Predicting preterm birth in women with previous preterm birth and cervical length ≥ 25 mm

The PRECISION study protocol: Can cervical stiffness in the second trimester predict preterm birth in high-risk singleton pregnancies? A feasibility, cohort study

BACKGROUND

Preterm birth (PTB) is a leading cause of neonatal morbidity and mortality. More than 13 million babies are affected globally every year and PTB will contribute to over 900,000 deaths. In the UK, PTB affects 8% of pregnancies and costs more than £260 million annually in neonatal care. Identifying those at risk of this devastating complication of pregnancy and implementing preventative treatment remains a maternal health priority. The mainstay of PTB prevention has been assessment of cervical length (CL) in women at high-risk of PTB. However, CL has limitations, namely it is invasive, user dependent and varies over time through pregnancy. Importantly, not all those who are high-risk with a short CL will subsequently deliver preterm and CL screening doesn't identify a sub-set of women who have a spontaneous PTB without a short cervix. Therefore, existing care pathways for managing PTB can potentially benefit from additional assessments of risk. Novel ways of assessing cervical structure and function may improve our ability to predict spontaneous PTB and refine preventative intervention. This feasibility study will explore the use of a new antenatal test of cervical stiffness for assessing risk of spontaneous PTB in a high-risk singleton population.

METHODS

PRECISION is a single site prospective, feasibility, cohort study of asymptomatic women with singleton pregnancies at high risk for spontaneous PTB attending an inner-city tertiary maternity hospital in the UK. All study participants will be undergoing routine screening and management of PTB as per local guidance (NICE/Saving Babies Lives guidance) including CL screening with transvaginal ultrasound. Cervical stiffness will be assessed using the Pregnolia System; a novel, licensed, CE-marked, aspiration-based device. A measurement is obtained by applying the device directly to the anterior lip of the cervix, visualised via placement of a speculum, and gives a quantitative assessment of cervical stiffness represented as the Cervical Stiffness Index (CSI, in mbar). Participants will undergo cervical stiffness assessments at up to three timepoints in the second trimester between 14+0 weeks and 25+6 weeks gestation. The cervical stiffness index data will be paired with routine PTB clinic CL measurements taken at the same time points. The primary outcome will focus on the feasibility of using this novel antenatal test in this high-risk population and explore any association between cervical stiffness and PTB.

DISCUSSION

This is an exploratory study to assess the use of this novel device in clinical practice. Direct comparison between cervical stiffness assessment using the Pregnolia System and CL assessment will determine the acceptability of this new assessment in this population, as well as explore its potential association with PTB. Our findings from this feasibility study will provide data on the potential of this novel device to impact PTB screening and evaluate acceptability of use in a high-risk population. Data on eligibility, recruitment rates and participant feedback will help inform future study design using the device.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05837390.

Prediction of preterm birth in multiparous women using logistic regression and machine learning approaches

To predict preterm birth (PTB) in multiparous women, comparing machine learning approaches with traditional logistic regression. A population-based cohort study was conducted using data from the Ontario Better Outcomes Registry and Network (BORN). The cohort included all multiparous women who delivered a singleton birth at 20-42 weeks' gestation in an Ontario hospital between April 1, 2012 and March 31, 2014. The primary outcome was PTB < 37 weeks, with spontaneous PTB analyzed as a secondary outcome. Stepwise logistic regression and the Boruta machine learning were used to select the important variables during the first and second trimester. For building prediction models, the whole data set were divided for the two independent parts: two-third for training the classifiers (Logistic regression, random forests, decision trees, and artificial neural networks) and one-third for model validation. Then, the training data set were balanced by random over sampling technique. The best hyper parameters were obtained by the tenfold cross validation. The performance of all models was evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristics (AUC). The cohort included 145,846 births, of which 8125 (5.57%) were preterm. In first-trimester models, the strongest predictors of PTB were previous PTB, preexisting diabetes, and abnormal pregnancy-associated plasma protein-A. In the testing data set, the highest predictive ability was seen for artificial neural networks, with an area under the receiver operating characteristic curve (AUC) of 68.8% (95% CI 67.6-70.1%). In second-trimester models, addition of infant sex, attendance at first-trimester appointment, medication exposure, and abnormal alpha-fetoprotein concentrations increased the AUC to 72.1% (95% CI 71.1-73.1%) with logistic regression. With the inclusion of the variable complications during pregnancy, the AUC increased to 80.5% (95% CI 79.6-81.5%) using logistic regression. For both overall and spontaneous PTB, during both the first and second trimesters, models yielded negative predictive values of 97%. Overall, machine learning and logistic regression produced similar performance for prediction of PTB. For overall and spontaneous PTB, both first- and second-trimester models provided negative predictive values of ~ 97%, higher than that of fetal fibronectin.

Amniotic Sludge and Prematurity: Systematic Review and Meta-analysis

OBJECTIVE

 To perform a systematic review and meta-analysis of studies on maternal, fetal, and neonatal outcomes of women with singleton pregnancies, after spontaneous conception, and with the diagnosis of amniotic sludge before 37 weeks of gestational age.

DATA SOURCES

 We conducted a search on the PubMed, Cochrane, Bireme, and Theses databases until June 2022.

SELECTION OF STUDIES

 Using the keywords intra-amniotic sludge or fluid sludge or echogenic particles, we found 263 articles, 132 of which were duplicates, and 70 were discarded because they did not meet the inclusion criteria.

DATA COLLECTION

 The articles retrieved were analyzed by 2 reviewers; 61 were selected for full-text analysis, 18 were included for a qualitative analysis, and 14, for a quantitative analysis.

DATA SYNTHESIS

 Among the maternal outcomes analyzed, there was an increased risk of preterm labor (95% confidence interval [95%CI]: 1.45-2.03), premature rupture of ovular membranes (95%CI: 1.99-3.79), and clinical (95%CI: 1.41-6.19) and histological chorioamnionitis (95%CI: 1.75-3.12). Regarding the fetal outcomes, there was a significant increase in the risk of morbidity (95%CI: 1.80-3.17), mortality (95%CI: 1.14-18.57), admission to the Neonatal Intensive Care Unit (NICU; 95%CI: 1.17-1.95), and neonatal sepsis (95%CI: 2.29-7.55).

CONCLUSION

 The results of the present study indicate that the presence of amniotic sludge is a risk marker for preterm delivery. Despite the heterogeneity of the studies analyzed, even in patients with other risk factors for prematurity, such as short cervix and previous preterm delivery, the presence of amniotic sludge increases the risk of premature labor. Moreover, antibiotic therapy seems to be a treatment for amniotic sludge, and it may prolong pregnancy.

The effectiveness of vaginal progesterone in reducing preterm birth in high-risk patients diagnosed with short cervical length after 24 weeks: A retrospective cohort study

Objective

To assess the impact of progesterone treatment on maternal and neonatal outcomes in women with a history of preterm birth and short cervical length diagnosed after 24 weeks of gestation.

Methods

A retrospective cohort study included women with a history of preterm birth and a transvaginal sonographic cervical length measurement of ≤ 25 mm, diagnosed between 24+0 and 33+6 weeks of gestation. Exclusion criteria included prior progesterone treatment, cervical cerclage, or pessary. The study population was divided into the progesterone treatment group and the non-treatment group.

Results

The study included 104 women, with 46.2% (48/104) receiving progesterone treatment and 53.8% (56/104) not receiving treatment. The rate of spontaneous preterm birth before 37 weeks of gestation was 43% (24/56) in the non-treatment group and 31% (15/48) in the progesterone treatment group (P = 0.14); the rate of spontaneous preterm birth before 34 weeks was 7% (4/56) in the non-treatment group and 0% (0/48) in the progesterone treatment group (P = 0.05). Progesterone treatment was associated with a significant decrease in neonatal intensive care unit admissions (OR 0.20, 95% CI 0.05-0.74) and in the neonatal hospitalization period (mean difference in days 2.43, 95% CI 0.44-4.42). The risk of recurrent spontaneous preterm birth was highest (71%) among women with two or more previous preterm deliveries who did not receive progesterone treatment, and lowest (24%) among women with one previous preterm delivery who received progesterone treatment.

Conclusion

Progesterone treatment was associated with a reduction in rates of spontaneous preterm birth before 34 weeks of gestation, neonatal intensive care unit admission, and neonatal length of stay in high-risk patients, even when initiated after 24 weeks of gestation.

Gut and Reproductive Tract Microbiota Adaptation during Pregnancy: New Insights for Pregnancy-Related Complications and Therapy

Pregnancy is characterized by maternal adaptations that are necessary to create a welcoming and hospitable environment for the fetus. Studies have highlighted how the microbiota modulates several networks in humans through complex molecular interactions and how dysbiosis (defined as quantitative and qualitative alterations of the microbiota communities) is related to human pathologies including gynecological diseases. This review analyzed how maternal uterine, vaginal, and gut microbiomes could impact on fetus health during the gestational period. We evaluated the role of a dysbiotic microbiota in preterm birth, chorioamnionitis, gestational diabetes mellitus and pre-eclampsia. For many years it has been hypothesized that newborns were sterile organisms but in the past few years this paradigm has been questioned through the demonstration of the presence of microbes in the placenta and meconium. In the future, we should go deeper into the concept of in utero colonization to better understand the role of microbiota through the phases of pregnancy. Numerous studies in the literature have already showed interesting results regarding the role of microbiota in pregnancy. This evidence gives us the hope that microbiota modulation could be a novel strategy to reduce the morbidity and mortality related to pregnancy complications in the future.

The use of specialised preterm birth clinics for women at high risk of spontaneous preterm birth: a systematic review

Background

Specialised preterm birth clinics care for women at high risk of spontaneous preterm birth. This systematic review assesses current practice within preterm birth clinics globally.

Methods

A comprehensive search strategy was used to identify all studies on preterm birth clinics on the MEDLINE, Embase, PsycINFO, CENTRAL and CINAHL databases. There were no restrictions to study design. Studies were limited to the English language and publications from 1998 onwards. Two reviewers assessed studies for inclusion, performed data extraction and reviewed methodological quality. Primary outcomes were referral criteria, investigations and interventions offered in preterm birth clinics. Secondary outcomes were the timing of planned first and last appointments and frequency of review.

Results

Thirty-two records fulfilled eligibility criteria and 20 studies were included in the main analysis following grouping of records describing the same study or clinic. Studies were of mixed study design and methodological quality. A total of 39 clinics were described; outcome data was not available for all clinics. Referral criteria included previous spontaneous preterm birth (38/38, 100%), previous mid-trimester loss (34/38, 89%) and previous cervical surgery (33/38, 87%). All clinics offered transvaginal cervical length scans. Additional investigations varied, including urogenital swabs (16/28, 57%) and fetal fibronectin (8/28, 29%). The primary treatment of choice for a sonographic short cervix was cervical cerclage in 10/33 (30%) clinics and vaginal progesterone in 6/33 (18%), with 10/33 (30%) using multiple first-line options and 6/33 (18%) using a combination of treatments. The majority of clinics planned timing of first review for 12–16 weeks (30/35, 86%) and the frequency of review was usually determined by clinical findings (18/24, 75%). There was a wide variation in gestational age at clinic discharge between 24 and 37 weeks.

Conclusions

There is variation in the referral criteria, investigations and interventions offered in preterm birth clinics and in the timing and frequency of review. Consistency in practice may improve with the introduction of consensus guidelines and national preterm birth prevention programmes.

Trial registration

Systematic review registration number: CRD42019131470.

Effect of QUiPP prediction algorithm on treatment decisions in women with a previous preterm birth: a prospective cohort study

OBJECTIVE

The QUiPP algorithm combines cervical length, quantitative fetal fibronectin (qfFN) and medical history to quantify risk of preterm birth. We assessed the utility of QUiPP to inform preterm birth prevention treatment decisions.

DESIGN

A prospective cohort study with a subsequent impact assessment using the QUiPP risk of birth before 34 weeks' gestation.

SETTING

A UK tertiary referral hospital.

SAMPLE

In all, 119 women with previous spontaneous preterm birth (sPTB) or preterm premature rupture of membranes (PPROM) before 34 weeks' gestation.

METHODS

Cervical length and qfFN were measured at 19⁺⁰ to 23⁺⁰  weeks' gestation. Clinical management was based on history and cervical length. After birth, clinicians were unblinded to qfFN results and QUiPP analysis was undertaken.

MAIN OUTCOME MEASURES

Predictive statistics of QUiPP algorithm using 10% risk of sPTB before 34⁺⁰  weeks as treatment threshold.

RESULTS

Fifteen of 119 women (13%) had PPROM or sPTB before 34 weeks. Of these, 53% (8/15) had QUiPP risk of sPTB before 34⁺⁰  weeks above 10%. Applying this treatment threshold in practice would have doubled our treatment rate (20 versus 42%). QUIPP threshold of 10% had positive likelihood ratio (LR) of 1.3 (95% CI 0.76-2.18), and negative LR of 0.8 (95% CI 0.45-1.40) for predicting sPTB before 34⁺⁰  weeks.

CONCLUSIONS

Use of the QUiPP algorithm in this population may lead to substantial increase in interventions without evidence that currently available treatment options are beneficial for this particular group.

TWEETABLE ABSTRACT

Independent study finds that the QUiPP algorithm could lead to substantial increases in treatment without evidence of benefit.

Using an innovative stacked ensemble algorithm for the accurate prediction of preterm birth

Objective:

A birth before the normal term of 38 weeks of gestation is called a preterm birth (PTB). It is one of the major reasons for neonatal death. The objective of this article was to predict PTB well in advance so that it was converted to a term birth.

Material and Methods:

This study uses the historical data of expectant mothers and an innovative stacked ensemble (SE) algorithm to predict PTB. The proposed algorithm stacks classifiers in multiple tiers. The accuracy of the classiffication is improved in every tier.

Results:

The experimental results from this study show that PTB can be predicted with more than 96% accuracy using innovative SE learning.

Conclusion:

The proposed approach helps physicians in Gynecology and Obstetrics departments to decide whether the expectant mother needs treatment. Treatment can be given to delay the birth only in patients for whom PTB is predicted, or in many cases to convert the PTB to a normal birth. This, in turn, can reduce the mortality of babies due to PTB.

Mid-Trimester Cervical Consistency Index and Cervical Length to Predict Spontaneous Preterm Birth in a High-Risk Population

Background  Short cervical length (CL) has not been shown to be adequate as a single predictor of spontaneous preterm birth (sPTB) in high-risk pregnancies. Objective  The objective of this study was to evaluate the performance of the mid-trimester cervical consistency index (CCI) to predict sPTB in a cohort of high-risk pregnancies and to compare the results with those obtained with the CL. Study Design  Prospective cohort study including high-risk singleton pregnancies between 19 ⁺⁰ and 24 ⁺⁶ weeks. The ratio between the anteroposterior diameter of the uterine cervix at maximum compression and at rest was calculated offline to obtain the CCI. Results  Eighty-two high sPTB risk women were included. CCI (%) was significantly reduced in women who delivered <37 ⁺⁰ weeks compared with those who delivered at term, while CL was not. The area under the curve (AUC) of the CCI to predict sPTB <37 ⁺⁰ weeks was 0.73 (95% confidence interval [CI], 0.61-0.85), being 0.51 (95% CI, 0.35-0.67), p  = 0.03 for CL. The AUC of the CCI to predict sPTB <34 ⁺⁰ weeks was 0.68 (95% CI, 0.54-0.82), being 0.49 (95% CI, 0.29-0.69), p  = 0.06 for CL. Conclusion  CCI performed better than sonographic CL to predict sPTB. Due to the limited predictive capacity of these two measurements, other tools are still needed to better identify women at increased risk.

Probing the potential of mucus permeability to signify preterm birth risk

Preterm birth is the leading cause of neonatal mortality, and is frequently associated with intra-amniotic infection hypothesized to arise from bacterial ascension across a dysfunctional cervical mucus plug. To study this dysfunction, we assessed the permeability of cervical mucus from non-pregnant ovulating (n = 20) and high- (n = 9) and low-risk (n = 16) pregnant women to probes of varying sizes and surface chemistries. We found that the motion of negatively charged, carboxylated microspheres in mucus from pregnant patients was significantly restricted compared to ovulating patients, but not significantly different between high- and low-risk pregnant women. In contrast, charged peptide probes small enough to avoid steric interactions, but sensitive to the biochemical modifications of mucus components exhibited significantly different transport profiles through mucus from high- and low-risk patients. Thus, although both microstructural rearrangements of the components of mucus as well as biochemical modifications to their adhesiveness may alter the overall permeability of the cervical mucus plug, our findings suggest that the latter mechanism plays a dominant role in the impairment of the function of this barrier during preterm birth. We expect that these probes may be readily adapted to study the mechanisms underlying disease progression on all mucosal epithelia, including those in the mouth, lungs, and gut.

Risk of recurrent spontaneous preterm birth: a systematic review and meta-analysis

OBJECTIVE

To determine the risk of recurrent spontaneous preterm birth (sPTB) following sPTB in singleton pregnancies.

DESIGN

Systematic review and meta-analysis using random effects models.

DATA SOURCES

An electronic literature search was conducted in OVID Medline (1948-2017), Embase (1980-2017) and ClinicalTrials.gov (completed studies effective 2017), supplemented by hand-searching bibliographies of included studies, to find all studies with original data concerning recurrent sPTB.

STUDY ELIGIBILITY CRITERIA

Studies had to include women with at least one spontaneous preterm singleton live birth (<37 weeks) and at least one subsequent pregnancy resulting in a singleton live birth. The Newcastle-Ottawa Scale was used to assess study quality.

RESULTS

Overall, 32 articles involving 55 197 women, met all inclusion criteria. Generally studies were well conducted and had a low risk of bias. The absolute risk of recurrent sPTB at <37 weeks' gestation was 30% (95% CI 27% to 34%). The risk of recurrence due to preterm premature rupture of membranes (PPROM) at <37 weeks gestation was 7% (95% CI 6% to 9%), while the risk of recurrence due to preterm labour (PTL) at <37 weeks gestation was 23% (95% CI 13% to 33%).

CONCLUSIONS

The risk of recurrent sPTB is high and is influenced by the underlying clinical pathway leading to the birth. This information is important for clinicians when discussing the recurrence risk of sPTB with their patients.

Maternal Whole Blood Gene Expression at 18 and 28 Weeks of Gestation Associated with Spontaneous Preterm Birth in Asymptomatic Women

The heterogeneity of spontaneous preterm birth (SPTB) requires an interdisciplinary approach to determine potential predictive risk factors of early delivery. The aim of this study was to investigate maternal whole blood gene expression profiles associated with spontaneous preterm birth (SPTB, <37 weeks) in asymptomatic pregnant women. The study population was a matched subgroup of women (51 SPTBs, 114 term delivery controls) who participated in the All Our Babies community based cohort in Calgary (n = 1878). Maternal blood at 17–23 (sampling time point 1, T₁) and 27–33 weeks of gestation (T₂) were collected. Total RNA was extracted and microarray was performed on 326 samples (165 women). Univariate analyses determined significant clinical factors and differential gene expression associated with SPTB. Thirteen genes were validated using qRT-PCR. Three multivariate logistic models were constructed to identify gene expression at T₁ (Model A), T₂ (Model B), and gene expression fold change from T₁ to T₂ (Model C) associated with SPTB. All models were adjusted for clinical factors. Model C can predict SPTB with 65% sensitivity and 88% specificity in asymptomatic women after adjusting for history of abortion and anaemia (occurring before T₂). Clinical data enhanced the sensitivity of the Models to predict SPTB. In conclusion, clinical factors and whole blood gene expression are associated with SPTB in asymptomatic women. An effective screening tool for SPTB during pregnancy would enable targeted preventive approaches and personalised antenatal care.

Individualized assessment of preterm birth risk using two modified prediction models

OBJECTIVES

To construct two prediction models for individualized assessment of preterm delivery risk within 48h and before completed 32 weeks of gestation and to test the validity of modified and previously published models.

STUDY DESIGN

Data on 617 consecutive women with preterm labor transferred to a tertiary care center for threatened preterm delivery between 22 and 32 weeks of gestation were analysed. Variables predicting the risk of delivery within 48h and before completed 32 weeks of gestation were assessed and applied to previously published prediction models. Multivariate analyses identified variables that were incorporated into two modified models that were subsequently validated.

RESULTS

Two modified prediction models were developed and internally validated, incorporating four and six of the following variables to predict the risk of delivery within 48h and before completed 32 weeks of gestation, respectively: presence of preterm premature rupture of membranes and/or vaginal bleeding, sonographic cervical length, week of gestation, fetal fibronectin, and serum C-reactive protein. The correspondence between the actual and the predicted preterm birth rates suggests excellent calibration of the models. Internal validation analyses for the modified 48h and 32 week prediction models revealed considerably high concordance-indices of 0.8 (95%CI: [0.70-0.81]) and 0.85 (95%CI: [0.82-0.90]), respectively.

CONCLUSIONS

Two modified prediction models to assess the risk of preterm birth were constructed and validated. The models can be used for individualized prediction of preterm birth and allow more accurate risk assessment than based upon a single risk factor. An online-based risk-calculator was constructed and can be assessed through: http://cemsiis.meduniwien.ac.at/en/kb/science-research/software/clinical-software/prematurebirth/.