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Non‐steroidal anti‐inflammatory drugs and the risk of <i>Clostridium difficile</i>‐associated disease

2012· article· en· W1485516808 on OpenAlexafffund
Daniel Suissa, Joseph A. Delaney, Sandra Dial, Paul Brassard

Bibliographic record

VenueBritish Journal of Clinical Pharmacology · 2012
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsJewish General HospitalMcGill University Health CentreCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health Research
KeywordsOdds ratioMedicineDiclofenacClostridium difficileInternal medicinePopulationCase-control studyConfidence intervalIntensive care medicineAntibioticsPharmacologyEnvironmental healthBiologyMicrobiology

Abstract

fetched live from OpenAlex

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Increasing age, length of hospital stay and previous antibiotic use have been established as important risk factors in the development of Clostridium difficile associated disease (CDAD). Several case reports over the past 30 years have linked diclofenac, a non‐steroidal anti‐inflammatory drug (NSAID) with CDAD. We assessed whether NSAID use in general, and diclofenac use in particular, is associated with an increased risk of CDAD. WHAT THIS STUDY ADDS • In this population based study, the use of diclofenac was associated with a 35% increase in the risk of developing CDAD. This association persisted when we limited the analysis to non‐hospitalized patients. No association was found between the use of any other NSAIDs and the risk of CDAD. AIM Several case reports have linked diclofenac, a non‐steroidal anti‐inflammatory drug (NSAID), with Clostridium difficile associated disease (CDAD). We assessed whether NSAID use in general, and diclofenac use in particular, is associated with an increased risk of CDAD. METHODS We used the United Kingdom's General Practice Research Database (GPRD) to conduct a population‐based case–control study. All cases of CDAD occurring between 1994 and 2005 were identified and were matched to 10 controls each. Conditional logistic regression was used to estimate the odds ratio of CDAD associated with current NSAID use, adjusting for covariates. RESULTS We identified 1360 CDAD cases and 13 072 controls. We found an increased risk of CDAD associated with diclofenac (adjusted odds ratio (RR) 1.35, 95% confidence interval (CI) 1.10, 1.67). We did not observe an increased risk of CDAD with use of any other NSAID. No dose–response for diclofenac exposure was found. When we analyzed only patients who were not hospitalized in the year before the index date, we found diclofenac to have a similar effect on CDAD risk (adjusted RR 1.43, 95% CI 1.11, 1.84). CONCLUSION Diclofenac use is associated with a modest increase in the risk of CDAD. In patients at risk of CDAD, other NSAIDs could be prescribed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.358
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2012
Admission routes2
Has abstractyes

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