Value of cervical electrical impedance spectroscopy to predict spontaneous preterm delivery in asymptomatic women: the ECCLIPPx prospective cohort study

Techniques for detecting cervical remodeling as a predictor for spontaneous preterm birth: current evidence and future research avenues in patients with multiple pregnancies

BACKGROUND

Spontaneous preterm birth occurs more frequently in multiple pregnancies. This syndrome has multiple triggers that result in a unified downstream pathway of cervical remodeling, uterine activity, and progressive cervical dilatation. Whilst the triggers for labor in multiple pregnancy may be different from singletons, the downstream changes will be the same. Identifying patients at risk of preterm birth is a priority as interventions to delay delivery and optimize the fetus can be initiated. Methods for screening for risk of preterm birth which focus on the detection of cervical remodeling may therefore have potential in this population.

METHODS

This review explores the evidence for the predictive utility for preterm birth of several published techniques that assess the physical, biomechanical, and optical properties of the cervix, with a focus on those which have been studied in multiple pregnancies and highlighting targets for future research in this population.

RESULTS

Fifteen techniques are discussed which assess the physical, biomechanical, and optical properties of the cervix in pregnancy. Of these, only three techniques that evaluated the predictive accuracy of a technique in patients with multiple pregnancies were identified: uterocervical angle, cervical consistency index, and cervical elastography. Of these, measurement of the uterocervical angle has the strongest evidence. Several techniques have shown predictive potential in singleton pregnancies, but have not yet been studied in multiple pregnancies, which would be a logical expansion of research.

CONCLUSION

Research on techniques with predictive utility for PTB in patients with multiple pregnancies is limited but should be a research priority. Overall, the theory supports the investigation of cervical remodeling as a predictor of PTB, and there are numerous techniques in development that may have potential in this field.

Bioengineering and the cervix: The past, current, and future for addressing preterm birth

The uterine cervix plays two important but opposing roles during pregnancy - as a mechanical barrier that maintains the fetus for nine months and as a compliant structure that dilates to allow for the delivery of a baby. In some pregnancies, however, the cervix softens and dilates prematurely, leading to preterm birth. Bioengineers have addressed and continue to address the lack of reduction in preterm birth rates by developing novel technologies to diagnose, prevent, and understand premature cervical remodeling. This article highlights these existing and emerging technologies and concludes with open areas of research related to the cervix and preterm birth that bioengineers are currently well-positioned to address.

A systematic review of prediction models for spontaneous preterm birth in singleton asymptomatic pregnant women with risk factors

Backgrounds

Spontaneous preterm birth (SPB) is a global problem. Early screening, identification, and prevention in asymptomatic pregnant women with risk factors for preterm birth can help reduce the incidence and mortality of preterm births. Therefore, this study systematically reviewed prediction models for spontaneous preterm birth, summarised the model characteristics, and appraised their quality to identify the best-performing prediction model for clinical decision-making.

Methods

PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, China Biology Medicine disc, VIP Database, and Wanfang Data were searched up to September 27, 2021. Prediction models for spontaneous preterm births in singleton asymptomatic pregnant women with risk factors were eligible for inclusion. Six independent reviewers selected the eligible studies and extracted data from the prediction models. The findings were summarised using descriptive statistics and visual plots.

Results

Twelve studies with twelve developmental models were included. Discriminative performance was reported in 11 studies, with an Area Under the Curve (AUC) ranging from 0.75 to 0.95. The AUCs of the seven models were greater than 0.85. Cervical length (CL) is the most commonly used predictor of spontaneous preterm birth. A total of 91.7% of the studies had a high risk of bias in the analysis domain, mainly because of the small sample size and lack of adjustment for overfitting.

Conclusion

The accuracy of the models for spontaneous preterm births in singleton asymptomatic women with risk factors was good. However, these models are not widely used in clinical practice because they lack replicability and transparency. Future studies should transparently report methodological details and consider more meaningful predictors with new progress in research on preterm birth.

The acceptability of cervical electrical impedance spectroscopy within a multi-modal preterm birth screening package: a mixed methods study

BACKGROUND

Reducing the rate of preterm birth is a cornerstone of global efforts to address child mortality, however existing screening tests offer imperfect prediction. Cervical electrical impedance spectroscopy (EIS) is a novel technique to quantify the ripening changes which precede labour. Mid-trimester EIS measurements have been shown to accurately predict preterm birth in asymptomatic women. This study aimed to comprehensively evaluate the acceptability of cervical EIS to low and high-risk women as part of a package of screening tests performed during a larger prospective trial.

METHODS

In this parallel convergent mixed methods study, 40 women completed questionnaires before and after screening tests (EIS, cervical length measurement and fetal fibronectin quantification). Quantitative outcomes were anxiety levels before and after screening (Spielberger State Trait Anxiety Inventory, STAI-6), pain (Short Form McGill Pain Questionnaire) and ratings of EIS device appearance and test acceptability (visual analogue scales). Twenty-one women (11 high-risk, 10 low-risk) also attended a semi-structured qualitative interview. Interviews were recorded and transcribed, then thematic analysis was performed. A convergence coding matrix was constructed to enable triangulation of quantitative and qualitative results.

RESULTS

High risk women demonstrated a significant reduction in anxiety following screening (mean STAI-6 score 34.5 vs. 29.0, p = 0.002). A similar trend was observed among low-risk participants. Ratings of pain, EIS device appearance and procedural acceptability did not differ between groups. Mean pain ratings were low (visual analogue scale 0.97 and 1.01), comparing favourably to published evaluations of conventional screening tests. Qualitative analysis provided insight into both the physical consequences and emotional experiences of screening. Additional determinants of the screening experience included device design, pre-existing perspectives on intimate examination, attitudes to knowledge in pregnancy and interaction with clinical staff. Finally, a range of practical considerations regarding wider use of EIS were identified, with valuable complementary detail regarding acceptability for use in antenatal care.

CONCLUSIONS

Cervical EIS is well tolerated and acceptable to both low and high-risk women when performed as part of a multi-modal screening package. These results provide useful insights to inform the design of future study and screening protocols.

Computational Modelling for Electrical Impedance Spectroscopy-Based Diagnosis of Oral Potential Malignant Disorders (OPMD)

A multiscale modelling approach has been applied to the simulation of the electrical properties of oral tissue, for the purpose of informing an electrical impedance-based method of oral potential malignant disorder (OPMD) diagnosis. Finite element models of individual cell types, with geometry informed by histological analysis of human oral tissue (normal, hyperplastic and dysplastic), were generated and simulated to obtain electrical parameters. These were then used in a histology-informed tissue scale model, including the electrode geometry of the ZedScan tetrapolar impedance-measurement device. The simulations offer insight into the feasibility of distinguishing moderate dysplasia from severe dysplasia or healthy tissue. For some oral sites, simulated spectra agreed with real measurements previously collected using ZedScan. However, similarities between simulated spectra for dysplastic, keratinised and non-dysplastic but hyperkeratinised tissue suggest that significant keratinisation could cause some OPMD tissues to exhibit larger than expected impedance values. This could lead to misidentification of OPMD spectra as healthy. Sources of uncertainty within the models were identified and potential remedies proposed.

Tensor electrical impedance myography identifies clinically relevant features in amyotrophic lateral sclerosis

Objective.Electrical impedance myography (EIM) shows promise as an effective biomarker in amyotrophic lateral sclerosis (ALS). EIM applies multiple input frequencies to characterise muscle properties, often via multiple electrode configurations. Herein, we assess if non-negative tensor factorisation (NTF) can provide a framework for identifying clinically relevant features within a high dimensional EIM dataset.Approach.EIM data were recorded from the tongue of healthy and ALS diseased individuals. Resistivity and reactivity measurements were made for 14 frequencies, in three electrode configurations. This gives 84 (2 × 14 × 3) distinct data points per participant. NTF was applied to the dataset for dimensionality reduction, termed tensor EIM. Significance tests, symptom correlation and classification approaches were explored to compare NTF to using all raw data and feature selection.Main Results.Tensor EIM provides highly significant differentiation between healthy and ALS patients (p< 0.001, AUROC = 0.78). Similarly tensor EIM differentiates between mild and severe disease states (p< 0.001, AUROC = 0.75) and significantly correlates with symptoms (ρ= 0.7,p< 0.001). A trend of centre frequency shifting to the right was identified in diseased spectra, which is in line with the electrical changes expected following muscle atrophy.Significance.Tensor EIM provides clinically relevant metrics for identifying ALS-related muscle disease. This procedure has the advantage of using the whole spectral dataset, with reduced risk of overfitting. The process identifies spectral shapes specific to disease allowing for a deeper clinical interpretation.

A Combination of Cervicovaginal Fluid Glutamate, Acetate and D-Lactate Identified Asymptomatic Low-Risk Women Destined to Deliver Preterm: a Prospective Cohort Study

Due to the modest predictive capacities and limited clinical application of transvaginal ultrasonographic cervical length (CL) and quantitative fetal fibronectin (qfFN) in pregnant women at low risk of preterm birth (PTB), we sought to determine the utility of cervicovaginal fluid (CVF) metabolites (by-products of host-microbial metabolism) for prediction of spontaneous PTB in asymptomatic low-risk women at mid-gestation. This was a prospective sub-cohort study from the ECCLIPPx study cohort. CVF from asymptomatic singleton women (20–22 weeks, n = 168) without a prior history of PTB were analysed for metabolites by enzyme-based spectrophotometry. CL, vaginal pH and qfFN were also measured. Correlation and predictive analyses were performed by Spearman’s correlation, and binary logistic regression and area under receiver operating characteristic curve (AUC), respectively. Of the 168 women enrolled, only CVF samples from 135 (80.4%) women were analysed. There were 6/135 (4.4%) spontaneous PTB (sPTBs), with two of these pregnancies ending ≤ 28 weeks’ gestation. Individually (AUC, 95% CI), only glutamate (0.72, 0.64–0.80) and CL (0.69, 0.60–0.77) were predictive of PTB. However, five multivariable models that more accurately predicted sPTB were also identified, i.e. a combination of: glutamate, acetate and D-lactate (GAD, 0.82, 0.74–0.89); CL and qfFN only (0.78, 0.70–0.85); CL, qfFN, glutamate and acetate (0.88, 0.81–0.93); CL, qfFN and GAD (0.94, 0.88–0.98); and GAD and pH (0.86, 0.79–0.92). Correlations between CL, pH and qfFN and metabolites were also observed. In this cohort, a midtrimester combination of CVF glutamate, acetate and D-lactate predicted preterm birth more accurately than individual metabolites, cervical length and fetal fibronectin with a very low false-positive rate and high positive predictive value. Further testing in populations with higher preterm birth rates is required.