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Related Concept Videos

Pharmacovigilance01:19

Pharmacovigilance

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Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
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Pharmaceutical Poisoning: Potential Scenarios01:26

Pharmaceutical Poisoning: Potential Scenarios

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Pharmaceutical poisoning can occur through various channels, impacting an estimated 2 million hospitalized patients in the U.S. annually with serious adverse drug responses. These scenarios encompass both therapeutic uses, such as drug toxicity, where even standard dosages can lead to severe central nervous system depression, and non-therapeutic exposures, including accidental ingestion by children, and environmental and occupational exposures.Unintentional poisonings often involve exploratory...
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Drug Toxicity: Risk factors01:24

Drug Toxicity: Risk factors

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Adverse Drug Reactions (ADRs) are potential complications that arise during pharmacotherapy, influenced by multiple risk factors. Age plays a significant role; both neonates and the elderly are at heightened risk due to their respective immature and diminished metabolic and elimination processes. Gender also impacts ADRs, with females experiencing a 1.5 to 1.7-fold greater risk than males, which may be linked to pharmacokinetic, pharmacodynamic, and hormonal differences. Notably, neonates, the...
170
Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

255
It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...
255
Allergic Drug Reactions01:27

Allergic Drug Reactions

1.6K
Allergic reactions related to drugs are hypersensitivity responses driven by the immune system and bear no connection to the drug's therapeutic action. While drugs in isolation do not trigger an immune response, they can interact with endogenous proteins to form antigens. These antigens stimulate lymphocytes to produce antibodies. IgE-type antibodies attach themselves to mast cells. Upon subsequent exposure to the same stimulus, the antigen-antibody interaction is initiated, unleashing...
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Drug Toxicity: Overview01:00

Drug Toxicity: Overview

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Drug toxicity quantifies the harm a compound causes to an organism, varying by dose and potentially impacting whole systems or specific organs like the liver. Toxic reactions may arise from venomous insect or spider bites, with effects ranging from mild symptoms to severe outcomes such as brain damage or death. Common forms of acute poisoning include ethanol intoxication and overdose of pain or fever medications, with substances like GHB and heroin being particularly lethal at doses close to...
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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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Rough-set-based ADR signaling from spontaneous reporting data with missing values.

Wen-Yang Lin1, Lin Lan1, Feng-Hsiung Huang2

  • 1Dept. of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan.

Journal of Biomedical Informatics
|November 6, 2015
PubMed
Summary
This summary is machine-generated.

This study explores using rough set theory to detect adverse drug events (ADRs) in databases with missing information. The new method shows comparable ADR signal detection to traditional approaches, sometimes with earlier warnings.

Keywords:
Adverse drug reactionMissing dataPharmacovigilanceRough set theorySpontaneous reporting data

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Area of Science:

  • Pharmacovigilance
  • Data Mining
  • Computational Statistics

Background:

  • Spontaneous reporting systems collect adverse drug events (ADRs) globally.
  • Missing data in ADR reports is a common issue, often handled by deletion.
  • Few studies investigate methods that incorporate missing data for ADR detection.

Purpose of the Study:

  • To explore the feasibility of applying rough set theory to ADR detection.
  • To develop and evaluate novel methods for ADR signal detection using incomplete data.

Main Methods:

  • Proposed twelve rough set-based methods for measuring ADR signal strength.
  • Utilized characteristic set-based approximation within the rough set framework.
  • Evaluated methods on the FARES database, comparing with traditional listwise deletion.

Main Results:

  • Identified six feasible rough set-based methods for ADR detection.
  • The rough-set-based approach demonstrated similar timeline warning capabilities for ADR signals compared to traditional methods.
  • Observed instances where the new approach yielded earlier detection of suspicious ADR signals.

Conclusions:

  • Rough set theory is a feasible approach for ADR detection, even with missing data.
  • Incorporating missing data via rough sets can maintain or improve ADR signal detection efficiency.
  • This methodology offers a promising alternative to data deletion in pharmacovigilance databases.