Hospital Practices and Research

Abstract Background: Kidney stones significantly raise healthcare expenses due to the requirement for specialized treatments and frequent hospital visits. Kidney stones lower workforce productivity because affected individuals frequently miss work or are less efficient due to pain and the necessity of treatment. In society, kidney stones lead to reduced productivity and quality of life, affecting both individuals and the broader economy.
Objectives: The primary objective of this study is to analyze the influence of urine-based biochemical and physical parameters on kidney stone formation and to develop a high-accuracy machine learning model for early kidney stone prediction.
Methods: In this paper, data analytics methods are used to investigate kidney stones based on urea analysis and uncover valuable insights from the relationship between various factors. Additionally, a predictive model is developed by integrating deep learning with Particle swarm optimization (PSO) algorithms, where PSO is utilized to tune the model hyperparameters.
Results: This model boasts an impressive 98.1% accuracy in predicting kidney stones. Such a proactive approach can significantly enhance patient outcomes by preventing the onset of painful and debilitating kidney stones.
Conclusion: In this research, it was shown that early prediction allows for timely medical intervention, reducing symptom severity and preventing complications like urinary tract infections or kidney damage. Consequently, the need for emergency treatments and hospitalizations is minimized, lowering healthcare costs.

Abstract Background: Craniosynostosis, is defined as the premature fusion of the cranial sutures, which can cause impair brain development and cognitive problems.
Objectives: The purpose of this study was to assess the epidemiological features of children with craniosynostosis. This assessment includes the characteristics of the patients, their parents as well as their socioeconomic status.
Methods: This cross-sectional study was performed from 2015 to 2020 in Imam Hossein Children's Hospital, Isfahan, Iran. For this purpose, 220 patients under craniosynostosis treatment were included. Accordingly, multidisciplinary team examined the participants. Furthermore, a CT-scan was performed on all patients. Participants underwent surgical intervention. The recorded information was classified into four sections: 1. characteristic data of children with craniosynostosis 2. Family history and parental information, including underlying diseases and drug history 3. Socioeconomic status 4. Treatment and surgery.
Results: According to findings, 151 (68.7 %) of participants were male and 171 (77.9%) had term delivery.  The average birth weight was 2.92 kg and head circumference were 34.4 cm. The mean age of children at the time of surgery was 7.74 months and the mortality rate was 3 (1.4%). Moreover, 90% were operated once and 10% were operated two or three times. The most common type of craniosynostosis was Metopic 59 (59.4%). In relation to parenteral data, 96 (43.6%) of parents had consanguineous marriage and 6.4% had 1st and 2nd degree family with craniosynostosis.
Conclusion: To coclude, attention must be directed towards the potential risk of craniosynostosis in offspring born to consanguineous couples. Moreover, parents must receive guidelines for managing children affected by craniosynostosis.