A simple and cost‐effective HPLC‐UV method for the detection of levetiracetam in plasma/serum of patients with epilepsy

Engelbrecht, Lynette; Grobler, Christa; Rheeders, Malie

doi:10.1002/bmc.3969

Cited by 15 publications

(21 citation statements)

References 26 publications

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“…Several fast and cost-effective HPLC methods have been developed. For example, HPLC with ultraviolet detection can be used to detect levetiracetam in plasma/serum of patients with epilepsy in only 15 minutes (Engelbrecht et al, 2017). In our medical practice, after psychiatrists conduct a diagnostic interview, a psychological assessment and blood biochemistry examination are arranged.…”

Section: Discussionmentioning

confidence: 99%

Plasma d-glutamate levels for detecting mild cognitive impairment and Alzheimer’s disease: Machine learning approaches

et al. 2021

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Background: d-glutamate, which is involved in N-methyl-d-aspartate receptor modulation, may be associated with cognitive ageing. Aims: This study aimed to use peripheral plasma d-glutamate levels to differentiate patients with mild cognitive impairment (MCI) and Alzheimer’s disease (AD) from healthy individuals and to evaluate its prediction ability using machine learning. Methods: Overall, 31 healthy controls, 21 patients with MCI and 133 patients with AD were recruited. Serum d-glutamate levels were measured using high-performance liquid chromatography (HPLC). Cognitive deficit severity was assessed using the Clinical Dementia Rating scale and the Mini-Mental Status Examination (MMSE). We employed four machine learning algorithms (support vector machine, logistic regression, random forest and naïve Bayes) to build an optimal predictive model to distinguish patients with MCI or AD from healthy controls. Results: The MCI and AD groups had lower plasma d-glutamate levels (1097.79 ± 283.99 and 785.10 ± 720.06 ng/mL, respectively) compared to healthy controls (1620.08 ± 548.80 ng/mL). The naïve Bayes model and random forest model appeared to be the best models for determining MCI and AD susceptibility, respectively (area under the receiver operating characteristic curve: 0.8207 and 0.7900; sensitivity: 0.8438 and 0.6997; and specificity: 0.8158 and 0.9188, respectively). The total MMSE score was positively correlated with d-glutamate levels ( r = 0.368, p < 0.001). Multivariate regression analysis indicated that d-glutamate levels were significantly associated with the total MMSE score ( B = 0.003, 95% confidence interval 0.002–0.005, p < 0.001). Conclusions: Peripheral plasma d-glutamate levels were associated with cognitive impairment and may therefore be a suitable peripheral biomarker for detecting MCI and AD. Rapid and cost-effective HPLC for biomarkers and machine learning algorithms may assist physicians in diagnosing MCI and AD in outpatient clinics.

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Section: Discussionmentioning

confidence: 99%

Plasma d-glutamate levels for detecting mild cognitive impairment and Alzheimer’s disease: Machine learning approaches

et al. 2021

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Section: Discussionmentioning

confidence: 99%

“…Studies for the determination of levetiracetam in human plasma [13][14][15][16][17] are sparse. LC with ultraviolet detection [13,14], LC-photodiode array detection [15], GC-MS [16], and LC-tandem MS [17][18][19][20][21][22][23] methods have been developed for the determination of levetiracetam. Some of these studies require complex sample preparation procedures, such as SPE and evaporation under a nitrogen stream [15][16][17][18][19], whereas others required protein precipitation [13,14,[20][21][22][23].…”

Section: Discussionmentioning

confidence: 99%

“…Various analytical techniques (HPLC, CE, and GC) are typically used for the separation of drugs, and among them, HPLC is the most common approach [11,12]. Despite the importance, there are few analytical methods reported for the determination of levetiracetam in human plasma [13][14][15][16][17][18][19][20][21][22][23]. Further, online heart-cutting LC methods have not been reported for the determination of levetiracetam in plasma.…”

Section: Introductionmentioning

confidence: 99%

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Determination of levetiracetam in human plasma by online heart‐cutting liquid chromatography: Application to therapeutic drug monitoring

Önal¹,

Kul

Ozdemir

et al. 2020

J of Separation Science

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Levetiracetam is an antiepileptic drug for the treatment of psychiatric patients. In this study, a selective, straightforward, and rapid online heart‐cutting liquid chromatography method was developed for the therapeutic drug monitoring of levetiracetam. This method allows for the determination of levetiracetam in human plasma without complex sample preparation. The mobile phases consisted of 30 mM aq. orthophosphoric acid solution/methanol (70:30) at a flow rate of 1 mL/min for the first system and 10 mM aq. orthophosphoric acid solution/methanol (55:45) at a flow rate of 1 mL/min for the second system. The first separation was carried out on a GL Sciences Intersil ODS‐3 column (4.6 mm × 150 mm, 3 µm) and the second separation was carried out on a Restek Ultra PFPP column (4.6 mm × 150 mm, 5 µm). The detection was carried out at 205 nm for both systems. The method was validated for selectivity and linearity, which were in the 6–60 µg/mL range. Intra‐ and interassay accuracies were <112.6%, and the intra‐ and interassay precisions were <6.4% for all quality control samples. The lower limit of quantitation was 6 µg/mL. The developed method was successfully applied for therapeutic drug monitoring of plasma samples from patients.

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“…This is a clinical field devoted to the monitoring of the blood level of different classes of drug molecules. In this framework, it is currently of interest to develop time‐ and cost‐effective techniques complementary to those currently adopted (mainly high‐performance liquid chromatography‐mass spectrometry and immunoassay) …”

Section: Introductionmentioning

confidence: 99%

Functionalization of nanostructured gold substrates with chiral chromophores for SERS applications: The case of 5‐Aza[5]helicene

et al. 2018

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Nanostructured gold thin films can be fabricated by controlled pulsed laser deposition to get efficient sensors, with uniform morphology and optimized plasmon resonance, to be employed as plasmonic substrates in surface enhanced Raman scattering spectroscopy. By attaching 5-aza[5]helicen-6-yl-6-hexanethiol to such gold nanostructures, used in a previous work for label-free drug sensing with biomedical purposes, we successfully prepared functionalized substrates with remarkable surface enhanced Raman scattering activity. The long-term motivation is to develop probes for drug detection at low concentrations, where sensitivity to specific chiral targets is required.

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A simple and cost‐effective HPLC‐UV method for the detection of levetiracetam in plasma/serum of patients with epilepsy

Cited by 15 publications

References 26 publications

Plasma d-glutamate levels for detecting mild cognitive impairment and Alzheimer’s disease: Machine learning approaches

Plasma d-glutamate levels for detecting mild cognitive impairment and Alzheimer’s disease: Machine learning approaches

Determination of levetiracetam in human plasma by online heart‐cutting liquid chromatography: Application to therapeutic drug monitoring

Functionalization of nanostructured gold substrates with chiral chromophores for SERS applications: The case of 5‐Aza[5]helicene

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