Literature DB >> 27848201

The Role of Hemoglobin Laboratory Test Results for the Detection of Upper Gastrointestinal Bleeding Outcomes Resulting from the Use of Medications in Observational Studies.

Elisabetta Patorno1, Joshua J Gagne2, Christine Y Lu3, Kevin Haynes4, Andrew T Sterrett5, Jason Roy6, Xingmei Wang6, Marsha A Raebel5.   

Abstract

INTRODUCTION: The identification of upper gastrointestinal (UGI) bleeding and perforated ulcers in claims data typically relies on inpatient diagnoses. The use of hemoglobin laboratory results might increase the detection of UGI events that do not lead to hospitalization.
OBJECTIVES: Our objective was to evaluate whether hemoglobin results increase UGI outcome identification in electronic databases, using non-steroidal anti-inflammatory drugs (NSAIDs) as a test case.
METHODS: From three data partner sites within the Mini-Sentinel Distributed Database, we identified NSAID initiators aged ≥18 years between 2008 and 2013. Numbers of events and risks within 30 days after NSAID initiation were calculated for four mutually exclusive outcomes: (1) inpatient UGI diagnosis of bleeding or gastric ulcer (standard claims-based definition without laboratory results); (2) non-inpatient UGI diagnosis AND ≥3 g/dl hemoglobin decrease; (3) ≥3 g/dl hemoglobin decrease without UGI diagnosis in any clinical setting; (4) non-inpatient UGI diagnosis, without ≥3 g/dl hemoglobin decrease.
RESULTS: We identified 2,289,772 NSAID initiators across three sites. Overall, 45.3% had one or more hemoglobin result available within 365 days before or 30 days after NSAID initiation; only 6.8% had results before and after. Of 7637 potential outcomes identified, outcome 1 accounted for 21.7%, outcome 2 for 0.8%, outcome 3 for 34.3%, and outcome 4 for 43.3%. Potential cases identified by outcome 3 were largely not suggestive of UGI events. Outcomes 1, 2, and 4 had similar distributions of specific UGI diagnoses.
CONCLUSIONS: Using available hemoglobin result values combined with non-inpatient UGI diagnoses identified few additional UGI cases. Non-inpatient UGI diagnostic codes may increase outcome detection but would require validation.

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Year:  2017        PMID: 27848201     DOI: 10.1007/s40264-016-0472-3

Source DB:  PubMed          Journal:  Drug Saf        ISSN: 0114-5916            Impact factor:   5.606


  18 in total

1.  Design considerations, architecture, and use of the Mini-Sentinel distributed data system.

Authors:  Lesley H Curtis; Mark G Weiner; Denise M Boudreau; William O Cooper; Gregory W Daniel; Vinit P Nair; Marsha A Raebel; Nicolas U Beaulieu; Robert Rosofsky; Tiffany S Woodworth; Jeffrey S Brown
Journal:  Pharmacoepidemiol Drug Saf       Date:  2012-01       Impact factor: 2.890

2.  Positive predictive value of computerized medical records for uncomplicated and complicated upper gastrointestinal ulcer.

Authors:  Andrea V Margulis; Luis A García Rodríguez; Sonia Hernández-Díaz
Journal:  Pharmacoepidemiol Drug Saf       Date:  2009-10       Impact factor: 2.890

3.  Standardized bleeding definitions for cardiovascular clinical trials: a consensus report from the Bleeding Academic Research Consortium.

Authors:  Roxana Mehran; Sunil V Rao; Deepak L Bhatt; C Michael Gibson; Adriano Caixeta; John Eikelboom; Sanjay Kaul; Stephen D Wiviott; Venu Menon; Eugenia Nikolsky; Victor Serebruany; Marco Valgimigli; Pascal Vranckx; David Taggart; Joseph F Sabik; Donald E Cutlip; Mitchell W Krucoff; E Magnus Ohman; Philippe Gabriel Steg; Harvey White
Journal:  Circulation       Date:  2011-06-14       Impact factor: 29.690

4.  Positive predictive value of ICD-9 codes in the identification of cases of complicated peptic ulcer disease in the Saskatchewan hospital automated database.

Authors:  D S Raiford; S Pérez Gutthann; L A García Rodríguez
Journal:  Epidemiology       Date:  1996-01       Impact factor: 4.822

5.  Validation of claims-based diagnostic and procedure codes for cardiovascular and gastrointestinal serious adverse events in a commercially-insured population.

Authors:  Peter M Wahl; Keith Rodgers; Sebastian Schneeweiss; Brian F Gage; Javed Butler; Charles Wilmer; Marshall Nash; Gregory Esper; Norman Gitlin; Neal Osborn; Louise J Short; Rhonda L Bohn
Journal:  Pharmacoepidemiol Drug Saf       Date:  2010-06       Impact factor: 2.890

6.  Evidence of the depletion of susceptibles effect in non-experimental pharmacoepidemiologic research.

Authors:  Y Moride; L Abenhaim; M Yola; A Lucein
Journal:  J Clin Epidemiol       Date:  1994-07       Impact factor: 6.437

7.  Validation of diagnoses of peptic ulcers and bleeding from administrative databases: a multi-health maintenance organization study.

Authors:  Susan E Andrade; Jerry H Gurwitz; K Arnold Chan; James G Donahue; Arne Beck; Myde Boles; Diana S M Buist; Michael Goodman; Andrea Z LaCroix; T R Levin; Richard Platt
Journal:  J Clin Epidemiol       Date:  2002-03       Impact factor: 6.437

8.  A study of the effects of exposure misclassification due to the time-window design in pharmacoepidemiologic studies.

Authors:  T P van Staa; L Abenhaim; H Leufkens
Journal:  J Clin Epidemiol       Date:  1994-02       Impact factor: 6.437

9.  Evaluating medication effects outside of clinical trials: new-user designs.

Authors:  Wayne A Ray
Journal:  Am J Epidemiol       Date:  2003-11-01       Impact factor: 4.897

Review 10.  Individual NSAIDs and upper gastrointestinal complications: a systematic review and meta-analysis of observational studies (the SOS project).

Authors:  Jordi Castellsague; Nuria Riera-Guardia; Brian Calingaert; Cristina Varas-Lorenzo; Annie Fourrier-Reglat; Federica Nicotra; Miriam Sturkenboom; Susana Perez-Gutthann
Journal:  Drug Saf       Date:  2012-12-01       Impact factor: 5.606

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