Developing a nomogram for predicting acute complicated course in pediatric acute hematogenous osteomyelitis.
Chaochen Zhao1, Qizhi Jiang2, Wangqiang Wu2
1Department of Orthopedics, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Italian Journal of Pediatrics
|July 29, 2024
Summary
A new nomogram predicts complicated Acute Hematogenous Osteomyelitis (AHO) in children. It uses delayed source control, suppurative arthritis, albumin, and platelet-to-lymphocyte ratio (PLR) for better risk assessment.
Area of Science:
- Pediatric Orthopedics
- Infectious Diseases
- Medical Informatics
Background:
- Acute Hematogenous Osteomyelitis (AHO) is a serious bone infection in children.
- Predicting complicated AHO courses is crucial for timely intervention.
- Existing predictive tools may lack accuracy or comprehensive evaluation.
Purpose of the Study:
- To develop and validate a nomogram for predicting the risk of complicated AHO in pediatric patients.
- To identify key clinical, imaging, and laboratory factors associated with adverse outcomes.
- To compare the novel nomogram's performance against established scoring systems.
Main Methods:
- Retrospective analysis of 82 pediatric AHO cases.
- Development of a predictive model using logistic regression.
- Internal validation via bootstrap methods, including ROC curves, calibration plots, and DCA.
- Comparison with A-score and Gouveia scoring systems.
Main Results:
- Delayed source control, suppurative arthritis, low albumin, and high platelet-to-lymphocyte ratio (PLR) were independent predictors.
- The nomogram demonstrated good discriminative ability (AUC 0.829) and calibration.
- The model outperformed existing A-score and Gouveia scoring systems.
Conclusions:
- A practical nomogram was developed to predict acute complicated AHO in children.
- The model incorporates easily accessible variables: delayed source control, suppurative arthritis, albumin, and PLR.
- This tool can assist clinicians in guiding treatment decisions and improving patient outcomes.
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