Causality Assessment Tool Research Articles

Vaccine-associated paralytic poliomyelitis in oral polio vaccine recipients: disproportionality analysis using VAERS and systematic review

ABSTRACT Background Vaccine-associated paralytic poliomyelitis (VAPP) is a rare adverse event of oral poliovirus vaccines (OPV), particularly affecting immunodeficient individuals. Research design and methods This study aimed to (1) Assess the association between OPV and VAPP using Vaccine Adverse Event Reporting System (VAERS) database (2) Outline patient characteristics and risk factors associated with the occurrence of VAPP in OPV recipients through a systematic review of case reports and case series. A disproportionality analysis was conducted using the data from VAERS, encompassing adverse events reported from 1990 till February 2023. Additionally, we conducted a systematic review of case reports and case series using PubMed, Scopus, and Embase databases. Results The VAERS data revealed 130 VAPP reports among 1,739,903 OPV linked adverse events, with year 2010 reporting the strongest association. The systematic review of 37 studies highlighted VAPP occurrence within 2 months to 4 years post-vaccination, typically with acute flaccid paralysis. Immunodeficiency and perianal abscess emerged as major risk factors. Out of the 37 included studies, 27 showed consistent causal association of VAPP with OPV using WHO-AEFI causality assessment tool. Conclusion The study emphasized the seriousness of VAPP and highlights its association with OPV, identifying immunodeficiency as a prominent contributor to VAPP manifestation.

Minimising Adverse Drug Reactions and Verifying Economic Legitimacy-Pharmacogenomics Implementation in Children (MARVEL- PIC): protocol for a national randomised controlled trial of pharmacogenomics implementation

IntroductionDNA-informed prescribing (termed pharmacogenomics, PGx) is the epitome of personalised medicine. Despite international guidelines existing, its implementation in paediatric oncology remains sparse.Methods and analysisMinimising Adverse Drug Reactions and Verifying Economic...

ALDRESS: A Retrospective Pilot Study to Develop a Pharmacological Causality Algorithm for Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS).

Background: The drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome represents a severe form of drug hypersensitivity reaction characterized by significant morbidity, mortality, and long-term sequelae, coupled with limited therapeutic avenues. Accurate identification of the causative drug(s) is paramount for acute management, exploration of safe therapeutic alternatives, and prevention of future occurrences. However, the absence of a standardized diagnostic test and a specific causality algorithm tailored to DRESS poses a significant challenge in its clinical management. Methods: We conducted a retrospective case-control study involving 37 DRESS patients to validate a novel causality algorithm, the ALDRESS, designed explicitly for this syndrome, comparing it against the current standard algorithm, SEFV. Results: The ALDRESS algorithm showcased superior performance, exhibiting an 85.7% sensitivity and 93% specificity with comparable negative predictive values (80.6% vs. 97%). Notably, the ALDRESS algorithm yielded a substantially higher positive predictive value (75%) compared to SEFV (51.40%), achieving an overall accuracy rate of 92%. Conclusions: Our findings underscore the efficacy of the ALDRESS algorithm in accurately attributing causality to drugs implicated in DRESS syndrome. However, further validation studies involving larger, diverse cohorts are warranted to consolidate its clinical utility and broaden its applicability. This study lays the groundwork for a refined causality assessment tool, promising advancements in the diagnosis and management of DRESS syndrome.

Accuracy in patient-reported adverse drug reactions and their recognition: a mixed-methods study.

The causality assessment tool can be utilized to assist patients in identifying adverse drug reactions (ADRs). To evaluate the accuracy of the causality assessment tool for patients identifying ADRs compared to assessments made by pharmacists, and to explore how patients recall and recognize symptoms as ADRs. Mixed methods study consisting of self-administered questionnaires (phase 1) and semi-structured, face-to-face interviews (phase 2) with patients who had experienced ADRs in the past year at a tertiary care hospital in Thailand. Out of 769 questionnaires, 716 were returned and 622 of these were both valid and had at least one ADR (86.8%). Classification of patient-reported symptoms using the causality assessment tool found 12 (1.9%) highly-probable ADRs, 399 (64.1%) probable ADRs, 207 (33.3%) possible ADRs, and 4 (0.6%) that were not classified as ADRs. There was fair agreement between patient-assessed and pharmacist-assessed causality classifications using the Naranjo algorithm (K = 0.268) and the World Health Organization Uppsala Monitoring Centre (WHO-UMC) criteria (K = 0.373). The timing relationship between the occurrence of symptoms and administration of a suspected drug was the most frequently mentioned reason that patients gave for recalling and recognizing suspected ADRs. Promoting the causality assessment tool for use by patients in collaboration with healthcare professionals is likely to enhance patients' ability to correctly identify ADRs and ultimately contribute to increased medication safety.

Comparing patient reported and medical record data of adverse drug reactions to anti-seizure drugs.

Anti-seizure drugs (ASDs) can potentially cause serious adverse drug reactions (ADRs). Patient self-reporting can increase the rate of ADR detection, but studies examining patient self-reporting of ADRs caused by ASDs are lacking. To determine the characteristics of ADRs reported by patients receiving ASDs, assess laboratory data and medical record confirmation of patient-reported ADRs, and explore factors associated with laboratory data and medical record confirmation. A self-reporting questionnaire was distributed to patients prescribed ASDs at outpatient clinics. Patients assessed the causality of suspected ADRs using Causality Assessment Tool. Naranjo's algorithm was used by researchers for causality assessment. Medical records were used to gather information on ADR symptoms, ASD medication, and abnormal laboratory data. From 478 distributed questionnaires, 93.1% completed the questionnaire and 67.4% of respondents reported at least one ADR. The most common ADRs were drowsiness (50.7%), dizziness (9.7%), and ataxia (4.3%). For causality, suspected ADRs were classified as possible in 52.3% of cases and probable in 46.3% of cases by patients, and possible in 64.7% of cases and probable in 25.7% of cases by researchers. Only 12.7% of patients had laboratory data and/or medical record confirmation of suspected ADRs. The psychiatry clinic was less likely to confirm suspected ADRs compared to the epilepsy clinic (OR = 0.412, p = 0.022). Confirmation of patient-reported ADRs with either laboratory data or medical records was uncommon. Recording patient-reported ADRs in patients' medical history and monitoring laboratory tests related to patient-reported symptoms should be promoted to increase the safety of ASD treatment.

Idiosyncratic DILI and RUCAM under One Hat: The Global View

Drugs are prescribed worldwide to treat diseases but with the risk of idiosyncratic drug-induced liver injury (iDILI). The most important difficulty is how best to establish causality. Based on strong evidence and principles of artificial intelligence (AI) to solve complex processes through quantitative algorithms using scored elements, progress was achieved with the Roussel Uclaf Causality Assessment Method (RUCAM) in its original and updated versions, often viewed now as the gold standard. As a highly appreciated diagnostic algorithm, the RUCAM is in global use with around 100,000 iDILI cases published worldwide using RUCAM to assess causality, largely outperforming any other specific causality assessment tool in terms of case numbers. Consequently, the RUCAM helps to establish a list of top-ranking drugs worldwide implicated in iDILI and to describe clinical and mechanistic features of iDILI caused by various drugs. In addition, the RUCAM was recently applied in iDILI cases of patients treated for coronavirus disease 2019 (COVID-19) infections or cancer patients treated with immune checkpoint inhibitors (ICIs), as well as in the search for new treatment options with conventional drugs in iDILI. Analyses of RUCAM-based iDILI cases are helpful to support pathogenetic steps like immune reactions, genetic predisposition as evidenced by human leucocyte antigens (HLA) genotypes for selected drugs, and the role of the gut microbiome. To achieve consistency in data collection, analysis, and specific clinical and pathogenetic presentation, researchers, regulatory agencies, and pharmaceutical firms should place iDILI and the updated RUCAM as the causality tool under one and the same hat in review articles and clinical guidelines for the diagnosis and treatment of iDILI.

An econometric identification of ineffective common-cold advertising

PurposeThis study aims to highlight potential savings in advertising budgets.Design/methodology/approachThis study uses modern computer-based tools including stochastic dominance to check if advertising expenses are increasing sales by using modern causality assessment tools which allow for nonlinearities and use sophisticated assessment of causal impact of ads on sales.FindingsThis study identifies specific media spots where ad budget savings are possible. The marketing managers can take the next step to make small-scale local experiments to reassess this study’s findings.Research limitations/implicationsThis study is a statistical observational assessment not based on controlled experiments.Practical implicationsThe authors have tools to identify ineffective advertising which can produce huge savings for the organization. The over-the-counter cold remedies have become important due to the pandemic. The tools have wider applicability in marketing research.Social implicationsLess wasteful expenses always benefit the society.Originality/valueTo the best of the authors’ knowledge, this may be the first such attempt to use sophisticated causal identification tools. Remedies for the common cold sold by seven major US retailers help identify specific retailers and specific media with negative returns on investment.

#6706 ACUTE KIDNEY DISEASE FOLLOWING COVID-19 VACCINATION: A RETROSPECTIVE, SINGLE- CENTER STUDY

Abstract Background and Aims The rare de novo or relapsed kidney diseases associated with coronavirus disease 2019 (COVID-19) vaccination have been increasingly reported. The aim of the study was to investigate the incidence, characteristics, and outcome of acute kidney disease (AKD) following COVID-19 vaccination. Method This retrospective study scrutinized the data from renal registry in a single academic medical center from Jan. 1st, 2020, to Apr. 30th, 2022. Patients who developed AKD within 90 days after COVID-19 vaccination were first included. Naranjo score as a causality assessment tool for adverse vaccination reaction and charts review by peer nephrologists were utilized for the exclusion of other causes. The etiologies of AKD, their characteristics, treatment, and outcome attributing to the COVID-19 vaccines were examined (Fig. 1). Results Twenty-seven aged 23 to 80 patients with AKD were identified from 1897 patients (incidence of 6.3 per 1000 patient-years). Their Naranjo score was 7.7± 1.5, and 14 of 27 patients (51.9%) had definite diagnosis (Naranjo score ≥ 9). They incorporated both glomerular disease (n = 16) including IgA nephropathy (n = 7), anti-neutrophil cytoplasmic antibodies-associated glomerulonephritis (AAN) (n = 4), membranous glomerulonephritis (n = 3), minimal change disease (MCD) (n = 2), and chronic kidney disease (CKD) with acute deterioration (n = 11). The majority (21 of 27, 77.8%) of COVID-19 vaccination was messenger RNA (mRNA)-based regimen. Four patients (14.8%) rapidly progressed to end stage kidney disease (ESKD) requiring dialysis despite aggressive management. Extra-renal features such as pulmonary hemorrhage, myopericarditis and hepatitis/pancreatitis were observed in 4 patients. Conclusion In summary, AKD after COVID-19 vaccination may occur with more alarm in this renal registry. In addition to GN, patients with pre-existing moderate to severe CKD should also receive more intensive evaluation before vaccination despite the established benefits of vaccination in this vulnerable population likely outweigh the risk.

Acute kidney disease following COVID-19 vaccination: a single-center retrospective study.

Rare cases of de novo or relapsed kidney diseases associated with vaccination against coronavirus disease 2019 (COVID-19) have been increasingly reported. The aim of this study was to report the incidence, etiologies, and outcomes of acute kidney disease (AKD) following COVID-19 vaccination. This retrospective study extracted cases from renal registry of a single medical center from 1 March 2021 to 30 April 2022, prior to the significant surge in cases of the Omicron variant of COVID-19 infection in Taiwan. Adult patients who developed AKD after COVID-19 vaccination were included. We utilized the Naranjo score as a causality assessment tool for adverse vaccination reactions and charts review by peer nephrologists to exclude other causes. The etiologies, characteristics, and outcomes of AKD were examined. Twenty-seven patients (aged 23 to 80 years) with AKD were identified from 1,897 vaccines (estimated rate of 13.6 per 1000 patient-years within the renal registry). A majority (77.8%) of vaccine received messenger RNA-based regimens. Their median (IQR) Naranjo score was 8 (6-9) points, while 14 of them (51.9%) had a definite probability (Naranjo score ≥ 9). The etiologies of AKD included glomerular disease (n = 16) consisting of seven IgA nephropathy, four anti-neutrophil cytoplasmic antibodies-associated glomerulonephritis (AAN), three membranous glomerulonephritis, two minimal change diseases, and chronic kidney disease (CKD) with acute deterioration (n = 11). Extra-renal manifestations were found in four patients. Over a median (IQR) follow-up period of 42 (36.5-49.5) weeks, six patients progressed to end-stage kidney disease (ESKD). Besides glomerulonephritis (GN), the occurrence of AKD following COVID-19 vaccination may be more concerning in high-risk CKD patients receiving multiple doses. Patients with the development of de novo AAN, concurrent extra-renal manifestations, or pre-existing moderate to severe CKD may exhibit poorer kidney prognosis.

Comparison of the Liverpool Causality Assessment Tool vs. the Naranjo Scale for predicting the likelihood of an adverse drug reaction: A retrospective cohort study.

The aim of this study is to compare the Liverpool Causality Assessment Tool vs. Naranjo Scale for screening suspected adverse drug reaction (ADR) cases. We retrospectively reviewed patient charts with a history of suspected ADR, scored using both tools, and determined how each correlates with laboratory and other investigations. A total of 924 charts from the Clinical Pharmacology Clinic at the London Health Sciences Centre were reviewed, and 529 charts contained objective findings to support or against the diagnosis of ADR. The participant age ranged from 1 month to 93 years. We determined that the sensitivity (SN) and specificity (SP) of Liverpool and Naranjo tools for predicting ADRs with scores ranging from Possible to Definite were considered positive and Unlikely/Doubtful as negative for ADR. These results were confirmed by laboratory or clinical (re-challenge) testing in 529 cases. Liverpool causality tool had SN of 97.2 ± 2.4% and SP of 2.3 ± 1.57%. The positive (PPV) and negative predictive values (NPV) were 34.1 and 61.5%, respectively. The Naranjo Scale had SN of 81.2 ± 5.69% and SP of 13.2 ± 3.56%. PPV and NPV were 32.7 and 57.5%, respectively. The Liverpool Causality Assessment Tool is a more sensitive tool than the Naranjo Scale in the assessment of possible ADRs, but both tools have poor SP. The Liverpool Tool can be a useful screening tool in settings where other tests may not be readily available. However, the low PPV and NPV of both tools suggest that to pursue further testing is needed to confirm or deny an ADR.

MARVEL-PIC: minimising adverse drug reactions and verifying economic legitimacy: pharmacogenomic implementation in children

Background: Adverse drug reactions account for 30% of hospital admissions and cost the healthcare system 1.4 billion per annum. Concerningly, 60% of paediatric oncology patients experience adverse drug reactions during cancer treatment, of which 20% are severe or life threatening. Importantly, 75% of adverse drug reactions reported in paediatric patients are preventable through greater pharmacovigilance and pharmacogenetic testing. Objective: The of this research program (MARVEL-PIC) is to reduce preventable adverse drug reactions in paediatric oncology patients through an extensive pharmacogenetics program that integrates broad pharmacogenomic implementation and education and training frameworks. Method: This first of its kind in paediatric oncology randomised control trial (RCT) randomises patents to receive extended pharmacogenomic results (derived from all current actionable pharmacogenomics variants as per international guidelines (PGx) or standard of care (SoC) (control arm) for a period of 12 weeks. Symptom reporting will be performed via prospective surveys (NCI Ped-PRO-CTCAE) followed by formal CTCAE grading of symptoms by academic pharmacists. The Liverpool adverse drug reaction (ADR) causality assessment tool (CAT) will be used to ascribe causality. Health economics analysis will involve actual costs calculation collected via the Department of Health and the Centre for Victorian Data Linkage (CVDL) and Services Australia. Results: We have piloted a pipeline for using a whole genome sequencing approach to call and verify diplotypes (and subsequent metaboliser states) for a range of pharmacogenes. To date this approach is feasibly and 80% of paediatric patients have a high risk genotype identified. Conclusion: We have piloted a WGS bioinformatic approach to verifying pharmacogenes for the purposes MARVEL-PIC. This approach allows for rapid turnaround and repurposes WGS used for tumour biology for the purposes of precision medicine, in an effort to reduce AME. We look forward to reporting on the results of the MARVEL-PIC trial in due course.

A novel quantitative computer-assisted drug-induced liver injury causality assessment tool (DILI-CAT).

Background and aimsWe hypothesized that a drug’s clinical signature (or phenotype) of liver injury can be assessed and used to quantitatively develop a computer-assisted DILI causality assessment-tool (DILI-CAT). Therefore, we evaluated drug-specific DILI-phenotypes for amoxicillin-clavulanate (AMX/CLA), cefazolin, cyproterone, and Polygonum multiflorum using data from published case series, to develop DILI-CAT scores for each drug.MethodsDrug specific phenotypes were made up of the following three clinical features: (1) latency, (2) R-value, and (3) AST/ALT ratio. A point allocation system was developed with points allocated depending on the variance from the norm (or “core”) for the 3 variables in published datasets.ResultsThe four drugs had significantly different phenotypes based on latency, R-value, and AST/ALT ratio. The median cyproterone latency was 150 days versus < 43 days for the other three drugs (median: 26 for AMX/CLA, 20 for cefazolin, and 20 for Polygonum multiflorum; p<0.001). The R-value for the four drugs was also significantly different among drugs (cyproterone [median 12.4] and Polygonum multiflorum [median 10.9]) from AMX/CLA [median 1.44] and cefazolin [median 1.57; p<0.001]). DILI-CAT scores effectively separated cyproterone and Polygonum multiflorum from AMX/CLA and cefazolin, respectively (p<0.001). As expected, because of phenotypic overlap, AMX/CLA and cefazolin could not be well differentiated.ConclusionsDILI-CAT is a data-driven, diagnostic tool built to define drug-specific phenotypes for DILI adjudication. The data provide proof of principle that a drug-specific, data-driven causality assessment tool can be developed for different drugs and raise the possibility that such a process could enhance causality assessment methods.

RECAM: A New and Improved, Computerized Causality Assessment Tool for DILI Diagnosis.

RECAM: A New and Improved, Computerized Causality Assessment Tool for DILI Diagnosis.

Evaluation of voriconazole related adverse events in pediatric patients with hematological malignancies.

Despite therapeutic drug monitoring and pharmacogenetic-guided dose selection are recommended for pediatric patients, safety of voriconazole is mostly monitored by clinical assessment. Having comprehensive knowledge of safety profile and distinguishing incidental events from the reactions that are truly related to voriconazole use are crucial for safer and uninterrupted treatment. This study aimed to address adverse reactions during the first month of voriconazole use by systematically evaluating retrospective records of all adverse events. Patients/Methods: It is a single-center, retrospective analysis of patients who received voriconazole from 1 September 2010 to 1 September 2020. Severity of abnormal findings in medical records were systematically graded. Causality between voriconazole and the events was evaluated by Liverpool Causality Assessment Tool (LCAT), Naranjo Algorithm and World Health Organization Causality Assessment System. The events with possible or probable causal relation to voriconazole are classified as adverse reaction. Records of 45 patients included in the study. The overall frequency of adverse reactions was 51.1%. Hepatobiliary laboratory adverse reactions identified in 48.9% of the patients and led to treatment discontinuation in 20.0%. Amylase and lipase elevation (2.2%), ventricular extra systoles (2.2%), hallucination and nightmares (2.2%) were other adverse reactions. Hepatobiliary abnormalities were the most common adverse reactions and the most common cause of treatment discontinuation. For safer treatment in critically ill patients, the dose should be personalized. To clearly identify the accurate frequency and the causality of all adverse reactions, prospective studies with much larger sample size are needed.

A novel phenotype-based drug-induced liver injury causality assessment tool (DILI-CAT) allows for signal confirmation in early drug development.

SummaryBackgroundDrug‐induced liver injury (DILI) requires accurate case adjudication, with expert opinion being the current best practice.AimWe utilised a novel DILI causality assessment tool (DILI‐CAT), which uses drug‐specific liver injury phenotypes, to examine potential DILI in early phase ximelagatran clinical development.MethodsWe conducted a retrospective analysis of liver injury events from four Stroke Prevention using an ORal Thrombin Inhibitor in Atrial Fibrillation (SPORTIF) trials, in which patients were randomised to receive oral ximelagatran or adjusted‐dose warfarin. A stepwise process was used with iterative adjustments. The DILI phenotype was characterised by latency, R‐value, and AST/ALT ratio. A scoring algorithm was applied to liver events to assess how closely the liver events matched the Interquatile‐Range for the working phenotype for each of the three parameters.FindingsData from 3115 patients included in the SPORTIF trials as above were available. The initial ximelagatran phenotype was developed based on five liver injury cases from the ximelagatran arm and was then validated against an additional eight cases (5 ximelagatran, 3 warfarin); in these eight cases, there was a statistically significant difference in the total DILI‐CAT scores of the two drugs (p = 0.016) between ximelagatran and warfarin. Together, these ten ximelagatran cases generated a second, refined ximelagatran phenotype, which was validated against an additional 75 cases (53 ximelagatran/22 warfarin)—again with statistically significant different DILI‐CAT ximelagatran vs. warfarin scores (p < 0.001).ConclusionDILI‐CAT, a clinically intuitive, data‐driven, computer‐assisted scoring algorithm, is a useful tool for early detection of drug’s hepatotoxicity in clinical drug development.

Agreement Among Different Scales for Causality Assessment in Drug-Induced Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis.

Identification of the offending drug is crucial and challenging in cases of severe cutaneous adverse drug reactions (CADR) like Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). Poor reproducibility and varying levels of agreement have been observed among different causality assessment tools (CATs) in assessing severe CADRs. This study was conducted to examine the agreement among four different CATs in assessing cases of drug-induced SJS, TEN and SJS/TEN overlap. All cases of drug-induced SJS, TEN and SJS/TEN overlap, which were reported between January 2012 and January 2020, were identified from the ADR register at an ADR monitoring centre. Causality assessment was done in these reported cases using the following CATs: The World Health Organization-Uppsala Monitoring Centre (WHO-UMC) scale, Naranjo algorithm, Liverpool algorithm and Algorithm of drug causality for epidermal necrolysis (ALDEN). Weighted kappa (κw) test was used to evaluate the agreement among four CATs. A total of 30 cases of drug-induced SJS, TEN and SJS/TEN overlap were included in our analyses. The most common offending groups of drugs were anticonvulsants (46.7%), antimicrobials (40%) and nonsteroidal anti-inflammatory drugs (13.3%). Of the anticonvulsants, phenytoin (13.3%), carbamazepine (10%), and valproate (10%) were the commonly reported offending drugs. Poor agreement was observed among the four different causality assessment scales. Discrepancies were observed among four different CATs in assessing drug-induced SJS and TEN. A CAT, which is more specific to drug-induced SJS and TEN, simple, user-friendly with limited subjective interpretation, incorporating new immunological and pharmacogenetic markers, is necessary.

Assessment of Causality in Hospitalized Children With Aminoglycoside-Related Nephrotoxicity

To evaluate the incidence of aminoglycoside-related nephrotoxicity and ascertain drug causality and its risk factors. This prospective study was conducted from January, 2019 to January, 2021, and recruited 110 consecutively admitted children aged 1 month to 12 years, receiving aminoglycosides for ≥4 days. Drug causality was assessed using Liverpool adverse drug reaction causality assessment tool. 42 (38.2%) children developed acute kidney injury (AKI), with 71 (64.5%) having composite nephrotoxicity (AKI and/or tubular-dysfunction). Only 17 (15.5%) had AKI definitively attributable to aminoglycosides. Hypotension [OR 0.016 (95% CI 0.01-0.71), P=0.03], PRISM-III score 20-29% [OR 55.48 (95% CI 3.66-840.53), P=0.004] and post-surgery patients [OR 3.2 (95% CI 1.01-10.1), P=0.047] were independent predictors of AKI. Only a small proportion of children receiving aminoglycosides had AKI definitively attributable to the drug.

Translation, transcultural adaptation and validation to Brazilian Portuguese of tools for adverse drug reaction assessment in children

BackgroundChildren are more vulnerable to adverse drug reactions (ADRs) due to complex changes in the body during the growth process and lack specific pharmacoepidemiologic studies. Causality and Avoidability assessment of ADRs are relevant to clinical guidelines development and pharmacovigilance. This study aimed to translate and transcultural adapt two new tools—Liverpool Causality Assessment Tool (LCAT) and the Liverpool Avoidability Assessment Tool (LAAT)—to Brazilian-Portuguese and evaluate the psychometric properties of these tools to analyse ADRs in Brazilian children.MethodsThe validation of the cross-cultural adaptation of tools was obtained by the functional (conceptual, semantic, operational, and measurement) equivalence between the original and translated versions of each instrument. The translated version of LCAT and LAAT was applied to assessing the twenty-six case reports of suspected adverse drug reactions in a Brazilian teaching paediatric hospital. The inter-rater reliability (a pharmacist and a physician) was evaluated using Cronbach’s alpha. The exact agreement percentages (%EA) and extreme disagreement (%ED) were computed. Overall Kappa index was calculated with a 95% confidence interval.ResultsThere was a need to modify some terms translated into Portuguese for semantic and conceptual equivalence. The Cronbach’s alpha coefficient values obtained were 0.95 and 0.85, and the weighted Kappa (95% confidence interval) were 0.82 (0.67–0.97) and 0.68 (0.45–0.91) for LCAT and LAAT, respectively. The Brazilian-Portuguese versions of the LCAT and LAAT showed reliable and valid tools for the diagnosis and follow-up of ADRs in children.ConclusionThe methodological approach allowed the translation, transcultural adaptation, and validation to Brazilian-Portuguese of two easy and quick to perform tools for causality and avoidability of ADRs in children by a multidisciplinary expert specialist committee, including the authors of original tools. We believe these versions may be applied by professionals (patient safety teams) and researchers in Brazil in groups or by a single reviewer.Trial registrationThis study was evaluated and approved by the Research Ethics Committee (Instituto de Pediatria e Puericultura Martagão Gesteira – Federal University of Rio de Janeiro – Number: 3.264.238.

Causality and avoidability of adverse drug reactions of antibiotics in hospitalized children: a cohort study.

Adverse drug reactions are a problem in healthcare systems worldwide. Children are more susceptible than adults, especially when exposed to specific drug classes, such as antibiotics. To assess the incidence, causality, severity, andavoidabilityof antibiotic-associated adverse drug reactions in hospitalized pediatric patients. Pediatric ward of a high-complexity public hospital in northeast Brazil. A prospective cohort study was conducted over six months, including children aged between 28days and 12years, hospitalized for more than 48h, and receiving antibiotics. Liverpool's causality and avoidability assessment tools were used.Primary outcome measures: Incidence of adverse drug reactions, causality, severity, and avoidability,major antibiotics implicated, risk factors. A total of 183 patients were followed, and 35 suspected adverse drug reactions were recorded overall incidence equal to 14.7%. Most adverse drug reactions were classified as moderate severity (76.7%), probable (57.1%) and defined (28.6%) causality, and unavoidable (66.7%). The affected organs were the gastrointestinal system (74.1%) and skin (25.9%). Major antibiotics implicated were ceftriaxone (40.7%), azithromycin (25.9%), and crystalline penicillin (11.1%). The number of antibiotics prescribed per patient during hospitalization and the length of stay were the risk factors identified. Causality and severity assessment indicated that most adverse drug reactions were probable and moderate. Possibly avoidable reactions occurred due to inappropriate prescribing when preventive measures were not implemented. Monitoring the use of antibiotics in children is essential to ensure the safety of these patients.

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.&#x0D; 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.&#x0D; 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).&#x0D; 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.