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Transient and persistent small-bowel intussusception in children: a decision tree analysis model based on ultrasound
Shao Wang1, Yu Wang1, Liqun Jia1
1Department of Ultrasound, NationalCenterforChildren'sHealth, Beijing Children's Hospital, Capital Medical University, No.56 Nanlishi Road, Xicheng District, Beijing, China.
Insights
A new decision tree analysis (DTA) model accurately differentiates transient and persistent small-bowel intussusception in children. The model achieved 98.6% clinical concordance, improving diagnostic accuracy for pediatric small-bowel intussusception.
Area of Science:
- Pediatric Radiology
- Medical Imaging Analysis
- Diagnostic Decision Support Systems
Background:
- Small-bowel intussusception (SBI) in children presents diagnostic challenges.
- Differentiating transient (TSBI) from persistent (PSBI) forms is crucial for appropriate management.
- Current diagnostic methods may lack sufficient accuracy.
Purpose of the Study:
- To develop a systematic and efficient decision tree analysis (DTA) model.
- To enhance the diagnostic accuracy for TSBI and PSBI in pediatric patients.
- To improve the differential diagnosis of SBI subtypes.
Main Methods:
- Ultrasound (US) features and clinical data from 331 pediatric SBI patients were analyzed.
- Key US findings included SBI diameter, wall thickness, intussusceptum characteristics, and pathological lead points (PLPs).
- A classification and regression tree algorithm was employed to build and validate the DTA model using training and validation datasets.
Main Results:
- The DTA model identified the presence of a PLP via US as the primary diagnostic predictor, followed by intussusceptum length.
- The model demonstrated high diagnostic performance with 98.2% sensitivity, 100% specificity, and 98.6% accuracy.
- A total of 331 patients (270 TSBI, 61 PSBI) were included in the study.
Conclusions:
- The developed DTA model effectively facilitates the differential diagnosis between TSBI and PSBI in children.
- The model achieved a high clinical concordance rate of 98.6%.
- This approach offers a systematic and efficient tool for diagnosing pediatric SBI.
Purpose:
To develop a systematic and efficient decision tree analysis (DTA) model to improve the diagnostic accuracy of transient small-bowel intussusception (TSBI) and persistent small-bowel intussusception (PSBI) in children.
Methods:
From February 2019 to June 2022, ultrasound (US) features and clinical findings of pediatric patients with small-bowel intussusception (SBI)-including SBI diameter, outer bowel wall thickness, thickness of the head and body of the intussusceptum, length of the intussusceptum, and presence of pathological lead points (PLPs)-were recorded and analyzed. A classification and regression tree algorithm was then used to develop a DTA model, which was trained and validated by randomly categorizing the patients into training (60%, 200/331) and validation (40%, 131/331) datasets to assess diagnostic performance.
Results:
A total of 331 patients with SBI (270 with TSBI and 61 with PSBI) were included; the maximum age was 9 years. The initial diagnostic predictor in the DTA model was the detection of a PLP via US, followed by intussusceptum length (P < 0.001). The sensitivity, specificity, and accuracy of the DTA model were 98.2%, 100%, and 98.6%, respectively.
Conclusion:
The DTA model developed in this study facilitated the differential diagnosis of TSBI and PSBI in pediatric patients with SBI, with a clinical concordance rate of 98.6%.
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