title: Detection of adverse drug reactions by medication antidote signals and comparison of their sensitivity with common methods of ADR detection.
abstract: OBJECTIVE
  To determine the PPVs of selected ten medication antidote signals in recognizing potential ADRs and comparison of their sensitivity with manual chart analysis, and voluntary reporting recognizing the same ADRs.
  
  
  METHODS
  The inpatient EMR database of internal medicine department was utilized for a period of one year, adult patients prescribed at least one of the ten signals, were included in the study, recipient patients of antidote signals were assessed for the occurrence of an ADR by Naranjo's tool of ADR evaluation. PPVs of each antidote signal were verified.
  
  
  RESULTS
  PPV of Methylprednisolone and Phytonadione was 0.28, Metoclopramide and Potassium Chloride - 0.29, Dextrose 50%, Promethazine, Sodium Polystyrene and Loperamide - 0.30, Protamine and Acetylcysteine - 0.33. In comparison of confirmed ADRs of antidote signals with other methods, Dextrose 50%, Metoclopramide, Sodium Polystyrene, Potassium Chloride, Methylprednisolone and Promethazine seem to be extremely significant (P value > 0.0001), while ADRs of Phytonadione, Protamine, Acetylcysteine and Loperamide were insignificant.
  
  
  CONCLUSIONS
  Antidote medication signals have definitive discerning evaluation value of ADRs over routine methods of ADR detection with a high detection rate with a minimum cost; Their integration with hospital EMR database and routine patient safety surveillance enhances transparency, time-saving and facilitates ADR detection.
authors.affiliation: Department of Pharmacology, Faculty of Medicine, King Abdulaziz University, Saudi Arabia.
authors.forename: Lateef M
authors.initials: LM
authors.lastname: Khan
authors.affiliation: Department of Pharmacology, Faculty of Medicine, King Abdulaziz University, Saudi Arabia.
authors.forename: Sameer E
authors.initials: SE
authors.lastname: Al-Harthi
authors.affiliation: Department of Pharmacology, Faculty of Medicine, King Abdulaziz University, Saudi Arabia.
authors.forename: Huda M
authors.initials: HM
authors.lastname: Alkreathy
authors.affiliation: Department of Pharmacology, Faculty of Medicine, King Abdulaziz University, Saudi Arabia ; National Cancer Institute, Cairo University, Egypt.
authors.forename: Abdel-Moneim M
authors.initials: AM
authors.lastname: Osman
authors.affiliation: Department of Pharmacology, Faculty of Medicine, King Abdulaziz University, Saudi Arabia.
authors.forename: Ahmed S
authors.initials: AS
authors.lastname: Ali
keywords: Adverse drug reactions; Electronic medical record; Medication antidote signals; Positive predictive value