and is associated significantly with IOL outcome. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Objectives: Cervical length (CL) measurement ≤ 25 mm on mid‐trimester ultrasound scan is a known risk factor for preterm birth, for which vaginal progesterone is recommended. The aims of this study were to evaluate whether CL measurement is affected by observer bias and to assess the impact on short cervix prevalence of masking CL measurement during routine mid‐trimester ultrasound scan.Methods: This was a flash study designed for a 2‐month period (October and November 2018) at Cruces University Hospital (Bizkaia, Spain), in which all CL measurements from routine mid‐trimester scans were masked. During the study period, there was no modification of the routine screening method, and women with a short cervix were prescribed 200 mg vaginal progesterone daily as per usual. The control group included women examined in a 2‐month period (April and May 2018) prior to the study, in which CL measurements were taken as usual by a non‐blinded operator. The primary outcome was the prevalence of short cervix in each group.Results: A total of 983 CL measurements were analyzed, including 457 in the blinded group and 526 in the control group. The prevalence of short cervix was 2.7% in the non‐blinded group and 5.5% in the blinded group (P = 0.024). We identified a statistically significant difference in the incidence of CL of 24–25 mm between the two groups, with a lower prevalence in the non‐blinded vs blinded group (0.6% vs 2.4%; P < 0.005). Moreover, the distribution of CL values was normal in the blinded group, in contrast to the non‐blinded group, which was characterized by skewed distribution of CL values.Conclusions: Expected‐value bias exists and should be taken into account when measuring CL in mid‐trimester preterm birth screening. Blinding has demonstrated to be an effective strategy to improve the performance of CL screening in clinical practice. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

To assess the performance of the PAMG-1 and fFN tests using real-world data for the prediction of spontaneous preterm delivery (sPTD) in patients presenting to an emergency obstetrical unit with threatened preterm labour (PTL) by conducting a retrospective audit of patient medical records over two different one-year time periods during which either fFN or PAMG-1 was used as the standard of care biochemical test. A retrospective cohort study chart review of women with threatened PTL electronic medical records (EMR) from a Level III maternity hospital was conducted for two periods of one year each: (1) the “Baseline” time period, during which the qualitative fFN test with a cutoff of 50 ng/ml was used as standard of care biochemical test for the risk assessment of preterm delivery, and (2) the “Comparative” time period, during which the PAMG-1 test with a cutoff of 1 ng/mL was used as the standard of care biomarker test. Patients with singleton gestations between 24⁺⁰ to 34⁺⁶ weeks of gestation with symptoms of early preterm labour, clinically intact membranes, and cervical dilation 4 times more reliable than a positive fFN test in predicting imminent sPTD. Fewer positive biomarker test results that are more reliable is associated with a reduction in unnecessary admissions, avoidable treatments, and preventable use of hospital resources.

Labor induction is defined as the artificial stimulation of uterine contractions aimed to induce vaginal birth. Occurring in about 20% of pregnancies labor induction has become one the most commonly practiced procedures in obstetrics. One of the risk related to labor induction is cesarean section which accounts about 20% of the inductions. A requirement for a successful labor is a ripe cervix (soft and distensible). Microestructural changes occurring in the cervix during the ripening process, will affect the interaction between cervical tissues and sound waves during ultrasound transvaginal scanning and will be perceived as gray level intensity variations in the echographic image. A non-invasive method using image processing of ultrasound images may help in predicting the outcome of labor induction. In this paper a set of echography images from labor induction patients is analyzed using a multiscale methodology based on Center Symmetric Local Binary Patterns and Gabor filters. Results show that it is feasible to predict the outcome of a labor induction procedure using this method with a good accuracy.