Machine Learning-Driven Evaluation of Lithium and Valproate Combination Therapy in Bipolar Disorder

Background Bipolar disorder (BD) is characterized by recurrent episodes of mania and depression, requiring long-term mood stabilization. While lithium is a well-established treatment for BD, its efficacy can vary among individuals. Combination therapy with valproate has been explored to enhance treatment outcomes. Objective This case series aims to demonstrate the superior effectiveness of lithium and valproate combination therapy over lithium monotherapy in stabilizing mood in patients with bipolar disorder. Methods This retrospective study includes data from 2 patients diagnosed with bipolar disorder. Patients initially treated with lithium monotherapy who showed inadequate response were subsequently treated with a combination of lithium and valproate. Clinical assessments were conducted using the Mood Disorder Questionnaire (MDQ), Clinical Global Impression-Severity (CGI-S), Hamilton Depression Rating Scale (HDRS), and Global Assessment of Functioning (GAF) before and after combination therapy. Results Combination therapy with lithium and valproate significantly improved mood stability in patients compared to lithium monotherapy. On average, MDQ scores decreased from 22.4 to 8.3, CGI-S scores improved from 4.8 to 2.1, HDRS scores reduced from 25.6 to 9.7, and GAF scores increased from 50.3 to 75.4. These improvements were sustained over a followup period of 12 months. The combination of lithium and valproate provides superior mood stabilization in patients with bipolar disorder compared to lithium alone. These findings suggest that combination therapy should be considered in patients who do not achieve adequate symptom control with lithium monotherapy

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Publication Details

Journal
Journal of Mathematical Techniques and Computational Mathematics
Published
2024-08-20
DOI
https://doi.org/10.33140/jmtcm.03.08.004
Primary Topic
Bipolar Disorder and Treatment
Type
article
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article

Machine Learning-Driven Evaluation of Lithium and Valproate Combination Therapy in Bipolar Disorder

Rocco de Filippis, Abdullah Al Foysal
Journal of Mathematical Techniques and Computational Mathematics
Bipolar Disorder and Treatment
article

Machine Learning-Driven Evaluation of Lithium and Valproate Combination Therapy in Bipolar Disorder

Rocco de Filippis, Abdullah Al Foysal
article en

Abstract

Background Bipolar disorder (BD) is characterized by recurrent episodes of mania and depression, requiring long-term mood stabilization. While lithium is a well-established treatment for BD, its efficacy can vary among individuals. Combination therapy with valproate has been explored to enhance treatment outcomes. Objective This case series aims to demonstrate the superior effectiveness of lithium and valproate combination therapy over lithium monotherapy in stabilizing mood in patients with bipolar disorder. Methods This retrospective study includes data from 2 patients diagnosed with bipolar disorder. Patients initially treated with lithium monotherapy who showed inadequate response were subsequently treated with a combination of lithium and valproate. Clinical assessments were conducted using the Mood Disorder Questionnaire (MDQ), Clinical Global Impression-Severity (CGI-S), Hamilton Depression Rating Scale (HDRS), and Global Assessment of Functioning (GAF) before and after combination therapy. Results Combination therapy with lithium and valproate significantly improved mood stability in patients compared to lithium monotherapy. On average, MDQ scores decreased from 22.4 to 8.3, CGI-S scores improved from 4.8 to 2.1, HDRS scores reduced from 25.6 to 9.7, and GAF scores increased from 50.3 to 75.4. These improvements were sustained over a followup period of 12 months. The combination of lithium and valproate provides superior mood stabilization in patients with bipolar disorder compared to lithium alone. These findings suggest that combination therapy should be considered in patients who do not achieve adequate symptom control with lithium monotherapy

Journal of Mathematical Techniques and Computational MathematicsVol. 3(8)
Openalex Percentile: Top 70%
Bipolar Disorder and Treatment
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Machine Learning-Driven Evaluation of Lithium and Valproate Combination Therapy in Bipolar Disorder — Rocco de Filippis, Abdullah Al Foysal · Journal of Mathematical Techniques and Computational Mathematics (2024) | TGRS Research Map | TGRS