Prediction Of Preterm Delivery Research Articles

Cervical length evolution in pregnancy and prediction of preterm delivery.

To construct reference charts for cervical length (CL) in pregnancy based on longitudinal measurements and to assess the value of measuring cervical length after 24weeks of gestation. CL was measured transvaginally in singleton pregnancies at 5 to 41weeks. Pregnancies with more than one measurement were used for creating the CL chart, whereas any measurement after 24weeks was considered for assessing the correlation of CL with preterm delivery. The dataset consisted of 12,601 pregnancies and 33,899 observations. Gestational age was the main predictor of CL (R2 = 67.3%). Further adjustments in the fixed effects part for maternal characteristics (age, BMI, smoking status, parity, history of miscarriage, and cervical surgery) improved the prediction ability (R2 = 78.4%). CL was predictive of spontaneous preterm delivery before 37weeks when measured at any gestation between 24 and 35weeks and it was predictive of spontaneous preterm delivery before 32weeks when measured between 28 and 31weeks (AUC = 0.68). Gestational age is the main predictor of CL followed by maternal characteristics and history. CL assessment between 24 and 35 + 6weeks can enhance our ability to predict spontaneous preterm delivery.

Serum calcium level at 32 weeks of gestation could be applied as a predictor of preterm delivery: a retrospective study

Preterm delivery (PTD) is associated with severe adverse maternal and neonatal outcomes and higher medical costs. Therefore, PTD warrants more attention. However, predicting PTD remains a challenge for researchers. This study aimed to investigate potential prenatal predictors of PTD. We retrospectively recruited pregnant women who experienced either PTD or term delivery (TD) and underwent laboratory examinations at 32 weeks of gestation. We compared the test results between the two groups and performed logistic regression analysis and receiver operating characteristic (ROC) curve analysis to identify risk factors and predictive factors for PTD. Our investigation revealed that the PTD cohort exhibited statistically significant elevations in lymphocyte count, mean corpuscular hemoglobin concentration, calcium, uric acid, alkaline phosphatase, triglycerides, and total bile acids. Conversely, the PTD group demonstrated statistically significant reductions in mean corpuscular volume, homocysteine, neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), neutrophils to (white blood cells–neutrophils) ratio (dNLR), and (neutrophils × monocytes) to lymphocyte ratio (SIRI). The ROC curve analysis revealed that calcium had an area under the curve (AUC) of 0.705, with a cut-off value of 2.215. Logistic regression analysis showed that premature rupture of membranes was an independent risk factor for PTD. Our study demonstrated that serum calcium levels, NLR, dNLR, and other laboratory tests conducted at 32 weeks of gestation can serve as predictors for PTD. Furthermore, we identified premature rupture of membranes as a risk factor for PTD.

Automatic semantic segmentation of EHG recordings by deep learning: An approach to a screening tool for use in clinical practice

Background and ObjectivePreterm delivery is an important factor in the disease burden of the newborn and infants worldwide. Electrohysterography (EHG) has become a promising technique for predicting this condition, thanks to its high degree of sensitivity. Despite the technological progress made in predicting preterm labor, its use in clinical practice is still limited, one of the main barriers being the lack of tools for automatic signal processing without expert supervision, i.e. automatic screening of motion and respiratory artifacts in EHG records. Our main objective was thus to design and validate an automatic system of segmenting and screening the physiological segments of uterine origin in EHG records for robust characterization of uterine myoelectric activity, predicting preterm labor and help to promote the transferability of the EHG technique to clinical practice. MethodsFor this, we combined 300 EHG recordings from the TPEHG DS database and 69 EHG recordings from our own database (Ci2B-La Fe) of women with singleton gestations. This dataset was used to train and evaluate U-Net, U-Net++, and U-Net 3+ for semantic segmentation of the physiological and artifacted segments of EHG signals. The model's predictions were then fine-tuned by post-processing. ResultsU-Net 3+ outperformed the other models, achieving an area under the ROC curve of 91.4 % and an average precision of 96.4 % in detecting physiological activity. Thresholds from 0.6 to 0.8 achieved precision from 93.7 % to 97.4 % and specificity from 81.7 % to 94.5 %, detecting high-quality physiological segments while maintaining a trade-off between recall and specificity. Post-processing improved the model's adaptability by fine-tuning both the physiological and corrupted segments, ensuring accurate artifact detection while maintaining physiological segment integrity in EHG signals. ConclusionsAs automatic segmentation proved to be as effective as double-blind manual segmentation in predicting preterm labor, this automatic segmentation tool fills a crucial gap in the existing preterm delivery prediction system workflow by eliminating the need for double-blind segmentation by experts and facilitates the practical clinical use of EHG. This work potentially contributes to the early detection of authentic preterm labor women and will allow clinicians to design individual patient strategies for maternal health surveillance systems and predict adverse pregnancy outcomes.

The utility of combined utero-cervical ındex in predicting preterm delivery in pregnant women with preterm uterine contractions.

To evaluate the utility of a novel ultrasound index "combined utero-cervical index (CUCI)" in the prediction of preterm delivery. The present prospective cohort study was conducted in Ankara Bilkent City Hospital Perinatology Clinic between January 1, 2023, and March 31, 2023. Pregnant women with uterine contractions between 24 and 36th gestational weeks but did not have dilatation or effacement were included. CUCI was calculated as: (utero-cervical angle)/(anterior cervical lip thickness + fundal thickness + lower uterine segment thickness + cervical length). In the presence of cervical funneling, one point was added to the final result. A ROC analysis was conducted to determine the potential of CUCI in predicting delivery <37weeks of gestation, <34weeks of gestation, and <4weeks after the first admission to the hospital for uterine contractions, respectively. Optimal cut-off values of CUCI were found to be 1.4 (67.1% sensitivity, 67.2% specificity) for predicting delivery at <37th weeks, 1.7 (72.7% sensitivity, 65.7% specificity) for predicting delivery at <34th weeks, and 1.4 (62.5% sensitivity, 61.7% specificity) for predicting delivery at <4weeks. CUCI may be used in the prediction of preterm delivery for pregnant women admitted to hospital with preterm uterine contractions.

EP19.06: Cervix elastography: prediction of preterm delivery in threatened preterm labour and adjunctive role in positive predictive value of fetal fibronectin

EP19.06: Cervix elastography: prediction of preterm delivery in threatened preterm labour and adjunctive role in positive predictive value of fetal fibronectin

Prediction of Preterm Delivery among Low-risk Indian Pregnant Women: Discriminatory Power of Cervical Length, Serum Ferritin, and Serum Alpha-fetoprotein.

Around 80% of preterm births (PTBs) occur spontaneously. Various biomarkers are being evaluated to assess the possible role of chorioamniotic inflammation in PTBs. The aim of this study was to establish the accuracy of serum bio-markers( cut off values of ferritin and alpha-fetoprotein [AFP] at midtrimester) along with cervical length [CL] assessment to predict preterm delivery among low-risk women. Three hundred low-risk pregnant women attending the antenatal clinic of a tertiary health care facility were included and underwent CL measurement during mid-trimester by transvaginal ultrasonography and their serum levels of ferritin and AFP were recorded. All were followed up till delivery. Receptor-operated characteristic curves for ferritin, AFP, and CL were constructed. Area under curves and Youden Index calculated for each marker were very low (<0.5) which is statistically considered very poor for a screening test. Serum ferritin and AFP together with CL measurement in the second trimester of pregnancy had poor discriminatory value in predicting preterm delivery among low-risk asymptomatic pregnant women.

Outperformance of interleukin-6 over placental alpha microglobulin-1 in predicting preterm delivery in symptomatic women

Threatened preterm labor is the major cause of hospital admission during the second half of pregnancy. An early diagnosis is crucial for adopting pharmacologic measures to reduce perinatal mortality and morbidity. Current diagnostic criteria are based on symptoms and short cervical length. However, there is a high false-positive rate when using these criteria, which implies overtreatment, causing unnecessary side effects and an avoidable economic burden. This study aimed to compare the use of placental alpha microglobulin-1 and interleukin-6 as vaginal biomarkers combined with cervical length and other maternal characteristics to improve the prediction of preterm delivery in symptomatic women. A prospective observational study was conducted in women with singleton pregnancies complicated by threatened preterm labor with intact membranes at 24+0 to 34+6 weeks of gestation. A total of 136 women were included in this study. Vaginal fluid was collected with a swab for placental alpha microglobulin-1 determination using the PartoSure test, interleukin-6 was assessed by electrochemiluminescence immunoassay, cervical length was measured by transvaginal ultrasound, and obstetrical variables and newborn details were retrieved from clinical records. These characteristics were used to fit univariate binary logistic regression models to predict time to delivery <7 days, time to delivery <14 days, gestational age at delivery ≤34 weeks, and gestational age at delivery ≤37 weeks, and multivariate binary logistic regression models were fitted with imbalanced and balanced data. Performance of models was assessed by their F2-scores and other metrics, and the association of their variables with a risk or a protective factor was studied. A total of 136 women were recruited, of whom 8 were lost to follow-up and 7 were excluded. Of the remaining 121 patients, 22 had a time to delivery <7 days and 31 had a time to delivery <14 days, and 30 deliveries occurred with a gestational age at delivery ≤34 weeks and 55 with a gestational age at delivery ≤37 weeks. Univariate binary logistic regression models fitted with the log transformation of interleukin-6 showed the greatest F2-scores in most studies, which outperformed those of models fitted with placental alpha microglobulin-1 (log[interleukin-6] vs placental alpha microglobulin-1 in time to delivery <7 days: 0.38 vs 0.30; time to delivery <14 days: 0.58 vs 0.29; gestational age at delivery ≤34 weeks: 0.56 vs 0.29; gestational age at delivery ≤37 weeks: 0.61 vs 0.16). Multivariate logistic regression models fitted with imbalanced data sets outperformed most univariate models (F2-score in time to delivery <7 days: 0.63; time to delivery <14 days: 0.54; gestational age at delivery ≤34 weeks: 0.62; gestational age at delivery ≤37 weeks: 0.73). The performance of prediction of multivariate models was drastically improved when data sets were balanced, and was maximum for time to delivery <7 days (F2-score: 0.88±0.2; positive predictive value: 0.86±0.02; negative predictive value: 0.89±0.03). A multivariate assessment including interleukin-6 may lead to more targeted treatment, thus reducing unnecessary hospitalization and avoiding unnecessary maternal-fetal treatment.

Pregnancy outcomes following radical trachelectomy for early-stage cervical cancer: A retrospective observational study in the Kanto area, Japan.

The authors aimed to investigate the prevalence of pregnancy and obstetric outcomes in patients who underwent radical trachelectomy (RT) for early-stage cervical cancer in the Kanto area, Japan. A survey among 113 perinatal centers affiliated with the Kanto Society of Obstetrics and Gynecology was conducted to investigate their experience in managing pregnancies following RT, between 2010 and 2020. The association between preterm delivery (before 34 gestational weeks) and a midtrimester short cervix (<13 mm) was evaluated. The authors retrospectively collected maternal and perinatal data from 13 hospitals. There were 135 pregnancies among 115 women following RT. Of the 135 pregnancies, 32 were miscarriages (<12 gestational weeks: n = 22; >12 gestational weeks: n = 10), and 103 were delivered after 22 gestational weeks. The incidences of preterm delivery before 28 and 34 gestational weeks were 8.7% and 30.1%, respectively. A midtrimester short residual cervix was associated with preterm delivery (P = 0.046). Since more than 100 pregnancies were recorded after RT in the Kanto area, many physicians had more opportunities to manage pregnancy after RT. Pregnancy following RT is associated with increased risk of preterm delivery, and midtrimester short residual cervix is a good predictor of preterm delivery.

Predictive value of post-cervical cerclage transabdominal ultrasound measurements of cervical length and anterior cervical angle

ObjectiveCervical cerclage is a surgical procedure commonly used to treat cervical insufficiency, a condition that can lead to preterm birth. Identifying reliable predictors of preterm delivery in women who have undergone cervical cerclage is crucial for risk assessment and appropriate management. This paper intends to assess the predictive value of cervical length and anterior cervical angle, two parameters captured by transabdominal ultrasound for preterm delivery after cervical cerclage. MethodsClinical data of 250 pregnant women who underwent cervical cerclage from June 2020 to August 2022 were selected and analyzed in a retrospective manner. In the light of the pregnancy outcome, the selected subjects were split into a test group (n = 42) and a control group (n = 114). The cervical length and anterior cervical angle of each subject were captured by transabdominal ultrasound. After that, the predictive value of the two parameters was assessed for preterm delivery, with the aid of the receiver operating characteristic (ROC) curves. ResultsInsignificant variations were observed in age, history of pregnancy, history of induced abortion, history of cervical surgery, gestational age at surgery, and other baseline characteristics between the test group and the control group (P > 0.05). Nevertheless, the anterior cervical angle of the test group was larger than that angle of the control group, while the cervical length was shorter in the test group. These variations are significant (P < 0.05). ConclusionsWhen captured by transabdominal ultrasound, cervical length and anterior cervical angle has predictive value for preterm delivery after cervical cerclage (P < 0.05), and cervical length boasts more predictive value than anterior cervical angle. After cervical cerclage, females face a high risk of premature birth, when the cervical length is smaller than 24.5 mm or anterior cervical angle is greater than 110°.

Development of risk prediction models for preterm delivery in a rural setting in Ethiopia

Preterm birth complications are the leading causes of death among children under five years. However, the inability to accurately identify pregnancies at high risk of preterm delivery is a key practical challenge, especially in resource-constrained settings with limited availability of biomarkers assessment. We evaluated whether risk of preterm delivery can be predicted using available data from a pregnancy and birth cohort in Amhara region, Ethiopia. All participants were enrolled in the cohort between December 2018 and March 2020. The study outcome was preterm delivery, defined as any delivery occurring before week 37 of gestation regardless of vital status of the foetus or neonate. A range of sociodemographic, clinical, environmental, and pregnancy-related factors were considered as potential inputs. We used Cox and accelerated failure time models, alongside decision tree ensembles to predict risk of preterm delivery. We estimated model discrimination using the area-under-the-curve (AUC) and simulated the conditional distributions of cervical length (CL) and foetal fibronectin (FFN) to ascertain whether they could improve model performance. We included 2493 pregnancies; among them, 138 women were censored due to loss-to-follow-up before delivery. Overall, predictive performance of models was poor. The AUC was highest for the tree ensemble classifier (0.60, 95% confidence interval = 0.57-0.63). When models were calibrated so that 90% of women who experienced a preterm delivery were classified as high risk, at least 75% of those classified as high risk did not experience the outcome. The simulation of CL and FFN distributions did not significantly improve models' performance. Prediction of preterm delivery remains a major challenge. In resource-limited settings, predicting high-risk deliveries would not only save lives, but also inform resource allocation. It may not be possible to accurately predict risk of preterm delivery without investing in novel technologies to identify genetic factors, immunological biomarkers, or the expression of specific proteins.

Newborn Outcomes After Maternal COVID-19 Infection in Pregnancy and the Potential Role of Infection Severity [ID: 1373946

INTRODUCTION: COVID-19 poses health risks in pregnancy including increased rates of cesarean sections, preeclampsia, and miscarriage. However, less is known about newborn effects and the effect of severity of infection. We evaluated the link between pregnancy COVID-19 infection status and severity, and newborn outcomes. METHODS: Participants in this IRB-approved retrospective chart review study were identified via medical records from a single university-affiliated obstetric practice and grouped as COVID-19 positive during pregnancy (n=69), or COVID-19 negative delivering pre-COVID (n=59). Severity of infection was based on emergency department visit, hospitalization, oxygen treatment, steroids, antibodies, or ventilation. Information on socioeconomic factors, medical history, and birth outcomes was also abstracted. RESULTS: Compared to controls, and after adjustment for background differences, those with COVID-19 infection during pregnancy had newborns 242 g lighter and were 4.3 times more likely to deliver preterm, 2.6 times more likely to have a newborn with a 1-minute Apgar score less than 8, and 2.9 times more likely to remain hospitalized a week or more. Differences were largely driven by earlier delivery. Finally, severe COVID-19 infection (which occurred for 41% of participants with COVID-19) was a strong predictor of preterm delivery, low birth weight, receipt of oxygen, neonatal intensive care unit admission, and longer hospital stay. CONCLUSION: COVID-19 infection during pregnancy predicts adverse newborn outcomes, especially as a result of reduced gestational duration. Additionally, severity of infection may predict worse outcomes. A larger, more diverse sample is needed to confirm findings, and to examine potential effect of vaccination in reducing the effect of COVID-19 infection during pregnancy.

Quantitative cervicovaginal fetal fibronectin as a predictor of cervical ripening and induced labour duration in late-term pregnancy

We evaluated quantitative cervicovaginal foetal-fibronectin as a predictor of cervical ripening and labour duration in late-term pregnant women with an unfavourable cervix. This was an analytical cross-sectional study wherein 152 women, with late-term pregnancy and unfavourable cervix, at 41weeks3days gestational age, had pre-induction quantitative cervicovaginal foetal-fibronectin determined using ELISA. Data were compared in nulliparas and multiparas at a significance level < 0.05. The mean age of late-term pregnant women was 30.4 ± 4.3 years. Median cervicovaginal foetal-fibronectin levels in nulliparous and multiparous women were 45.35 ng/ml and 46.93 ng/ml respectively(p = 0.289). The correlation between foetal-fibronectin levels and cervical ripening duration was poor in nulliparous(r = 0.014) and multiparous(r = 0.024) women. The Youden’s foetal-fibronectin cut-off level had a sensitivity of 53.5% and specificity of 71.6% in predicting cervical ripening duration of > 12 hours in late-term pregnancy with an area under the ROC curve of 0.634. Quantitative cervicovaginal foetal-fibronectin is a poor correlate and predictor of cervical ripening and induced labour duration in late-term pregnancy. IMPACT STATEMENT What is already known on this subject? Cervicovaginal foetal fibronectin is useful in the prediction of preterm delivery but its role in prolonged pregnancy is unclear. What the results of this study add? Cervicovaginal foetal fibronectin is a poor correlate and predictor of cervical ripening and induced labour duration in late-term pregnancy What the implications are of these findings for clinical practice and/or further research? Cervicovaginal fibronectin should not be used to predict ease and success of cervical ripening and induction of labour in women with late-term pregnancy.

Development and validation of a new antenatal warning score system (DRRiP) for neonatal complications of gestational diabetes.

To evaluate the DRRiP (Diabetes Related Risk in Pregnancy) score warning system as a tool for predicting neonatal morbidity in gestational diabetes. A retrospective observational cohort study. By applying nine parameters from an antenatal trichotomy of glycemic, ultrasound, and clinical characteristics, DRRiP scores were calculated and assigned to each patient using a checklist tool. Logistic regression models were used to evaluate the association between DRRiP score and adverse fetal outcomes, after adjusting for maternal age and body mass index (calculated as weight in kilograms divided by the square of height in meters). In all, 627 women were studied. DRRiP score was an excellent predictor of macrosomia and shoulder dystocia (both areas under the receiver operating characteristics curves [AUROC]=0.86), and a modest predictor of preterm delivery, hyperbilirubinemia, neonatal intensive care unit admission and a composite of either of the studied events (AUROC range 0.63-0.69). For the composite outcome, the sensitivity of an amber trigger score of 1 was 68.7% (95% confidence interval [CI] 62.27%-74.63%) and specificity was 48.87% (95% CI 43.85%-53.9%). Specificity at a red trigger score of 3 (89.7%) and a graded increase in post-test probability (90.7% risk at a score of 5) were highly encouraging. DRRiP score offers reasonable discriminative performance that could be clinically useful for meaningful risk stratification when making delivery plans.

Prediction of preterm delivery based on thyroid peroxidase antibody levels and other identified risk factors

ObjectiveThyroid dysfunction and TPOAb positivity during pregnancy are associated with adverse pregnancy outcomes such as preterm delivery. The aim of this study was to predict preterm delivery based on identified risk factors, especially TPOAb levels. Study designA secondary analysis was run on data collected in the Tehran Thyroid and Pregnancy study (TTPs). We used the data of 1515 pregnant women with singletons. The association between risk factors and preterm birth (delivery before 37 completed weeks of gestation) was investigated in univariate analysis. Multivariate logistic regression analysis was performed to identify independent risk factors, and a stepwise backward elimination method was used to determine the helpful combination of risk factors. The nomogram was developed based on a multivariate logistic regression model. The performance of the nomogram was evaluated using a concordance index and calibration plots with bootstrap samples. Statistical analysis was performed using STATA software package; the significance level was set at P < 0.05. ResultsBased on multivariate logistic regression analysis, a combination of previous preterm delivery [OR: 5.25; 95 %CI: (2.13–12.90), p < 0.01], TPOAb [OR: 1.01; 95 %CI: (1.01–1.02), and T4 [OR: 0.90; 95 %CI: (0.83–0.97); p = 0.04] as independent risk factors that most precisely predicted preterm birth. The area under the curve (AUC) was 0.66 (95% CI: 0.61–0.72). The calibration plot suggests that the fit of the nomogram is reasonable. ConclusionA combination of T4, TPOAb, and previous preterm delivery was identified as independent risk factors that accurately predicted preterm delivery. The total score obtained based on the nomogram designed based on risk factors can predict the risk of preterm delivery.

Comparison of Vaginal and Plasma Fibronectin Concentrations for Prognosis of Preterm Delivery: A Cross-Sectional Study

Background &amp; Objective: Prediction of preterm delivery can reduce a large number of its complications. The present study aimed to compare vaginal and plasma fibronectin concentrations in the diagnosis of preterm delivery.Materials &amp; Methods: Serum samples were obtained from 105 women at 24-36 weeks of gestation. However, only 40 women gave permission to collect vaginal samples. Fibronectin concentration was measured using the ELISA technique. Then, plasma and vaginal fibronectin levels were compared in term and preterm deliveries.Results: The mean plasma fibronectin level was 6226.43±7174.97 ng/ml among the mothers with term infants and 7724.01±1143.82 ng/ml among those with preterm infants (p=0.667). The mean fetal fibronectin level was 156.61±126.42 ng/ml among the mothers with term infants and 127.71±43.14 ng/ml among those with preterm infants (p=0.241). The cut-off point of plasma fibronectin level was 1750 ng/ml with a sensitivity of 80.25% and specificity of 85.17%. Additionally, the cut-off point of vaginal fibronectin level was 158.98 ng/ml with a sensitivity of 94.62% and specificity of 22.08%.Conclusion: Plasma fibronectin analysis had lower sensitivity and higher specificity compared to vaginal fibronectin analysis. This implies that plasma testing has lower false-positive cases and can identify a more significant number of true positive cases of preterm delivery.

Value of cervical strain in ultrasound elastography as a predictor of spontaneous preterm delivery

BackgroundCervical incompetence is a failure of the cervix to retain the products of conception throughout pregnancy, which results into cervical dilatation and preterm delivery. Many methods are conducted for early detection of cervical shortening, ripening and eventually dilatation to lessen the incidence of the preterm delivery, which is responsible for about 75% of neonatal comorbidities. Ultrasound plays an important role in the diagnosis and early detection of cervical incompetence. Elastography is a relatively new technique, which investigates into another important factor for cervical insufficiency which is “tissue stiffness”. The process of early cervical ripening, which is an important and main step in spontaneous preterm delivery, precedes cervical shortening and renders the human cervix soft which can be diagnosed through the color-coding method of the sonoelastography technique. The aim of this study is to determine the value of cervical elastography as a predictor of spontaneous preterm labor and validate the role of strain ratio in such technique.ResultsIn our study, we examined the pregnant females by transvaginal conventional B-mode ultrasound and complementary elastography technique and recorded the elastography index of their cervix, internal os and external os together with measuring the amount of strain and strain ratio at internal and external os.ConclusionsWe concluded that women who had preterm delivery did have higher strain and elastography index as their cervices were softer than those who had full-term deliveries. Elastography therefore can be a reliable method for the prediction of preterm delivery.

Development and validation of nomogram for the prediction of preterm delivery based on patient characteristics and circulating inflammatory cells in patients with gestational diabetes mellitus.

The incidence of preterm delivery (<37 weeks' gestation) is increased due to gestational diabetes mellitus (GDM). The preterm delivery is the leading cause of death in children. If potential preterm delivery can be diagnosed early and then prevented, adverse pregnancy outcomes can be improved. Therefore, effective methods are needed for early prediction of preterm delivery in women with GDM. Patients with GDM defined as the presence of at least 1 plasma glucose abnormality at 24-28 weeks of pregnancy [fasting plasma glucose ≥5.1 mmol/L, 60-min ≥10.0 mmol/L, 120-min ≥8.5 mmol/L by 75 g oral glucose tolerance test (OGTT)] from the First Affiliated Hospital of Wenzhou Medical University were enrolled. The data (564 patients) recorded from January 2017 to June 2020 were named the training cohort, and the data (242 patients) obtained from patients with GDM, from July 2020 to January 2022, were named the validation cohort. Mann-Whitney U test and chi-square test were used to compare the skewed distributed and categorical data, respectively. According to the results of univariate logistic regression analysis, the multivariate logistic regression model was developed in the training cohort. Then, the nomogram was established. The validation of the nomogram was conducted on the training and validation cohort. No significant differences in baseline characteristics were detected between the 2 cohorts (all P>0.05). The multivariate analysis suggested that maternal age, insulin use, NLR, and monocyte count were the independent predictors of preterm delivery. A nomogram for predicting the probability of preterm delivery was developed. The model suggested good discrimination [areas under the curve (AUC) =0.885, 95% confidence interval (95% CI): 0.855-0.910, sensitivity =83.0%, specificity =83.1% in the training cohort; AUC =0.919, 95% CI: 0.858-0.980, sensitivity =90.6%, specificity =84.8% in the validation cohort] and good calibration [Hosmer-Lemeshow (HL) test: χ2=3.618, P=0.306 in the training cohort; χ2=6.012, P=0.111 in the validation cohort]. The visual nomogram model appears to be a reliable approach for the prediction of preterm delivery, allowing clinicians to take timely measures to prevent the occurrence of preterm delivery in women with GDM at the time of GDM diagnosis, and deserves further investigation.

Cervical funneling is more predictive of preterm birth than cervical length alone in nulliparous women

Universal mid-trimester cervical length (CL) screening is a well-accepted practice for detection of women at risk of spontaneous preterm birth (sPTB). In those identified with a short cervix, progesterone supplementation is recommended. However, current guidelines do not consider a short cervix an indication for cerclage without a history of sPTB as it has poor sensitivity for this outcome. It is currently unclear if other sonographic features such as cervical funneling can identify a higher sPTB risk in a population without prior sPTB. This was a secondary analysis of the nuMom2b study, which enrolled a large prospective observational cohort of pregnant nulliparous women. Patients were stratified based on CL < 25mm or ≥25mm and presence or absence of funneling at the time of cervical length evaluation between 16-22 weeks’ gestation. Logistic regression was used to calculate adjusted odds ratios (aOR) and 95% confidence intervals (CI) for sPTB adjusting for confounders. A Kaplan-Meier survival analysis was performed between groups and gestational age at delivery. 7,648 nulliparous women were included in the analysis. There were 169 (2.2%) women identified with a short CL < 25 mm and 52 (0.7%) with funneling. While a short CL had a higher risk of PTB (Table 1), a short CL was detected in only 24 (7.1%) of women who ultimately had a sPTB. The presence of a funnel was independently associated with higher odds of sPTB (OR 3.4, CI 1.9-8.1) when compared to CL < 25mm (OR 2.7, CI 1.7-4.4). On survival analysis, a short CL with funneling showed the lowest mean gestational age at delivery (Figure 2, p< .001). In a nulliparous population without prior sPTB, transvaginal cervical length alone is a poor predictor of preterm delivery, but presence of funneling significantly increases risk. This may identify a population of women who would benefit from cerclage.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

A Prospective Study of Mid-Trimester MCP-1 Levels as a Predictor of Preterm Delivery.

Background: The prevention of preterm delivery (PTD) represents one of the major topics in modern obstetrics. The aim was to design a prospective study and investigate if mid-trimester serum and amniotic fluid levels of MCP-1 could predict the occurence of spontaneous PTD. Methods: The study involved 198 women who underwent genetic amniocentesis and blood sampling in the middle of their trimester. After applying the criteria for inclusion in the study, there were 16 respondents in the study group, and 38 respondents in the control group. Level of MCP-1 in amniotic fluid and serum was measured with commercially available enzyme-linked immunosorbent assays (ELISA) and statistical analysis was conducted. Results:&amp;nbsp;There was no statistically significant difference in serum or amniotic fluid MCP1 levels between PTD and the control groups. Conclusion: The results suggest that MCP-1 is probably not the most relevant marker for predicting PTD. This study provides new normative data for MCP-1 levels in amniotic fluid and maternal sera and is a valuable tool for future diagnostic and comparative studies.

Prediction of Preterm Delivery From the Endocervical Length at 11 to 14 Weeks

Background and Objectives Premature delivery is called delivery before 37 weeks. It is estimated that every year, about 15 million babies are born with preterm delivery worldwide, which is approximately equal to 11% of the total number of deliveries. In this study, a number of pregnant women with 11-14 weeks of pregnancy were evaluated in order to evaluate the value of cervical length at the end of the first trimester of pregnancy in predicting preterm delivery. Subjects and Methods In this cohort study, 156 asymptomatic pregnant women with a gestational age of 11-14 weeks were randomly selected and evaluated. Cervical length was measured by transvaginal ultrasound using a standard method. Cervical length and gestational age at delivery were recorded in a computer database along with demographic information, clinical history, and pregnancy information. Results The mean length of the cervix in women with preterm delivery was 31.32±6.71 mm and in women with term delivery was 38.96±5.80 mm. Data analysis showed that shorter cervical length was significantly associated with preterm delivery. With a threshold of 34.5 mm, the length of the cervix from 3rd month to 6th month could predict preterm delivery with a sensitivity of 76% and a specificity of 81%. Conclusion Measuring cervical length with transvaginal ultrasound in the second trimester can predict preterm delivery.