Predicting severe pain after major surgery: a secondary analysis of the Peri-operative Quality Improvement Programme (PQIP) dataset.

Armstrong, R A; Fayaz, A; Manning, G L P; Moonesinghe, S R; Oliver, C M

Armstrong, R A; Fayaz, A; Manning, G L P; Moonesinghe, S R; Oliver, C M.

Affiliation

Armstrong RA; Department of Population Health Sciences, University of Bristol, Bristol, UK.
Fayaz A; Department of Anaesthesia, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.
Manning GLP; Department of Anaesthesia and Peri-operative Medicine, University College London Hospital NHS Foundation Trust, London, UK.
Moonesinghe SR; Central London School of Anaesthesia, London, UK.
Oliver CM; Department of Anaesthesia and Peri-operative Medicine, University College London Hospital NHS Foundation Trust, London, UK.

Anaesthesia ; 78(7): 840-852, 2023 07.

Article in En | MEDLINE | ID: mdl-36862937

Subject(s)

Pain, Postoperative; Quality Improvement; Female; Humans; Pain, Postoperative/prevention & control; Risk Factors; Logistic Models; Analgesics, Opioid/therapeutic use

Key words

major surgery; observational study; postoperative pain; risk factors

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pain, Postoperative / Quality Improvement Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Anaesthesia Year: 2023 Type: Article Affiliation country: United kingdom

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