Approximately 20.5 million infants were born weighing <2500 g (defined as low birthweight or LBW) in 2015, primarily in low- and middle-income countries (LMICs). Infants born LBW, including those born preterm (<37 weeks gestation), are at increased risk for numerous consequences, including neonatal mortality and morbidity as well as suboptimal health and nutritional status later in life. The objective of this study was to identify predictors of LBW and preterm birth among infants in rural Uganda.Data were derived from a prospective birth cohort study conducted from 2014–2016 in 12 districts across northern and southwestern Uganda. Birth weights were measured in triplicate to the nearest 0.1 kg by trained enumerators within 72 hours of delivery. Gestational age was calculated from the first day of last menstrual period (LMP). Associations between household, maternal, and infant characteristics and birth outcomes (LBW and preterm birth) were assessed using bivariate and multivariable logistic regression with stepwise, backward selection analyses.Among infants in the study, 4.3% were born LBW , and 19.4% were born preterm . In multivariable analysis, mothers who were taller (>150 cm) (adjusted Odds Ratio (aOR) = 0.42 ), multigravida ), or with adequate birth spacing (>24 months) ) had lower odds of delivering a LBW infant Mothers with severe household food insecurity ) or who tested positive for malaria during pregnancy ) had higher odds of delivering a LBW infant. In addition, in multivariable analysis, mothers who resided in the Southwest ), were ≥20 years old ), with adequate birth spacing ), or attended ≥4 antenatal care (ANC) visits ) had lower odds of delivering a preterm infant; mothers who were neither married nor cohabitating ) or delivered at home ) had higher odds.In rural Uganda, severe household food insecurity, adolescent pregnancy, inadequate birth spacing, malaria infection, suboptimal ANC attendance, and home delivery represent modifiable risk factors associated with higher rates of LBW and/or preterm birth. Future studies on interventions to address these risk factors may be warranted. Low birthweight (LBW) (defined as <2500 g) among newborn infants (which includes those born preterm (<37 weeks gestation), with intrauterine growth restriction (IUGR), or both), is a significant predictor of neonatal mortality and morbidity as well as future health and nutritional status , 2. DespAcross the globe, including in Uganda, persistent high rates of LBW continue to hinder global efforts to reduce infant mortality and improve child growth outcomes. Overall, it is estimated that LBW is a significant underlying factor in >80% of neonatal deaths  . In UganGiven the serious health implications of LBW, United Nations Member States endorsed the target of a 30% reduction in LBW globally between 2012 and 2025 during the 65th World Health Assembly (WHA), . HoweverStudy approval was obtained from the Makerere University Research Ethics Committee at the School of Public Health in Kampala, Uganda; the Uganda National Council for Science and Technology in Kampala, Uganda; the Tufts Health Sciences Institutional Review Board in Boston, MA; and the Institutional Review Board at Harvard T.H. Chan School of Public Health, Boston, MA. Before enrollment into the study, written informed consent was obtained from all participants.The Uganda Birth Cohort Study  was a prospective birth cohort study conducted from 2014–2016 in 12 districts/16 sub-counties in rural northern and southwestern Uganda. The study, which enrolled 5,044 pregnant women, was designed to assess the impact of the Uganda Community Connector Program (UCCP), a five-year agriculture, livelihoods, and nutrition program funded by the United States Agency for International Development (USAID) which aimed to improve the nutritional status of women and children and the livelihoods of vulnerable populations in rural Uganda.The enrollment period for the UBCS lasted approximately 12 months. Eligible women, who were identified as pregnant from a urine pregnancy test administered by village health team (VHT) workers, were referred to study staff for enrollment into the main study. Following enrollment, which occurred primarily during the second or third trimester of pregnancy, mother-infant pairs were prospectively followed every three months until infants reached six or nine months of age. Data collected in the UBCS included information on demographics and household characteristics , maternal dietary intake and diversity, pregnancy history and outcomes, breastfeeding and complementary feeding, and infant morbidity and mortality. Maternal and infant anthropometry, including infant birth weight, were also collected.S1 Table. The target enrollment for the UBCS was 5,152 pregnant women . This sample size allowed for a detection of a 0.14-unit difference in child length-for-age Z-score (LAZ) (the primary outcome variable of the parent study) with 80% power and a 0.05 level of significance, assuming 30% attrition between enrollment of pregnant women and delivery for reasons such as maternal death, fetal loss, household migration, temporary relocation of the mother for delivery, withdrawal, and loss to follow-up. Furthermore, it assumed 10% attrition among live births between delivery and completion of follow-up.Pregnant women 15–49 years of age were eligible to participate in the UBCS if they planned to reside in the study area through the completion of follow-up and provided written informed consent. The inclusion, exclusion, referral, and termination criteria for the UBCS are presented in Fig 1 shows the study profile for this analysis. In total, 5,044 women met the eligibility criteria and were enrolled into the UBCS. Of these, women were excluded from this analysis if they had a missing enrollment visit (n = 95) or a missing birth visit (n = 851). Furthermore, they were excluded if their infant was not born alive (n = 120) or if they had a multiple birth (n = 8). Women were excluded from the LBW analysis if birth weight of the newborn was not recorded within 72 hours (n = 633) after birth and from the preterm birth analysis if gestational age data were missing (n = 129). After exclusion criteria were applied, a total of 3,337 women were included in the LBW analysis and 3,841 in the preterm birth analysis. S2 Table presents the breakdown of enrollment by region, district, and sub-county for both the UBCS and this analysis.The UBCS questionnaires consisted of 13 modules which were programmed onto handheld Android devices using Open Data Kit (ODK) software. Trained enumerators conducted household visits every three months from the time of enrollment until the child reached six or nine months of age. With the exception of pregnancy and birth outcome characteristics, data for this analysis came from the UBCS questionnaire administered at the enrollment visit, which occurred during the second or third trimester of pregnancy.Household food security status was assessed using the Household Food Insecurity Access Scale (HFIAS) , a validDietary diversity during pregnancy was assessed from dietary recall data collected using the Food and Agriculture Organization (FAO) Minimum Dietary Diversity for Women (MDD-W) index . Scores At the enrollment visit, tests for maternal malaria infection and hemoglobin status in pregnancy were conducted by trained nursing staff at participants’ households. Malaria infection was diagnosed using a rapid diagnostic test , and hemoglobin levels were measured using a portable hemoglobinometer . Depending on the results, appropriate counseling, treatment, and/or referral to local health facilities were provided in accordance with UBCS standard operating procedure (SOP).Gestational age was calculated from the first day of mothers’ last menstrual period (LMP). Maternal height was measured to the nearest 0.1 cm using a portable height board . Infant birth weight was measured within 72 hours to the nearest and 0.1 kg using an electronic scale . In all anthropometric measures, triplicate measurements were averaged to provide a single measurement.For the purpose of this analysis, infants born <2,500 grams were considered LBW, and infants born <37 weeks gestation were considered preterm. Adolescent pregnancy was defined as <20 years old. A binary indicator for adequate dietary diversity  was calculated per FAO’s recommendation . Per recPrior to regression analyses, categorical summary statistics for household , maternal , and infant  characteristics were cross tabulated among LBW and non-LBW infants and among preterm and non-preterm infants.Bivariate logistic regression analyses were conducted to identify the relationship between independent household, maternal, and infant characteristics and the birth outcomes of interest . All variables in the bivariate analysis were considered for multivariable logistic regression analysis. Backward stepwise logistic regression models, which produced adjusted odds ratios (aORs), with a 0.05 cut-off for inclusion, were used to test for the predictors of LBW and preterm birth. All analyses were conducted using STATA 15 software . In all cases, p<0.05 was considered statistically significant.Half of the study households were located in the northern region of Uganda, and half were located in the southwestern region. Household heads were overwhelmingly male and either married or cohabitating. Mothers were on average 27 years old, 159 cm tall, and the majority had, at most, a primary school level of education (<8 years). Furthermore, a majority were multigravida, with adequate birth spacing (>24 months), and reported taking deworming medication and iron tablets during pregnancy.Fig 2 shows a distribution of birth weights. Among the 3,337 infants included in the birth weight analysis, mean birth weight was 3.2 ± 0.5 kg, and 4.3% were classified as LBW (<2500 g). Furthermore among 3,841 infants included in the analysis, 19.4% were born preterm (<37 weeks gestation).Half of infants were male, and about one-third were delivered at home. Table 1), being taller (>150 cm) and attending ≥4 ANC visits were associated with a significantly lower odds of delivering a LBW infant. In addition, severe household food insecurity and malaria infection during pregnancy were associated with a significantly higher odds of LBW.In bivariate analyses (Table 2), mothers who were taller (>150 cm) ), multigravida ), or with adequate birth spacing (>24 months) ) had lower odds of delivering a LBW infant. Furthermore, mothers from households with severe household food insecurity ) or who tested positive for malaria during pregnancy ) had higher odds.In multivariable analysis (Table 3), residing in the Southwest, being older (≥ 20 years), better educated (≥ 8 years), having more dietary diversity, with adequate birth spacing, and attending ≥4 ANC visits were associated with a significantly lower odds of delivering preterm. In addition, severe household food insecurity, not taking deworming medication or iron tablets during pregnancy, and delivering at home were associated with a significantly higher odds of delivering preterm.Analyses were also performed to help identify the relationship between household, maternal, and infant characteristics and preterm birth. In bivariate analyses (Table 4), mothers who resided in the Southwest ), were ≥20 years old ), with adequate birth spacing ), or attended ≥4 ANC visits ) had lower odds of delivering preterm. Furthermore, mothers who were neither married nor cohabitating ) or delivered at home ), had higher odds of delivering preterm.In multivariable analysis ) and malaria infection during pregnancy ) were associated with a higher odds of delivering a LBW infant. In the Southwest, mothers who were taller ) or with adequate birth spacing ) had a lower odds of delivering a LBW infant.With regard to preterm birth, mothers in the North who were older (≥20) ), attended ≥4 ANC visits ), or with adequate birth spacing ) had a lower odds of delivering preterm. In the Southwest, mothers who attended ≥4 ANC visits ) had a lower odds of delivering a preterm infant; mothers who delivered at home  had a higher odds of delivering preterm.While the predictors of adverse birth outcomes, including LBW and preterm birth, are complex, multidimensional, and geographically context-specific, their identification is key to the development of future policies and programs to improve morbidity and mortality among infants in LMICs as well as to meet the global nutrition target of a 30% reduction in LBW globally between 2012 and 2025. Using data from a large birth cohort study in rural Uganda, we identified several modifiable risk factors associated with LBW and/or preterm birth, including severe household food insecurity, adolescent pregnancy, inadequate birth spacing, malaria infection, suboptimal ANC attendance, and home delivery.The World Food Summit in 1996 defined food security as “when all people, at all times, have physical and economic access to sufficient safe and nutritious food to meet their dietary needs and food preferences for a healthy and active life” . While tAdolescence, a period characterized by biological immaturity, i.e., incomplete anatomical and physiological development, is a relatively well-established risk factor for adverse birth outcomes. A study by Fall et al. which pooled data from five birth cohort studies , found significant associations between younger maternal age (≤19 years) and both LBW (aOR = 1.18 (95% CI = 1.02–1.36)) and preterm birth (aOR = 1.26 (95% CI = 1.03–1.53)) compared with mothers aged 20–24 years . In a syAccording to WHO, after a live birth, the recommended interval before attempting the next pregnancy is at least 24 months in order to reduce the risk of adverse maternal, perinatal, and infant outcomes . Based oPlasmodium falciparum infection, and associated inflammatory processes increase energy expenditure and protein catabolism causing nutritional depletion in the mother and IUGR in the fetus [It is established that malaria in pregnancy, particularly he fetus . Overallhe fetus , 36, makhe fetus . InterveIn addition, WHO currently recommends a minimum of 8 ANC visits to “reduce perinatal mortality and improve women’s experience of care” . UniversFinally, according to the 2016 Demographic and Health Survey (DHS), 73% of births in Uganda occur at a health facility [Strengths of the study include a large sample size as well as a prospective study design, with data collection beginning during pregnancy, allowing for temporal relationships between predictors and outcomes to be examined. Birth weights were measured by trained enumerators within 72 hours of delivery, and we were able to capture births that occurred both inside and outside a health facility. Limitations of the study include imprecisions associated with assessing gestational age from date of LMP and a relatively small sample of infants born LBW. Notably, this relatively small sample may even be an overestimate of LBW as birthweights were collected over a period of 72 hours, a time when newborns typically lose weight.Despites efforts to reduce the incidence of LBW, it remains a significant public health concern for the majority of LMICs, including Uganda. As meeting the target of reducing LBW by 30% between 2012 and 2025 will require more than doubling the current rate of progress [S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Live birth is the most important concern for assisted reproductive technology (ART) patients. Therefore, in the medical reproductive centre, obstetricians often need to answer the following question: “What are the chances that I will have a healthy baby after ART treatment?” To date, our obstetricians have no reference on which to base the answer to this question. Our research aimed to solve this problem by establishing prediction models of live birth for ART patients. Between January 1, 2010, and May 1, 2017, we conducted a retrospective cohort study of women undergoing ART treatment at the Reproductive Medicine Centre, Xiangya Hospital of Central South University, Hunan, China. The birth of at least one live-born baby per initiated cycle or embryo transfer procedure was defined as a live birth, and all other pregnancy outcomes were classified as no live birth. A live birth prediction model was established by stepwise multivariate logistic regression. All eligible subjects were randomly allocated to two groups: group 1 (80% of subjects) for the establishment of the prediction models and group 2 (20% of subjects) for the validation of the established prediction models. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each prediction model at different cut-off values were calculated. The prediction model of live birth included nine variables. The area under the ROC curve was 0.743 in the validation group. The sensitivity, specificity, PPV, and NPV of the established model ranged from 97.9–24.8%, 7.2–96.3%, 44.8–83.8% and 81.7–62.5%, respectively, at different cut-off values. A stable, reliable, convenient, and satisfactory prediction model for live birth by ART patients was established and validated, and this model could be a useful tool for obstetricians to predict the live rate of ART patients. Meanwhile, it is also a reference for obstetricians to create good conditions for infertility patients in preparation for pregnancy. Fundamentally, numerous key factors play important roles in live birth outcomes, including embryo parameters3, reproductive hormone levels6, and the patient’s age8, among others; however, the degrees to which these factors affect birth outcomes are not clear. Consequently, it is very significant to investigate how these factors affect live birth outcomes, determine their degrees of influence and then establish live birth prediction models.Live birth is the most important concern for assisted reproductive technology (ART) patients; additionally, it is the only criterion used to determine whether ART treatment is successful. In recent years, ART in humans has developed very quickly, but the live birth rate is still less than optimal9, intracytoplasmic sperm injection (ICSI) patients10, ICSI patients with uncompromised ovarian reserve11, and poor ovarian responders13. Different strategies have included risk scoring systems14 deep phenotyping9, granulosa cell biomarkers1, and clinical characteristics 15. The sensitivity and specificity of these live birth prediction models exhibit large variations. Prajna Banerjee et al.9 used 52 clinical characteristics to establish a model. The area under the receiver operating characteristic (ROC) curve was up to 0.80 for IVF patients in their first cycles, but in their subsequent treatments, this value decreased to less than 0.68. Although many live birth prediction models have been established, they are rarely used in clinical practice. The main reasons may include the following: (1) they cannot be applied to all ART patients because the model is based on only 1–2 types of ART patients; (2) some predictors need more complicated and expensive laboratory tests; (3) the use of these models is not sufficiently convenient, and (4) some models are less accurate than others for predicting live birth.Previous studies have used various strategies to predict live birth for different sub-groups of ART patient, including in vitro fertilization (IVF) patientsWe aimed to establish a convenient and practical live birth prediction model that has higher predictive value and that can be applied to all ART patients.There were 15,717 ART treatments performed from 2012 to 2017. Of these, 1891 subjects who had missing information on their live birth outcomes were excluded, leaving 13,826 subjects for analysis. Among them, 80% of the subjects  were allocated to group 1 (establishment model), and 20% of them (2755) were allocated to group 2 .p-value < 0.05, Tables We analysed the relationships between the variables and live birth outcomes by univariate analysis. Twenty-two variables were found to be significantly associated with live birth outcomes ]. The area under the ROC curve was 0.743   of Xiangya Hospital Central South University. The inclusion criteria for data analysis were as follows: (1) completion of the basic medical examination; (2) completion of the entire ART treatment cycle; (3) complete record of the couple’s basic information; and (4) thorough documentation of the live birth outcome.In our study, we focused on live birth. The birth of at least one live-born baby per initiated cycle or embryo transfer procedure was defined as a live birth, and all the other adverse pregnancy outcomes were classified as no live birth.p value was less than 0.05; second, it contributed to improving the area under the ROC curve. All eligible subjects were randomly allocated to two groups: group 1 (80% of subjects) for the establishment of the prediction models and group 2 (20% of subjects) for the validation of the established prediction models. Subjects of the two groups were independent without repetition. The areas under the ROC curve generated by the logistic regression model were applied to evaluate the effectiveness of the prediction models. We further calculated the sensitivity, specificity, positive predictive value, and negative predictive value of the prediction models with different cut-off values.A live birth prediction model was established by stepwise multivariate logistic regression . When establishing the model, the criteria for selecting predictive variables were as follows: first, p values corresponded to two-sided tests, and p < 0.05 was considered statistically significant.All data were managed and analysed using the statistical package for social sciences (SPSS) software version 17.0  and Excel . Measurement data are described as the mean ± standard deviation (SD), and enumeration data are described as numbers (percentages). All The study was approved by the Ethics Committee of Xiangya Hospital of Central South University, mainly including the use of data from various clinical examination and laboratory tests of patients. All infertility patients presenting to the Reproductive Medicine Centre, Xiangya Hospital of Central South University, Hunan, China, who were planned for ART treatments and who signed the informed consent were enrolled in the study from January 1 2010 and May 1 2017. In addition, we confirmed that all methods were performed in accordance with the assisted reproductive technology relevant guidelines and regulations.Supplementary Table.


This work analyzed the available evidence in the scientific literature about the risk of preterm birth and/or giving birth to low birth weight newborns in pregnant women with periodontal disease. A systematic search was carried out in three databases for observational cohort studies that related periodontal disease in pregnant women with the risk of preterm delivery and/or low birth weight, and that gave their results in relative risk (RR) values. Eleven articles were found, meeting the inclusion criteria. Statistically significant values were obtained regarding the risk of preterm birth in pregnant women with periodontitis (RR = 1.67 (1.17–2.38), 95% confidence interval (CI)), and low birth weight (RR = 2.53 (1.61–3.98) 95% CI). When a meta-regression was carried out to relate these results to the income level of each country, statistically significant results were also obtained; on the one hand, for preterm birth, a RR = 1.8 (1.43–2.27) 95% CI was obtained and, on the other hand, for low birth weight, RR = 2.9 (1.98–4.26) 95% CI. A statistically significant association of periodontitis, and the two childbirth complications studied was found, when studying the association between these results and the country’s per capita income level. However, more studies and clinical trials are needed in this regard to confirm the conclusions obtained. Periodontal diseases comprise a wide range of inflammatory disorders that affect the supporting structures of the tooth and can lead to both tooth loss and contribute to systemic inflammation; the disease begins and spreads due to the interaction between a dysbiosis of the oral microbiota and a vulnerable host immune system ,2.The initial stage of this disease is called “gingivitis”, which corresponds to a localized inflammation of the gum, with redness and/or bleeding, due, in most cases, to the deposit of bacterial plaque due to poor oral hygiene. If gingivitis is left untreated, it may progress to chronic periodontitis, characterized by a loss of the gum, bone, and periodontal ligament, resulting in what are known as periodontal pockets. The severity of periodontal disease depends on host and environmental risk factors, whether modifiable  or non-modifiable (genetic susceptibility) ,3.Symptoms of periodontitis include redness, change in texture and inflammation of the marginal gingiva, bleeding when probing the periodontal pocket, destruction of tooth support structures, recession of the marginal gingiva, increased morbidity and dental mobility and ultimately, tooth loss . Oral diAt the European level, approximately 50% of the adult population suffers from some form of periodontal disease and between 10–15% suffer from severe periodontitis ,3,6.Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola) and Fusobacterium nucleatum, while Prevotella intermedia and Actinobacillus actinomycetemcomitans stand out. The latter is more associated with aggressive periodontitis, while the former with chronic periodontitis [In recent decades, there has been a growing interest in the study of the oral microbiota and its important role in systemic health . Gram-nedontitis ,9,10.The presence of an oral infection such as periodontal disease can be a cause or exacerbation of various systemic conditions. It is unknown whether the presence of periodontal disease together with any systemic disease is merely accidental, occurring simultaneously due to sharing similar risk factors ,7 or if Over the years, more evidence has emerged that local infectious diseases such as periodontitis can influence a wide variety of systemic diseases ,11. DentChronic oral infections, particularly periodontitis, could be the underlying cause of various fatal systemic diseases, such as endocarditis. Numerous studies show that heart conditions such as coronary heart disease, acute myocardial infarction, coronary infection, cardiomyopathies, peripheral vascular disease, and atherosclerosis are related to chronic processes of infection and inflammation ,2,12,13.Two pathogenic mechanisms are proposed that may explain the potential effect of periodontitis on pregnancy outcomes: On the one hand, the periodontopathogenic bacteria that inhabit the gingival biofilm, due to a translocation phenomenon, can directly affect the fetus due to bacteremia ,10. On tDuring pregnancy, hormonal changes increase vascular permeability in the gingival tissues, which facilitates the diffusion of pathogenic microorganisms and their products to the circulation and to the placenta ,9. In adEvery year, around 15 million premature babies are born in the world. Preterm delivery is considered as delivery occurring before 37 weeks of gestation. These children, moreover, tend to be born with low weight, considered to be less than 2500 g . Low birNot only can pregnancy interfere with the periodontal disease, but it can also alter its progression. The physiological changes induced during pregnancy can alter the inflammatory response, amplifying gingival inflammation. Gestational gingivitis affects 36–100% of pregnant women. Clinical parameters such as bleeding on probing and pocket depth can be increased without the need for an increase in plaque index and then decreased after delivery. The mechanisms by which the severity of periodontitis increases during pregnancy have been related to increased vascular permeability, depression of the immune system, and changes in the composition of the supra and subgingival microbiota [Case-control studies show that women with periodontitis are more prone to preterm delivery and low birth weight ,21,22,23The objective of this work will be to analyze all the evidence available in the scientific literature on the risk of preterm birth and/or giving birth to low birth weight newborns in pregnant women with periodontal disease.In order to carry out a standardized review and meta-analysis, as well as to minimize the appearance of bias in the review process as much as possible, the PRISMA  recommendation of 2009 has been followed as the review protocol . This stCohort studies that study the relationship between periodontal disease in pregnancy and preterm delivery and/or low birth weight were selected. To facilitate the study of this association, only those studies that included the relative risk values and their confidence interval have been considered. No study has been ruled out due to the language of publication; all have been published in English or contained a translation in this language.The purpose of most of the studies was to determine the association between pregnant women with periodontal disease and the risk of premature delivery and/or low birth weight ,29,30,31The PICO (Population/Income/Comparison/Outcome) question was set up as follows: Whether there was a higher risk of preterm delivery and/or low birth weight in the population of pregnant women with periodontal disease compared to the population of healthy pregnant women.This was followed by a systematic search for studies in three databases , together with a manual search of the bibliographic references of the studies selected in the databases. It was possible to obtain the full texts of all the articles without needing to contact their authors.The search strategy used in PubMed was: ((preterm birth) OR low birth weight) AND periodontal disease, obtaining 667 articles.The search strategy used in Scopus was: (TITLE-ABS-KEY (preterm AND birth) OR TITLE-ABS-KEY (low AND birth AND weight) AND TITLE-ABS-KEY ) obtaining 683 articles.The search strategy used in Embase was: (‘premature labor’ OR ‘low birth weight’) AND ‘periodontal disease’, revealing 580 articles.The date of the last search was 6 May 2020.The keywords were “preterm birth” or “premature labor”, “low birth weight” and “periodontal disease”.The inclusion criteria consisted of cohort studies that analyzed the relative risk of preterm delivery and/or low birth weight in pregnant women with periodontal disease. Those that only describe the possible association between these variables have been accepted, as well as those in which periodontal treatment has been carried out during pregnancy to observe the influence of this on the risk variable for preterm birth and/or periodontal disease and its comparison with the cohort of pregnant women with untreated periodontitis. The women studied had to be clinically diagnosed with periodontitis during the course of their pregnancy. Exclusion criteria were not determined.Two calibrated reviewers (C.A.M.-S. and J.E.I.-C.) performed the database search and selection of articles for inclusion in the study. In case of discrepancy, a third reviewer (J.M.M.-C.) decided to include or exclude the article in the study. A kappa value of 0.87 was obtained to determine the inter-reviewer reliability. After reading the title and abstract, a first screening was carried out, eliminating those studies that did not meet the inclusion criteria. Subsequently, a reading of the full text of the articles that had not been discarded was made, finally selecting those that met all the eligibility criteria.Six main sets of data have been extracted from the articles, from which their study will allow us to answer our PICO question.Author/year.Country. This will make it possible to study a possible relationship between the results obtained and the level of income per capita in the region.Sample size. The greater the number of patients studied, the more representative the results obtained will be. A distinction has been made between the population of pregnant women with periodontitis and those without this disease.Population characteristics. Weeks of gestation and mean age of the patients studied.Definition of periodontal disease.Definition of premature delivery and/or low weight.Relative risk (RR) of preterm birth (PB) and/or low birth weight (LBW).Conclusions. Whether or not an association has been observed.The Newcastle-Ottawa scale has been used to assess the quality of the cohort studies, seeking to incorporate quality assessments in the meta-analysis interpretation of the results obtained. It is made up of eight items, divided into three dimensions .The selection criterion is made up of four items, so it will have a maximum score of four points. These are: The representativeness of the exposed cohort, description of the selection of the unexposed cohort, verification of the exposure, and whether the outcome of interest was not present at the beginning of the study.The comparison criterion is made up of a single item, but the maximum score that can be obtained in it confers two points. This item assesses whether a comparison of the cohorts has been made in the study.The exposure criterion is made up of three items: Assessment of results, sufficient follow-up for the appearance of results, and adequate cohort follow-up. Its maximum score is three points.Ultimately, the maximum evaluation that an article can obtain will be 8 points. Depending on the total points obtained, the article will be of greater or lesser quality. Those articles whose total sum ranges from 8 and 7 will be of high quality; of medium quality are those ranging between 6 and 5, while low quality ones have a score of less than 5.The data of this study have been analyzed with the statistical program “Comprehensive Metanalysis 3.0”.2 statistical index, Q test, and p-value. Statistical heterogeneity tries to quantify the variability of the result measured in the different studies with respect to the average global result and determine if the said variability is higher than what would be expected by pure chance.The heterogeneity of the meta-analyses was quantified using the I2 parameter indicates the proportion of the variation between the studies with respect to the total variation; that is, the proportion of the total variation attributable to heterogeneity. It relates the variability between studies with the internal variability in the studies. When its value falls within the range between 25 and 50, it has mild heterogeneity, while between 50–75 it is considered moderate, and if it is greater than 75, it denotes high heterogeneity.The Ip-value, it is considered that there is heterogeneity when the value of “p” is less than 0.1.Regarding the Q test and Finally, the studies will be combined using the random effects model, which considers that there is an intra- and inter-study variability.Publication bias occurs when study results are selectively published, leading to an inadequate estimate of the true effect of an intervention.To assess the symmetry between the studies, the risk of bias was rigorously quantified in each of the meta-analyses using a “Funnel plot” or funnel diagram, “Classic Fail-Safe Number”, “Egger’s regression intercept”, and “Duval and Tweedie’s trim and fill”.The “Funnel plot” includes the standard error on its abscissa axis and, on the ordinate axis, the parameter to be analyzed for each study . In this way, a funnel-shaped figure is obtained, which allows a visual assessment of the risk of bias.The “Classic Fail-Safe Number” indicates the number of studies that would be necessary for the results obtained to cease being significant.“Egger’s regression intercept” is a regression method on graphs. Obtains, among other data, the standard error, and its confidence interval. If the numbers that make up this interval comprise 0, it means that there is no publication bias.The “Duval and Tweedie’s trim and fill” allows us to analyze the existence of differences between the risk estimate obtained with imputed studies and the original. Its results are obtained by means of an imputed Funnel plot.As an additional method of analysis, a meta-regression was performed to assess the possible influence of the socio-economic level of the country on the results obtained; that is, if in countries with a lower socioeconomic level there is a higher incidence of premature births or low birth weight in pregnant women with periodontitis, than in countries with a higher per capita income. To carry out the study of this association, a Scatter plot was performed.From this initial search, 1930 articles were obtained . Two stuWhen comparing the articles obtained in each database, all duplicates were eliminated, leaving a total of 942 articles to review. After reading the title and “abstract” this number was reduced considerably, since only cohort studies were chosen that gave data on relative risk (inclusion criterion), reducing the total number of articles to 21.Of these, after reading them in detail, 10 were eliminated, as they did not meet any of the inclusion criteria; three of them for not answering our PICO question, and the remaining one for giving erroneous relative risk results.In the end, a total of 11 studies entered the meta-analysis; the full text was available for all of them.All the articles included in the work are, as already mentioned, observational cohorts. Therefore, all of them include a control group of pregnant women without periodontitis, except for Macones et al. and Michalowicz et al. ,36, whosThe sample size of each study is considerable, ranging from 200 to 1600 pregnant women, all of whom were followed up. The age of the pregnant women included in the studies varied between 18–40 years and their onset of participation in the study ranged from week 6 to 24 of gestation.All the examiners diagnosed periodontal disease through clinical examinations assessing attachment loss, probing depth, and number of affected teeth. In general, periodontitis was diagnosed when there was an attachment loss of ≥3 mm in ≥3 teeth.In all cases, premature birth was established as: When the child is born before 37 weeks of pregnancy, except the one carried out by Macones, who established it at 35 weeks.Only seven of the studies ,30,31,34Of the 11 articles analyzed, six concluded a statistically significant relationship between periodontal disease during pregnancy and preterm birth  ,30,31,34To assess the quality of the articles included in the work, the Newcastle-Ottawa Scale for cohort studies was used . Seven oAll of them are considered to meet the four items that made up the selection criteria. Regarding the comparability criterion, only two articles did not show the comparison data between the two cohorts  with a 95% confidence interval, indicating a greater probability of occurrence of preterm birth in pregnant women with periodontal disease.For the meta-analysis of periodontal disease and preterm birth, the I2 = 59.1% with p = 0.032 and Q test value = 12.2. This indicates a moderate level of heterogeneity. A statistically significant relative risk was obtained: 2.54 (1.61–3.98) with a confidence interval of 95%, indicating a higher probability of occurrence of low birth weight in pregnant women with periodontitis.On the other hand, for the meta-analysis of periodontal disease and low birth weight, the results were IResults quite similar to those of preterm birth were observed: Studies carried out in countries with a high socioeconomic level did not establish a statistically significant relationship between periodontitis and low birth weight, while studies carried out in countries such as Chile, Malaysia, Brazil, Madagascar, and India concluded significant relationships between one variable and another.p-value: 0.005). It shows a statistically significant relationship between periodontitis and preterm birth  with a 95% confidence interval  has been estimated. It shows a statistically significant relationship between periodontitis and low birth weight  with a 95% confidence interval , with a Using the Duval and Tweedie’s trim and fill for preterm labor, we obtained the imputed Funnel plot. Obtained as adjusted RR 1.46 (1.03–2.06); no publication bias was detected a.For low birth weight, a standard error Funnel plot was performed to assess the symmetry between the studies. Graphically, a symmetrical distribution of the studies was observed along the funnel; that is, there is no publication bias.Regarding the Classic Fail-Safe Number for low birth weight, it was established that 56 articles were necessary for our results so that this variable ceased to be significant. This finding supports our assertion that there is no publication bias.p-value of 0.052. The confidence interval and the p-value comprise more adjusted values than those obtained for preterm delivery; there is greater exposure to bias, but it can be concluded that there is no bias.In the Egger’s regression intercept for low passage at birth, the result was 3.63 (−0.05–7.31), with a Using the Duval and Tweedie’s trim and fill for low birth weight, we obtain the Funnel plot. It is obtained as adjusted RR 2.54 (1.61–3.98); no study could be identified, so there is no publication bias b.The relationship between the risk of preterm birth in pregnant women with periodontitis and the income level of the country of each article in the study was analyzed using a meta-regression. The 2018 “World Bank list of economies” was used to classify the countries in which the different studies were carried out according to their per capita income.Countries were categorized according to their income. Thus, a value of 2 was given to the countries with a low-to-middle socioeconomic level , 3 to those with a medium-to-high level , and 4 to high , taking as reference the value of 1 = very low socioeconomic level .2 indicates the predictive capacity of the linear meta-regression model that has been generated; in this case it was 84%. The significant result occurs in group 4 of per capita income, with a coefficient of -0.89 and a value of p = 0.002. This means that the RR of preterm birth decreases 0.89 times in high-income countries   .Likewise, another meta-regression analysis was carried out that related the socioeconomic level of the countries included in the study with the relative risk of LBW. The countries were categorized according to their income following the same previous model: A value of 2 for the countries with a low-to-middle socioeconomic level (India), 3 for the medium-to-high , and 4 for the high (USA and Canada), taking the value of 1 as a reference = lowest level (Madagascar).2 indicates the predictive capacity of the linear meta-regression model that has been generated; in this case it was 100%. The significant result occurs in group 4 of income per capita, with a coefficient of −0.98 and a value of p = 0.03. This means that the RR of preterm birth decreases 0.98 times in high-income countries  .In recent years, there has been an increase in scientific evidence suggesting an association between oral health status, specifically periodontal disease, and an increased risk of systemic diseases. These diseases are multiple and varied: Atherosclerosis, hypertension, infective endocarditis and other cardiovascular diseases, erectile dysfunction, rheumatoid arthritis, chronic kidney disease, diabetes mellitus, and various adverse pregnancy outcomes, such as an increased risk of low birth weight babies, childbirth prematurity, preeclampsia, and gestational diabetes ,37.Regarding the reason for the relationship between periodontitis and premature delivery and/or low birth weight, it seems that the hypothesis most supported by the medical literature is that of inflammatory processes in the placental-fetal junction or elevated systemic inflammation  can produce these adverse effects in childbirth .Furthermore, the presence of periodontal disease in pregnancy can lead to the translocation of periodontopathogenic bacteria to the utero-placental circulation. This bacterial accumulation can provoke a response from the fetal membrane, whose functions may be interrupted and, therefore, predispose the said membrane to rupture and premature delivery ,39.It could be said that the relationship between periodontal disease and pregnancy is bidirectional as the latter is also strongly related to the incidence periodontal disease. The increased hormonal level of estrogens and progesterone that occurs in pregnant women causes an increase in the blood supply to the gum tissue, resulting in inflammation and bleeding of the gums. This situation of gingivitis, maintained over time, will evolve into periodontitis .A premature newborn is one that is born before completing the 37th week of gestation. The difficulty of knowing the gestational age of the newborn makes it necessary to use birth weight as a reference parameter. The neonate is classified as underweight when its birth weight is less than 2500 g; very low weight when it is less than 1500 g and, extremely low weight, when it is less than 1000 g .The identification of young children for their gestational age  is important because they present an increased risk of perinatal morbidity and mortality, and of cardiovascular disease in adulthood . Low birBy establishing the relationship between the parameters of weight and gestational age, we can subdivide the preterm population into high weight, adequate weight, and low weight for their gestational age, a situation that will determine the probability of postnatal morbidity .Prematurity is a serious public health problem due to the great morbidity and mortality it generates, being the leading cause of mortality in children under 5 years of age, in addition to the high economic and social costs that its care causes . Most ofAccording to the World Health Organization (WHO), it is estimated that 15 million premature babies are born annually worldwide; that is, one in 10 births is premature. Of these, approximately one million die each year due to complications from this preterm delivery. Of the babies that survive, many develop some type of permanent disability, mostly related to learning, visual, or hearing problems.The determining factors of this complication in pregnancy are multiple. In preterm birth, in addition to biological determinants, those that are the responsibility of the health of each country and the state are involved . As it is a public health problem, the prevention and treatment of prematurity should be an obligatory public policy . The strIt has also been suggested that social and psychological factors affect health behavior and this in turn affects periodontal disease. These factors include oral hygiene, dental health monitoring, and smoking, and are related to both socioeconomic conditions and periodontal disease .Regarding the etiopathogenesis of low weight for gestational age of the newborn child, maternal, placental, and fetal causes have been described as factors involved in this event. However, in most cases the cause is not clear. Maternal factors seem to be involved in half of the cases, highlighting in developed countries the importance of severe gestational hypertension, the history of a previous SGA child and, as a preventable and avoidable cause, maternal smoking stands out .The fundamental objective that was the basis for the start of the work has been fulfilled. On the one hand, a statistically significant relationship has been established between periodontal disease in pregnancy and preterm delivery. Based on the results obtained, the fact that the pregnant mother suffers from periodontal disease increases the risk of premature birth 1.67 times; RR = 1.67 (1.17–2.38), 95% CI.On the other hand, regarding the possibility of giving birth to a low-weight baby in women with periodontitis, this relationship was also demonstrated with a relative risk value of 2.53 (1.61–3.98), 95% CI.Therefore, the findings of this work indicate that the presence of periodontal disease in the pregnant mother is a determining risk factor when suffering such adverse outcomes in pregnancy.Within the classification of levels of evidence according to the Oxford Centre for Evidence-Based Medicine (CEBM), a meta-analysis of cohort studies corresponds to a high level of 2a evidence. According to the modified GRADE system, we have a grade of recommendation 1B. This indicates a strong recommendation for the results obtained and evidence of moderate quality.The advantage of using only cohort studies in the meta-analysis is that they will allow the results obtained to be extrapolated more easily to the general population, giving greater external validity.The fact that only published studies had been analyzed could have led to an overestimation of the risk caused by periodontal disease for the pregnant mother, but this is not the case in this study, since we have estimated this publication bias and found that it is non-existent.We think that the work provides a good estimate of the association between periodontal disease and the two study variables, since the sources of variability in the results of the different studies have been quantified.However, the limited number of studies in the scientific literature on this topic has determined that the number of articles analyzed has been limited, this being a possible bias for the results obtained.This meta-analysis differs from others already carried out ,47 by foHeterogeneity has been controlled by combining the studies using the random effects model, which allows it to be assessed by both an intra- and inter-study. One of the main sources of heterogeneity that has been studied has been the country in which each study was carried out; specifically, its per capita income level.Already in the meta-analysis carried out by Vergnes and Mixou in 2007  the econThe country’s income level not only determines an increased risk of preterm or low birth weight, but also influences the survival of that child born prematurely. The WHO estimates that in low-income countries, half of preterm infants die because they have not received simple care such as breastfeeding or basic care to avoid infections and respiratory problems; in contrast, in high-income countries most of these babies survive.In this study, we wanted to establish if there could be a relationship between the increased risk of premature birth in pregnant women with periodontal disease and the income level of each country; for this, a meta-regression was carried out. The existence of a statistically significant association was determined, with RR: 1.8 (1.43–2.27), CI 95%. The risk of suffering preterm birth increases in countries with a lower level of income per capita, such as Malaysia, India, Chile, Brazil, Madagascar or India, and disappears in those with a high level of income that, in this work, corresponded with the United States and Canada. Likewise, it has been determined that the country’s income level is also closely related to the appearance of low birth weight, with a RR of 2.9 (1.98–4.26), 95% CI. These are very similar results to those obtained in the meta-regression for preterm birth, since the risk of low birth weight ceases to exist in countries with higher per capita income. The fact that this risk disappears in developed countries could be explained by the important role that psychosocial factors play in oral health care.However, some studies ,47 suggeDespite the evidence associating periodontitis with gestational complications, the effect of periodontal treatment in pregnancy is not yet supported by scientific evidence ,29,36. RThe objective of this work was to analyze the evidence available in the scientific literature on the risk of preterm birth and/or giving birth to low birth weight newborns in pregnant women with periodontal disease, and how other factors such as the per-capita income can affect it. In our approach, we limited the data mining to relative risk, leading to include 11 studies in the final synthesis. In future studies, more variables should be included to avoid this limitation.Another limitation of our study was the per-capita income definition. Only one study was carried in a country with socio-economic level 1. Maybe including other variables and not only the relative risk could lead to include more countries of this socio-economic level. Moreover, the definition of the socio-economic level was made through the theoretical level of the country, and maybe it is not the same in all the departments of the country.Finally, the definition of the periodontal disease in each study is different, making the data mined heterogeneous. In future studies, the definition of this disease could be an exclusion criteria, focusing in probing depth or periodontal loss.After analyzing the published literature, we can conclude that the risk of suffering preterm birth is 1.67 times higher in women with periodontitis, and the risk of a newborn with low birth weight, is 1.42 times, with a 2a evidence level.In addition, when comparing these results with the per capita income level of each country, we have observed that the risk of suffering preterm birth in pregnant women with periodontitis increases 1.8 times in countries with lower socioeconomic levels, and seems to disappear in countries with higher per capita incomes. Similarly, the same happens with regard to the risk of giving birth to low-weight babies in pregnant women with periodontal disease: This fact is 2.9 times more likely to happen in countries with a lower economic level, and disappears in those with greater income levels. These results may not be attributed only to income, but to other factors such as education levels and therefore, this relationship should be more closely examined in future research.


Background: Synovial cysts rarely occur after a laminectomy and are difficult to detect if there are no symptoms; however, they can cause lower back pain or symptoms of radiculopathy. Various methods are used to treat synovial cysts. Here, we will introduce the first case with treatment using the transforaminal epiduroscopic laser annuloplasty (TELA) system. Case report: A 64-year-old female patient visited the pain clinic with lower back pain and pain radiating from the left lower extremity. An MRI T2 image showed a synovial cyst of facet joint origin at the L4–L5 level; the patient had undergone a laminectomy 10 years ago at the same spinal level. The patient rated the pain an 8 on the numerical rating scale (NRS), and pain was reduced after epidural steroid injection, but symptoms recurred a month later. The cyst ablation was performed using the TELA system with a 1414 nm neodymium-doped yttrium-aluminum-garnet (Nd:YAG) laser, and after the procedure, pain decreased to 4 points immediately and was reduced to 2 points on the NRS after 1 week. Six months after the procedure, the pain level was measured on NRS 2 and cyst was not recurred in the additional MRI. Conclusion: We introduced the TELA system as a noninvasive therapy for treating synovial cysts. Ablation of cystic necks using a 1414 nm Nd:YAG laser could be a method to prevent cyst recurrence, but long-term follow-up and large scale control studies will be needed to verify the effectiveness of this method. Spinal synovial cysts can be found incidentally, but typically present with lumbar pain or radiculopathy. There is evidence that they are associated with arthrosis due to instability of the facet joint and excessive load on the joint . AlthougEvidence for adequate treatment of symptomatic synovial cysts is lacking. Surgical removal is possible, but non-surgical methods are preferred, due to the invasiveness of the surgery and the burden of post anesthetic recovery. Non-surgical treatment methods, such as bed rest, physiotherapy, chiropractic treatment, acupuncture, oral analgesics, braces, and lumbar spine injections have been attempted . EpiduraHerein, we report a new method using the neodymium-doped yttrium-aluminum-garnet (Nd:YAG) laser of the transforaminal epiduroscopic laser annuloplasty (TELA) system to remove a synovial cyst that occurred after a laminectomy.The patient gave written, informed consent for publication. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Kyung Hee University Hospital . A patient visited the pain clinic with lower back pain and radiating pain from the left lower extremity that began a week prior. The magnetic resonance imaging (MRI) T2 image showed a synovial cyst of facet joint origin at the L4–L5 level A,B; the ®, Ilsan, South Korea), was introduced through the working cannula. After debridement of the cyst with forceps, ablation was performed using an Nd:YAG laser set at 2.5 to 6 W. While monitoring the patient for nerve irritation, the laser ablation was performed using a side-firing Nd:YAG laser cable included in the TELA system  with an operating wavelength of 1414 nm. The patient was observed postoperatively for neurological deficits or other procedure-related problems and was discharged one day after the procedure with no complications.The patient was in the prone position, awake, and under local anesthesia. After infiltration with 1% lidocaine, anteroposterior and lateral fluoroscopy was used to advance a spinal needle into the L5 suprapedicular notch at the Kambin’s triangle. This was performed through a 1 cm incision 14 cm left of the vertebral midline. A series of anteroposterior and lateral radiographs were performed throughout the procedure to ensure the correct trajectory. At the suprapedicular notch, 1% lidocaine was injected into the foraminal space. After sequential dilation, a beveled working cannula was placed below the superior articular process (SAP) A,B. A seThe patient’s pain, measured with the NRS, decreased to 4 points immediately after the procedure and was 2 points after 1 week. Subsequently, at a 6-month follow-up, the patient was treated with pregabalin 50 mg twice a day, and pain control was well-maintained at 1–2 points. In addition, MRI was performed, indicating that cyst did not recur A,B.Synovial cysts are rare, and synovial cysts post-laminectomy are even more rare ,4. As a One report used a side-firing holmium-doped yttrium-aluminum-garnet (HO:YAG) laser through endoscopy to remove a discal cyst . The autTELA is a recently developed method for patients with disc herniation with radiculopathy. TELA decompresses herniated discs using a laser or forceps. This procedure is usually performed using a side-firing 1414 nm Nd:YAG laser to decompress the herniated disc ,11. An NSafety and efficacy should be considered when using laser ablation. Ablation can be carried out with high energy lasers, but it is important to use an appropriate level of energy, as it can damage surrounding structures. One study reported that access to the cervical articular facet joints with an Nd:YAG laser had the potential to facilitate ankylosis procedures without affecting the spinal cord when 2000 J of energy was used . In the There is a limitation in this report, which is the fact that the follow-up period is short. In other paper, after removal of cyst, the degree of pain was followed up to 6 months  or otherTo the best of our knowledge, there have been no reports on the use of a 1414 nm Nd:YAG laser for the removal of a synovial cyst. Forceps were used to debridement of the cyst and the laser was used to ablate the cyst neck to prevent recurrence. It is not clear how much laser ablation contributes to the complete removal of cysts to prevent recurrence. However, after the laser ablation, the symptoms improved for 6 months, while, after the epidural block, the symptoms recurred 1 month later. MRI is a definite way to check for recurrence of a synovial cyst, and MRI taken 6 months after the procedure showed no recurrence of cyst.We introduced the TELA system as a noninvasive therapy for treating synovial cysts. Ablation of cysts using a 1414 nm Nd:YAG laser could be suggested as one of the ways to prevent recurrence of the cyst, but long-term follow-up and large scale control studies will be needed to confirm as an effective method.


We then evaluated transcript expression profiles using the Affymetrix Human GeneChip Transcriptome Array 2.0. Transcriptional profiles of sufficient quality for analysis were obtained from 54 women; 19 of these women delivered <34 weeks and were defined as preterm cases and 35 controls delivered >37 weeks. The median time to birth from sample collection was 13 weeks. No transcripts were significantly associated with preterm birth in a case-control study of matched term and preterm birth (n = 42 women). In the influenza-stimulated samples, expression of IFNL1 was associated with longer time to delivery—the amount of time between sample collection and delivery (n = 54 women). A qPCR analysis confirmed that influenza-induced IFNL expression was associated with longer time to delivery. These data indicate that during pregnancy, ex vivo influenza stimulation results in altered transcriptional response and is associated with time to delivery in cohort of women residing in an area with high preterm birth prevalence.Specific causes of preterm birth remain unclear. Several recent studies have suggested that immune changes during pregnancy are associated with the timing of delivery, yet few studies have been performed in low-income country settings where the rates of preterm birth are the highest. We conducted a retrospective nested case-control evaluation within a longitudinal study among HIV-uninfected pregnant Kenyan women. To characterize immune function in these women, we evaluated unstimulated and stimulated peripheral blood mononuclear cells  Preterm birth, defined as birth before the 37th week of gestation, is a highly prevalent disorder of pregnancy that is a major driver of childhood morbidity and mortality –4. PreteIncreasingly, attention has turned to the critical role the immune system plays in establishing and maintaining a healthy pregnancy . Changesin vitro  in a cohort of women in Kisumu, Kenya, an area with a high prevalence of preterm birth. We profiled immune function using RNA microarrays in peripheral blood mononuclear cell (PBMC) samples from pregnant women who were followed until birth. In order to identify perturbations in the ability of immune cells to respond to threats, PBMC samples were tested directly Mama Salama Study  and Kenyatta National Hospital, Nairobi, Kenya (KNH IRB P114/4/2010).The objective of this study was to identify associations between immune function and pregnancy outcomes (preterm birth and the time to delivery) in a setting of high prevalence of preterm birth. We used previously banked samples from a prospective cohort study of HIV-1 acquisition in pregnant and postpartum Kenyan women, the ma Study . The Mam6 cells/well. To each well, either PBS or influenza virus  was added at an MOI of 1 for 1 h, followed by the addition of serum-containing media for 6 additional hours at 37°C. Following incubation, cells were centrifuged, washed once with complete RPMI (200 uL/well), then resuspended in RNA lysis buffer (Qiagen). RNA was extracted from each well using the column-based RNeasy kit (Qiagen) according to the manufacturer's instructions. Purified RNA was quantified and characterized using a Nanodrop 3000. For samples with RNA Integrity Number > 6, RNA aliquots were submitted for microarray analysis  at the Stanford PAN Facility (http://pan.stanford.edu/index.html).PBMCs were purified in Kisumu, Kenya by Ficoll density gradient centrifugation and stored in liquid nitrogen before shipping to the University of Washington and subsequently to Stanford University. PBMCs were thawed rapidly in a 37°C water bath before dropwise addition of 1 mL of warm complete RPMI media (supplemented with 10% FBS and antibiotics) containing Benzonase (nuclease added to reduce cell clumping). The sample was transferred to a 50 ml conical tube containing an additional 9 mL of pre-warmed media with Benzonase. Cells were spun for 10 min at 400 × g, the supernatant was decanted, and the cell pellet was resuspended in 10 mL complete RPMI before cell counting using a BioRad TC20 cell counter. Cells were spun again for 10 min at 400 × g, the supernatant was removed, the cells were resuspended in RPMI media and were dispensed into a 96-well U bottom plate at 10oligo  algorithm implemented in R package oligo . We remo package . Finallylimma  was generated using the SuperScript VILO Master Mix Kit (Thermo Fisher 11755250) using the total RNA isolated from each PBMC sample. Quantitative polymerase chain reaction (qPCR) was performed using the Taqman Universal Master Mix II Kit with UNG (Thermo Fisher 4440044). Primers and probes were ordered as separate oligos through ElimBio  with added modification 5 -FAM/3 -BHQ-1 to the probes: IFNL Forward Primer 5′-ATC TGT CAC CTT CAA CCT CTT C-3′, IFNL reverse primer 5′-GTA GGG CTC AGC GCA TAA ATA-3′, IFNL Prober 5′-AAT ATG TGG CCG ATG GGA ACC TGT- 3′, Samples were run on the Thermo Fisher Scientific Step One Real-Time PCR System. All values were standardized to the constitutively expressed hypoxanthine phosphoribosyltransferase 1 (HPRT1) endogenous control (Thermo Fisher 4326321E) and relative mRNA expression levels were determined using the 2-ΔΔCT analysis method.MASS . In the analysis of samples stimulated with influenza virus, we detected 170 differentially expressed genes . We fitted a robust linear regression model. The robust fit yielded a https://github.com/ChristofSeiler/PTB_Study. The resulting reports can be found in the The entire analysis workflow is written in R markdown and available from our GitHub repository at Preterm birth is a major contributor to childhood morbidity and mortality worldwide, particularly in low income countries. Better understanding of the mechanisms underlying preterm birth may highlight pathways that could be therapeutically targeted to reduce the rates of preterm birth. One of the major challenges in identifying such mechanisms is the fact that several distinct pathways, including prior pregnancy history, infection, and genetic factors can contribute to preterm birth , 56. ManOur case control analyses did not reveal any transcripts that were significantly associated with preterm birth, but we hope the availability of this data will inform future studies. We did find that the magnitude of the influenza-induced IFN-lambda transcriptional response significantly decreased as delivery approaches, suggesting that such inflammatory pathways are influenced temporarily during pregnancy. Overall, these data highlight the heterogeneity in these pathways and the difficulty in identifying a single factor predictive of preterm birth. In fact, a prior meta-analysis highlighted the heterogeneity in preterm birth . This stMany aspects of immune function are altered during pregnancy to strike a balance between accommodating the semi-allogeneic fetus and protecting both mother and fetus from infection . These cOur finding that an entire transcriptional network of IFN-associated genes was temporally altered in pregnancy was consistent with the study by Aghaeepour and colleagues, in which they found multiple functional modules that were temporally altered during pregnancy, leading them to propose the idea of an “immune clock” . Both stOur study provides insight into potential immune mechanisms that could drive preterm birth, but did not identify a clear biomarker for preterm birth akin to the signature recently identified using analysis of cell-free DNA . In factThis study has several important limitations, the first of which is the relatively modest sample size and availability of good quality PBMC and RNA samples for these analyses. Particularly in light of the multiple distinct risk factors for preterm birth, which could be operating through distinct immune pathways, this definitely hinders our ability to find a clear signal. Another possible limitation was highlighted by a recent paper demonstrating that Affymetrix arrays were the least sensitive method to identify signatures associated with preterm birth in placental tissues . We hopeOverall, many risk factors for preterm birth are well-characterized, and many could drive preterm birth by inducing changes in immune function. Here we sought to identify specific immune pathways associated with preterm birth in women in a setting of high preterm birth prevalence in Kenya. While we did not identify a clear signature of preterm birth, we did find that the IFN response following a viral stimulation is temporally regulated during pregnancy, with reduced IFN induction as delivery approaches. This adds to our knowledge of immune regulation during pregnancy, but more study is clearly needed to further understand this complex immunologic time.GSE140939.The datasets generated for this study can be found in the Gene Expression Omnibus (GEO) under accession numbers All subjects gave informed and written consent. All studies were performed in accordance with the Declaration of Helsinki, and all study procedures were approved by the Institutional Review Boards of the University of Washington, Seattle, WA, USA and Kenyatta National Hospital, Nairobi, Kenya.NB, GJ-S, and CB conceptualized this study. JP, JK, LO, DM, BR, and GJ-S developed and maintained the cohort. NB and CB designed experiments. NB and RV conducted experiments. CS, NB, RV, JP, BR, and SH analyzed the data. CS, NB, and CB wrote the manuscript. All authors contributed to revisions and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Preterm birth is the leading cause of death worldwide in children under five years. Due to its complex multifactorial nature, prediction is a challenge. Current research is aiming to develop accurate predictive models using patient history, ultrasound and biochemical markers. Volatile organic compound (VOC) analysis is an approach, which has good diagnostic potential to predict many disease states. Analysis of VOCs can reflect both the microbiome and host response to a condition. We aimed to ascertain if VOC analysis of vaginal swabs, taken throughout pregnancy, could predict which women go on to deliver preterm. Our prospective observational cohort study demonstrates that VOC analysis of vaginal swabs, taken in the midtrimester, is a fair test (AUC 0.79) for preterm prediction, with a sensitivity of 0.66 (95%CI 0.56–0.75) and specificity 0.89 (95%CI 0.82–0.94). Using vaginal swabs taken closest to delivery, VOC analysis is a good test (AUC 0.84) for the prediction of preterm birth with a sensitivity of 0.73 (95%CI 0.64–0.81) and specificity of 0.90 (95%CI 0.82–0.95). Consequently, VOC analysis of vaginal swabs has potential to be used as a predictive tool. With further work it could be considered as an additional component in models for predicting preterm birth. Spontaneous preterm birth is a syndrome, which can be precipitated by a variety of factors (or combination of these) including; infection, inflammation, vascular disease and uterine overdistention2. The multifactorial complex nature of spontaneous preterm birth makes its prediction a challenge. A number of factors are needed to activate one or more of the common pathways required for myometrial contractions leading to the premature onset of labour, these include a maternal susceptibility, and an infective, inflammatory, ischaemic or mechanical (over distention) insult3. Increasingly research is being carried out to try to improve the predictive value of various tests for preterm birth, including the development of prognostic models that account for both the maternal susceptibility and the insult, using patient history, ultrasound findings and biomarkers8. First, this aims to enable earlier interventions to facilitate targeted prevention strategies. Secondly to permit better prediction of those patients whom will deliver preterm, to assist in timely administration of treatments to optimise neonatal outcomes, whilst reducing their unnecessary administration as they are not without ramifications10.Globally, preterm birth is the leading cause of death in children under 5 years with 15 million babies being born before 37 weeks’ gestation each year11. Its presence, detected in early pregnancy is associated with an increased risk of preterm labour11. Despite this, treatment of BV with antibiotics has not been demonstrated to prevent preterm birth as demonstrated by a recent randomised controlled trial (RCT) and a preceding systematic review and meta-analysis13. However, this trial focused on the low risk population for spontaneous preterm birth,12 and the meta-analysis had substantial heterogeneity (I2 = 48%)13, therefore treatment of the high risk population for BV with antibiotics to reduce the risk of preterm birth could warrant further investigation due to numerous factors contributing to the onset of preterm labour in a susceptible individual.The association between bacterial vaginosis (BV) detected using laboratory techniques and preterm labour has been recognised for many years11. More recently molecular-based technologies have allowed for the description of the bacterial component of the vaginal microbiome. These molecular-based techniques have found that a vaginal microbiome with reduced Lactobacillus spp. abundance and increased bacterial diversity is associated with preterm delivery18 and that this can be detected prior to the onset of symptoms14.A characteristic of bacterial vaginosis is a lack of lactobacilli and an increase in other organisms23, sexual activity25 and hygiene practices26.The mutualistic association between the vagina and the microbiota is a fine balance under the influence of many factors, including sex steroid hormones29, cancers31, sepsis32 and diabetes33. With recent developments in VOC detection and analysis technology it now has the potential to be realistically translated into clinical practice.Volatile organic compound (VOC) analysis is a technique to monitor microbiota and its metabolic activity, providing insight into the interactions between microbiota and their host. It provides a non-invasive and potentially rapid means to monitor the microbiota and host response. In recent years, VOCs have been demonstrated as a non-invasive diagnostic biomarkers for several diseases including inflammatory bowel disease34. Thus, for the prediction of preterm labour, a test that both detects differences in the vaginal flora and the host epithelial response to these differences could be clinically useful.In some cases preterm labour is thought to be the result of both vaginal flora and host response to this flora36. However, much of the previous VOC detection and analysis work deployed instruments which had several limitations for the clinical setting including the need for excessive training, substantial costs, significant data analysis, and concerns with reproducibility of results, consequently these instruments were not amenable to become a rapid point of care test at that time37. In our study we aimed to build on this work and assess whether novel VOC technology could detect BV and thus reflect vaginal flora. We aimed to identify if specific patterns of VOCs from vaginal swabs taken in pregnancy, were associated with preterm delivery in a population of pregnant women attending a preterm prevention clinic due to pre-existing risk factors for preterm birth using VOC detection and analysis technology involving machine learning, which with development has the potential to be translated into clinical practice and overcome the previously discussed concerns.Previous studies have demonstrated promise for the diagnosis of BV using VOC technologyth January 2014 and sponsored by the University of Warwick. Approval from University Hospitals Coventry & Warwickshire Research & Development was acquired on 17th January 2014. All participants gave written informed consent. The study was funded by the Biomedical Research Unit in Reproductive Health, University of Warwick. Research was carried out according to The Code of Ethics of the World Medical Association (Declaration of Helsinki).The study was approved by the NHS Research Ethics Committee West Midlands Birmingham South on 14The population was a prospective observational cohort of repeated sampling of 216 patients between weeks 10–29 of pregnancy , from women attending the high-risk preterm prevention clinic at a tertiary level teaching hospital from January 2017-August 2018. Women were excluded from analysis relating to preterm delivery if they required iatrogenic preterm delivery (n = 11) or delivery data were not available (n = 9). This left a remaining cohort of 196 women with spontaneous onset of labour at a known gestation. Demographic data including age at booking pregnancy, BMI, ethnicity, smoking status and indication for attendance to the preterm prevention clinic were collected about each woman . Others, for example those caused by poor placental function or uterine anomalies are unlikely to be predicted using this test. The AUCs are good for the clinical context in prediction of spontaneous preterm birth in high risk asymptomatic women with the first swabs taken in the second trimester (AUC of 0.79), which improved in the last swabs taken closest to delivery (AUC 0.84). Of importance is that VOCs had a positive predictive value of up to 86% even when sampled 10–24 weeks before the event. This raises the possibility of using VOCs to develop a personalised approach to preterm labour prevention as there is plenty of time between the test and delivery to introduce preventative measures in susceptible individuals. Again, as expected, the nearer to delivery that the swab was taken the better the predictive performance and indeed the second swab taken 3–21 weeks before delivery had negative predictive value of up to 88% which could be useful clinically for planning location of delivery.39. Nearly two thirds of women who had a positive swab for BV, despite treatment went on to deliver preterm, supporting the previous studies that BV is associated with an increased risk of preterm birth but treatment for BV in pregnancy does not reduce the risk of preterm delivery13. Future risk stratification using VOCs could include these variables as has been done successfully by others40.In our population, the indication for attendance to the preterm prevention clinic varied between those who delivered preterm or delivered at term. As expected, there was a higher proportion of those with a high-risk risk factor (previous second trimester loss) who went on to deliver preterm and higher proportion of those with an intermediate-risk risk factor  who went on to deliver at term40. VOCs have potential benefits, in addition to the existing published model for several reasons. Firstly because of the physiological difference between the tests. Quantitative fetal fibronectin is thought to detect inflammation of fetal membranes and together with the cervical length and clinical risk factors in the QUiPP App perhaps suggest cerclage or pessary to preterm prevention40. In contrast the VOCs test is thought to detect a combination of the vaginal microbiome and the maternal response hence suggesting treatment to restore the vaginal flora41 and reduce the maternal response to this flora perhaps with progesterone44. Secondly, quantitative fetal fibronectin is limited by the gestation at which it can be measured, after 22 weeks, this is not a limitation that applied to VOCs. Thirdly VOC analysis is likely to be a cheaper test requiring the purchase of a machine then using usual hospital swabs in the sensor rather than having to buy cassettes containing chemical assays per swab. We suggest that the addition VOC analysis to existing models could lead to the development of a test that is the basis of a personalised approach to preterm labour prevention. Much more work is needed to determine the use of VOCs in this field. We plan to compare our VOC analysis to the vaginal microbiome and determine if specific VOCs correlate with bacterial communities.More recently cervical length measurement, quantitative fetal fibronectin and clinical factors have been combined and developed into a predictive model for preterm birth in asymptomatic women. This work has demonstrated that spontaneous preterm both can be accurately predicted with AUC values ranging from 0.75 to 0.9045, supporting the chances that the VOCs detected on our swabs could be similar from the midtrimester onwards. However, this is making the presumption that the host isn’t changing and influencing the VOCs produced. Steroid hormones are known to change throughout pregnancy, they could influence VOCs, which reflect interactions between the microbiome and the host.At this point in time, we do not have the specific biomarkers that resulted in these differences. Furthermore, we do not have any data about how individual patients vaginal VOCs change throughout gestation. In future studies we are planning to collect and analyse swabs throughout pregnancy and closer to delivery and undertake a deeper VOC analyses to understand how these specific VOCs change. Recent work on the vaginal microbiome after 20 weeks gestation has demonstrated the microbiome diversity in both women who deliver preterm and term converges and remains stable for the remaining weeks of pregnancyIn conclusion, this novel work has demonstrated that VOC analysis has the potential to be used as a predictive tool to support the prediction of preterm birth and aid personalised prevention strategies. In the future this could be considered as an additional component to be utilised in models to help solve the multifactorial complex problem of accurate prediction and prevention of preterm delivery.A speculum examination was performed and a vaginal swab taken for microbiology culture and sensitivity testing and for examination under the microscope using the Hay/Ison criteria. This was placed into a nonnutritive transport medium as per routine care. Concurrently, two cotton swabs were used to obtain index test vaginal samples for VOC analysis. The index test swabs were then placed in a universal containers and snap frozen in liquid nitrogen and stored at − 80 °C. Specimens were obtained by gently rotating the swabs across the mucosa of the vagina. Samples were taken in a consecutive series from all women who consented in the clinic, some women consented to samples being taken during every attendance to the clinic.Swabs were analysed to first to assess whether VOCs could detect BV. Subsequently, the first swab, taken at the earliest gestation per patient was analysed using VOC detection technology to identify if specific VOC patterns could be detected in those who went on to deliver preterm (before 37 + 0 weeks gestation). Then the swab taken closest to delivery per patient was analysed using VOC detection technology to identify if specific VOC patterns predicted preterm birth.47. In brief, the GC front end is used to pre-separate molecules based on their interaction with a stationary phase coating on a long column, eluding from the column at different times. These molecules are then ionized (in our case with a tritium sounce) and enter a drift tube IMS. Here, the ions are pushed through a tube by applying an electric field and detected as they exit the tube. Against the flow of sample ions, a buffer gas is pushed through the tube in the opposite direction to the ions. In general, large sample molecules were struck many times and slowed down, whilst smaller sample molecules were struck less and kept their momentum. Therefore, drift time is a function of the interaction between the electric field the buffer gas and the ions. This instrument was chosen over more traditional GCMS, as the basic sensitivity of the instrument is much higher, it can use nitrogen as the carrier gas (so no expensive gas such as helium), has a lower unit cost than GCMS and has a smaller form factor, thus has the potential to be used on a ward setting. However, a limitation of this setup was that we were unable to identify specific VOC biomarkers. Thus, the output of the instrument was analysed using a pattern recognition technique.For chemical vapour analysis, index swabs were shipped to the BioMedical Sensors Laboratory, School of Engineering, University of Warwick. The odours/VOCs emanating from the samples were analysised using G.A.S. GC-IMS instrument , which is based on Gas Chromatograph – Ion Mobility Spectrometery principles (GC-IMS). This is a highly sensitive odour detection technology that has been previously used by our group in clinical studies analysing a range of biological samplesSamples were shipped from University Hospitals Coventry and Warwickshire to Warwick University on dry-ice and briefly stored at − 20 °C before testing. Sample preparation comprised of thawing the swab at 4 °C and transferring it to a 20 ml gas vial, which is subsequently sealed with a crimp top lid fitted with a PTFE septum. Prior to measurement samples were heated to 40 °C for 10 min. The sample line for the GC-IMS was inserted into the septa of the vial using a needle and 2 ml of sample was pulled into the analytical platform. The machine settings were as follows: E1: 150 ml/min (for the drift tube IMS), E2: 20 ml/min (for the GC column) and the pump at 25% total power. The total run time was 10 min. The temperatures were set to: T1: 45 °C, T2: 80 °C, and T3: 70 °C.p value were taken forward for classification. Then, two different classifiers, specifically Random Forest and Gaussian process, were applied. These have previously been found to be good classifiers for GC-IMS data47. Once the training models have been created, they were applied to the same features in the test set. This process is repeated ten times until all the data has a test result. Utilising this method, we needed to have the same number of index test positive and negative samples, negative samples were chosen at random. This process provided test probabilities for each sample and from this, statistical values, including sensitivity and specificity were calculated.For data analysis, the data was first extracted from the native file format to a text file using the L.A.V. Software . Then dimentional reduction steps were used to decrease the number of datapoints and remove the backgound. This is undertaken as the data has high dimensionality , but low information content, with the majority of the data located in the centre of the output .Supplementary Information 1.Supplementary Information 2.