Drug-induced parkinsonism

Drug-induced parkinsonism (DIP) is the most common drug-induced movement disorder and is most commonly associated with antipsychotic drugs, monoamine reuptake inhibitors, and calcium channel blockers. DIP manifests as a typical movement disorder, which makes it practically indistinguishable from idiopathic Parkinson's disease (PD) and requires differential diagnosis. DIP symptoms develop fairly quickly (hours to weeks) after the antipsychotic is started or after the dose is increased. Therefore, DIP is predominantly a clinical diagnosis that must be kept in mind when a patient develops typical symptoms during treatment onset or increasing the dose of drugs that most often lead to such an adverse reaction (ADR). DIP evaluation includes using the Naranjo algorithm, which helps assess a causal relationship between drug intake and the development of parkinsonism symptoms. The primary DIP treatment is the reduction of the dose of the inducer drug, or its cancellation, or replacement with another drug. In patients with schizophrenia and antipsychotic-induced DIP, dose reduction, replacement with another medication, or prescription of a drug with anticholinergic activity may be possible. The awareness of the doctor and the patient about the possibility of developing this ADR is crucial in the prevention of DIP. Therefore, choosing a drug with the lowest risk of developing DIP is necessary for pharmacotherapy.

Upaya Peningkatan Pengetahuan tentang Efek Samping Obat pada Warga Dasa Wisma dalam Upaya Penerapan Farmakovigilans

The lack of public understanding and awareness about safe drug information and misleading social media news related to drug use is a new challenge that cannot be underestimated. The purpose of this community service was to overcome the problem of the lack of public knowledge about side effects, especially as an effort to implement pharmacovigilance in the community. The method started from intervention to the community included providing education (socialization) on the dangers of drug side effects and workshops on the use of the method of measuring drug side effects using the Naranjo algorithm. The target of this activity was the residents of the Mertoudan, Mojosongo, Surakarta would get additional knowledge about drug side effects and know how to monitor it, also creating people who are aware of drug side effects. This activity increased the knowledge of residents about drug side effects and the ability to measure the probability of the occurrence of drug side effects. The implementation of this activity received a good response from the Chairperson of Dasa Wisma and the participants, who were very enthusiastic to increase their knowledge about drug side effects and the measurement method with the Naranjo algorithm.

Capecitabine-induced leukoencephalopathy in a patient with triple-negative breast cancer: A case report and review of the literature

Introduction Capecitabine is an orally administered prodrug that converts preferentially to 5-fluorouracil within tumors, resulting in enhanced concentrations of 5-fluorouracil in tumor tissue. The use of capecitabine has shown efficacy in the metastatic setting for breast cancer, and more recently, efficacy as adjuvant therapy for triple-negative breast cancer (TNBC). Capecitabine has been shown to be well tolerated with minimal side effects, but the incidence of leukoencephalopathy is rare with a risk of less than one percent. Case report We report on a 34-year-old female patient with left TNBC, moderately differentiated, stage IIB that experienced symptoms of neurotoxicity following initiation of adjuvant chemotherapy with capecitabine. Management and outcome Naranjo Algorithm Assessment score of nine indicated patient had drug-induced leukoencephalopathy leading to discontinuation of capecitabine and resolution of the neurotoxicity symptoms. Discussion Early detection of capecitabine-induced neurotoxicity by magnetic resonance imaging is crucial as symptoms may be reversible to the condition that capecitabine is immediately discontinued.

Pharmacovigilance in Neuroscience

Background: Adverse drug reactions (ADRs) have a high impact on morbidity and mortality of the population, becoming a public health issue. Studying and publishing about these is referred as pharmacovigilance.Objective: To describe and compare the adverse reactions produced by drugs of nervous system action (CNS-D) and neurological ADRs produced by drugs of systemic action (Sys-D). To further develop the need of reporting adverse reactions. Methods: An observational, cross-sectional, retrospective study performed on a database of neurological consultations which took place at the Neurology department. Patients meeting the inclusion criteria were selected and divided into two groups: Sys-D and CNS-D. Demographic and neurological variables were analyzed. Parametric and non-parametric statistics were used according to distribution. The Naranjo Algorithm (NA) was used to define causality.Results: 71 ADRs were described, from which 63.38% (n=45) were produced by CNS-D, especially antiepileptics by 47% (n=21) and psycholeptics by 44%. Of the total, 36.62% (n=26) were caused by Sys-D, such as antineoplastics (n=9) and antibiotics (n=9), being Cefepime the most frequent. The diagnosis of ADRs caused by a Sys-D was delayed prolonging hospitalization (p 0.05) due to a lower NA score (p 0.003) compared to the CNS-D group.Conclusion: Multiple frequently used drugs of systemic action, such as antineoplastics and antibiotics, generate neurological adverse effects. From our analysis, it was presumed that the suspicion of a neurological ADR caused by these drugs was scarce, thus causing a higher morbidity for the patient.

A cross sectional survey of side effects of antiretroviral (ARV) in outpatients HIV by Naranjo Algorithm

Background: The main modality in HIV patients is the administration of long-treatment antiretroviral therapy (ARV). One of the problems from the use of ARV therapy is the side effects that can reduce patient compliance in taking medication, which has the potential to cause treatment failure. Objective: This study aims to examine the side effects and their causality in the use of ARVs in outpatient HIV patients at the VCT Clinic, Bhayangkara H.S. Hospital. Samsoeri Mertojoso Surabaya. Methods: This research was a prospective observational study with a cross-sectional design. Side effect data were taken from HIV patients by interview using the Naranjo algorithm. HIV patients who met the inclusion criteria were included in the study sample using consecutive sampling. This research was conducted from January to March 2020. Results: There were 72 outpatient HIV patients who met the inclusion criteria. The most opportunistic infections found in HIV patients are tuberculosis and Pneumocystis pneumonia. The results showed that the most common side effects experienced by patients were dizziness (43%), nausea and vomiting (31%), and rash (11%) with the highest Naranjo score being in the probable category of 86%. The Naranjo score in HIV patients with opportunistic infections and with comorbidities was significantly smaller than those in HIV patients without opportunistic infections or without comorbidities with independent t-test (P <0.05). Conclusion: The side effects in HIV patients while undergoing treatment with antiretroviral therapy are classified as a minor side effect and the cause of the side effects that occur is thought to be due to the probable category of ARV therapy. Keywords: HIV Patients, Antiretroviral, Side Effects, Naranjo's Algorithm.

A case of olanzapine-associated rhabdomyolysis

AimsTo describe the case of olanzapine-associated rhabdomyolysis in a 20-year-old patient with a suspected diagnosis of paranoid schizophrenia.MethodA 20-year-old male Caucasian patient was admitted to the Psychiatric Department with a one-month history of irrational behavior, talking to himself, persecutory delusions, and poor sleep. He was prescribed oral olanzapine at a dose of 10 mg per day. After two days of olanzapine monotherapy, the patient experienced muscle jerks in the legs. Four days after the initiation of olanzapine treatment, he complained about fatigue and weakness in the lower extremities along with myalgia. Physical examination revealed decreased muscle power with no extrapyramidal symptoms. Blood chemistry showed serum creatine kinase (CK) and serum lactate dehydrogenase (LDH) of 9,725 U/L and 843 U/L, respectively, on day four of the therapy. The Naranjo algorithm score of 6 suggested that olanzapine was the probable cause of rhabdomyolysis. A diagnosis of drug-induced rhabdomyolysis was established from the background of blood tests (increased serum CK and LDH levels), clinical presentation (fatigue and weakness in the lower extremities, muscle jerks, and myalgia), and Naranjo algorithm score of 6 for olanzapine. On suspicion of its contribution to rhabdomyolysis, olanzapine was immediately withdrawn. The patient was referred to the intensive care unit. To prevent acute renal failure, high-volume alkaline diuresis was initiated. After consulting a clinical pharmacologist, the patient's primary physician decided to perform a pharmacogenetic test to develop an individualized treatment regimen. Pharmacogenetic test results were interpreted using the PGX2 software (Meditsina LLC, Moscow, Russia). The test revealed that the patient was a homozygous mutant for CYP2D6*4, which corresponds to CYP2D6 PM phenotype. With this in mind, trifluoperazine was prescribed at a daily dose of 10 mg instead of olanzapine as recent data indicate that trifluoperazine is metabolized by CYP1A2 and UGT1A4 instead of CYP2D6. Subsequently, the patient recovered well and was discharged without any nephrological sequelae.ResultRecent research demonstrates that CYP2D6 is one of the most important isoenzymes implicated in drug metabolism because the CYP2D6 gene is highly polymorphic. Few reports on the association between olanzapine use and rhabdomyolysis have been published to date, and the present case report draws attention to pharmacogenetic testing which allowed the psychiatrist to prescribe another antipsychotic with no risk of rhabdomyolysis.ConclusionThe presented case demonstrates that pharmacogenetic-guided personalization of treatment may allow selecting the best medication and determining the right dosage, resulting in the reduced risk of adverse drug reactions and pharmacoresistance.

Psychometric validation of the modified Naranjo algorithm used in homeopathy for chronic cases

Objectives The modified Naranjo algorithm assesses the physician assigned cause-effect relationship for homeopathic medicines. It is being adopted in homeopathy researches, but not yet validated systematically. We intended to validate the modified Naranjo algorithm by examining its psychometric properties. Methods An online survey sought agreement of 25 experts on the 10 items of the tool on 5-point agreement scale. Next, 285 responses from collected prospectively from chronic cases enrolled under the clinical verification program of the council in 2018 were subjected to testing of construct validity using exploratory principal component analysis (PCA). Confirmatory factor analysis (CFA; n=150) was performed to verify the goodness-of-fit of the model. Reliability was tested using internal consistency, test–retest reliability, and inter-rater reliability by kappa statistics. Results Experts’ responses mean values were 4 or higher (i.e. responses were relevant) and standard deviations were less than 1 (i.e. less heterogeneous). In PCA using varimax, all the items loaded above the pre-specified value of 0.4 and identified 4 components explaining 64.1% of variation. The goodness-of -fit of the 4-component CFA model was acceptable (chi-square 89.253, p<0.001). Internal consistency (Cronbach’s alpha 0.7) was borderline; test–retest reliability was acceptable. Kappa statistics was moderate to fair, but poor for few of the items. Conclusions Statistical evaluations indicate that the modified Naranjo algorithm is useful, but needs improvement.

A STUDY OF AGREEMENT BETWEEN WHO-UPPSALA MONITORING CENTRE CRITERIA, NARANJO ALGORITHM, AND LIVERPOOL ALGORITHM FOR CAUSALITY ASSESSMENT OF ADVERSE DRUG REACTIONS

Objective: A standard causality assessment tool of an adverse drug reaction (ADR) is essential to compute the risk-benefit assessment of the medication taken by the patient and categorize its relationship likelihood. It should be reproducible and should not differ with the background and experience of the evaluator. Though there are a large number of causality assessment tools, none is unanimously accepted worldwide. So, this study was done to assess the agreement between three frequently used methods of causality assessment, the World Health Organisation-Uppsala Monitoring Centre (WHO-UMC) system, the Naranjo’s algorithm, and the Liverpool algorithm. Methods: 172 ADR forms from the pharmacovigilance unit were randomly selected for the study. Causality assessment was done using three different methods, the WHO-UMC system, Naranjo’s algorithm, and the Liver pool algorithm. Cohen’s Kappa statistics was applied to look for agreement between the causality assessment methods. Results: The agreement between the WHO-UMC criteria and Naranjo’s algorithm was the highest (136), with a Kappa value of 0.511, suggesting a moderate level of agreement. A maximum number of disagreements were noted between the WHO-UMC system and the Liverpool algorithm method (110). Conclusion: A moderate agreement exists between the WHO-UMC system and the Naranjo algorithm. There is poor agreement between the Liverpool algorithm and the other two scales. Therefore, it is recommended that both the WHO-UMC system and the Naranjo algorithm be used for causality assessment of ADRs.

Validation of a novel causality assessment scale for adverse events in non-small cell lung carcinoma patients treated with platinum and pemetrexed doublet chemotherapy

Aim: Accurate causality assessment (CA) of adverse events (AEs) is important in clinical research and routine clinical practice. The Naranjo scale (NS) used for CA lacks specificity, leading to a high rate of false positive causal associations. NS is a simple scale for CA; however, its limitations have reduced its popularity in favour of other scales. We therefore attempted to improvise the algorithm by addressing specific lacunae in NS. Methods: We attempted to modify the existing NS by (a) changing the weightage given to certain responses, (b) achieving higher resolution to certain responses for delineating drug related and unrelated AEs and (c) modifying the slabs for classification of association as ‘likely’ and ‘unlikely’. The new scale, named as the Sharma-Nookala-Gota (SNG) algorithm, was evaluated in a training set of 19 AEs in a tertiary care cancer hospital in western India, and further validated in a set of 104 AEs. Consensus of four physician opinion was taken as gold standard for comparison. Results: Of the 19 AEs in the training set, 6 were described by the treating physician as ‘not related’ and 13 as related to the drug. The SNG algorithm had 100% concordance with physician opinion, whereas the NS had only 73.7% concordance. NS showed a tendency to misclassify AEs as ‘related’ when they were indeed ‘not related’. In the validation set of 104 AEs, NS and SNG algorithms misclassified 30 and 2 AEs, respectively, leading to a concordance of 70.2% and 98.1%, respectively, with physician opinion. Conclusion: Decisive modifications of the NS resulted in the SNG scale, with superior specificity while retaining sensitivity against the gold standard. Plain Language Summary SNG algorithm – A novel tool for causality assessment of adverse drug reactions Adverse events (AEs) can cause increased morbidity, hospitalisation, and even death. Hence it is essential to recognise AEs and to establish their correct causal relationship to a drug. Many causality assessment methods, scales and algorithms are available to assess the relationship between an AE and a drug. The Naranjo algorithm is most commonly employed in spite of its many drawbacks as it is simple to use. Concerns have been raised regarding the performance of the scale, and researchers have tried to answer them, but none of them could address all issues satisfactorily. We too experienced many problems while using it in our routine clinical practice and in clinical trials. For instance, the Naranjo scale is non-specific and shows a bias toward implicating the drug as the causal factor for AEs. This improper assessment has often led to drug discontinuation, thereby compromising the efficacy of treatment. Hence, we modified the existing Naranjo scale to a new one (the Sharma-Nookala-Gota – SNG algorithm) to address these shortcomings. We piloted the SNG causality assessment algorithm in patients suffering from AEs due to various drugs. The SNG algorithm was found to have good concordance with the physicians’ assessment of causality. As a next step, we validated the SNG algorithm in patients receiving a standard drug combination of pemetrexed and carboplatin for lung cancer combination. Out of the 104 AEs observed in 65 patients, the SNG causality assessment algorithm showed good concordance (except in two cases) with the physicians’ decision of causality assessment, while the Naranjo algorithm was not so successful. Hence, the SNG algorithm can be a better guide for causality assessment of AEs.