Literature DB >> 14528523

Predicting the risk of gastrointestinal bleeding due to nonsteroidal antiinflammatory drugs: NSAID electronic assessment of risk.

T Craig Cheetham1, Gerald Levy, Michele Spence.   

Abstract

OBJECTIVE: To validate that, using patient demographics and other risk factors readily obtained from computerized databases, one can predict a priori the risk for developing a nonsteroidal antiinflammatory drug (NSAID) associated gastrointestinal (GI) bleed prior to exposing patients to therapy.
METHODS: We conducted a retrospective cohort analysis using computer-stored information from a large group-model health maintenance organization. All patients who received one or more prescriptions for a single NSAID over a 9 month period were eligible. Historical and risk factor data was obtained for age, sex, prior GI bleeds, use of GI medications, prednisone use, and use of disease modifying antirheumatic drugs (DMARD). We tested a model (eSCORE) that is based on a previous risk stratification method. The primary outcome was a hospital admission for a GI bleed (GI event).
RESULTS: A total of 303,211 NSAID patient-users met eligibility requirements. Serious GI events occurred in 302 patients, for a rate of 0.68% (0.68 events per 100 patient-years' exposure). All the risk factors except DMARD use were associated with a significant increase in the GI event rate. Higher eSCORE points were associated with increased GI event rates.
CONCLUSION: The study supports the concept that the rate of GI events can be predicted by a defined set of easily assessed patient criteria using the eSCORE. Stratification of patients by risk score can guide the physician to appropriate therapeutic options, with the potential of protecting patients at greatest risk for a GI event.

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Year:  2003        PMID: 14528523

Source DB:  PubMed          Journal:  J Rheumatol        ISSN: 0315-162X            Impact factor:   4.666


  5 in total

1.  Nonsteroidal anti-inflammatory drug use and risk of acute kidney injury and hyperkalemia in older adults: a population-based study.

Authors:  Danielle M Nash; Maureen Markle-Reid; Kenneth S Brimble; Eric McArthur; Pavel S Roshanov; Jeffrey C Fink; Matthew A Weir; Amit X Garg
Journal:  Nephrol Dial Transplant       Date:  2019-07-01       Impact factor: 5.992

2.  Individual and population benefits of daily aspirin therapy: a proposal for personalizing national guidelines.

Authors:  Jeremy B Sussman; Sandeep Vijan; HwaJung Choi; Rodney A Hayward
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2011-04-12

3.  Data quality in the outpatient setting: impact on clinical decision support systems.

Authors:  Eta S Berner; Ramkumar K Kasiraman; Feliciano Yu; Midge N Ray; Thomas K Houston
Journal:  AMIA Annu Symp Proc       Date:  2005

4.  Improving ambulatory prescribing safety with a handheld decision support system: a randomized controlled trial.

Authors:  Eta S Berner; Thomas K Houston; Midge N Ray; Jeroan J Allison; Gustavo R Heudebert; W Winn Chatham; John I Kennedy; Gerald L Glandon; Patricia A Norton; Myra A Crawford; Richard S Maisiak
Journal:  J Am Med Inform Assoc       Date:  2005-12-15       Impact factor: 4.497

5.  Prescription pattern of NSAIDs and the prevalence of NSAID-induced gastrointestinal risk factors of orthopaedic patients in clinical practice in Korea.

Authors:  Sung-Hun Lee; Chang-Dong Han; Ick-Hwan Yang; Chul-Won Ha
Journal:  J Korean Med Sci       Date:  2011-03-28       Impact factor: 2.153

  5 in total

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