ReviewDrug safety2008
An automated standardized system for managing adverse events in clinical research networks.
Review in Drug safety, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed, 13 citations in OpenAlex.
- The Vigilance Gradient: Nine Years of Adverse Event Trends in Pediatric Critical Care.Critical care explorations · 2026Observational
- Article
- The Rare Diseases Clinical Research Network's organization and approach to observational research and health outcomes research.Journal of general internal medicine · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Multi-site clinical protocols and clinical research networks require tools to manage and monitor adverse events (AEs). To be successful, these tools must be designed to comply with applicable regulatory requirements, reflect current data standards, international directives and advances in pharmacovigilance, and be convenient and adaptable to multiple needs. We describe an Adverse Event Data Management System (AEDAMS) that is used across multiple study designs in the various clinical research networks and multi-site studies for which we provide data and technological support. Investigators enter AE data using a standardized and structured web-based data collection form. The automated AEDAMS forwards the AE information to individuals in designated roles (investigators, sponsors, Data Safety and Monitoring Boards) and manages subsequent communications in real time, as the entire reporting, review and notification is done by automatically generated emails. The system was designed to adhere to timelines and data requirements in compliance with Good Clinical Practice (International Conference on Harmonisation E6) reporting standards and US federal regulations, and can be configured to support AE management for many types of study designs and adhere to various domestic or international reporting requirements. This tool allows AEs to be collected in a standard way by multiple distributed users, facilitates accurate and timely AE reporting and reviews, and allows the centralized management of AEs. Our design justification and experience with the system are described.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.