ReviewNaunyn-Schmiedeberg's archives of pharmacology2025
A review on adverse drug reaction related to medication in health sector: an account of what we have discovered and implemented-pharmacovigilance.
Review in Naunyn-Schmiedeberg's archives of pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the extensive research on medication-related adverse events (MRAEs) in healthcare, the assessment of the present scenario is made more difficult by the high degree of variability in study results. This study's primary goal was to create a current picture of what is currently known about the prevalence, risk factors, and surveillance of MRAEs in healthcare and overview of pharmacovigilance in preventing MRAEs. In order to find specific research on the prevalence, risk factors, economic effects, and monitoring techniques of medication-related adverse events, a comprehensive search was conducted using relevant search terms across electronic databases. Only research/review published after 2015 were considered in this analysis in order to provide the most current picture of the scenario. Patients who are elderly and have reduced liver or renal function, polypharmacy, or have several other comorbidities are more likely to experience medication-related side effects. Nevertheless, the use of high-risk medications and specific care settings also significantly raises the risk of MRAEs. Computerized techniques may open up new opportunities for event forecasting across all MRAE subtypes when paired with machine learning. Supporting collaborative research between computer science and medicine should be a top priority for pharmacovigilance research and patient safety initiatives in the future in order to provide prospects for the creation of clever preventative work strategies. However, the creation of effective real-time detection techniques may lead to significant advancements in predicting and incident avoidance in the future.
Indexed as
Identifiers
40387927What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.