scholarly journals Nomogram to Early Screen Multiparous Women for Preterm Birth in a Cohort Study

2021 ◽  
Vol 15 ◽  
pp. 135-141
Author(s):  
Mayssa A. Traboulsi ◽  
Zainab. El Alaoui Talibi ◽  
Abdellatif Boussaid
Keyword(s):  
Cohort Study ◽  
Preterm Birth ◽  
Low Income ◽  
Health Indicators ◽  
Penalized Regression ◽  
Low Income Countries ◽  
Medical Surveillance ◽  
Spontaneous Preterm Birth ◽  
Multiparous Women ◽  
Low Prevalence

Preterm Birth (PTB) can negatively affect the health of mothers as well as infants. Prediction of this gynecological complication remains difficult especially in Middle and Low-Income countries because of limited access to specific tests and data collection scarcity. Machine learning methods have been used to predict PTB but the low prevalence of this pregnancy complication led to rather low prediction values. The objective of this study was to produce a nomogram based on improved prediction for low prevalence PTB using up sampling and lasso penalized regression. We used data from a cohort study in Northern Lebanon of 922 multiparous presenting a PTB prevalence of 8%. We analyzed the personal, demographic, and health indicators available for this group of women. The improved Positive Predictive Value for PTB reached around 88%. The regression coefficients of the 6 selected variables (Pre-hemorrhage, Social status, Residence, Age, BMI, and Weight gain) were used to create a nomogram to screen multiparous women for PTB risk. The nomogram based on readily available indicators for multiparous women reasonably predicted most of the at PTB risk women. The physicians can use this tool to screen for women at high risk for spontaneous preterm birth to improve medical surveillance that can reduce PTB incidence.

scholarly journals Nomogram to Early Screen Multiparous Women for Preterm Birth in a Cohort Study

2020 ◽  
Author(s):  
Mayssa Traboulsi ◽  
Zainab El Alaoui Talibi ◽  
Abdellatif Boussaid
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Preterm Birth ◽  
Regression Model ◽  
Low Income ◽  
Logistic Regression Model ◽  
Penalized Regression ◽  
Low Income Countries ◽  
Nulliparous Women ◽  
Multiparous Women

Abstract Background: Preterm Birth (PTB) can negatively affect the health of mothers as well as infants. Prediction of this gynecological complication remains difficult especially in Middle and Low-Income countries because of limited access to specific tests and data collection scarcity. Multiparous women in our study presented a higher PTB prevalence compared to nulliparous women. Methods: In a cohort study from Northern Lebanon of 1996 women, 922 were multiparous presenting a PTB prevalence of 8%. We analyzed the personal, demographic, and health indicators available for this group of women. We compared 4 modified logistic regression models (up-sampling, lasso penalized regression) to develop a nomogram that can screen for preterm in multi-parous women. The models were trained and validated on different data sets.Results: The best PTB prediction of the Logistic regression model reached around 88%. This was obtained using a Logistic Regression Model trained on up-sampled datasets and LASSO (Least Absolute Shrinkage and Selection Operator) penalized. The regression coefficients of the 6 selected variables (Pre-hemorrhage, Social status, Residence, Age, BMI, and Weight gain) were used to create a nomogram to screen multiparous women for PTB risk. Conclusions: The nomogram based on readily available indicators for multiparous women reasonably predicted most of the at PTB risk women. This tool will allow physicians to screen women that represent a high risk for spontaneous preterm birth and run furthermore adequate additional tests leading to better medical surveillance that can reduce PTB incidence.

scholarly journals Nomogram to Early Screen Multiparous Women for Preterm Birth in a Cohort Study

2020 ◽  
Author(s):  
Mayssa Traboulsi ◽  
Zainab E. El Alaoui- Talibi ◽  
Abdellatif Boussaid
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Preterm Birth ◽  
Regression Model ◽  
Low Income ◽  
Logistic Regression Model ◽  
Penalized Regression ◽  
Low Income Countries ◽  
Nulliparous Women ◽  
Multiparous Women

Abstract Background: Preterm Birth (PTB) can negatively affect the health of mothers as well as infants. Prediction of this gynecological complication remains difficult especially in Middle and Low-Income countries because of limited access to specific tests and data collection scarcity. Multiparous women in our study presented a higher PTB prevalence compared to nulliparous women. Methods: In a cohort study from Northern Lebanon of 1996 women, 922 were multiparous presenting a PTB prevalence of 8%. We analyzed the personal, demographic, and health indicators available for this group of women. We compared 4 modified logistic regression models (up-sampling, lasso penalized regression) to develop a nomogram that can screen for preterm in multi-parous women. The models were validated on a separate set of data.Results: The best PTB prediction of the Logistic regression model reached around 88%. This was obtained using a Logistic Regression Model trained on up-sampled datasets and LASSO (Least Absolute Shrinkage and Selection Operator) penalized. The regression coefficients of the 6 selected variables (Pre-hemorrhage, Social status, Residence, Age, BMI, and Weight gain) were used to create a nomogram to screen multiparous women for PTB risk. Conclusions: The nomogram based on readily available indicators for multiparous women reasonably predicted most of the at PTB risk women. This tool will allow physicians to screen women and run furthermore adequate additional tests leading to better medical surveillance that can reduce PTB incidence.

scholarly journals Phenotypic Classification of preterm Birth Among Multiparous Women: A Population-Based Cohort Study

2019 ◽  
Vol 41 (10) ◽  
pp. 1433-1443.e12
Author(s):  
Siavash Maghsoudlou ◽  
Joseph Beyene ◽  
Zhijie Michael Yu ◽  
Sarah D. McDonald
Keyword(s):  
Cohort Study ◽  
Preterm Birth ◽  
Population Based ◽  
Multiparous Women ◽  
Phenotypic Classification

Effectiveness of the Bactiseal Universal Shunt for reducing shunt infection in a sub-Saharan African context: a retrospective cohort study in 160 Ugandan children

2014 ◽  
Vol 13 (2) ◽  
pp. 140-144 ◽  
Author(s):  
Jordan D. Lane ◽  
John Mugamba ◽  
Peter Ssenyonga ◽  
Benjamin C. Warf
Keyword(s):  
Cohort Study ◽  
Low Income ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Shunt Infection ◽  
Low Income Countries ◽  
Rank Test ◽  
Log Rank Test ◽  
Significant Difference ◽  
Chi Square Analysis

Object Antibiotic-impregnated shunts have yet to find widespread use in the developing world, largely due to cost. Given potential differences in the microbial spectrum, their effectiveness in preventing shunt infection for populations in low-income countries may differ and has not been demonstrated. This study is the first to compare the efficacy of a Bactiseal shunt system with a non–antibiotic-impregnated system in a developing country. Methods The Bactiseal Universal Shunt (BUS) was placed in 80 consecutive Ugandan children who required a shunt. In this retrospective cohort study, the outcome for that group was compared with the outcome for the immediately preceding 80 consecutive children in whom a Chhabra shunt had been placed. The primary end points were shunt failure, shunt infection, and death. Shunt survival was analyzed using the Kaplan-Meier method. Significance of differences between groups was tested using the log-rank test, chi-square analysis, Fisher's exact test, and t-test. Results There was no difference between groups in regard to age, sex, or etiology of hydrocephalus. Mean follow-up for cases of nonfailure was 7.6 months (median 7.8 months, interquartile range 6.5–9.5 months). There was no significant difference between groups for any end point. The BUS group had fewer infections (4 vs 11), but the difference was not significant (p = 0.086, log-rank test). Gram-positive cocci were the most common culturable pathogens in the Chhabra group, while the only positive culture in the BUS group was a gram-negative rod. Conclusions These results provide equipoise for a randomized controlled trial in the same population and this has been initiated. It is possible that the observed trends may become significant in a larger study. The more complex task will involve determining not only the efficacy, but also the cost-effectiveness of using antibiotic-impregnated shunt components in limited-resource settings.

scholarly journals Global Surgery, Obstetric, and Anesthesia Indicator Definitions and Reporting: An Utstein Consensus Report

2021 ◽  
Author(s):  
Justine Ina Davies ◽  
Adrian W. Gelb ◽  
Julian Gore-Booth ◽  
Janet Martin ◽  
Jannicke Mellin-Olsen ◽  
...  
Keyword(s):  
Low Income ◽  
Data Science ◽  
Health Indicators ◽  
Obstetric Care ◽  
Global Surgery ◽  
Low Income Countries ◽  
Financial Risk Protection ◽  
Current Time ◽  
Timely Access ◽  
Data Points

Background Indicators to evaluate progress towards timely access to safe surgical, anaesthesia, and obstetric (SAO) care were proposed in 2015 by the Lancet Commission on Global Surgery. Despite being rapidly taken up by practitioners, datapoints from which to derive them were not defined, limiting comparability across time or settings. We convened global experts to evaluate and explicitly define - for the first time - the indicators to improve comparability and support achievement of 2030 goals to improve access to safe affordable surgical and anaesthesia care. Methods and findings The Utstein process for developing and reporting guidelines through a consensus building process was followed. In-person discussions at a two day meeting were followed by an iterative process conducted by email and virtual group meetings until consensus was reached. Participants consisted of experts in surgery, anaesthesia, and obstetric care, data science, and health indicators from high, middle, and low income countries. Considering each of the six indicators in turn, we refined overarching descriptions and agreed upon data points needed for construction of each indicator at current time (basic data points), and as each evolves over 2-5 (intermediate) and >5 year (full) timeframes. We removed one of the original six indicators (one of two financial risk protection indicators was eliminated) and refined descriptions and defined data points required to construct the 5 remaining indicators: geospatial access, workforce, surgical volume, perioperative mortality, and catastrophic expenditure. Conclusions To track global progress toward timely access to quality SAO care, these indicators – at the basic level - should be implemented universally. Intermediate and full evolutions will assist in developing national surgical plans, and collecting data for research studies.

scholarly journals Accelerated Fetal Growth in Early Pregnancy and Risk of Preterm Birth: A Prospective Cohort Study

2020 ◽  
Author(s):  
Evangelia Elenis ◽  
Anna-Karin Wikström ◽  
Marija Simic
Keyword(s):  
Cohort Study ◽  
Preterm Birth ◽  
Prospective Cohort Study ◽  
Fetal Growth ◽  
Early Pregnancy ◽  
Prospective Cohort ◽  
Late Gestation ◽  
Second Trimester ◽  
Spontaneous Preterm Birth ◽  
Increased Risk

Abstract Background: Preterm birth (occurring before 37 completed weeks of gestation) affects 15 million infants annually, 7.5% of which die due to related complications. The detection and early diagnosis are therefore paramount in order to prevent the development of prematurity and its consequences. So far, focus has been laid on the association between reduced intrauterine fetal growth during late gestation and prematurity. The aim of the current study was to investigate the association between accelerated fetal growth in early pregnancy and the risk of preterm birth. Methods: This prospective cohort study included 69 617 singleton pregnancies without congenital malformations and with available biometric measurements during the first and second trimester. Estimation of fetal growth was based on measurements of biparietal diameter (BPD) at first and second trimester scan. We investigated the association between accelerated fetal growth and preterm birth prior to 37 weeks of gestation. The outcome was further stratified into very preterm birth (before 32 weeks of gestation) or moderate preterm birth (between 32 and 37 weeks of gestation) and medically induced or spontaneous preterm birth and was further explored. Results: The odds of prematurity were increased among fetuses with accelerated BPD growth (> 90th centile) estimated between first and second ultrasound scan, even after adjustment for possible confounders (aOR 1.36; 95% CI 1.20-1.54). The findings remained significant what regards moderate preterm births but not earlier births. Regarding medically induced preterm birth, the odds were found to be elevated in the group of fetuses with accelerated growth in early pregnancy (aOR 1.34; 95% CI 1.11-1.63). On the contrary, fetuses with delayed fetal growth exhibited lower risk for both overall and spontaneous preterm birth.Conclusions: Fetuses with accelerated BPD growth in early pregnancy, detected by ultrasound examination during the second trimester, exhibited increased risk of being born preterm. The findings of the current study suggest that fetal growth in early pregnancy should be taken into account when assessing the likelihood for preterm birth.

scholarly journals Time trends and sociodemographic determinants of preterm births in pregnancy cohorts in Matlab, Bangladesh, 1990–2014

2019 ◽  
Vol 4 (4) ◽  
pp. e001462 ◽  
Author(s):  
Anisur Rahman ◽  
Monjur Rahman ◽  
Jesmin Pervin ◽  
Abdur Razzaque ◽  
Shaki Aktar ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Preterm Birth ◽  
Low Income ◽  
Time Trends ◽  
Maternal Education ◽  
Preterm Births ◽  
Population Based ◽  
Low Income Countries ◽  
Sociodemographic Determinants ◽  
Gestational Age At Birth

IntroductionPreterm birth is the major cause of under-five mortality. Population-based data on determinants and proportions of children born preterm are limited, especially from low-income countries. This study aimed at assessing time trends and social, reproductive and environmental determinants of preterm births based on a population-based pregnancy cohort over 25 years in rural Bangladesh.MethodsIn this cohort study in Matlab, a rural area in Bangladesh, we used data from the Health and Demographic Surveillance System from 1990 to 2014. Gestational age at birth was based on the reported last menstrual period and verified by ultrasound assessments. Preterm birth proportions were assessed within strata of social and reproductive characteristics, and time series analysis was performed with decomposition for trend and seasonality. We also determined the prevented fractions of preterm birth reduction associated with social and demographic changes during the follow-up period.ResultsAnalyses were based on 63 063 live births. Preterm birth decreased from 29% (95% CI 28.6 to 30.1) in 1990–1994 to 11% (95% CI 10.5 to 11.6) in 2010–2014. Low education, older age and multi-parity were associated with higher proportions of preterm births across the study period. Preterm births had a marked seasonal variation. A rapid increase in women’s educational level and decrease in parity were associated with the decline in preterm births, and 27% of the reduction observed from 1990 to 2014 could be attributed to these educational and reproductive changes.ConclusionThe reduction in preterm birth was to a large extent associated with the sociodemographic transition, especially changes in maternal education and parity. The persistent seasonal variation in the proportion of preterm birth may reflect the environmental stressors for pregnant women across the study period. Continued investments in girls’ education and family planning programmes may contribute to further reduction of preterm births in Bangladesh.

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