Evidence map›Paper›PMID 34546893›Full record

Observational studyThe western journal of emergency medicine2021

A Clinical Prediction Tool for MRI in Emergency Department Patients with Spinal Infection.

Steven R Shroyer, William T Davis, Michael D April, Brit Long, Greg Boys, Sumeru G Mehta, Sarah F Mercaldo

Abstract readObservational Study
In one paragraph

Observational study in The western journal of emergency medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Steven R ShroyerMethodist Hospital System, Greater San Antonio Emergency Physicians, San Antonio, Texas.
William T DavisUniformed Services University of the Health Sciences, Department of Military and Emergency Medicine, Bethesda, Maryland.
Michael D AprilUniformed Services University of the Health Sciences, Department of Military and Emergency Medicine, Bethesda, Maryland.
Brit LongUniformed Services University of the Health Sciences, Department of Military and Emergency Medicine, Bethesda, Maryland.
Greg BoysMethodist Hospital System, Department of Radiology, San Antonio, Texas.
Sumeru G MehtaMethodist Hospital System, Greater San Antonio Emergency Physicians, San Antonio, Texas.
Sarah F MercaldoMassachusetts General Hospital, Department of Radiology, Boston, Massachusetts.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPatients 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.

methodsWe 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.

resultsIn 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) ≥ 50 milligrams per liter (mg/L). At a threshold SIRCH score of ≥ 3, the predictive model's 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 ≥ 3 would prompt significantly fewer MRIs compared to using an elevated CRP (only 99/174 MRIs compared to 144/174 MRIs, P <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.

conclusionThe 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.

Indexed as

Decision Support Systems, ClinicalAdultAgedBack PainC-Reactive ProteinDelayed DiagnosisEmergency Service, HospitalHospitalizationHumansMagnetic Resonance ImagingMaleMiddle AgedPredictive Value of TestsProspective StudiesSensitivity and SpecificityC-Reactive Protein

Identifiers

PMID34546893
PMCPMC8463051

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.