Serious Adverse Events Associated with Off-Label Use of Azithromycin or Fentanyl in Children in Intensive Care Units: A Retrospective Chart Review

Perceptions and experiences of community pharmacists with off-label prescribing in the pediatric population

OBJECTIVES

This study aimed to investigate and provide insight into the prevalence and patterns of off-label drug use in the pediatric population from the perspective of community pharmacists, addressing the existing data gap in a developing setting.

METHODS

A questionnaire-based cross-sectional study was conducted on Albanian community pharmacists in June 2021. The online administered survey explored the participants' demographic details, perceptions, and experiences with off-label prescriptions in pediatric patients. The statistical analysis conducted on the survey data comprised the construction of frequency tables and the application of the chi-square test for independence.

KEY FINDINGS

Three hundred and thirty-six community pharmacists nationwide completed the survey, out of which 186 (55.3%) were practiced in Tirana, the capital of Albania. Over 80% of surveyed pharmacists (n = 275) had encountered off-label drug prescriptions in pediatric patients, yet only 40% of participants reported dispensing medicines for off-label use. Community pharmacists reported that general pediatricians tended to prescribe off-label medications more frequently than pediatric subspecialists or general practitioners. It was found that off-label prescriptions were more frequently observed among children aged between 2 and 11 years. Antibiotics were the most reported medicines for off-label use in this study mentioned in almost all off-label categories.

CONCLUSIONS

Prescribing medicines for unapproved uses for the treatment of pediatric patients is present in community settings in Albania. This indicates the need for further data collection and analysis to understand off-label practices in our country's pediatric population comprehensively.

Feasibility and acceptability of integrating mass distribution of azithromycin to children 1-11 months into a trachoma mass drug administration campaign to reduce child mortality in Côte d'Ivoire

Evidence suggests that bi-annual mass drug administration (MDA) of single-dose azithromycin to 1-11 month-old children reduces child mortality in high child-mortality settings. Several countries conduct annual MDAs to distribute azithromycin to individuals ages 6 months and older to prevent trachoma infection. This study examined the feasibility and acceptability of reaching 1-11 months-old children during a trachoma MDA in Côte d'Ivoire by extending azithromycin distribution to infants 1-5 months old during the campaign. In November 2020, the study piloted single-dose azithromycin for 1-5 month-olds during a trachoma MDA in one health district. Monitoring data included the number of children reached and occurrences of adverse drug reactions. Feasibility, the extent to which the target population received the intervention (coverage), was assessed through a population-based, household survey with parents/caregivers of eligible children conducted after the MDA. Acceptability was explored through in-depth interviews (IDIs) with parents/caregivers of eligible children, focus group discussions (FGDs) with community drug distributors (CDDs), and IDIs with their supervisors. CDD FGDs and supervisor IDIs also documented implementation challenges and recommendations for scale-up. 1,735 1-5 month-olds received azithromycin during the pilot activity (estimated population coverage of 90.2%). Adverse drug reactions were reported for 1% (n = 18) infants; all were mild and self-limited. The post-MDA coverage survey interviewed 267 parents/caregivers; survey-based intervention coverage was 95.4% of 1-5 month-olds. Qualitative data revealed high intervention acceptability among parents, CDDs, and supervisors. Implementation challenges included the need to weigh babies to calculate dosage for 1-5 month-olds and the need to obtain written informed consent from parents to provide the drug to 1-5 month-olds. CDDs also indicated the need for more information on azithromycin and possible side effects during training. Delivering azithromycin to younger infants appears acceptable to parents and implementers; >90% coverage indicates feasibility to integrate into a trachoma MDA. (Clinicaltrials.gov ID number: NCT04617626).

Population Pharmacokinetics and Individualized Medication of Azithromycin for Injection in Children Under 6 Years Old

Pharmacokinetic data for injectable azithromycin in children remain limited. This study aims to develop and validate a population pharmacokinetic model of azithromycin for injection in children under 6 years old and optimize its dosage regimen in this population. We prospectively enrolled patients under 6 years old who received azithromycin for injection at Beijing Friendship Hospital, Capital Medical University. Demographic information, clinical characteristics, and venous blood samples were collected in accordance with the research protocol. Azithromycin concentrations were determined using a validated UPLC-MS/MS method. The population pharmacokinetic model was structured using Phoenix NLME. The adequacy and robustness of the model was evaluated using VPC and bootstrap. We optimized azithromycin's dosing regimen for injection through Monte Carlo simulations. We included 254 plasma concentration data from 148 patients to establish the model. The clearance and volume were 1.27 L/h/kg and 45.6 L/kg, respectively. The covariates included were weight and age. VPC plots and nonparametric bootstrap showed that the final PPK model was reliable and robust. Based on Monte Carlo simulation, we derived a simple and practical dosing scheme. The results provided reference for individualized dosing in this population. The individualized dosing scheme based on Monte Carlo simulation can optimize clinical decision-making and guide personalized therapy.

Immediate release fentanyl in general practices: Mostly off-label prescribing

BACKGROUND

The immediacy of the onset of opioids may be associated with the risk of dependency and accidental overdose. Nasal and oromucosal fentanyl dosage forms are so called immediate release fentanyl (IRF). These IRFs have been approved to treat breakthrough pain in patients with cancer who are on chronic opioid treatment only. There are signals of increased off-label prescribing of IRFs in general practices.

OBJECTIVES

This study aims to provide insight into the frequency of IRF prescription in Dutch general practices and the extent to which IRF is prescribed off-label.

METHODS

Routinely collected electronic health records of general practices (GPs) participating in Nivel Primary Care Database were used. Adult patients with IRF prescriptions in 2019 were selected from whom dispensing data on 2018 and 2019 was available. Diagnoses were recorded by GPs using International Classification of Primary Care. Descriptive analyses were performed.

RESULTS

This study included 342 GPs with a patient population of 1,297,942 patients, 1,368 patients received at least one IRF prescription in 2019, which is equal to 1.1 patients per 1,000 registered patients. Most patients (74.9%) with an IRF prescription received an off-label prescription. A slight majority had a cancer diagnosis but nearly 65.2% did not have a maintenance therapy and 14% were opioid-naive before receiving their first IRF prescription.

CONCLUSION

IRFs are not prescribed frequently in Dutch general practices. However, when prescribed, a relatively large portion of patients received an off-label prescription.

A report on SARS-CoV-2 first wave in Ecuador: drug consumption dynamics

Introduction: The first COVID-19 wave in Ecuador started in March 2020 and extended until November. Several types of drugs have been proposed as a potential treatment during this period, and some affected people have self-medicated. Method: A retrospective study was conducted with 10,175 individuals who underwent RT-PCR tests for SARS-CoV-2 from July to November 2020. We compared the number of positive and negative cases in Ecuador with symptoms and drug consumption. The Chi-square test of independence compared clinical and demographic data and PCR test results. Odds ratios analyzed drug consumption dynamics. Results: Of 10,175 cases, 570 were positive for COVID-19, while 9,605 were negative. In positive cases, there was no association between the RT-PCR result and sex, age, or comorbidities. When considering demographic data, Cotopaxi and Napo had the highest rates of positive cases (25.7% and 18.8%, respectively). Manabí, Santa Elena, and Guayas regions had fewer than 10% positive cases. The Drug consumption dynamic analysis showed that negative COVID-19 cases presented higher drug consumption than positive cases. In both groups, the most consumed medication was acetaminophen. Acetaminophen and Antihistamines had higher odds of consumption in positive PCR cases than in negative. Symptoms like fever and cough were more related to positive RT-PCR results. Conclusion: The first COVID-19 wave in Ecuador has affected the provinces differently. At a national level, the consumption of drugs has been highly associated with self-medication.

Analyzing adverse drug reaction using statistical and machine learning methods: A systematic review

BACKGROUND

Adverse drug reactions (ADRs) are unintended negative drug-induced responses. Determining the association between drugs and ADRs is crucial, and several methods have been proposed to demonstrate this association. This systematic review aimed to examine the analytical tools by considering original articles that utilized statistical and machine learning methods for detecting ADRs.

METHODS

A systematic literature review was conducted based on articles published between 2015 and 2020. The keywords used were statistical, machine learning, and deep learning methods for detecting ADR signals. The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA) guidelines.

RESULTS

We reviewed 72 articles, of which 51 and 21 addressed statistical and machine learning methods, respectively. Electronic medical record (EMR) data were exclusively analyzed using the regression method. For FDA Adverse Event Reporting System (FAERS) data, components of the disproportionality method were preferable. DrugBank was the most used database for machine learning. Other methods accounted for the highest and supervised methods accounted for the second highest.

CONCLUSIONS

Using the 72 main articles, this review provides guidelines on which databases are frequently utilized and which analysis methods can be connected. For statistical analysis, >90% of the cases were analyzed by disproportionate or regression analysis with each spontaneous reporting system (SRS) data or electronic medical record (EMR) data; for machine learning research, however, there was a strong tendency to analyze various data combinations. Only half of the DrugBank database was occupied, and the k-nearest neighbor method accounted for the greatest proportion.

Drug safety of frequently used drugs and substances for self-medication in COVID-19

During the COVID-19 pandemic, the behavior of self-medication has increased. The dissemination of misleading information regarding the efficacy of certain drugs or substances for the prevention and treatment of COVID-19 has been the major contributing factor for this phenomenon. Alongside with the increase in self-medication behavior, the inherent risks to this act such as drug-drug interactions, adverse events, drug toxicity, and masking of symptoms have also increased. Self-medication in the context of COVID-19 has led to drug misuse leading in some cases to the development of fatal adverse drug reactions. It is important that during this ongoing pandemic drugs with potential clinical efficacy against COVID-19 are adequately analyzed regarding their efficacy, safety, and monitoring. The aim of this review is to describe the available evidence regarding the efficacy, safety, and monitoring of the drugs and substances that have been shown to be frequently used for self-medication in patients with COVID-19 (hydroxychloroquine, non-steroidal anti-inflammatory drugs, ivermectin, azithromycin, vitamins, aspirin, and chlorine dioxide) to adequately characterize their risks, safe use, monitoring strategies, and to reinforce the concept that these substances should not be used for self-medication and require a medical prescription.

Plain Language Summary

Drug safety of frequently used drugs and substances for self-medication in COVID-19 Dissemination of information about potential COVID-19 treatments has led individuals to self-medicate and expose themselves to risks such as drug-drug interactions, side effects, antibiotic resistance, and misdiagnosis. There is a need to review the medical literature to evaluate the safety and efficacy of the drugs and substances commonly used by the population for the treatment and prevention of SARS CoV-2 infection. In this review, we included drugs that are frequently used for self-medication and commonly advertised such as ivermectin, hydroxychloroquine, chlorine dioxide, azithromycin, and non-steroidal anti-inflammatory drugs, among others. A brief introduction of the drug and its mechanism of action, followed by a summary of the efficacy in COVID-19 and safety, will be described for each drug in order to promote their responsible use.

Safety of azithromycin in pediatric infectious diseases: a clinical systematic review and meta-analysis

BACKGROUND

Azithromycin is a second-generation macrolide antibiotic which can be used in the treatment of diseases caused by sensitive bacterial infections. This article aimed to investigate the safety of azithromycin in the treatment of infectious diseases in children by meta-analysis.

METHODS

PubMed, Embase, and Cochrane were selected as the search database platforms. Randomized controlled trials (RCTs) published after 2010 were searched using the following keywords: "azithromycin", "children", "adverse event", "intravenous event", and "oral". Included studies were all clinical trials of azithromycin in the treatment of pediatric diseases. After inclusion/exclusion criteria screening and bias risk assessment, data were extracted from the included studies. RevMan 5.3.5 software was used for statistical analysis to obtain both forest and funnel plots.

RESULTS

A total of nine articles involving 3,597 pediatric patients were included in this study. The results of meta-analysis showed that the nine articles exhibited statistical heterogeneity (I²=70%; P=0.001), and thus, a random-effects model was used. The obtained statistic was [odds ratio (OR) =0.65; 95% confidence interval (CI): (0.43, 0.97)], the statistical effect value was Z=2.10, P=0.04, and the difference was statistically significant. After excluding one article, the remaining eight articles showed homogeneity (I²=12%; P=0.34). So, using fixed-effects model analysis, the statistic was [OR =0.79; 95% CI: (0.67, 0.94)], and the effect size value was Z=2.73, P=0.006.

DISCUSSION

Compared with other antibiotics, the clinical safety of azithromycin is relatively good, but care should be taken when the dosage is high in treating some disease.

Secondary Use of Clinical Data in Data-Gathering, Non-Interventional Research or Learning Activities: Definition, Types, and a Framework for Risk Assessment

Background

The secondary use of clinical data in data-gathering, non-interventional research or learning activities (SeConts) has great potential for scientific progress and health care improvement. At the same time, it poses relevant risks for the privacy and informational self-determination of patients whose data are used.

Objective

Since the current literature lacks a tailored framework for risk assessment in SeConts as well as a clarification of the concept and practical scope of SeConts, we aim to fill this gap.

Methods

In this study, we analyze each element of the concept of SeConts to provide a synthetic definition, investigate the practical relevance and scope of SeConts through a literature review, and operationalize the widespread definition of risk (as a harmful event of a certain magnitude that occurs with a certain probability) to conduct a tailored analysis of privacy risk factors typically implied in SeConts.

Results

We offer a conceptual clarification and definition of SeConts and provide a list of types of research and learning activities that can be subsumed under the definition of SeConts. We also offer a proposal for the classification of SeConts types into the categories non-interventional (observational) clinical research, quality control and improvement, or public health research. In addition, we provide a list of risk factors that determine the probability or magnitude of harm implied in SeConts. The risk factors provide a framework for assessing the privacy-related risks for patients implied in SeConts. We illustrate the use of risk assessment by applying it to a concrete example.

Conclusions

In the future, research ethics committees and data use and access committees will be able to rely on and apply the framework offered here when reviewing projects of secondary use of clinical data for learning and research purposes.

Off-label use of pentazocine and the associated adverse events among pediatric surgical patients in a tertiary hospital in Northern Nigeria: a retrospective chart review

Background and aims: Pentazocine remains a widely used opioid pre-anesthetic medication and post-operative analgesic in low- and middle-income countries despite concerns. We assessed the adverse events (AEs) associated with off-label use of pentazocine in pediatric surgical patients and determined the possible risk factors associated with slow respiratory AEs.Method: Children ≤18 years old were administered pentazocine IM/IV as a pre-anesthetic medication or post-operative analgesic. Pertinent data including total daily dose and duration of use of pentazocine and its associated AEs were obtained from patients' case files. Risk factors associated with slow respiratory AEs were determined using logistic regression analyses.Results: One hundred and fifty-nine patients were included with a median age of 2 years; they were mainly males (52.8%). Pentazocine was administered off-label to all patients for post-operative pain management (96.2%) or pre-anesthetic medication (3.8%). All patients experienced at least one AE with most experiencing 2-7 AEs. Rapid breathing (120; 18.7%), followed by fast pulse (101; 15.7%) and sleepiness/sedation/drowsiness (81; 12.6%) were the most common AEs. None of the demographics and clinical variables significantly predicted the risk of slow respiratory AEs.Conclusion: Off-label use of pentazocine is common and associated with multiple AEs. Care is needed as no predictors of slow respiratory AEs were observed.