Evidence map›Paper›PMID 39220771›Full record

ArticleTherapeutics and clinical risk management2024

Risk Assessment Tool in Predicting the Therapeutic Outcomes of Antiseizure Medication in Adults with Epilepsy.

Rose Aniza Rusli, Mohd Makmor Bakry, Noraida Mohamed Shah, Xin Ling Loo, Stefanie Kar Yan Hung

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Article in Therapeutics and clinical risk management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Rose Aniza RusliFaculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Mohd Makmor BakryFaculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.ORCID 0000-0002-0592-0645
Noraida Mohamed ShahFaculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.ORCID 0000-0002-2509-4213
Xin Ling LooPharmacy Department, Hospital Tengku Ampuan Rahimah, Klang, Selangor, Malaysia.
Stefanie Kar Yan HungNeuromedical Unit, Hospital Tengku Ampuan Rahimah, Klang, Selangor, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: Identifying a patient's risk for poor outcomes after starting antiseizure medication (ASM) therapy is crucial in managing epilepsy pharmacologically. To date, there is a lack of designated tools to assess such risks. Purpose: To develop and validate a risk assessment tool for the therapeutic outcomes of ASM therapy. Patients and Methods: A cross-sectional study was carried out in a hospital-based specialist clinic from September 2022 to August 2023. Data was analyzed from patients' medical records and face-to-face assessments. The seizure control domain was determined from the patients' medical records while seizure severity (SS) and adverse effects (AE) of ASM were assessed using the Seizure Severity Questionnaire and the Liverpool Adverse Event Profile respectively. The developed tool was devised from prediction models using logistic and linear regressions. Concurrent validity and interrater reliability methods were employed for validity assessments. Results: A total of 397 patients were included in the analysis. For seizure control, the identified predictors include ≥10 years' epilepsy duration (OR:1.87,95% CI:1.10-3.17), generalized onset (OR:7.42,95% CI:2.95-18.66), focal onset seizure (OR:8.24,95% CI:2.98-22.77), non-adherence (OR:3.55,95% CI:1.52-8.27) and having ≥3 ASM (OR:3.29,95% CI:1.32-8.24). Younger age at epilepsy onset (≤40) (OR:3.29,95% CI:1.32-8.24) and neurological deficit (OR:3.55,95% CI:1.52-8.27) were significant predictors for SS. For AE, the positive predictors were age >35 (OR:0.12,95% CI:0.03-0.20), <13 years epilepsy duration (OR:2.89,95% CI:0.50-5.29) and changes in ASM regimen (OR:2.93,95% CI: 0.24-5.62). The seizure control domain showed a good discriminatory ability with a Conclusion: This newly developed tool (RAS-TO) is a promising tool that could help healthcare providers in determining optimal treatment strategies for adults with epilepsy.

Indexed as

antiseizure medicationrisk assessmentseizure controltherapeutic outcomes

Identifiers

PMID39220771
PMCPMC11363947

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