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Towards better predictive models of chronic post-surgical pain: fitting to the dynamic nature of the pain itself.
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Document type | Article de périodique (Journal article) – Éditorial |
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Access type | Accès libre |
Publication date | 2022 |
Language | Anglais |
Journal information | "British journal of anaesthesia" - Vol. 129, no.3, p. 281-284 (2022) |
Peer reviewed | yes |
Publisher | Elsevier ((United Kingdom) London) |
issn | 0007-0912 |
e-issn | 1471-6771 |
Publication status | Publié |
Affiliations |
UCL
- SSS/IONS/COSY - Systems & cognitive Neuroscience UCL - SSS/IREC/MEDA - Pôle de médecine aiguë UCL - (SLuc) Service d'anesthésiologie |
MESH Subject | Chronic Pain ; Humans ; Pain, Postoperative ; Reproducibility of Results |
Keywords | chronic pain ; neuropathic pain ; postoperative pain ; prediction model ; predictive factors |
Links |
Bibliographic reference | Fletcher, Dominique ; Lavand'homme, Patricia. Towards better predictive models of chronic post-surgical pain: fitting to the dynamic nature of the pain itself.. In: British journal of anaesthesia, Vol. 129, no.3, p. 281-284 (2022) |
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Permanent URL | http://hdl.handle.net/2078.1/280414 |