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Development of a prediction model for antimicrobial stewardship pharmacy consultations to identify high-risk
Xuanbao Lian1, Jun Luo2, Lizhi Wei3
1Guangxi Medical University, 22 Shuangyong Road, Qingxiu District, Nanning, Guangxi, 530021, China.
Insights
A new model using Antimicrobial Stewardship Pharmacy Consultation (ASPC) parameters can identify pediatric infectious disease patients at high risk for prolonged length of stay (LOS). This helps reduce patient burden and optimize care.
Area of Science:
- Pharmacology
- Infectious Diseases
- Health Services Research
Background:
- Antimicrobial Stewardship Pharmacy Consultation (ASPC) in China aims to reduce patient length of stay (LOS).
- Prolonged LOS in pediatric infectious disease patients incurs significant psychological and financial burdens.
- Identifying high-risk patients is crucial for targeted interventions.
Purpose of the Study:
- To develop a predictive model for identifying pediatric infectious disease patients at high risk of prolonged LOS despite ASPC.
- To utilize ASPC parameters within the model for enhanced risk stratification.
- To define high-risk status by prolonged LOS following ASPC interventions.
Main Methods:
- Lasso regression was used for predictor selection in the ASPC model.
- A nomogram was constructed using multivariate logistic regression.
- Internal validation was performed via tenfold cross-validation on 474 patient records.
- LOS was dichotomized at the median to define the outcome event.
Main Results:
- Five independent predictors were identified: crucial consultation suggestions, weight, first aid, consultation aim, and critical illness status.
- The model demonstrated good discrimination with a C-statistic of 0.772.
- The model exhibited good calibration, with intercept and slope values close to 0 and 1, respectively.
Conclusions:
- The developed ASPC model effectively identifies pediatric patients at high risk for prolonged LOS.
- The model shows strong discrimination and calibration, indicating its clinical utility.
- This tool can aid in optimizing antimicrobial stewardship and patient management.
Background:
Antimicrobial Stewardship Pharmacy Consultation (ASPC) in China has been shown to reduce patients' length of stay (LOS). However, prolonged LOS remains a challenge, resulting in unnecessary psychological and financial burden for patients.
Objective:
This study aimed to develop a prediction model using ASPC parameters to identify high-risk pediatric patients with infectious diseases. These patients received ASPC interventions but still experienced prolonged LOS, which defined their high-risk status.
Methods:
Predictors for the ASPC model were selected using lasso regression, a nomogram was developed using multivariate logistic regression, and internal validation was performed using tenfold cross-validation. The data set consisted of 474 electronic medical records of pediatric patients with infectious diseases from two hospitals. LOS was dichotomized at the median, and patients with LOS greater than the median were considered to have achieved the outcome.
Results:
The proportion of outcome events was set at 50% by design. Five independent predictors were identified in the ASPC model: (1) the suggestions from the crucial consultation (OR: 1.74; 95% CI: 1.10 to 2.74), (2) weight (OR: 0.98; 95% CI: 0.97 to 1.00), (3) whether the patient received first aid (OR: 0.54; 95% CI: 0.3 to 1.00), (4) the aim of the crucial consultation (OR: 0.15; 95% CI: 0.03 to 0.66), and (5) whether the patient was critically ill (OR: 0.22; 95% CI: 0.12 to 0.41). The ASPC model showed good discrimination with a C-statistic of 0.772 (95% CI: 0.748 to 0.797) and good calibration performance with intercept and slope values of 0.00 (95% CI: -0.12 to 0.12) and 0.93 (95% CI: 0.82 to 1.04), respectively, under tenfold cross-validation.
Conclusions:
The antimicrobial stewardship pharmacy consultation model has good discrimination and calibration, and effectively identifies patients at risk for prolonged length of stay.
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