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Association Between Abnormal Metabolic Parameters and Receiving Subsequent Interventions in Children and Adolescents
Swarnava Sanyal1, Ning Lyu1, Chadi Calarge2
1Department of Pharmaceutical Health Outcomes and Policy, University of Houston College of Pharmacy, Houston, Texas, USA.
Journal of Child and Adolescent Psychopharmacology
|September 7, 2023
Summary
Abnormal body mass index (BMI) in children and adolescents on second-generation antipsychotics (SGAs) increased the likelihood of metabolic adverse event interventions (mAEIs). However, abnormal lab results did not predict these interventions, highlighting weight gain as a primary driver for SGA metabolic monitoring.
Area of Science:
- Pediatric pharmacology
- Metabolic health
- Electronic Health Records (EHR) research
Background:
- Second-generation antipsychotics (SGAs) are associated with significant metabolic adverse events in pediatric populations.
- Early detection and intervention for SGA-related metabolic changes are crucial for patient outcomes.
- Understanding predictors of metabolic adverse event interventions (mAEIs) can optimize clinical management.
Purpose of the Study:
- To investigate the association between abnormal metabolic parameter readings and the initiation of mAEIs in pediatric patients treated with SGAs.
- To identify specific metabolic parameters that predict the need for interventions during SGA therapy.
Main Methods:
- A nested case-control study utilized TriNetX EHR data from patients aged 1-17 years with at least two SGA prescriptions (2010-2019).
- Cases (mAEI recipients) were matched with three controls (nonrecipients) using incident density sampling.
- Conditional logistic regression adjusted for covariates to assess the association between abnormal metabolic parameters (BMI, labs) and mAEI initiation.
Main Results:
- Of 1,884 pediatric patients receiving mAEIs, common interventions included weight management (40.6%) and SGA risk profile modification (30.9%).
- Abnormal body mass index (BMI) was significantly associated with a 43% increased odds of receiving an mAEI (OR 1.43; 95% CI: 1.13-1.79).
- Abnormal laboratory parameter readings (cholesterol, glucose, etc.) were not associated with the initiation of mAEIs.
Conclusions:
- The prescribing of mAEIs in pediatric SGA users is primarily driven by obesity, not by abnormal laboratory metabolic findings.
- Current interventions may not adequately address or predict metabolic complications beyond weight gain.
- Further research is needed to clarify the long-term implications of other SGA-related metabolic adverse events and optimize intervention timing.
Keywords:
SGA-associated adverse drug eventsconditional logistic regressioneventsmetabolic adverse event interventionmetabolic monitoringnested case–control studyMore Related Videos
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