Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset

Abstract

More than 1 billion people suffer from chronic respiratory diseases worldwide, accounting for more than 4 million deaths annually. Inhaled corticosteroid is a popular medication for treating chronic respiratory diseases. Its side effects include decreased bone mineral density and osteoporosis. The aims of this study are to investigate the association of inhaled corticosteroids and fracture and to design a clinical support system for fracture prediction. The data of patients aged 20 years and older, who had visited healthcare centers and been prescribed with inhaled corticosteroids within 2002–2010, were retrieved from the National Health Insurance Research Database (NHIRD). After excluding patients diagnosed with hip fracture or vertebrate fractures before using inhaled corticosteroid, a total of 11645 patients receiving inhaled corticosteroid therapy were included for this study. Among them, 1134 (9.7%) were diagnosed with hip fracture or vertebrate fracture. The statistical results showed that demographic information, chronic respiratory diseases and comorbidities, and corticosteroid-related variables (cumulative dose, mean exposed daily dose, follow-up duration, and exposed duration) were significantly different between fracture and nonfracture patients. The clinical decision support systems (CDSSs) were designed with integrated genetic algorithm (GA) and support vector machine (SVM) by training and validating the models with balanced training sets obtained by random and cluster-based undersampling methods and testing with the imbalanced NHIRD dataset. Two different objective functions were adopted for obtaining optimal models with best predictive performance. The predictive performance of the CDSSs exhibits a sensitivity of 69.84–77.00% and an AUC of 0.7495–0.7590. It was concluded that long-term use of inhaled corticosteroids may induce osteoporosis and exhibit higher incidence of hip or vertebrate fractures. The accumulated dose of ICS and OCS therapies should be continuously monitored, especially for patients with older age and women after menopause, to prevent from exceeding the maximum dosage.

Machine Learning Solutions for Osteoporosis—A Review

“…Among the 32 studies that investigated fracture detection (Table 3), (66–97 ) 11 were on vertebral fractures, ( 66–76 ) 17 hip fractures, ( 74–90 ) and 10 other fracture sites such as humerus or wrist. ( 75,76,90–97 ) Nineteen studies developed CNN models for image analysis.…”

“…( 66,67,71,72,77–86,90,91,93–95 ) Others used features extracted from images or collected from non‐imaging data. ( 68–70,73–77,87–89,92,96,97 ) Studies reported average best AUC of 0.92 (range 0.63 to 1.00) and average best accuracy of 89.8% (range 78.4% to 99.1%]. Surprising findings were that hospital‐related variables, such as the scanner device model, were better predictors of fractures than patients' characteristics or their images (AUC = 0.89 [95% confidence interval (CI) 0.87–0.91] versus 0.79 [95% CI 0.75–0.82] and 0.78 [95% CI 0.74–0.81], respectively), ( 77 ) which the authors acknowledged as a potential bias induced by the triage process.…”

“…( 82 ) Several studies did not report the confidence intervals or standard errors for the performance metrics that they reported. ( 66,68,69,72–74,79,81,83,84,86,88,89,92 ) Four studies obtained both high overall quality scores and near perfect AUCs (AUC ≥ 0.99). ( 78,79,91,94 ) Possible reasons for these unusual performances are the use of images' regions of interest ( 79,91 ) or the presence of potential data set bias, ( 78 ) which can significantly simplify the task.…”

Meta-design knowledge for Clinical Decision Support Systems

“…Zolhavarieha and Parry (2017) developed a candidate matrix from their developed CDSS framework called Knowledge Quality Assessment (KQA) for discovering and evaluating the clinical knowledge for CDSS design. Chen et al (2018) investigated an association of inhaled corticosteroids and fracture in order to develop a CDSS. In the research Chen et al (2018) particularly addressed the issue of improving predictive performance of the CDSS.…”

“…Chen et al (2018) investigated an association of inhaled corticosteroids and fracture in order to develop a CDSS. In the research Chen et al (2018) particularly addressed the issue of improving predictive performance of the CDSS. Yu (2015) improved the utility of the CDSS by focusing on the importance of the relationship of knowledge bases and the CDSS system as key drivers of rapid learning in clinical care service.…”