METHODS: In this study, performance, co-citation, co-word, and document analyses were used as bibliometric analysis techniques.
RESULTS: The study identified 3 main themes in terms of the intellectual structure of Shoulder Dystocia (SD): \"Management of SD, Risk Factors and Associated Complications,\" \"Clinical Practices, Birth Abnormalities and Effects of Complications,\" and \"Impact of Education, Clinical Maneuvers and Fetal Health Outcomes.\" Co-occurrence analysis identified 4 significant themes: \"Management and Clinical Practice of SD,\" \"Fetal Macrosomia and Risk Factors,\" \"Obstetric Maneuvers and Brachial Plexus Injury,\" and \"Clinical Trends and Risks in SD.\" Additionally, ten consolidated themes were identified as a result of thematic coding analysis.
CONCLUSIONS: Shoulder dystocia remains a critical component of obstetric practice. Themes such as training and simulation, risk factors, and technical and management approaches are consistently emphasized. Technological advances and studies on how machine learning techniques can be used effectively in this field reflect innovative approaches in the scientific literature. This analysis confirms that shoulder dystocia is a complex topic requiring a multidisciplinary approach and that research in this field is constantly evolving.
方法:在本研究中,性能,共同引文,共词,文献分析被用作文献计量分析技术。
结果:该研究确定了肩难产(SD)的智力结构方面的3个主要主题:“SD的管理,风险因素和相关并发症,\"\"临床实践,出生异常和并发症的影响,“和”教育的影响,临床操作和胎儿健康结果。“共现分析确定了4个重要主题:“SD的管理和临床实践,“\”巨大胎儿和危险因素,\"\"产科机动和臂丛神经损伤,“和”SD的临床趋势和风险。\"此外,通过专题编码分析,确定了十个综合主题。
结论:肩难产仍然是产科实践的重要组成部分。培训和模拟等主题,危险因素,一贯强调技术和管理方法。关于如何在该领域有效使用机器学习技术的技术进步和研究反映了科学文献中的创新方法。该分析证实,肩难产是一个复杂的主题,需要多学科的方法,并且该领域的研究正在不断发展。