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Titre : | Red flags for spinal pain in patients diagnosed with spinal infection in Nigeria : a 10-year medical records review (2022) |
Auteurs : | James Selfe ; Chidozie Mbada ; Bashir Kaka ; Adesola Odole ; Jane Ashbrook ; Mohamed Yusuf ; Nick Dobbin ; Dave Lee ; Francis Fatoye |
Type de document : | Article |
Dans : | Musculoskeletal Science and Practice (Vol. 60, August 2022) |
Article en page(s) : | p. 102571 |
Note générale : | https://doi.org/10.1016/j.msksp.2022.102571 |
Langues: | Anglais |
Descripteurs : |
HE Vinci Lombalgie ; Maladies ostéomusculaires ; Moelle spinale ; Nigéria ; Signes et symptômes ; Techniques de physiothérapie |
Résumé : | Background Spinal infection is a diagnostic challenge, the personal and economic consequences of misdiagnosis can be significant resulting in paralysis and instability of the spine and can ultimately be fatal. To aid identification of those at risk of spinal infection, a better understanding of the red flags for spinal infection is needed. Objective To better understand which red flags may help to identify spinal infection. Design and Methods: A 10-year medical records review of red flags for spinal infection in Nigeria, using a bespoke data extraction tool. Univariable and multivariable logistic regression was used to identify the main independent predictors of spinal pain. Results 124,913 records were reviewed, 1,645 patients were diagnosed with spinal infection. 79% of patients presented with spinal pain Univariable analysis revealed nine factors (some centres, all age groups above 16 years, co-morbidities, environmental factors, history of TB, radicular pain, pins and needles, numbness and spine tenderness.) were associated with greater odds (OR = 1.77?21.7, p |
Disponible en ligne : | Oui |
En ligne : | https://login.ezproxy.vinci.be/login?url=https://www.sciencedirect.com/science/article/pii/S2468781222000704 |