Selfe, James ORCID: https://orcid.org/0000-0001-9931-4998, Mbada, Chidozie ORCID: https://orcid.org/0000-0003-3666-7432, Kaka, Bashir, Odole, Adesola, Ashbrook, Jane, Yusuf, Mohamed, Dobbin, Nick ORCID: https://orcid.org/0000-0001-7508-1683, Lee, Dave and Fatoye, Francis ORCID: https://orcid.org/0000-0002-3502-3953 (2022) Red flags for spinal pain in patients diagnosed with spinal infection in Nigeria: A 10-year medical records review. Musculoskeletal Science and Practice, 60. 102571. ISSN 2468-8630
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Abstract
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 < 0.001), whilst four (some centres, fatigue, fever and myotomal weakness) were associated with lower odds (OR = 0.51–0.59) of spine pain. Six factors were included in the final multivariable model associated with higher odds of spine pain: age groups above 16 years (OR 2.57 to 5.33, p < 0.05), co-morbidity (OR = 1.68, p < 0.05), history of TB (OR = 3.02, p < 0.05), weight loss (OR = 1.75, p < 0.01), radicular pain (OR = 19.88, p < 0.001); spine tenderness (OR = 6.54, p < 0.001). Myotomal weakness (OR = 0.66, p < 0.05) and fatigue (OR = 0.50, p < 0.01) were associated with lower odds of spinal pain in the final model. Conclusion: Using data from ten hospitals in Nigeria within a ten-year period, we have produced a shortlist of red flags that can inform clinical decision making about potential spinal infection.
Impact and Reach
Statistics
Additional statistics for this dataset are available via IRStats2.