Related Experiment Video
Updated: May 23, 2025
Improved Methodology for Studying Postnatal Osteogenesis via Intramembranous Ossification in a Murine Bone Marrow Injury Model
Published on: February 7, 2025
Predictive model for surgical intervention in pediatric acute hematogenous osteomyelitis
Jiale Guo1,2, Wei Feng1,2, Baojian Song1,2
1Department of Orthopaedic, Beijing Children's Hospital, Capital Medical University, Nanlishi Road 56, Xicheng District, Beijing, 100045, China.
Insights
This study identifies key predictors for surgical intervention in acute hematogenous osteomyelitis (AHO). Elevated neutrophil counts and MRSA presence indicate higher surgical risk, aiding in better patient management.
Area of Science:
- Pediatric Orthopedics
- Infectious Diseases
- Medical Informatics
Background:
- Multidrug-resistant bacteria complicate acute hematogenous osteomyelitis (AHO) treatment.
- Increased surgical intervention necessity due to worsening prognoses.
- Need for predictive models for surgical risk in AHO patients.
Purpose of the Study:
- Identify risk factors for surgical intervention in pediatric AHO.
- Develop and validate prediction models for surgical outcomes.
- Improve clinical decision-making for AHO management.
Main Methods:
- Retrospective chart review of 218 pediatric AHO patients (2015-2022).
- Multivariate logistic regression to identify risk factors for single/multiple surgeries.
- Nomogram and ROC curve analysis for model validation.
Main Results:
- Absolute neutrophil count (ANC) and Methicillin-resistant Staphylococcus aureus (MRSA) predicted surgical intervention (AUC=0.76).
- C-reactive protein (CRP) levels predicted multiple surgeries (AUC=0.91).
- Developed models showed good fit and discriminative ability.
Conclusions:
- Two validated prediction models for AHO surgical risk were developed.
- Models demonstrate promising accuracy and discrimination for clinical application.
- Predictive tools can aid in optimizing AHO patient care.
Background:
The emergence of multidrug-resistant bacteria has resulted in more complicated disease courses and worsening prognoses for patients with acute hematogenous osteomyelitis (AHO), increasing the necessity for surgical intervention. This research attempts to identify the risk variables related to surgical patients and build prediction models.
Method:
From December 2015 to December 2022, children admitted to a single quaternary care pediatric hospital with AHO had their charts retrospectively reviewed. Based on the therapy methods, the patients were divided into 3 cohorts: multiple surgery, single surgery, and conservative care. Multivariate logistic regression analysis was used to identify independent risk factors related to single and recurrent surgery. A nomogram was created to visually represent the various risk factors, and a calibration curve was plotted to evaluate the model's goodness of fit. The Hosmer-Lemeshow test and the area under the receiver operating characteristic (ROC) curve were used to assess how well the models matched.
Results:
A total of 218 patients were included in the analysis, out of which 150 patients underwent surgical procedures, with 21 individuals undergoing multiple surgeries. The multivariate binary logistic regression revealed that an increase in absolute neutrophil counts (ANC) (adjusted odds ratio [aOR], 1.14 [95% confidence interval {CI}, 1.05-1.24]) and the presence of Methicillin-resistant Staphylococcus aureus (MRSA) (aOR, 6.97 [95% CI, 1.94-25.06]) were strong predictors of surgical intervention. The prediction model demonstrated an area under the curve (AUC) value of 0.76, while the Hosmer-Lemeshow test showed χ2 = 7.3, P = 0.50. In another separated model, the C-reactive protein (CRP) level upon admission (aOR, 1.02 [95% CI, 1.00-1.03]) and the CRP level after the initial surgery (aOR, 1.04 [95% CI, 1.01-1.06]) strongly predict multiple surgeries, with the AUC value of 0.91 obtained and HosmerLemeshow test (χ2 = 8.7, P = 0.36) yielded. The calibration curves of the two models were drawn separately, and it was observed that the slopes of both models were close to one.
Conclusion:
Two prediction models were developed by statistical analysis of clinical data. Their accuracy and discrimination were validated, indicating a promising potential for clinical application.
More Related Videos
06:38Establishment of a Segmental Femoral Critical-size Defect Model in Mice Stabilized by Plate Osteosynthesis
Published on: October 12, 2016
08:20A Reliable and Reproducible Critical-Sized Segmental Femoral Defect Model in Rats Stabilized with a Custom External Fixator
Published on: March 24, 2019