{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T09:30:48Z","timestamp":1776936648300,"version":"3.51.4"},"reference-count":35,"publisher":"Western Journal of Emergency Medicine","issue":"5","license":[{"start":{"date-parts":[[2021,8,30]],"date-time":"2021-08-30T00:00:00Z","timestamp":1630281600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["WestJEM"],"abstract":"<jats:p>Introduction: Patients with pyogenic spinal Infection (PSI) are often not diagnosed at their initial presentation, and diagnostic delay is associated with increased morbidity and medical-legal risk. We derived a decision tool to estimate the risk of spinal infection and inform magnetic resonance imaging (MRI) decisions.\n\nMethods: We conducted a two-part prospective observational cohort study that collected variables from spine pain patients over a six-year derivation phase. We fit a multivariable regression model with logistic coefficients rounded to the nearest integer and used them for variable weighting in the final risk score. This score, SIRCH (spine infection risk calculation heuristic), uses four clinical variables to predict PSI. We calculated the statistical performance, MRI utilization, and model fit in the derivation phase. In the second phase we used the same protocol but enrolled only confirmed cases of spinal infection to assess the sensitivity of our prediction tool.\n\nResults: In the derivation phase, we evaluated 134 non-PSI and 40 PSI patients; median age in years was 55.5 (interquartile range [IQR] 38-70 and 51.5 (42-59), respectively. We identified four predictors for our risk score: historical risk factors; fever; progressive neurological deficit; and C-reactive protein (CRP) \u2265 50 milligrams per liter (mg\/L). At a threshold SIRCH score of \u2265 3, the predictive model\u2019s sensitivity, specificity, and positive predictive value were, respectively, as follows: 100% (95% confidence interval [CI], 100-100%); 56% (95% CI, 48-64%), and 40% (95% CI, 36-46%). The area under the receiver operator curve was 0.877 (95% CI, 0.829-0.925). The SIRCH score at a threshold of \u2265 3 would prompt significantly fewer MRIs compared to using an elevated CRP (only 99\/174 MRIs compared to 144\/174 MRIs, P &lt;0.001). In the second phase (49 patient disease-only cohort), the sensitivities of the SIRCH score and CRP use (laboratory standard cut-off 3.5 mg\/L) were 92% (95% CI, 84-98%), and 98% (95% CI, 94-100%), respectively.\n\nConclusion: The SIRCH score provides a sensitive estimate of spinal infection risk and prompts fewer MRIs than elevated CRP (cut-off 3.5 mg\/L) or clinician suspicion.<\/jats:p>","DOI":"10.5811\/westjem.2021.5.52007","type":"journal-article","created":{"date-parts":[[2021,9,14]],"date-time":"2021-09-14T00:53:45Z","timestamp":1631580825000},"page":"1156-1166","source":"Crossref","is-referenced-by-count":7,"title":["A Clinical Prediction Tool for MRI in Emergency Department Patients with Spinal Infection"],"prefix":"10.5811","volume":"22","author":[{"given":"Steven","family":"Shroyer","sequence":"first","affiliation":[{"name":"Methodist Hospital System, Greater San Antonio Emergency Physicians, San Antonio, Texas"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William","family":"Davis","sequence":"additional","affiliation":[{"name":"Uniformed Services University of the Health Sciences, Department of Military and Emergency Medicine, Bethesda, Maryland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"April","sequence":"additional","affiliation":[{"name":"Uniformed Services University of the Health Sciences, Department of Military and Emergency Medicine, Bethesda, Maryland; Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brit","family":"Long","sequence":"additional","affiliation":[{"name":"Uniformed Services University of the Health Sciences, Department of Military and Emergency Medicine, Bethesda, Maryland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Greg","family":"Boys","sequence":"additional","affiliation":[{"name":"Methodist Hospital System, Department of Radiology, San Antonio, Texas"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sumeru","family":"Mehta","sequence":"additional","affiliation":[{"name":"Methodist Hospital System, Greater San Antonio Emergency Physicians, San Antonio, Texas"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah","family":"Mercaldo","sequence":"additional","affiliation":[{"name":"Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"3840","published-online":{"date-parts":[[2021,8,30]]},"reference":[{"key":"ref0","doi-asserted-by":"publisher","unstructured":"Davis DP, Wold RM, Patel RJ, et al. 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