Aim: To establish a model predicting successful vaginal delivery (VD) in nulliparas with term cephalic singleton pregnancies.
Methods: We retrospectively identified 6799 term nulliparas with cephalic singletons (6416 VD and 383 cesarean section [CS] due to dystocia) who entered labor (cervical dilation ≥2 cm) between September 2014 and August 2015. Using VD as the dependent variable and age, maternal body height, educational attainment, gravidity, gestational age, pre-pregnancy body mass index (BMI), BMI upon admission for delivery, gestational weight gain, gestational hypertension and gestational diabetes as the independent variables, predictors of VD success were identified using a multivariate binary logistic regression and then ranked with decision-tree analysis.
Results: While multiple factors are associated with improved VD success, we found body height, gestational age, and intrapartum BMI to be the best predictors of successful VD. Our predictive model has a classification accuracy, sensitivity and specificity of 76.6%, 96.7% and 16.4%, respectively, and it was subsequently confirmed by both internal and external validation.
Conclusion: Our predictive model indicates body height, gestational age and intrapartum BMI as the major predictors of successful VD in low-risk patients.
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http://dx.doi.org/10.1111/jog.14011 | DOI Listing |
J Vasc Access
January 2025
College of Nursing, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Objective: To develop and validate a nomogram model for predicting central venous catheter-related infections (CRI) in patients with maintenance hemodialysis (MHD).
Methods: MHD patients with central venous catheters (CVCs) visiting the outpatient hemodialysis (HD) center of Xuzhou Medical University Affiliated Hospital from January 2020 to December 2023 were retrospectively selected through a HD monitoring system. Patient data were collected, and the patients were divided into training and validation sets in a 7:3 ratio.
J Chem Inf Model
January 2025
Key Laboratory for Photonic and Electronic Bandgap Materials, Ministry of Education, College of Chemistry and Chemical Engineering, Harbin Normal University, Harbin 150025, China.
Tryptophan participates in important life activities and is involved in various metabolic processes. The indole and aromatic binuclear ring structure in tryptophan can engage in diverse interactions, including π-π, π-alkyl, hydrogen bonding, cation-π, and CH-π interactions with other side chains and protein targets. These interactions offer extensive opportunities for drug development.
View Article and Find Full Text PDFIntroductionAsthma attacks are set off by triggers such as pollutants from the environment, respiratory viruses, physical activity and allergens. The aim of this research is to create a machine learning model using data from mobile health technology to predict and appropriately warn a patient to avoid such triggers.MethodsLightweight machine learning models, XGBoost, Random Forest, and LightGBM were trained and tested on cleaned asthma data with a 70-30 train-test split.
View Article and Find Full Text PDFCurr Med Chem
January 2025
Shree S K Patel College of Pharmaceutical Education and Research, Ganpat University, Mahesana, Gujarat, 384012, India.
Therapeutic hurdles persist in the fight against lung cancer, although it is a leading cause of cancer-related deaths worldwide. Results are still not up to par, even with the best efforts of conventional medicine, thus new avenues of investigation are required. Examining how immunotherapy, precision medicine, and AI are being used to manage lung cancer, this review shows how these tools can change the game for patients and increase their chances of survival.
View Article and Find Full Text PDFCurr Med Chem
January 2025
Department of Electronics & Communication Engineering, Jaypee University of Information Technology, Solan, H.P., India.
A planktonic population of bacteria can form a biofilm by adhesion and colonization. Proteins known as "adhesins" can bind to certain environmental structures, such as sugars, which will cause the bacteria to attach to the substrate. Quorum sensing is used to establish the population is dense enough to form a biofilm.
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