Literature DB >> 25300384

A description of clinical characteristics and treatment patterns observed within prescribed opioid users in Germany and the UK.

Pierre Chevalier1, Maartje Smulders, Soheil Chavoshi, Mark Sostek, Robert LoCasale.   

Abstract

AIMS: To describe a cohort of new opioid users (adult noncancer patients) in terms of clinical characteristics and treatment patterns in the UK and Germany. MATERIAL &
METHODS: Data used were extracted from electronic medical records databases (UK: Clinical Practice Research Database-Hospital Episode Statistics; Germany: IMS Disease Analyzer) covering the 2008-2012 period.
RESULTS: Most eligible patients were treated with opioids for less than 6 months (UK: 78.7% and Germany: 93.7%) and indexed on weak opioids (UK: 89.5% and Germany: 88.6%). Most prescribed opioids were codeine (UK) and tramadol (Germany). Most prevalent comorbidities were dorsalgia/depression. Constipation was observed in 16.8%/17.4% (UK/Germany) of chronic users (>6 months).
CONCLUSION: While both populations were highly morbid populations largely initiated on weak opioids, chronic use was less common in Germany.

Entities:  

Keywords:  CPRD; drug utilization; electronic medical records; epidemiology; opioid; pain

Mesh:

Substances:

Year:  2014        PMID: 25300384     DOI: 10.2217/pmt.14.26

Source DB:  PubMed          Journal:  Pain Manag        ISSN: 1758-1869


  5 in total

1.  Temporal trend of opioid and nonopioid pain medications: results from a national in-home survey, 2001 to 2018.

Authors:  Yun Wang; Dan Wu; Alexandre Chan; Chih-Hung Chang; Vivian W Y Lee; Michael B Nichol
Journal:  Pain Rep       Date:  2022-05-17

2.  Examining patterns in opioid prescribing for non-cancer-related pain in Wales: preliminary data from a retrospective cross-sectional study using large datasets.

Authors:  Emma Davies; Ceri Phillips; Jaynie Rance; Berni Sewell
Journal:  Br J Pain       Date:  2018-09-25

3.  Tramadol and the risk of seizure: nested case-control study of US patients with employer-sponsored health benefits.

Authors:  Richard L Morrow; Colin R Dormuth; Michael Paterson; Muhammad M Mamdani; Tara Gomes; David N Juurlink
Journal:  BMJ Open       Date:  2019-03-13       Impact factor: 2.692

4.  Machine learning approach to predict postoperative opioid requirements in ambulatory surgery patients.

Authors:  Akira A Nair; Mihir A Velagapudi; Jonathan A Lang; Lakshmana Behara; Ravitheja Venigandla; Nishant Velagapudi; Christine T Fong; Mayumi Horibe; John D Lang; Bala G Nair
Journal:  PLoS One       Date:  2020-07-31       Impact factor: 3.240

5.  Trends in long-term opioid prescribing in primary care patients with musculoskeletal conditions: an observational database study.

Authors:  John Bedson; Ying Chen; Richard A Hayward; Julie Ashworth; Kate Walters; Kate M Dunn; Kelvin P Jordan
Journal:  Pain       Date:  2016-07       Impact factor: 7.926

  5 in total

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