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The most common type of urinary incontinence in women is stress urinary incontinence (SUI) which negatively impacts several aspects of life. The newly introduced vaginal laser therapy is being considered for treating SUI. This systematic review aimed to evaluate the efficacy of vaginal laser therapy for stress urinary incontinence in menopausal women. We searched the following databases: MEDLINE (via PubMed), EMBASE, Cochrane Library databases, Web of Science, clinical trial registry platforms, and Google Scholar, using the MeSH terms and keywords [Urinary Incontinence, Stress] and [(lasers) OR laser]. In our systematic review, prospective randomized clinical studies on women diagnosed with SUI as per the International Continence Society’s diagnostic criteria were included. The Cochrane Risk-of-Bias assessment tool for randomized clinical trials was used to evaluate the quality of studies. A total of 256 relevant records in literature databases and registers and 25 in additional searches were found. Following a review of the titles, abstracts, and full texts, four studies involving 431 patients were included. Three studies used CO2-lasers, and one used Erbium: YAG-laser. The results of all four studies revealed the short-term improvement of SUI following both the Erbium: YAG-laser and CO2-laser therapy. SUI treatment with CO2-laser and Erbium: YAG-laser therapy is a quick, intuitive, well-tolerated procedure that successfully improves incontinence-related symptoms. The long-term impact of such interventions has not been well established as most trials focused on the short-term effects.

Background Developing a prediction model that incorporates several risk factors and accurately calculates the overall risk of birth asphyxia is necessary. The present study used a machine learning model to predict birth asphyxia. Methods Women who gave birth at a tertiary Hospital in Bandar Abbas, Iran, were retrospectively evaluated from January 2020 to January 2022. Data were extracted from the Iranian Maternal and Neonatal Network, a valid national system, by trained recorders using electronic medical records. Demographic factors, obstetric factors, and prenatal factors were obtained from patient records. Machine learning was used to identify the risk factors of birth asphyxia. Eight machine learning models were used in the study. To evaluate the diagnostic performance of each model, six metrics, including area under the receiver operating characteristic curve, accuracy, precision, sensitivity, specificity, and F1 score were measured in the test set. Results Of 8888 deliveries, we identified 380 women with a recorded birth asphyxia, giving a frequency of 4.3%. Random Forest Classification was found to be the best model to predict birth asphyxia with an accuracy of 0.99. The analysis of the importance of the variables showed that maternal chronic hypertension, maternal anemia, diabetes, drug addiction, gestational age, newborn weight, newborn sex, preeclampsia, placenta abruption, parity, intrauterine growth retardation, meconium amniotic fluid, mal-presentation, and delivery method were considered to be the weighted factors. Conclusion Birth asphyxia can be predicted using a machine learning model. Random Forest Classification was found to be an accurate algorithm to predict birth asphyxia. More research should be done to analyze appropriate variables and prepare big data to determine the best model.

BackgroundLittle is known about potential urban-rural differences in adverse pregnancy outcomes. The purpose of this study is to look into the urban-rural differences in the trend of adverse maternal and neonatal outcomes.MethodsWe retrospectively assessed the pregnancy outcome of singleton pregnant mothers who gave birth at a tertiary hospital in Bandar Abbas, Iran, between January 1st, 2020, and January 1st, 2022. Mothers were divided into two groups based on living residency: 1) urban groupand 2) rural group.Demographic factors, obstetrical factors, maternal comorbidities, and adverse maternal and neonatal outcomeswere extracted from the electronic data of each mother. The Chi-square testwas used to compare differences between the groups for categorical variables. Logistic regression models were used to assess the association of adverse pregnancy, childbirth, and neonatal outcome with living residency.ResultsOf 8888 mothers that gave birth during the study period, 2989 (33.6%) lived in rural areas. Adolescent pregnancy was more common in the rural area. Urban mothers had a higher education than rural mothers. Rural mothers were at higher risk for preterm birth aOR 1.81 (CI:1.24-2.99), post-term pregnancy aOR 1.5 (CI: 1.07-2.78), anemia aOR 2.02 (CI:1.07-2.34), low birth weight (LBW) aOR 1.89 (CI: 1.56-2.11), need for neonatal resuscitation aOR 2.66 (CI: 1.78-3.14), and neonatal intensive care unit (NICU) admission aOR 1.98 (CI:1.34-2.79). On the other hand, the risk of cesarean section was significantly lower compared to urban mothers aOR 0.58 (CI: 0.34-0.99).ConclusionsOur study discovered that mothers living in rural areas had a higher risk of developing anemia, preterm birth, post-term pregnancies, LBW, need for neonatal resuscitation, and NICU admission, but a lower risk of cesarean section.

Background Several common maternal or neonatal risk factors have been linked to meconium amniotic fluid (MAF) development; however, the results are contradictory, depending on the study. This study aimed to assess the prevalence and risk factors of MAF in singleton pregnancies. Methods This study is a retrospective cohort that assessed singleton pregnant mothers who gave birth at a tertiary hospital in Bandar Abbas, Iran, between January 1st, 2020, and January 1st, 2022. Mothers were divided into two groups: 1) those diagnosed with meconium amniotic fluid (MAF) and 2) those diagnosed with clear amniotic fluid. Mothers with bloody amniotic fluid were excluded. Demographic factors, obstetrical factors, and maternal comorbidities were extracted from the electronic data of each mother. The Chi-square test was used to compare differences between the groups for categorical variables. Logistic regression models were used to assess meconium amniotic fluid risk factors. Results Of 8888 singleton deliveries during the study period, 1085 (12.2%) were MAF. MAF was more common in adolescents, mothers with postterm pregnancy, and primiparous mothers, and it was less common in mothers with GDM and overt diabetes. The odds of having MAF in adolescents were three times higher than those in mothers 20–34 years old (aOR: 3.07, 95% CI: 1.87–4.98). Likewise, there were significantly increased odds of MAF in mothers with late-term pregnancy (aOR: 5.12, 95% CI: 2.76–8.94), and mothers with post-term pregnancy (aOR: 7.09, 95% CI: 3.92–9.80). Primiparous women were also more likely than multiparous mothers to have MAF (aOR: 3.41, 95% CI: 2.11–4.99). Conclusions Adolescents, primiparous mothers, and mothers with post-term pregnancies had a higher risk of MAF. Maternal comorbidities resulting in early termination of pregnancy can reduce the incidence of MAF.