Does “idiopathic” preterm labor resulting in preterm birth exist?

doi:10.1016/S0002-9378(11)90785-6

American Journal of Obstetrics and Gynecology

Volume 168, Issue 5, May 1993, Pages 1480-1485

https://doi.org/10.1016/S0002-9378(11)90785-6 Get rights and content

OBJECTIVE: In an effort to elucidate possible causes of preterm labor, we undertook a prospective study of 50 patients consecutively admitted with intact membranes and preterm labor who eventually had a preterm delivery despite the use of tocolysis.

STUDY DESIGN: A comprehensive evaluation plan was instituted. This included a detailed history and physical examination, targeted ultrasonography, amniocentesis for Gram stain, culture, and glucose determination, laboratory analysis for infection (complete blood cell count, urinalysis, and cervical and urine cultures) and for antiphospholipid antibody syndrome (antinuclear antibody, lupus anticoagulant, anticardiolipin antibody), pathologic examination of the placenta, and a urine toxicology screen.

RESULTS: The following groups of possible causes of preterm labor were identified: (1) faulty placentation, 50% (25/50); (2) intrauterine infection 38% (19/50); (3) immunologic factors, 30% (15/50); (4) cervical incompetence, 16% (8/50); (5) uterine factors, 14% (7/50); (6) maternal factors 10% (5/50); (7) trauma and surgery, 8% (4/50); (8) fetal anomalies, 6% (3/50); and (9) idiopathic conditions, 4% (2/50). Among the 50 patients two or more possible causes were identified in 58% (29/50).

CONCLUSION: We suggest that an exhaustive evaluation plan can identify possible causes in the majority (96%) of cases of “idiopathic” preterm labor that result in preterm delivery.

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Spontaneous preterm birth (sPTB) is a global health concern and it is the most prevalent cause of infant mortality and morbidity with occurrence rate of 5 – 18% worldwide. Studies suggest infection and infection-driven activation of inflammatory responses are the potential risk factors for sPTB. MicroRNAs (miRNAs) are thought to control the expression of several immune genes, making them crucial components of the intricate immune regulatory network and the dysregulation of miRNAs in placenta has been associated to several pregnancy-related complications. However, studies on possible role of miRNAs in immunomodulation of cytokine signalling in infection-associated sPTB are scarce. Present study aimed to investigate expression/ correlation of a few circulating miRNAs (miR-223, −150-5p, −185-5p, −191-5p), miRNA target genes and associated cytokines in sPTB women found infected with Chlamydia trachomatis/ Mycoplasma hominis/ Ureaplasma urealyticum. Non-heparinized blood and placental sample were collected from 140 sPTB and 140 term women visiting Safdarjung hospital, New Delhi (India) for conducting PCR and RT-PCR for pathogen detection and miRNA/ target gene/ cytokine expression, respectively. Common target genes of differentially expressed miRNAs were obtained from databases. The correlation between select target genes/ cytokines and serum miRNAs was determined by Spearman’s rank correlation. 43 sPTB were infected with either pathogen and a significant upregulation of serum miRNAs was observed. However, miR-223 and 150–5p showed maximum fold-change (4.78 and 5.58, respectively) in PTB versus control group. IL-6ST, TGF-β R3 and MMP-14 were important target genes among 454 common targets, whereas, IL-6 and TGF-β were associated cytokines. miR-223 and 150–5p showed significant negative correlation with IL-6ST/ IL-6/ MMP-14 and positive correlation with TGF-β R3/ TGF-β. A significant positive correlation was found between IL-6ST and IL-6, TGF-β R3 and TGF-β. However, miR-185–5p and 191–5p were not significantly correlated. Although post-transcriptional validation is required, yet on the basis of mRNA findings, the study concludes that miR-223 and 150–5p are apparently of clinical importance in regulation of inflammatory processes during infection-associated sPTB.
Galectins are critical regulators of cytokine signalling at feto-maternal interface in infection-associated spontaneous preterm birth
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Spontaneous preterm birth (sPTB) is a global health issue. Studies suggest infections are chiefly associated with sPTB and galectins (gals) play a role in regulation of innate and adaptive maternal immune response against pathogens during sPTB. The aim of this study was to describe the gene expression of gal -1, -3, -8, -9, -13 in relation to gene expression of cyclooxygenase-2 (COX-2) and the cytokines IL-8, IL-10, TNF-α, IFN-ϒ in the setting of sPTB and confirmed infection with Chlamydia trachomatis, Mycoplasma hominis, and Ureaplasma urealyticum.
Placental samples were collected from 120 term control and 120 sPTB pregnancies. PCR was used to detect specific pathogens. Gene expression of galectins, cytokines, and COX-2 was performed using real time qPCR.
Fold-change expression of gal -1, -3, -8, -9, -13 was 5.13, 6.11, 1.14, 5.23 and 7.16 (p<0.001), respectively; while IL-10, IL-8, TNF-α, IFN-ϒ and COX-2 was 6.29, 6.55, 6.35, 6.36 and 2.73-fold upregulated (p<0.05), respectively in infected sPTB. Gal-1 was positively correlated with IL-10 (r=0.49, p=0.003) while gal-3 showed significant correlation with IL-8 (r=0.42, p=0.0113), TNF-α (r=0.65, p=< 0.001) and COX-2 (r=0.72, p=0.001). However, gal-8 was not significantly correlated with any cytokine. Gal-9, -13 were negatively correlated with IFN-ϒ (r=-0.45, p=0.006) and IL-8 (r=-0.39, p=0.018).
Gal-1, -9, -13 are anti-inflammatory and might play role in immune-tolerance while gal-3 is pro-inflammatory and possibly responsible for immunogenic response, having potential to anticipate the clinical beginning of preterm labour during infection.
Predicting the risk of spontaneous premature births using clinical data and machine learning
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Citation Excerpt :
Several clinical studies have identified the following as risk factors that influence sPTB: short cervix, multiple gestations, in vitro fertilization, ethnicity, stressful life events, chronic conditions such as high blood pressure and diabetes, smoking, uterine anomalies, short inter-pregnancy interval, maternal serum proteins, and prior spontaneous preterm birth [9–13]. However, most of these studies have focused on individual associations between these risk factors and sPTB rather understanding how the totality of life experiences and conditions affect sPTB risk as they interact and potentially amplify one another [14–19]. The increasing use of artificial intelligence to identify patterns, learn from experience, and make decisions has motivated recent investigations into preterm birth prediction [2,19–25].
Spontaneous preterm birth (sPTB) is a worldwide public health issue that affects millions of infants per year and causes long-lasting effects. Prediction of sPTB is critical for clinical management and patient referral to centers capable of treating preterm infants. The outstanding capabilities of machine learning to detect patterns and make predictions have motivated recent studies to improve the prediction of sPTB. However, there is still a high level of uncertainty, especially among patients without a prior sPTB.
The objectives of this study were to formulate more effective and accurate predictions of sPTB and to identify relevant sPTB risk factors.
From the data set collected by the NICHD Maternal Fetal Medicine Units (MFMU) Network between 1992 and 1994, we selected a cohort of women with no previous preterm birth (n = 2390). We then developed a pre-processing protocol that prioritized original information by limiting interpolation criteria to individual feature averages, reducing complexity and cross-feature correlation to increase generalization. Next we created a machine learning model based on support vector machines and a radial basis function kernel to: (i) predict the occurrence of spontaneous preterm birth, and (ii) accommodate clinical considerations for treatment.
In clinically conservative, moderate, and aggressively models, prediction of sPTB reached average true positive rate of 0.36, 0.62, and 0.82, respectively, and corresponding average false positive rate of 0.03, 0.38, and 0.56, respectively in an independent testing partition. The area under the receiver operating characteristics curve (AUC) was 0.75. The models benefited most from features collected in the earlier stages of the study protocol and pregnancy, generally ¡26 weeks gestational age, and involved a combination of socioeconomic and biological contributors identified as risk factors in previous studies.
Our findings provide a framework for improving clinical decision support system models to assist providers in predicting sPTB. Updating such models with more recent data that include multiple levels of individual and contextual factors could prove useful to predict sPTB.
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Preterm birth (PTB) is defined as delivery before 37 weeks of gestation. Globally, 15 million infants are born prematurely, putting these children at an increased risk of mortality and lifelong health challenges. Currently in the U.S., there is only one FDA approved therapy for the prevention of preterm birth. Makena is an intramuscular progestin injection given to women who have experienced a premature delivery in the past. Recently, however, Makena failed a confirmatory trial, resulting the Center for Drug Evaluation and Research’s (CDER) recommendation for the FDA to withdrawal Makena’s approval. This recommendation would leave clinicians with no therapeutic options for preventing PTB. Here, we outline recent interdisciplinary efforts involving physicians, pharmacologists, biologists, chemists, and engineers to understand risk factors associated with PTB, to define mechanisms that contribute to PTB, and to develop next generation therapies for preventing PTB. These advances have the potential to better identify women at risk for PTB, prevent the onset of premature labor, and, ultimately, save infant lives.
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Preterm birth remains the major cause of death and disability among children under the age of five. In developing countries antenatal preterm birth prevention clinics are set up to provide cervical length surveillance and/or treatment modalities such as cerclage or progesterone for those women with identified risk factors such as previous cervical treatment or preterm birth. However, 85% of women have no risk factors for PTB and currently there is no biomarker to screen women early in pregnancy. Women will present unexpectedly in threatened preterm labour and we have no choice but to adopt a re-active approach to their care by using predication and preparation strategies such as fetal fibronectin, tocolytic therapy and steroids. Despite these strategies approximately 15–20% of these women will give birth preterm before 34 weeks. There is a urgent need to re-design primary, secondary and tertiary prevention strategies for spontaneous preterm labour (sPTL) in singleton pregnancies aimed at identifying and addressing key gaps in clinical practice and research.
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The objective was to provide an update of progress made over time (including personal reflection) of our attempts to reduce the mortality and morbidity associated with spontaneous preterm labour that leads to preterm birth.
An experienced and evidence based approach was taken to provide an overview of progress made over a generation (∼40 years) in our understanding of spontaneous preterm labour.
It is evident that we have made significant progress in our understanding of the aetiology, the measurement of the burden, the basic science, systems biology and mechanical pathways of the preterm parturition syndrome. We have better ways of predicting, preventing and managing spontaneous preterm labour than existed a generation ago.
The profile of spontaneous preterm labour that leads to preterm birth, thanks to organisations such as the March of Dimes, WHO and PREBIC is much more evident than before. However, while we have come a long way, we must not be complacent, and clinicians and basic scientists must continue to work in harmony, while recruiting and encouraging young investigators to join the effort to improve survival and handicap in what is one of the Great Obstetric Syndromes.

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Does “idiopathic” preterm labor resulting in preterm birth exist?

Am J Obstet Gynecol

Am J Obstet Gynecol

Am J Obstet Gynecol

Am J Obstet Gynecol

Am J Obstet Gynecol

Placenta

Am J Obstet Gynecol

Am J Obstet Gynecol

Lifestyle influences on prematurity

J Dev Physiol

The Alabama preterm birth prevention project

Obstet Gynecol

Infection in the pathogenesis of preterm labor

Semin Perinatol

Microbiology of the lower genital tract and amniotic fluid in asymptomatic preterm patients with intact membranes and moderate to advanced degrees of cervical effacement and dilation

Am J Perinatol