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 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 Lasting s-ketamine block of spreading depolarizations in subarachnoid hemorrhage: a retrospective cohort study

Critical Care ◽  
2019 ◽  
Vol 23 (1) ◽  
Author(s):  
Edgar Santos ◽  
Arturo Olivares-Rivera ◽  
Sebastian Major ◽  
Renán Sánchez-Porras ◽  
Lorenz Uhlmann ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Subarachnoid Hemorrhage ◽  
Regression Model ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Logistic Regression Model ◽  
Poisson Model ◽  
High Dose ◽  
First Line

Abstract Objective Spreading depolarizations (SD) are characterized by breakdown of transmembrane ion gradients and excitotoxicity. Experimentally, N-methyl-d-aspartate receptor (NMDAR) antagonists block a majority of SDs. In many hospitals, the NMDAR antagonist s-ketamine and the GABAA agonist midazolam represent the current second-line combination treatment to sedate patients with devastating cerebral injuries. A pressing clinical question is whether this option should become first-line in sedation-requiring individuals in whom SDs are detected, yet the s-ketamine dose necessary to adequately inhibit SDs is unknown. Moreover, use-dependent tolerance could be a problem for SD inhibition in the clinic. Methods We performed a retrospective cohort study of 66 patients with aneurysmal subarachnoid hemorrhage (aSAH) from a prospectively collected database. Thirty-three of 66 patients received s-ketamine during electrocorticographic neuromonitoring of SDs in neurointensive care. The decision to give s-ketamine was dependent on the need for stronger sedation, so it was expected that patients receiving s-ketamine would have a worse clinical outcome. Results S-ketamine application started 4.2 ± 3.5 days after aSAH. The mean dose was 2.8 ± 1.4 mg/kg body weight (BW)/h and thus higher than the dose recommended for sedation. First, patients were divided according to whether they received s-ketamine at any time or not. No significant difference in SD counts was found between groups (negative binomial model using the SD count per patient as outcome variable, p = 0.288). This most likely resulted from the fact that 368 SDs had already occurred in the s-ketamine group before s-ketamine was given. However, in patients receiving s-ketamine, we found a significant decrease in SD incidence when s-ketamine was started (Poisson model with a random intercept for patient, coefficient − 1.83 (95% confidence intervals − 2.17; − 1.50), p < 0.001; logistic regression model, odds ratio (OR) 0.13 (0.08; 0.19), p < 0.001). Thereafter, data was further divided into low-dose (0.1–2.0 mg/kg BW/h) and high-dose (2.1–7.0 mg/kg/h) segments. High-dose s-ketamine resulted in further significant decrease in SD incidence (Poisson model, − 1.10 (− 1.71; − 0.49), p < 0.001; logistic regression model, OR 0.33 (0.17; 0.63), p < 0.001). There was little evidence of SD tolerance to long-term s-ketamine sedation through 5 days. Conclusions These results provide a foundation for a multicenter, neuromonitoring-guided, proof-of-concept trial of ketamine and midazolam as a first-line sedative regime.

scholarly journals Association between maternal ritodrine hydrochloride administration during pregnancy and childhood wheezing up to three years of age: The Japan Environment and Children’s Study

2021 ◽  
Author(s):  
Tsuyoshi Murata ◽  
Hyo Kyozuka ◽  
Shun Yasuda ◽  
Toma Fukuda ◽  
Akiko Yamaguchi ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Regression Model ◽  
Birth Cohort ◽  
Logistic Regression Model ◽  
Preterm Births ◽  
Birth Cohort Study ◽  
Odds Ratios ◽  
Ritodrine Hydrochloride ◽  
Term Births

Background: The effects of maternal ritodrine hydrochloride administration (MRA) during pregnancy on fetuses and offspring are not entirely clear. The present study aimed to evaluate the association between MRA and childhood wheezing using data from a nationwide Japanese birth cohort study. Methods: This study retrospectively analyzed data from the Japan Environment and Children’s Study, a nationwide birth cohort study, conducted between 2011 and 2014. Data of women with singleton births after 22 weeks of gestation were analyzed. The participants were divided according to MRA status. Considering childhood factors affecting the incidence of wheezing, a logistic regression model was used to calculate adjusted odds ratios for “wheezing ever,” diagnosis of asthma in the last 12 months, and “asthma ever” in women with MRA, with women who did not receive MRA as the reference. Participants were stratified by term births, and adjusted odds ratios for outcomes were calculated using a logistic regression model. Results: A total of 68,123 participants were analyzed. The adjusted odds ratio for wheezing ever was 1.17 (95% confidence interval, 1.12–1.22). The adjusted odds ratios for the other outcomes did not significantly increase after adjusting for childhood factors. The same tendency was confirmed after excluding women with preterm births. Conclusion: MRA was associated with an increased incidence of childhood wheezing up to three years, irrespective of term births or preterm births. It is important that perinatal physicians consider both the adverse maternal side effects of MRA and its potential effects on the offspring’s childhood.

Perfluoroalkyl Substances Exposure in Early Pregnancy and Preterm Birth in Singleton Pregnancies: A Prospective Cohort Study

2019 ◽  
Author(s):  
Xiaona Huo ◽  
Lin Zhang ◽  
Rong Huang ◽  
Liping Feng ◽  
Weiye Wang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Preterm Birth ◽  
Regression Model ◽  
Prospective Cohort Study ◽  
Early Pregnancy ◽  
Prospective Cohort ◽  
Maternal Plasma ◽  
Perfluoroalkyl Substances ◽  
Duration Of Gestation

Abstract Background: Preterm birth (PTB, < 37 completed weeks’ gestation) is one of the global public health concerns. Epidemiologic evidence on the potential impact of perfluoroalkyl substances (PFAS) on PTB is still limited and inconsistent. We aimed to investigate the associations between prenatal PFAS exposure and PTB among singleton live births. Methods: We studied 2849 mother-infant pairs in the Shanghai Birth Cohort (SBC) from 2013 to 2016. Ten PFAS in maternal plasma in early pregnancy were measured. Primary outcomes were duration of gestation, PTB, spontaneous PTB and clinically indicated PTB. A linear regression model was used to assess the associations between ln-transformed PFAS and duration of gestation (weeks). A logistic regression model was applied to estimate the risks of these outcomes within a ln-transformed continuous PFAS concentrations and across non-transformed quartiles of PFAS concentrations. A Cox proportional hazards model was also used to examine the associations by treating PFAS as continuous ln-transformed variables. Results: The incidence of overall PTB was 4.8% (95% confidence limit: 4.0% - 5.6%) in this study population. In the linear logistic regression analyses, PFAS were not associated with duration of gestation after controlling for potential confounders. In the multiple logistic model and Cox model analyses, no significant associations were observed between PFAS and overall PTB, spontaneous PTB or indicated PTB. Conclusion: Our prospective cohort study shows that maternal plasma PFAS concentrations in early pregnancy was not associated with gestational length, overall PTB, spontaneous PTB or indicated PTB.

scholarly journals Factors Influencing Children’s Regular Attendance at Dental Clinics in Al Madinah, Saudi Arabia

2021 ◽  
pp. 1-7
Author(s):  
Amal Aqeeli ◽  
Alla T. Alsharif ◽  
Estie Kruger ◽  
Marc Tennant
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Low Income ◽  
Logistic Regression Model ◽  
Family Income ◽  
Middle Income ◽  
Dental Visits ◽  
Dental Clinics ◽  
Behavioral Variables ◽  
Stratified Sample

<b><i>Objectives:</i></b> This study aimed to investigate sociodemographic, clinical, and behavioral characteristics of 9- to 12-year-old schoolchildren who attend regular dental visits. <b><i>Methods:</i></b> A stratified sample from 10 schools in Al Madinah, SA, was selected, and a total of 1,000 students aged 9–12 years were included in the study. The WHO criteria (2013) for assessing dental caries were used to collect clinical data, and information on dental visits and sociodemographic and behavioral variables was collected through the WHO questionnaire. The logistic regression model was used to examine the relationship between regular dental visits and sociodemographic, clinical, and behavioral factors. <b><i>Results:</i></b> Only 9.2% of the sample reported regular dental visits. The multiple logistic regression model showed that gender (female: OR = 1.715; <i>p</i> = 0.041), high family income (middle income: OR = 0.464; <i>p</i> = 0.024; and low income: OR = 0.517; <i>p</i> = 0.015), and the consumption of sugary food and drinks (almost daily: OR = 0.438; <i>p</i> = 0.017; and several times a week: OR = 0.511; <i>p</i> = 0.050) were associated with regular dental visits after accounting for other sociodemographic and clinical variables and other oral health behavior. <b><i>Conclusion:</i></b> In the population studied, &#x3c;10% of 9- to 12-year-olds made regular annual visits to dental clinics in Al Madinah, SA.

scholarly journals Routine Adoption of Urinary [IGFBP7]∙[TIMP-2] to Assess Acute Kidney Injury at Any Stage 12 hours After Intensive Care Unit Admission: a Prospective Cohort Study

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Fiorenza Ferrari ◽  
Gregorio Romero-González ◽  
Lilia Rizo Topete ◽  
Mara Senzolo ◽  
Anna Lorenzin ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Cohort Study ◽  
Regression Model ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Logistic Regression Model ◽  
Characteristic Curve ◽  
Kidney Injury ◽  
Patient Characteristics

Abstract The urinary tissue inhibitor of metalloproteinases-2 and insulin-like growth factor-binding protein 7 ([TIMP-2]∙[IGFBP7]) have been introduced to improve risk prediction of severe acute kidney injury (AKI) within 12 hours of measurement. We performed a prospective cohort study to evaluate if the predictive value of [TIMP-2]∙[IGFBP7] for AKI might continue after 12 hours. We enrolled 442 critically ill adult patients from June to December 2016. Urine samples were collected at admission for [TIMP-2]∙[IGFBP7] measurement. Baseline patient characteristics were recorded including patients’ demographics, prior health history, and the main reason for admission to build a logistic regression model to predict AKI. AKI occurrence differed between patients with [TIMP-2]∙[IGFBP7] ≤0.3 and >0.3 (ng/ml)2/1000 (31.9% and 68.10% respectively; p < 0.001). Patients with AKI had higher biomarker values compared to those without AKI (0.66 (0.21–2.84) vs 0.22 (0.08–0.63) (ng/ml)2/1000; p < 0.001). [TIMP-2]∙[IGFBP7] at ICU admission had a lower performance in predicting AKI at any stage within 48 hours and 7 days after measurement (area under the receiver operating characteristic curve (AUC) equal to 0.70 (95%CI 0.65–0.76), AUC 0.68 (95%CI 0.63–0.73)). In the logistic regression model, 0.1 (ng/ml)2/1000-unit increment was likely to increase the risk of AKI by 2% (p = 0.002).

scholarly journals Determinants of Satisfaction and Proper Management of Aged Population in Chapai Nawabgonj District in Bangladesh: Multivariate Approach

2021 ◽  
Vol 8 (1) ◽  
pp. 9-18
Author(s):  
Md. Shamsuzzaman
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Elderly People ◽  
Low Income ◽  
Living Arrangements ◽  
Logistic Regression Model ◽  
The Elderly ◽  
Aged Population ◽  
Proper Management ◽  
Significant Factors

Improving the ability of the satisfaction and proper management to reach the aged population is important for health and essential to mitigate the income erosion consequences of ill health in Bangladesh. This study examined the satisfaction and proper management of the elderly of some identified disadvantages of aged populations; including the effect of poverty-focused nongovernmental development interventions. The objective of the study is to determine the more influential factors that are affecting the health status and living arrangements of the elderly. The data were collected by direct interview method from Chapai-Nawabgonj District, Bangladesh. The chi-square test and logistic regression model were used to fulfill the objective of this study. The results of this study reveal that among literate the majority percent aged population has at least primary education and slightly over half of them have secondary level education. The majority of the elderly people are low income, economically dependent, living with married children. Also, they are unhealthy to suffer from different kinds of illnesses like Lame, Gastric, Blood pressure, Paralysis, Diabetics, etc. A large number of people is taking treatment from M.B.B.S, and a small portion of people are taking treatment from Homeopathic and Ayurvedic physician. Despite their suffering, most of them do not get the proper care. Television, Newspaper, monthly income-expenditure, family member, and educational status are associated with the satisfaction of elderly people. The logistic regression model exposed that serious operation and proper management are the most major significant factors effects satisfaction. It also exposed that mental torture, a different shelter for the elderly are major significant factors effects proper management. The paper concludes by emphasizing the importance of enhancing local capacities to determine whether self-treatment is indicated, to investigate socio-economic background, or in cases where satisfaction and proper management is sought, to judge provider competence and evaluate whether basic needs are justified. The provision of pharmaceutical training to the full spectrum of satisfied providers is also recommended.

Sign in / Sign up

Export Citation Format

Share Document