Adverse event reporting in intervention research for young autistic children.
Ontology highlight
ABSTRACT: Lay abstract
In this study, we looked at published research on interventions for young autistic children that did not involve administering medication. We were interested in determining how often studies reported on whether adverse events (i.e. physical or psychological distress to the participants) or adverse effects (i.e. adverse events that are thought to be caused by the intervention) had occurred. We found that of the 150 reports we examined, only 11 mentioned adverse events. One of these studies reported adverse events occurred, and three reported that adverse effects occurred. We also reviewed the studies to examine the reasons that were given to explain why any participants dropped out of the intervention (termed "withdrawal"), to determine if any of these reasons could be considered adverse events or adverse effects. Fifty-four studies described reasons for withdrawal, and 10 of these studies had reasons that could be categorized as an adverse event, 8 studies had reasons that could be categorized as an adverse effect, and an additional 12 studies had reasons that were too vaguely described to determine whether they were adverse events or not. We recommend that autism intervention researchers develop more systematic methods of looking for and reporting adverse events and effects, so that professionals and families can be better informed when choosing to enroll their autistic children in interventions.
SUBMITTER: Bottema-Beutel K
PROVIDER: S-EPMC7870528 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The wide-scale roll-out of artemisinin combination therapies (ACTs) for the treatment of malaria should be accompanied by continued surveillance of their safety. Post-marketing pharmacovigilance (PV) relies on adverse event (AE) reporting by clinicians, but as a large proportion of treatments are provided by non-clinicians in low-resource settings, the effectiveness of such PV systems is limited. To facilitate reporting, AE forms should be easily completed; however, most are challenging for lower-level health workers and non-clinicians to complete. Through participatory research, we sought to develop user-friendly AE report forms to capture information on events associated with ACTs.Following situation analysis, we undertook workshops with community medicine distributors and health workers in Jinja, Uganda, to develop a reporting form based on experiences and needs of users, and communication and visual perception principles. Participants gave feedback for revisions of subsequent versions. We then conducted 8 pretesting sessions with 77 potential end users to test and refine passive and active versions of the form.The development process resulted in a form that included a pictorial storyboard to communicate the rationale for the information needed and facilitate rapport between the reporter and the respondent, and a diary format to record the drug administration and event details in chronological relation to each other. Successive rounds of pretesting used qualitative and quantitative feedback to refine the form, with the final round showing over 80% of the form completed correctly by potential end users.We developed novel AE report forms that can be used by non-clinicians to capture pharmacovigilance data for anti-malarial drugs. The participatory approach was effective for developing forms that are intuitive for reporters, and motivating for respondents. The forms, or their key components, could be adapted for use in other low-literacy settings to improve quality and quantity of drug safety reports as new medicines are scaled-up.
| S-EPMC3315549 | biostudies-literature
Project description:AimAdverse drug events (ADEs) are harmful and unintended consequences of medications. Their reporting is essential for drug safety monitoring and research, but it has not been standardized internationally. Our aim was to synthesize information about the type and variety of data collected within ADE reporting systems.MethodsWe developed a systematic search strategy, applied it to four electronic databases, and completed an electronic grey literature search. Two authors reviewed titles and abstracts, and all eligible full-texts. We extracted data using a standardized form, and discussed disagreements until reaching consensus. We synthesized data by collapsing data elements, eliminating duplicate fields and identifying relationships between reporting concepts and data fields using visual analysis software.ResultsWe identified 108 ADE reporting systems containing 1782 unique data fields. We mapped them to 33 reporting concepts describing patient information, the ADE, concomitant and suspect drugs, and the reporter. While reporting concepts were fairly consistent, we found variability in data fields and corresponding response options. Few systems clarified the terminology used, and many used multiple drug and disease dictionaries such as the Medical Dictionary for Regulatory Activities (MedDRA).ConclusionWe found substantial variability in the data fields used to report ADEs, limiting the comparability of ADE data collected using different reporting systems, and undermining efforts to aggregate data across cohorts. The development of a common standardized data set that can be evaluated with regard to data quality, comparability and reporting rates is likely to optimize ADE data and drug safety surveillance.
| S-EPMC4917803 | biostudies-literature
Project description:UnlabelledBackgroundAdverse events (AEs) frequently occur in intensive care units (ICUs) and affect negatively patient outcomes. Targeted improvement strategies for patient safety are difficult to evaluate because of the intrinsic limitations of reporting crude AE rates. Single interventions influence positively the quality of care, but a multifaceted approach has been tested only in selected cases. The present study was designed to evaluate the rate, types, and contributing factors of emerging AEs and test the hypothesis that a multifaceted intervention on medication might reduce drug-related AEs.MethodsThis is a prospective, multicenter, before-and-after study of adult patients admitted to four ICUs during a 24-month period. Voluntary, anonymous, self-reporting of AEs was performed using a detailed, locally designed questionnaire. The temporal impact of a multifaceted implementation strategy to reduce drug-related AEs was evaluated using the risk-index scores methodology.ResultsA total of 2,047 AEs were reported (32 events per 100 ICU patient admissions and 117.4 events per 1,000 ICU patient days) from 6,404 patients, totaling 17,434 patient days. Nurses submitted the majority of questionnaires (n = 1,781, 87%). AEs were eye-witnessed in 49% (n = 1,003) of cases and occurred preferentially during an elective procedure (n = 1,597, 78%) and on morning shifts (n = 1,003, 49%), with a peak rate occurring around 10 a.m. Drug-related AEs were the most prevalent (n = 984, 48%), mainly as a consequence of incorrect prescriptions. Poor communication among caregivers (n = 776) and noncompliance with internal guidelines (n = 525) were the most prevalent contributing factors for AE occurrence. The majority of AEs (n = 1155, 56.4%) was associated with minimal, temporary harm. Risk-index scores for drug-related AEs decreased from 10.01 ± 2.7 to 8.72 ± 3.52 (absolute risk difference 1.29; 95% confidence interval, 0.88-1.7; p < 0.01) following the introduction of the intervention.ConclusionsAEs occurred in the ICU with a typical diurnal frequency distribution. Medication-related AEs were the most prevalent. By applying the risk-index scores methodology, we were able to demonstrate that our multifaceted implementation strategy focused on medication-related adverse events allowed to decrease drug related incidents.
| S-EPMC3526522 | biostudies-literature
Project description:The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) is an important source for detecting adverse drug event (ADE) signals. In this article, we propose a three-component mixture model (3CMM) for FAERS signal detection. In 3CMM, a drug-ADE pair is assumed to have either a zero relative risk (RR), or a background RR (mean RR = 1), or an increased RR (mean RR >1). By clearly defining the second component (mean RR = 1) as the null distribution, 3CMM estimates local false discovery rates (FDRs) for ADE signals under the empirical Bayes framework. Compared with existing approaches, the local FDR's top signals have noninferior or better sensitivities to detect true signals in both FAERS analysis and simulation studies. Additionally, we identify that the top signals of different approaches have different patterns, and they are complementary to each other.
| S-EPMC6118321 | biostudies-literature
Project description: Not available
| S-EPMC5816691 | biostudies-literature
Project description:Problem:Rapid growth in the use of medical devices has drawn attention to gaps in the systematic monitoring of medical device-associated adverse events in India. Approach:Implementation of national regulations on medical devices started in January 2018. Supported by a nationwide network of monitoring centres, the Indian Pharmacopoeia Commission coordinates adverse event reports from manufacturers, legal representatives and patients or users. The commission follows-up and reviews reports with subject expert groups and sends recommendations on necessary action to the national regulatory authority. Local setting:Before 2015, no systematic structure was in place to collate adverse events associated with medical devices. Several reports of deaths and hospitalization due to faulty hip implants, cardiac stents and poor-quality devices prompted the health ministry to launch the materiovigilance programme. Relevant changes:From July 2015 to October 2019, the commission received 1931 adverse event reports, mostly from marketing authorization holders; 1277 were serious events. Reporting increased markedly after 2017. Cardiac stents were the most reported device (926 events; 47.95%). To encourage a culture of reporting, the commission has raised awareness about the programme among stakeholders, developed user-friendly reporting tools and guidelines, and conducted training for hospital personnel on medical device adverse event reporting. Lessons learnt:Regular training to stakeholders develops a sense of responsibility towards reporting medical device adverse events and ensures quality data reporting. Reporters must be assured that reporting adverse events does not have any legal implications for them and given acknowledgement of their role in high-quality device associated adverse event reporting.
| S-EPMC7047028 | biostudies-literature
Project description:BackgroundTaxanes are an essential class of antineoplastic agents used to treat various cancers and are a fundamental cause of hypersensitivity reactions. In addition, other adverse events, such as bone marrow toxicity and peripheral neuropathy, can lead to chemotherapy discontinuation. This study aimed to evaluate the safety of taxanes in the real world.MethodsTaxane-associated adverse events were identified by the Medical Dictionary for Regulatory Activities Preferred Terms and analyzed and compared by mining the US Food and Drug Administration Adverse Event Reporting System pharmacovigilance database from January 2004 to December 2019. Reported adverse events, such as hypersensitivity reaction, bone marrow toxicity, and peripheral neuropathy, were analyzed with the following signal detection algorithms: reporting odds ratio (ROR), proportional reporting ratio (PRR), multi-item gamma Poisson shrinker (MGPS), Bayesian confidence propagation neural network (BCPNN), and logistic regression methods. Adverse outcome events and death outcome rates were compared between different taxane groups using Pearson's χ2 test, whereas significance was determined at P < 0.05 with a 95% confidence interval (CI).ResultsA total of 966 reports of hypersensitivity reactions, 1109 reports of bone marrow toxicity, and 1374 reports of peripheral neuropathy were analyzed. Compared with paclitaxel and docetaxel, bone marrow toxicity following the use of nab-paclitaxel had the highest ROR of 6.45 (95% two-sided CI, 6.05-6.88), PRR of 5.66, (χ2 = 4342.98), information component of 2.50 (95% one-sided CI = 2.34), and empirical Bayes geometric mean of 5.64 (95% one-sided CI = 5.34). Peripheral neuropathy following the use of nab-paclitaxel showed a higher ROR of 12.78 (95% two-sided CI, 11.55-14.14), PRR of 12.16 (χ2 = 4060.88), information component of 3.59 (95% one-sided CI = 3.25), and empirical Bayes geometric mean of 12.07 (95% one-sided CI = 11.09).ConclusionsThe results showed that bone marrow toxicity and peripheral neuropathy were the major adverse events induced by taxanes. Nab-paclitaxel exhibited the highest potential for taxane-associated adverse events. Further research in the future is warranted to explain taxane-associated adverse effects in real-world circumstances.
| S-EPMC8213312 | biostudies-literature
Project description:PurposeThe purpose of this study was to investigate the adverse events (AEs) related to the use of off-label drugs.Materials and methodsA cross-sectional study was carried out using available data pertaining to off-label drug were sourced from U.S. FDA spontaneous adverse drug reaction reporting database (FAERS) and Korea Adverse Event Reporting System database (KIDS-KD) for the years 2014 to 2018. The number and frequencies of AE cases were calculated. Disproportionality was analyzed using the proportional reporting ratio (PRR), the reporting odds ratio (ROR), the information component (IC), and the empirical Bayes geometric mean (EBGM) methods.ResultsThe reported AEs associated with off-label drug use were more common among older patients compared with younger patients. Gastric nonspecific symptoms and therapeutic procedure (4.16-4.57%) and haemorrage term (4.16-5.29%) were the most common AE symptoms and antithrombotic agents and immunosuppressants were the drugs most commonly reported to cause AEs in FAERS. Secondary term events (43.45-48.62%) including inappropriate schedule of drug administration and medication error were the most common AEs, and immunosuppressants and antipsychotics were the most common AE-related drugs from KIDS-KD. The numbers of reported AEs in new drug categories such as other antineoplastic agents trended to increase from 2014 to 2018 in both datasets.ConclusionThe numbers of reported AEs with off-label drug increased annually. AEs associated with off-label drugs may have a significant impact on older patients. Healthcare experts should be concerned about prescriptions of off-label drugs, especially anticoagulants and newly developed drugs such as immunosuppressants and antineoplastic agents.
| S-EPMC8387311 | biostudies-literature
Project description:Recent theories propose that domain-general deficits in prediction (i.e., the ability to anticipate upcoming information) underlie the behavioral characteristics associated with autism spectrum disorder (ASD). If these theories are correct, autistic children might be expected to demonstrate difficulties on linguistic tasks that rely on predictive processing. Previous research has largely focused on older autistic children and adolescents with average language and cognition. The present study used an eye-gaze task to evaluate predictive language processing among 3- to 4-year-old autistic children (n = 34) and 1.5- to 3-year-old, language-matched neurotypical (NT) children (n = 34). Children viewed images (e.g., a cake and a ball) and heard sentences with informative verbs (e.g., Eat the cake) or neutral verbs (e.g., Find the cake). Analyses of children's looking behaviors indicated that young autistic children, like their language-matched NT peers, engaged in predictive language processing. Regression results revealed a significant effect of diagnostic group, when statistically controlling for age differences. The NT group displayed larger difference scores between the informative and neutral verb conditions (in looks to target nouns) compared to the ASD group. Receptive language measures were predictive of looking behavior across time for both groups, such that children with stronger language skills were more efficient in making use of informative verbs to process upcoming information. Taken together, these results suggest that young autistic children can engage in predictive processing though further research is warranted to explore the developmental trajectory relative to NT development. LAY SUMMARY: This study found that 3- to 4-year-old autistic children and younger, language-matched neurotypical (NT) children both used verbs to predict upcoming nouns in sentences like "Eat the cake." For both autistic and NT children, those with stronger language skills were able to predict upcoming nouns more quickly.
| S-EPMC9090958 | biostudies-literature