Utilizing machine learning to predict the risk factors of episiotomy in parturient women.

Background: Episiotomy has specific indications that, if properly followed, can effectively prevent women from experiencing severe lacerations that may result in significant complications like anal incontinence. However, the risk factors related to episiotomy has been the center of much debate in the medical field in the past few years.

Objective: The present study used a machine learning model to predict the factors that put women at the risk of having episiotomy using intrapartum data.

Prevalence of stress urinary incontinence and urge urinary incontinence in multiples sclerosis patients: a systematic review and meta-analysis.

Urinary incontinence (UI), encompassing stress urinary incontinence (SUI) and urge urinary incontinence (UUI), is a prevalent and debilitating condition in patients with multiple sclerosis (MS), profoundly impacting their quality of life. This systematic review and meta-analysis aimed to elucidate the worldwide prevalence rates of SUI and UUI among MS patients. This study was conducted by examining observational studies published between 2000 and 2023.

Machine learning models for predicting preeclampsia: a systematic review.

Background: This systematic review provides an overview of machine learning (ML) approaches for predicting preeclampsia.

Method: This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) guidelines. We searched the Cochrane Central Register, PubMed, EMBASE, ProQuest, Scopus, and Google Scholar up to February 2023.

Coping Strategies with Genito-Pelvic Pain/Penetration Disorder: A Qualitative Study.

Background: Genital/pelvic pain penetration disorder (GPPPD) decreased mental and physical functioning, reduced quality of life, and reduced feelings of inadequacy and worthlessness, all of which impair the ability of women with GPPPD to enjoy sex. This qualitative study was conducted to identify which factors can reduce sexual stress and help Iranian women cope with GPPPD.

Methods: This qualitative study was conducted through the participation of 18 women with GPPPD diagnosed by a sexologist and using DSM-IV diagnostic criteria from March to July 2022, Iran.

Endophytic to total tumour volume ratio: An added variable to patients with T1b/T2 renal tumours undergoing partial nephrectomy.

Introduction: Partial nephrectomy is the standard of care to patients with small renal masses. It is still encouraged to larger tumours whenever feasible. The aim of this study is to look for the endophytic to total tumour volume ratio as an added variable to study the complexity of partial nephrectomy to patients with T1b/ T2 renal tumours.

Machine learning-based approach for predicting low birth weight.

Background: Low birth weight (LBW) has been linked to infant mortality. Predicting LBW is a valuable preventative tool and predictor of newborn health risks. The current study employed a machine learning model to predict LBW.

Manifestation of Spontaneous Rupture of the Urinary Bladder in Pregnancy: A Systematic Review of the Literature.

Spontaneous rupture of the urinary bladder (SRUB) during pregnancy is a potentially fatal event that necessitates immediate surgery. The aim of this systematic review is to determine the symptoms, causes, associated factors, and prognosis of SRUB in pregnancy. We searched the literature from inception until December 2022 using the Cochrane Central Register, PubMed, EMBASE, ProQuest, Scopus, and Google Scholar.

Analysis of Cesarean Section Rates in a Public Tertiary Hospital During Teaching and Non-teaching Periods Using the Robson Ten Group Classification System.

Introduction: The rising cesarean section (CS) rate is a global concern. One of the hospital characteristics that may explain the variation in CS among hospitals is hospital teaching status. This study aims to assess the rate of CS in a tertiary hospital during the teaching and non-teaching periods and to conduct an analysis using the Robson ten-group classification system.

Machine learning models for predicting pre-eclampsia: a systematic review protocol.

Introduction: Pre-eclampsia is one of the most serious clinical problems of pregnancy that contribute significantly to maternal mortality worldwide. This systematic review aims to identify and summarise the predictive factors of pre-eclampsia using machine learning models and evaluate the diagnostic accuracy of machine learning models in predicting pre-eclampsia.

Methods And Analysis: This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Machine Learning-Based Approach to Predict Intrauterine Growth Restriction.

Introduction: Creating a prediction model incorporating multiple risk factors for intrauterine growth restriction is vital. The current study employed a machine learning model to predict intrauterine growth restriction.

Methods: This cross-sectional study was carried out in a tertiary hospital in Bandar Abbas, Iran, from January 2020 to January 2022.

Rapid metachronous bladder metastasis of type 2 papillary renal cell carcinoma.

Renal cell carcinoma (RCC) frequently spreads to distant organs like the lung, lymph nodes, bone, and liver. However, there have been some reports of RCC bladder metastasis. We present a case of a 61-year-old man presented with total painless gross hematuria.

History of infantile BCG immunization did not predict lamina propria invasion and/or high-grade in patients with non-muscle invasive bladder cancer.

Objective: To evaluate the utility of infantile BCG vaccination history in predicting stage and grade of tumours in non-muscle invasive bladder cancer (NMIBC).

Materials And Methods: We retrospectively analyzed data from patients from a single center who were diagnosed with new NMIBC and underwent transurethral resection of bladder tumour (TURBT) between 2017 and 2022. We assessed BCG immunization status with various demographics and comorbidities, as well as tumour recurrence, progression, stage, and grade.

Prediction of postpartum hemorrhage using traditional statistical analysis and a machine learning approach.

Background: Early detection of postpartum hemorrhage risk factors by healthcare providers during pregnancy and the postpartum period may allow healthcare providers to act to prevent it. Developing a prediction model that incorporates several risk factors and accurately calculates the overall risk for postpartum hemorrhage is necessary.

Objective: This study used a traditional analytical approach and a machine learning model to predict postpartum hemorrhage.

Application of machine learning to identify risk factors of birth asphyxia.

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.

The Incidence and Outcomes of Late-Term Pregnancy.

Background: Little is known about the outcomes of late-term pregnancy. In this study, we aim to assess the incidence and adverse prenatal outcomes associated with late-term pregnancy.

Methods: We retrospectively assessed all singleton pregnant mothers who gave birth at Khalij-e-Fars Hospital in Bandar Abbas, Iran, between January 2020 and 2022.

Machine learning approach to predict postpartum haemorrhage: a systematic review protocol.

Introduction: Postpartum haemorrhage (PPH) is the most serious clinical problem of childbirth that contributes significantly to maternal mortality worldwide. This systematic review aims to identify predictors of PPH based on a machine learning (ML) approach.

Methods And Analysis: This review adhered to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol.

Vaginal Laser Therapy for Stress Urinary Incontinence: A Systematic Review of Prospective Randomized Clinical Trials.

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.

Partial Nephrectomy for T1b/T2 Renal Mass: An Added Shift from Radical Nephrectomy.

The aim of our study was to show our short-term experience in managing large renal masses (cT1b/T2) through partial nephrectomy (PN) over the last 3 years. Retrospective data collection for all patients managed by PN for renal masses larger than 4 cm over the last 3 years. Epidemiological data were collected.