Prediction of preterm birth in symptomatic women using decision tree modeling for biomarkers

Changes of serum cortisol during pregnancy and labor initiation: an onsite cross-sectional study

Background

Increased maternal cortisol secretion has been observed during pregnancy and labor. However, due to the limitations in diagnostic methods, the dynamic change of cortisol during the short period between threatened labor and labor is unknown. In this study, we aim to evaluate the changes in serum cortisol during late pregnancy and full-term labor initiation, verifying if cortisol could serve as a biomarker for the diagnosis of labor initiation from threatened labor.

Methods

This cross-sectional onsite study involved 564 participants of 6 different gestational stages (C: Control; T1: Trimester 1; T3: Trimester 3; E: expectant; TL: threatened labor; L: labor), all patients in the E, TL, and L groups were at full term. The serum cortisol concentration was quantified with a point-of-care test (POCT), and the gestation, age, parity, and BMI of participants were documented. Morning serum cortisol was collected between 8:00 and 10:00 a.m., except for the TL and L group women who were tested upon arrival or during latent labor. With cortisol levels or all five variables, L was distinguished from TL using machine learning algorithms.

Results

Significant elevation of cortisol concentration was observed between T1 and T3, or TL and L group (P< 0.001). Women belonging to the E and TL group showed similar gestation week and cortisol levels. Diagnosis of labor initiation using cortisol levels (cutoff = 21.46 μg/dL) yielded sensitivity, specificity, and AUC of 86.50%, 88.60%, and 0.934. With additional variables, a higher specificity (89.29%) was achieved. The diagnostic accuracy of all methods ranged from 85.93% to 87.90%.

Conclusion

Serum cortisol could serve as a potential biomarker for diagnosis of L form TL. The rapid onsite detection of serum cortisol with POCT could facilitate medical decision-making for admission and special treatments, either as an additional parameter or when other technical platforms are not available.

Unsupervised Learning Applied to the Stratification of Preterm Birth Risk in Brazil with Socioeconomic Data

Preterm birth (PTB) is a phenomenon that brings risks and challenges for the survival of the newborn child. Despite many advances in research, not all the causes of PTB are already clear. It is understood that PTB risk is multi-factorial and can also be associated with socioeconomic factors. Thereby, this article seeks to use unsupervised learning techniques to stratify PTB risk in Brazil using only socioeconomic data. Through the use of datasets made publicly available by the Federal Government of Brazil, a new dataset was generated with municipality-level socioeconomic data and a PTB occurrence rate. This dataset was processed using various unsupervised learning techniques, such as k-means, principal component analysis (PCA), and density-based spatial clustering of applications with noise (DBSCAN). After validation, four clusters with high levels of PTB occurrence were discovered, as well as three with low levels. The clusters with high PTB were comprised mostly of municipalities with lower levels of education, worse quality of public services-such as basic sanitation and garbage collection-and a less white population. The regional distribution of the clusters was also observed, with clusters of high PTB located mostly in the North and Northeast regions of Brazil. The results indicate a positive influence of the quality of life and the offer of public services on the reduction in PTB risk.

Effects of ambient temperature on the risk of preterm birth in offspring of adolescent mothers in rural henan, China

BACKGROUND

A number of studies have explored the association between ambient temperature and preterm birth (PTB), but rarely among adolescent mothers.

OBJECTIVES

To estimate the effects of ambient temperature on the risk of PTB and gestational age of newborns delivered by adolescent mothers in rural areas of Henan province.

METHODS

We obtained 5394 medical records of adolescent mothers with results of pre-pregnancy physical examination and pregnancy outcomes from the National Free Preconception Health Examination Project (NFPHEP) in Henan province. Meteorological information was obtained from the China Meteorological Data Sharing Service System. Individual exposure levels were evaluated with an inverse distance-weighted model. A multiple logistic regression model and multiple linear regression model were used to estimate the effects of ambient temperature on the risk of PTB and gestational age, respectively. Stratified and interaction analyses were also performed.

RESULTS

Of newborns in this study, 3.45% (186/5394) were PTB. Mean, maximum and minimum temperature during the entire pregnancy, especially the last 1-4 weeks of pregnancy, were positively associated with the risk of PTB and negatively associated with gestational age (P < 0.05). Nevertheless, a masking effect was observed that gestational age was positively associated with ambient temperature during the first trimester of pregnancy, due to the strongly inverse correlation between ambient temperature during the early and late stages of pregnancy. Stratified analyses showed that increasing temperature during the last 1-4 weeks of pregnancy increased the risk of PTB and decreased gestational age in newborns born in the cold season (P < 0.05). Furthermore, interaction analyses showed that birth season modified the effects of temperature on the gestational age (P_interaction < 0.10).

CONCLUSIONS

Elevated ambient temperature can decrease gestational age and increase the risk of PTB in offspring of adolescent mothers in rural areas. The birth season may modify the effects of temperature on gestational age.

Clinical risk models for preterm birth less than 28 weeks and less than 32 weeks of gestation using a large retrospective cohort

OBJECTIVE

To develop risk prediction models for singleton preterm birth (PTB) < 28 weeks and <32 weeks.

METHODS

Using a retrospective cohort of 267,226 singleton births in Ontario hospitals, we included variables from the first and second trimester in multivariable logistic regression models to predict overall and spontaneous PTB < 28 weeks and <32 weeks.

RESULTS

During the first trimester, the area under the curve (AUC) for prediction of PTB < 28 weeks for nulliparous and multiparous women was 68.5% (95% CI: 63.5-73.6%) and 73.4% (68.6-78.2%), respectively, while for PTB < 32 weeks it was 68.9% (65.5-72.3%) and 75.5% (72.3-78.7%), respectively. AUCs for second-trimester models were 72.4% (95% CI: 69.7-75.1%) and 78.2% (95% CI: 75.8-80.5%), respectively, in nulliparous and multiparous women. Predicted probabilities were well-calibrated within a wide range around expected base prevalence for the study outcomes.

CONCLUSIONS

Our prediction models generated acceptable AUCs for PTB < 28 weeks and <32 weeks with good calibration during the first and second trimester.

Predicting Unscheduled Emergency Department Return Visits Among Older Adults: Population-Based Retrospective Study

Background

Unscheduled emergency department return visits (EDRVs) are key indicators for monitoring the quality of emergency medical care. A high return rate implies that the medical services provided by the emergency department (ED) failed to achieve the expected results of accurate diagnosis and effective treatment. Older adults are more susceptible to diseases and comorbidities than younger adults, and they exhibit unique and complex clinical characteristics that increase the difficulty of clinical diagnosis and treatment. Older adults also use more emergency medical resources than people in other age groups. Many studies have reviewed the causes of EDRVs among general ED patients; however, few have focused on older adults, although this is the age group with the highest rate of EDRVs.

Objective

This aim of this study is to establish a model for predicting unscheduled EDRVs within a 72-hour period among patients aged 65 years and older. In addition, we aim to investigate the effects of the influencing factors on their unscheduled EDRVs.

Methods

We used stratified and randomized data from Taiwan’s National Health Insurance Research Database and applied data mining techniques to construct a prediction model consisting of patient, disease, hospital, and physician characteristics. Records of ED visits by patients aged 65 years and older from 1996 to 2010 in the National Health Insurance Research Database were selected, and the final sample size was 49,252 records.

Results

The decision tree of the prediction model achieved an acceptable overall accuracy of 76.80%. Economic status, chronic illness, and length of stay in the ED were the top three variables influencing unscheduled EDRVs. Those who stayed in the ED overnight or longer on their first visit were less likely to return. This study confirms the results of prior studies, which found that economically underprivileged older adults with chronic illness and comorbidities were more likely to return to the ED.

Conclusions

Medical institutions can use our prediction model as a reference to improve medical management and clinical services by understanding the reasons for 72-hour unscheduled EDRVs in older adult patients. A possible solution is to create mechanisms that incorporate our prediction model and develop a support system with customized medical education for older patients and their family members before discharge. Meanwhile, a reasonably longer length of stay in the ED may help evaluate treatments and guide prognosis for older adult patients, and it may further reduce the rate of their unscheduled EDRVs.

Prediction of preterm birth based on machine learning using bacterial risk score in cervicovaginal fluid

PROBLEM

Preterm birth (PTB) is a major cause of increased morbidity and mortality in newborns. The main cause of spontaneous PTB (sPTB) is the activation of an inflammatory response as a result of ascending genital tract infection. Despite various studies on the effects of the vaginal microbiome on PTB, a practical method for its clinical application has yet to be developed.

METHOD OF STUDY

In this case-control study, 94 Korean pregnant women with PTB (n = 38) and term birth (TB; n = 56) were enrolled. Their cervicovaginal fluid (CVF) was sampled, and a total of 10 bacteria were analyzed using multiplex quantitative real-time PCR (qPCR). The PTB and TB groups were compared, and a PTB prediction model was created using bacterial risk scores using machine learning techniques (decision tree and support vector machine). The predictive performance of the model was validated using random subsampling.

RESULTS

Bacterial risk scoring model showed significant differences (P < 0.001). The PTB risk was low when the Lactobacillus iners ratio was 0.812 or more. In groups with a ratio under 0.812, moderate and high risk was classified as a U. parvum ratio of 4.6 × 10^-3 . The sensitivity and specificity of the PTB prediction model using bacteria risk score were 71% and 59%, respectively, and 77% and 67%, respectively, when white blood cell (WBC) data were included.

CONCLUSION

Using machine learning, the bacterial risk score in CVF can be used to predict PTB.

Antepartum Depression and Preterm Birth: Pathophysiology, Epidemiology, and Disparities due to structural racism

PURPOSE OF REVIEW

Informed by the evidence of links between physiology of stress and parturition, we review recent epidemiologic evidence (2015-2020) of antenatal depression as a risk factor for preterm birth (PTB). We also explain racial/ethnic disparities in depression and preterm birth as a consequence of structural racism.

RECENT FINDINGS

Epidemiologic evidence is consistent in linking antepartum depression with an elevated risk of PTB. Antidepressant usage has been linked with an elevated risk of PTB. However, recent evidence suggests that severity of depression is the underlying driver of the elevated risk attributed to antidepressant usage. The number of depressive symptoms, as a proxy for severity of maternal stress, may be a more informative predictor of PTB than criterion based predictors. Across various study designs, measurement modalities, and populations, antenatal depression predicts an elevated risk of delivering preterm. The physiology of stress provides a plausible explanation for this observation. Excessive stress-induced elevations in maternal and then fetal HPA hormones can alter maternal and fetal homeostasis and hasten the timing of parturition. Antenatal depression and exposure to structural racism are two stressors that can trigger the maternal stress response. Chronically elevated levels of stress hormones among women of color in the USA provide a likely physiologic explanation for Black-White disparities in the risk of PTB. Focusing on the number of depressive symptoms as the more informative predictor of PTB raises several questions. We consider these questions as well as directions for future research in the context of recent advances in the field.

Multimodal immune phenotyping of maternal peripheral blood in normal human pregnancy

Changes in maternal immunity during pregnancy can result in an altered immune state, and as a natural perturbation, this provides an opportunity to understand functional interactions of the immune system in vivo. We report characterization of maternal peripheral immune phenotypes for 33 longitudinally sampled normal pregnancies, using clinical measurements of complete blood counts and major immune cell populations, as well as high parameter flow cytometry for 30 leukocyte antigens characterizing 79 cell populations, and monitoring of 1305 serum proteins using the SomaLogic platform. Cellular analyses characterized transient changes in T cell polarization and more persistent alterations in T and B cell subset frequencies and activation. Serum proteomic analysis identified a potentially novel set of 7 proteins that are predictive of gestational age: DDR1, PLAU, MRC1, ACP5, ROBO2, IGF2R, and GNS. We further show that gestational age can be predicted from the parameters obtained by complete blood count tests and clinical flow cytometry characterizing 5 major immune cell populations. Inferring gestational age from this routine clinical phenotyping data could be useful in resource-limited settings that lack obstetric ultrasound. Overall, both the cellular and proteomic analyses validate previously reported phenotypic immunological changes of pregnancy and uncover potentially new alterations and predictive markers.

Alterations in endogenous progesterone metabolism associated with spontaneous very preterm delivery

STUDY QUESTION

Do maternal serum levels of progesterone metabolites early in pregnancy correspond to an increased risk for very preterm delivery prior to 32 weeks?

SUMMARY ANSWER

Maternal serum levels of 11-deoxycorticosterone (DOC) measured during the late first trimester or early second trimester correlate with an increased risk for preterm delivery prior to 32 weeks, and the correlation becomes stronger when the ratio of DOC to 16-alpha-hydroxyprogesterone was measured.

WHAT IS KNOWN ALREADY

Progesterone is a pro-gestational steroid hormone that has been shown to decrease the risk of preterm birth in some pregnant women. Progesterone is metabolized by the body into various metabolites including members of the mineralocorticoid and glucocorticoid families. Our group has previously demonstrated that some progesterone metabolites enhance myometrial contractility in an ex vivo system, while others result in myometrial relaxation. The current exploratory study was designed to determine if pre-specified metabolites of progesterone measured early in pregnancy were associated with a woman's risk for delivery prior to 32 weeks, which is referred to as a very preterm delivery.

STUDY DESIGN SIZE DURATION

The Building Blocks of Pregnancy Biobank (BBPB) is a biorepository at Indiana University (IU) that follows women prospectively through their pregnancy. A variety of biospecimens are collected at various time points during a woman's pregnancy. Women participating in the IU BBPB who were enrolled after 8 weeks' gestation with pregnancy outcome data were eligible for participation.

PARTICIPANTS/MATERIALS SETTING METHODS

Women delivering prior to 37 weeks (preterm) and at or after 37 weeks (term) who had blood samples collected during the late first trimester/early second trimester and/or during the early third trimester were identified. These samples were then processed for mass spectroscopy, and the amount of progesterone and progesterone metabolites in the samples were measured. Mean values of each measured steroid metabolite were calculated and compared among women delivering at less than 32 weeks, less than 37 weeks and greater than or equal to 37 weeks. Receiver operating characteristic (ROC) curves were constructed and threshold levels determined for each compound to identify a level above or below which best predicted a woman's risk for delivery prior to 32 and prior to 37 weeks. Mann-Whitney U nonparametric testing with Holm-Bonferroni correction for multiple comparisons was utilized to identify steroid ratios that could differentiate women delivering spontaneously at less than 32 weeks from all other pregnancies.

MAIN RESULTS AND THE ROLE OF CHANCE

Steroid hormone levels and pregnancy outcome data were available for 93 women; 28 delivering prior to 32 weeks, 40 delivering between 32 0/7 and 36 6/7 weeks and 25 delivering at or greater than 37 weeks: the mean gestational age at delivery within the three groups was 27.0, 34.4 and 38.8 weeks, respectively. Among women delivering spontaneously at less than 37 weeks, maternal 11-deoxycorticosterone (DOC) levels drawn in the late first trimester/early second trimester were significantly associated with spontaneous preterm delivery prior to 32 weeks; a threshold level of 47.5 pg/ml had 78% sensitivity, 73% specificity and an AUC of 0.77 (P = 0.044). When DOC levels were analyzed as a ratio with other measured steroid hormones, the ratio of DOC to 16-alpha-hydroxyprogesterone among women delivering spontaneously prior to 37 weeks was able to significantly discriminate women delivering prior to 32 weeks from those delivering at or greater than 32 weeks, with a threshold value of 0.2 with 89% sensitivity, 91% specificity and an AUC of 0.92 (P = 0.002). When the entire study cohort population was considered, including women delivering at term and women having an iatrogenic preterm delivery, the ratio of DOC to 16-alpha-hydroxyprogesterone was able to discriminate women delivering spontaneously prior to 32 weeks from the rest of the population at a threshold of 0.18 and 89% sensitivity, 59% specificity and an AUC of 0.81 (P = 0.003).

LIMITATIONS REASONS FOR CAUTION

This is a discovery study, and the findings have not been validated on an independent cohort. To mitigate issues with multiple comparisons, we limited our study to pre-specified metabolites that are most representative of the major metabolic pathways for progesterone, and adjustments for multiple comparisons were made.

WIDER IMPLICATIONS OF THE FINDINGS

Spontaneous preterm birth is increasingly being recognized to represent a common end pathway for a number of different disease phenotypes that include infection, inflammation, premature rupture of the membranes, uterine over distension, cervical insufficiency, placental dysfunction and genetic predisposition. In addition to these phenotypes, longitudinal changes in the maternal-fetal hypothalamic-pituitary-adrenal (HPA) axis also likely contribute to a significant proportion of the disease burden of spontaneous preterm birth. Here, we demonstrate that differential production of steroid metabolites is associated with very early preterm birth. The identified biomarkers may hint at a pathophysiologic mechanism and changes in the maternal-fetal dyad that result in preterm delivery. The early identification of abnormal changes in HPA axis metabolites may allow for targeted interventions that reverse the aberrant steroid metabolic profile to a more favorable one, thereby decreasing the risk for early delivery. Further research is therefore required to validate and extend the results presented here.

STUDY FUNDING/COMPETING INTERESTS

Funding for this study was provided from the Office of the Vice Chancellor for Research at IUPUI, 'Funding Opportunities for Research Commercialization and Economic Success (FORCES) grant'.Both A.S.P. and C.A.G. are affiliated with Nixxi, a biotech startup. The remaining authors report no conflict of interest.

TRIAL REGISTRATION NUMBER

Not applicable.

Can Placental Corticotropin-Releasing Hormone Inform Timing of Antenatal Corticosteroid Administration?

CONTEXT

Antenatal corticosteroids are commonly administered to pregnant women at risk for delivering between 23 and 34 gestational weeks; they provide crucial benefits to fetal lung maturation and reduce risk for neonatal morbidity and mortality. Corticosteroids are maximally efficacious for lung maturation when administered within 2 to 7 days of delivery. Accurately identifying the timing of preterm delivery is thus critical to ensure that antenatal corticosteroids are administered within a week of delivery and to avoid unnecessary administration to women who will deliver at term. A plausible biomarker for predicting time of delivery is placental corticotropin-releasing hormone (pCRH).

OBJECTIVE

To assess whether pCRH concentrations predict time to delivery and specifically which women will deliver within a week of treatment.

DESIGN

pCRH concentrations were evaluated before administration of the corticosteroid betamethasone, and timing of delivery was recorded.

PARTICIPANTS

A total of 121 women with singleton pregnancies who were prescribed betamethasone.

RESULTS

Elevated pCRH concentrations were associated with a shorter time from treatment to delivery. Receiver-operating characteristic curves revealed that pCRH may improve the precision of predicting preterm delivery.

CONCLUSIONS

In the current sample, pCRH concentrations predicted the likelihood of delivering within 1 week of corticosteroid treatment. Current findings suggest that pCRH may be a diagnostic indicator of impending preterm delivery. Increasing the precision in predicting time to delivery could inform when to administer antenatal corticosteroids, thus maximizing benefits and reducing the likelihood of exposing fetuses who will be delivered at term.

Pregnancy anxiety predicts shorter gestation in Latina and non-Latina white women: The role of placental corticotrophin-releasing hormone

OBJECTIVE

Previous research has shown that a woman's anxiety about her pregnancy predicts gestational length. Placental corticotrophin-releasing hormone (CRH) is a stress-responsive peptide proposed as a mechanism. We examined placental CRH as a physiological mediator of the association between pregnancy anxiety and gestational length in Latina and non-Latina White women to replicate evidence of associations between pregnancy anxiety, placental CRH and gestational length; to test whether placental CRH levels or changes mediate effects of pregnancy anxiety on gestational length; to examine ethnic differences in pregnancy anxiety, placental CRH, and gestational length; and to explore whether the effects of pregnancy anxiety on gestational length as mediated by placental CRH vary by ethnicity.

METHODS

In a prospective study of 337 pregnant Latina and non-Latina White women, participants completed in-person interviews that included a 10-item measure of pregnancy anxiety and provided blood samples assayed using radioimmunoassay at three timepoints (19, 25, and 31 weeks gestation).

RESULTS

Pregnancy anxiety at 19 and 31 weeks and levels of placental CRH at 31 weeks predicted gestational length. Tests of indirect effects were consistent with mediation such that both pregnancy anxiety at 19 weeks and increases from 19 to 31 weeks predicted placental CRH at 31 weeks, which in turn predicted gestational length. Tests of moderated mediation by ethnicity showed that the mediated effect of placental CRH at 31 weeks was significant for Latinas only.

CONCLUSIONS

These findings add to growing evidence of the involvement of pregnancy anxiety in the timing of birth, address mechanisms, and suggest possible ethnic differences.

Simulation model of the relationship between cesarean section rates and labor duration

Cesarean delivery is the most common major abdominal surgery in many parts of the world, and it accounts for nearly one-third of births in the United States. For a patient who requires a C-section, allowing prolonged labor is not recommended because of the increased risk of infection. However, for a patient who is capable of a successful vaginal delivery, performing an unnecessary C-section can have a substantial adverse impact on the patient's future health. We develop two stochastic simulation models of the delivery process for women in labor; and our objectives are (i) to represent the natural progression of labor and thereby gain insights concerning the duration of labor as it depends on the dilation state for induced, augmented, and spontaneous labors; and (ii) to evaluate the Friedman curve and other labor-progression rules, including their impact on the C-section rate and on the rates of maternal and fetal complications. To use a shifted lognormal distribution for modeling the duration of labor in each dilation state and for each type of labor, we formulate a percentile-matching procedure that requires three estimated quantiles of each distribution as reported in the literature. Based on results generated by both simulation models, we concluded that for singleton births by nulliparous women with no prior complications, labor duration longer than two hours (i.e., the time limit for labor arrest based on the Friedman curve) should be allowed in each dilation state; furthermore, the allowed labor duration should be a function of dilation state.

Comparative analysis of gene expression in maternal peripheral blood and monocytes during spontaneous preterm labor

BACKGROUND

Preterm birth is the leading cause of newborn death worldwide, and is associated with significant cognitive and physiological challenges in later life. There is a pressing need to define the mechanisms that initiate spontaneous preterm labor, and for development of novel clinical biomarkers to identify high-risk pregnancies. Most preterm birth studies utilize fetal tissues, and there is limited understanding of the transcriptional changes that occur in mothers undergoing spontaneous preterm labor. Earlier work revealed that a specific population of maternal peripheral leukocytes (macrophages/monocytes) play an active role in the initiation of labor. Thus, we hypothesized that there are dynamic gene expression changes in maternal blood leukocytes during preterm labor.

OBJECTIVE

Using next-generation sequencing we aim to characterize the transcriptome in whole blood leukocytes and peripheral monocytes of women undergoing spontaneous preterm labor compared to healthy pregnant women who subsequently delivered at full term.

STUDY DESIGN

RNA sequencing was performed in both whole blood and peripheral monocytes from women who underwent preterm labor (24-34 weeks of gestation, N = 20) matched for gestational age to healthy pregnant controls (N = 30). All participants were a part of the Ontario Birth Study cohort (Toronto, Ontario, Canada).

RESULTS

We identified significant differences in expression of 262 genes in peripheral monocytes and 184 genes in whole blood of women who were in active spontaneous preterm labor compared to pregnant women of the same gestational age not undergoing labor, with 43 of these genes differentially expressed in both whole blood and peripheral monocytes. ADAMTS2 expression was significantly increased in women actively undergoing spontaneous preterm labor, which we validated through digital droplet reverse transcriptase polymerase chain reaction. Intriguingly, we have also identified a number of gene sets including signaling by stem cell factor-KIT, nucleotide metabolism, and trans-Golgi network vesicle budding, which exhibited changes in relative gene expression that was predictive of preterm labor status in both maternal whole blood and peripheral monocytes.

CONCLUSION

This study is the first to investigate changes in both whole blood leukocytes and peripheral monocytes of women actively undergoing spontaneous preterm labor through robust transcript measurements from RNA sequencing. Our unique study design overcame confounding based on gestational age by collecting blood samples from women matched by gestational age, allowing us to study transcriptomic changes directly related to the active preterm parturition. We performed RNA profiling using whole genome sequencing, which is highly sensitive and allowed us to identify subtle changes in specific genes. ADAMTS2 expression emerged as a marker of prematurity within peripheral blood leukocytes, an accessible tissue that plays a functional role in signaling during the onset of labor. We identified changes in relative gene expression in a number of gene sets related to signaling in monocytes and whole blood of women undergoing spontaneous preterm labor compared to controls. These genes and pathways may help identify potential targets for the development of novel drugs for preterm birth prevention.

Immunophenotyping and activation status of maternal peripheral blood leukocytes during pregnancy and labour, both term and preterm

The onset of labour in rodents and in humans is associated with physiological inflammation which is manifested by infiltration of activated maternal peripheral leukocytes (mPLs) into uterine tissues. Here, we used flow cytometry to immunophenotype mPLs throughout gestation and labour, both term and preterm. Peripheral blood was collected from non-pregnant women and pregnant women in the 1st, 2nd and 3rd trimesters. Samples were also collected from women in active labour at term (TL) or preterm (PTL) and compared with women term not-in-labour (TNIL) and preterm not-in-labour (PTNIL). Different leukocyte populations were identified by surface markers such as CD45, CD14, CD15, CD3, CD4, CD8, CD19 and CD56. Their activation status was measured by the expression levels of CD11b, CD44, CD55, CD181 and CD192 proteins. Of all circulating CD45+ leukocytes, we detected significant increases in CD15+ granulocytes (i) in pregnant women versus non-pregnant; (ii) in TL women versus TNIL and versus pregnant women in the 1st/2nd/3rd trimester; (iii) in PTL women versus PTNIL. TL was characterized by (iv) increased expressions of CD11b, CD55 and CD192 on granulocytes; (v) increased mean fluorescent intensity (MFI) of CD55 and CD192 on monocytes; (vi) increased CD44 MFI on CD3+ lymphocytes as compared to late gestation. In summary, we have identified sub-populations of mPLs that are specifically activated in association with gestation (granulocytes) or with the onset of labour (granulocytes, monocytes and lymphocytes). Additionally, beta regression analysis created a set of reference values to rank this association between immune markers of pregnancy and to identify activation status with potential prognostic and diagnostic capability.

The value of acute phase reactants in predicting preterm delivery

OBJECTIVE

We aimed to determine the potential value of maternal serum levels of acute phase reactants in the prediction of preterm delivery in women with threatened preterm labor (TPL).

METHODS

Ninety-one pregnant women diagnosed with TPL and 83 healthy pregnant women as a control group were included in this prospective controlled study. All the pregnant women were followed until delivery and obstetric data and the serum levels of acute phase reactants were recorded for each participant. The study group was further divided into two groups according to the gestational age at delivery, which include women delivering prematurely and the ones who gave birth at term.

RESULTS

Serum albumin levels were significantly lower and mean serum ferritin levels were significantly higher in the study groups when compared the control group.

CONCLUSION

Although an association between decreased serum albumin level and TPL, also between increased serum ferritin levels and preterm birth and low birth weight were demonstrated, more extensive studies are needed to clarify the potential use of the acute phase reactants in the prediction of preterm birth.

Amniotic fluid urocortin-1 concentrations for the prediction of preterm delivery

AIM

The aim of this study was to analyze whether urocortin-1 concentration in midtrimester amniotic fluid could serve as an indicative marker of preterm labor.

MATERIAL AND METHODS

A retrospective cohort study was conducted. Urocortin-1 concentrations in midtrimester amniotic fluid were measured in 22 pregnant women with preterm deliveries and 45 women who delivered at term using enzyme-linked immunosorbent assay.

RESULTS

The median amniotic fluid urocortin-1 concentration was significantly lower in the women with preterm birth (40.06 pg/mL; range, 13.77-67.58 pg/mL) than in the women who gave birth at term (49.56 pg/mL; range, 26.25-175.9 pg/mL; P = 0.022). The result of receiver-operator curve analysis indicates that an amniotic fluid urocortin-1 concentration ≤ 57.88 pg/mL had an area under the curve of 0.673 (95% confidence interval, 0.55-0.78; P = 0.01) with a sensitivity of 81.8%, specificity of 40.0%, positive predictive value of 40%, and a negative predictive value of 82% in identifying which of the patients subsequently delivered prematurely.

CONCLUSIONS

These results suggest that low urocortin-1 concentration in midtrimester amniotic fluid could be used as an indicative marker of preterm birth.

Maternal stress/distress, hormonal pathways and spontaneous preterm birth

BACKGROUND

Although second-trimester blood corticotrophin-releasing hormone (CRH) levels are robustly associated with preterm birth, the findings with respect to cortisol have been inconsistent, as have been those relating stress hormones to measured stressors and maternal distress.

METHODS

We measured plasma CRH, adrenocorticotrophic hormone (ACTH), cortisol, cortisol-binding globulin, oestradiol and progesterone at 24-26 weeks in a nested case-control study of 206 women who experienced spontaneous preterm birth and 442 term controls. We also related the hormonal levels to measures of environmental stressors, perceived stress and maternal distress (also assessed at 24-26 weeks) and to placental histopathology.

RESULTS

With the exception of an unexpectedly low oestradiol:progesterone ratio among cases (adjusted odds ratio = 0.5 [95% confidence interval 0.3, 0.8] for ratios above the median in controls), none of the hormonal measures was independently associated with spontaneous preterm birth; placental histopathological evidence of infection/inflammation, infarction or decidual vasculopathy; or measures of maternal stress or distress. CRH levels were positively associated with cortisol, but not with ACTH, whereas ACTH was also positively associated with cortisol.

CONCLUSIONS

Our findings suggest an intact pituitary-adrenal axis and confirm the positive feedback effect of cortisol on (placental) CRH. Neither of these hormonal pathways, however, was strongly linked to maternal stress/distress or to the risk of spontaneous preterm birth.

A model for prediction of spontaneous preterm birth in asymptomatic women

BACKGROUND

Preterm birth is a complex health problem with social, environmental, behavioral, and genetic determinants of an individual's risk and remains a major challenge in obstetrics. Recent research has caused improvements in predicting preterm birth; however, there is still controversy about the prediction of preterm birth in asymptomatic women. The purpose of this study was to determine if Bayesian filtering can be used in a clinical setting to predict spontaneous preterm birth in asymptomatic women.

METHODS

A model of predicting spontaneous preterm birth using PopBayes based on a Bayesian filtering algorithm was developed using a previously collected dataset, then applied to a prospectively collected cohort of asymptomatic women who delivered singleton live newborns at or after 24 weeks of gestation. Cases complicated with major congenital malformations were excluded.

RESULTS

The proportion of patients with spontaneous preterm birth was 18.4% (96 of 522) at <37 weeks gestation, 5.4% (28 of 522) at <34 weeks gestation, and 2.7% (14 of 522) at <32 weeks gestation. The match rates with the combination of demographic, clinical, and genetic factors using a Bayesian filtering method (PopBayes) were higher than the match rates using demographic and clinical factors only, including maternal age, maternal body mass index (BMI), prior preterm birth, education, occupation, income, and active and passive smoking. The match rates in preterm delivery before 32 weeks of gestation were higher than the match rates in preterm delivery before 37 and 34 weeks of gestation (94.3% vs. 84.7% and 82.0%, respectively). The negative predictive values for demographic, clinical, and genetic factors in predicting preterm delivery using PopBayes were consistently >90%.

CONCLUSIONS

We suggest that Bayesian filtering (PopBayes) is a customizable and useful tool in establishing a model for the prediction of preterm birth.

Immune aspects and myometrial actions of progesterone and CRH in labor

Progesterone and corticotropin-releasing hormone (CRH) have a critical role in pregnancy and labor, as changes related to these hormones are crucial for the transition from myometrial quiescence to contractility. The mechanisms related to their effect differ between humans and other species, thus, despite extensive research, many questions remain to be answered regarding their mediation in human labor. Immune responses to progesterone and CRH are important for labor. Progesterone acts as an immunomodulator which controls many immune actions during pregnancy, and its withdrawal releases the inhibitory action on inflammatory pathways. In humans, a "functional" progesterone withdrawal occurs with onset of labor through changes in progesterone metabolism, progesterone receptors, and other molecules that either facilitate or antagonize progesterone function. Placental CRH acts on the fetal pituitary-adrenal axis to stimulate adrenal production of androgens and cortisol and also acts directly on myometrial cells via its receptors. CRH also affects inflammatory signals and vice versa. Interactions between progesterone and CRH additionally occur during labor. We describe the role of these two hormones in human myometrium and their interactions with the immune system during labor.

All Our Babies Cohort Study: recruitment of a cohort to predict women at risk of preterm birth through the examination of gene expression profiles and the environment

Background

Preterm birth is the leading cause of perinatal morbidity and mortality. Risk factors for preterm birth include a personal or familial history of preterm delivery, ethnicity and low socioeconomic status yet the ability to predict preterm delivery before the onset of preterm labour evades clinical practice. Evidence suggests that genetics may play a role in the multi-factorial pathophysiology of preterm birth. The All Our Babies Study is an on-going community based longitudinal cohort study that was designed to establish a cohort of women to investigate how a women's genetics and environment contribute to the pathophysiology of preterm birth. Specifically this study will examine the predictive potential of maternal leukocytes for predicting preterm birth in non-labouring women through the examination of gene expression profiles and gene-environment interactions.

Methods/Design

Collaborations have been established between clinical lab services, the provincial health service provider and researchers to create an interdisciplinary study design for the All Our Babies Study. A birth cohort of 2000 women has been established to address this research question. Women provide informed consent for blood sample collection, linkage to medical records and complete questionnaires related to prenatal health, service utilization, social support, emotional and physical health, demographics, and breast and infant feeding. Maternal blood samples are collected in PAXgene™ RNA tubes between 18-22 and 28-32 weeks gestation for transcriptomic analyses.

Discussion

The All Our Babies Study is an example of how investment in clinical-academic-community partnerships can improve research efficiency and accelerate the recruitment and data collection phases of a study. Establishing these partnerships during the study design phase and maintaining these relationships through the duration of the study provides the unique opportunity to investigate the multi-causal factors of preterm birth. The overall All Our Babies Study results can potentially lead to healthier pregnancies, mothers, infants and children.

Magnetomyographic recording and identification of uterine contractions using Hilbert-wavelet transforms

We propose a multi-stage approach using Wavelet and Hilbert transforms to identify uterine contraction bursts in magnetomyogram (MMG) signals measured using a 151 magnetic sensor array. In the first stage, we decompose the MMG signals by wavelet analysis into multilevel approximate and detail coefficients. In each level, the signals are reconstructed using the detail coefficients followed by the computation of the Hilbert transform. The Hilbert amplitude of the reconstructed signals from different frequency bands (0.1-1 Hz) is summed up over all the sensors to increase the signal-to-noise ratio. Using a novel clustering technique, affinity propagation, the contractile bursts are distinguished from the noise level. The method is applied on simulated MMG data, using a simple stochastic model to determine its robustness and to seven MMG datasets.