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Drugs & Aging

, Volume 34, Issue 2, pp 135–142 | Cite as

Predicting the Risk of Adverse Drug Reactions in Older Inpatients: External Validation of the GerontoNet ADR Risk Score Using the CRIME Cohort

  • Mirko Petrovic
  • Balamurugan Tangiisuran
  • Chakravarthi Rajkumar
  • Tischa van der Cammen
  • Graziano Onder
Original Research Article

Abstract

Background

Adverse drug reactions (ADRs) in older people are often preventable, indicating that screening and prevention programs aimed at reducing their rate are needed in this population.

Objective

The aim of this study was to externally validate the GerontoNet ADR risk score and to assess its validity in specific subpopulations of older inpatients.

Methods

Data from the prospective CRIteria to assess appropriate Medication use among Elderly complex patients (CRIME) cohort were used. Dose-dependent and predictable ADRs were classified as type A, probable or definite ADRs were defined according to the Naranjo algorithm, and diagnostic accuracy was tested using receiver operating characteristic (ROC) analyses. Sensitivity and specificity were calculated for a cut-off point of 4.

Results

The mean age of the 1075 patients was 81.4 years (standard deviation 7.4) and the median number of drugs was 10 (range 7–13). At least one ADR was observed in 70 patients (6.5%); ADRs were classified as type A in 50 patients (4.7%) and defined as probable or definite in 41 patients (3.8%). Fair diagnostic accuracy to predict both type A and probable or definite ADRs was found in subpopulations aged <70 or ≥80 years with heart failure, diabetes, or a previous ADR. Good accuracy to predict type A ADRs was found in patients with a low body mass index (BMI; >18.5 kg/m2) and a Mini-Mental State Examination (MMSE) score of >24/30 points, as well as in patients with osteoarthritis. The cut-off point of 4 points yielded very good sensitivity but poor specificity results in these subpopulations.

Conclusion

This study suggests that the GerontoNet ADR risk score might represent a pragmatic approach to identifying specific subpopulations of older inpatients at increased risk of an ADR with a fair to good diagnostic accuracy.

Keywords

Adverse Drug Reaction Good Diagnostic Accuracy Naranjo Algorithm Crime Study Perform Medication Review 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors are indebted to Dr. Stefanie De Buyser for her skilful assistance with data analysis.

Compliance with Ethical Standards

Funding

This work was supported by the Ministry of Labour, Health and Social Policy, who funded the CRIME project (Bando Giovani Ricercatori 2007, convenzione no. 4).

Conflicts of interest

Mirko Petrovic, Balamurugan Tangiisuran, Chakravarthi Rajkumar, Tischa van der Cammen and Graziano Onder declare that they have no conflicts of interest directly relevant to the content of this study.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mirko Petrovic
    • 1
  • Balamurugan Tangiisuran
    • 2
  • Chakravarthi Rajkumar
    • 3
  • Tischa van der Cammen
    • 4
    • 5
  • Graziano Onder
    • 6
  1. 1.Department of Internal Medicine, Section of GeriatricsGhent UniversityGhentBelgium
  2. 2.School of Pharmaceutical SciencesUniversiti Sains MalaysiaPulau PinangMalaysia
  3. 3.Department of MedicineBrighton and Sussex Medical SchoolBrightonEngland, UK
  4. 4.Department of Internal Medicine (Geriatrics), Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
  5. 5.Faculty of Industrial Design EngineeringDelft University of TechnologyDelftThe Netherlands
  6. 6.Department of Geriatrics (Policlinico A. Gemelli)Catholic University of the Sacred HeartRomeItaly

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