External validation of the "deformity, edema, and pain in pronation" model for predicting wrist fractures.

BACKGROUND: The aim of this study is to externally validate the "Deformity, Edema, and Pain in Pronation" model, which determines the necessity for radiography in patients with wrist trauma. METHODS: This prospective, cross-sectional study was performed in a tertiary emergency department (ED). All patients admitted to the ED with wrist trauma aged 18 years and older were included in the study. Patients who did not have acute and blunt wrist trauma, those who could not be fully examined due to various reasons, and patients who did not wish to participate were excluded. Each patient was examined by their responsible physician, and imaging tests were requested based on the indications. All radiographic images were evaluated by an orthopedic surgeon who was blinded to the clinical information. This evaluation was accepted as the standard reference for diagnosing fractures. RESULTS: 391 patients were included in the study. 170 patients (43.5%) had at least one fracture. The sensitivity and specificity of the model formed in our study in predicting wrist fractures were 98.77% (95% CI: 95.61-99.85) and 27.60% (95% CI 21.82-34.00), respectively. The area under the receiver operating characteristic curve (AUC) on external validation of the model was 0.878 (p < 0.001; 95% CI: 0.844-0.913). With the practice of this rule, there would be a 16% decrease in X-ray imaging request, while only 0.5% patients would have missed inoperable fractures. CONCLUSION: The "deformity, edema, and pain in pronation" model is a reliable and practical clinical decision rule for determining the necessity of radiography in wrist trauma.

The Florida Geriatric Head Trauma CT Clinical Decision Rule.

BACKGROUND: Several clinical decision rules have been devised to guide head computed tomography (CT) use in patients with minor head injuries, but none have been validated in patients 65 years or older. We aimed to derive and validate a head injury clinical decision rule for older adults. METHODS: We conducted a secondary analysis of an existing dataset of consecutive emergency department (ED) patients >65 years old with blunt head trauma. The main predictive outcomes were significant intracranial injury and Need for Neurosurgical Intervention on CT. The secondary outcomes also considered in the model development and validation were All Injuries and All Intracranial Injuries. Predictor variables were identified using multiple variable logistic regression, and clinical decision rule models were developed in a split-sample derivation cohort and then tested in an independent validation cohort. RESULTS: Of 5776 patients, 233 (4.0%) had significant intracranial injury and an additional 104 (1.8%) met CT criteria for Need for Neurosurgical Intervention. The best performing model, the Florida Geriatric Head Trauma CT Clinical Decision Rule, assigns points based on several clinical variables. If the points totaled 25 or more, a CT scan is indicated. The included predictors were arrival via Emergency Medical Services (+30 points), Glasgow Coma Scale (GCS) <15 (+20 points), GCS <14 (+50 points), antiplatelet medications (+17 points), loss of consciousness (+16 points), signs of basilar skull fracture (+50 points), and headache (+20 points). Utilizing this clinical decision rule in the validation cohort, a point total ≥25 had a sensitivity and specificity of 100.0% (95% CI: 96.0-100) and 12.3% (95% CI: 10.9-13.8), respectively, for significant intracranial injury and Need for Neurosurgical Intervention. CONCLUSIONS: The Florida Geriatric Head Trauma CT Clinical Decision Rule has the potential to reduce unnecessary CT scans in older adults, without compromising safe emergency medicine practice.

Using the Kaiser Score as a clinical decision rule for breast lesion classification: Does computer-assisted curve type analysis improve diagnosis?

PURPOSE: We aimed to investigate the effect of using visual or automatic enhancement curve type assessment on the diagnostic performance of the Kaiser Score (KS), a clinical decision rule for breast MRI. METHOD: This IRB-approved retrospective study analyzed consecutive conventional BI-RADS 0, 4 or 5 patients who underwent biopsy after 1.5T breast MRI according to EUSOBI recommendations between 2013 and 2015. The KS includes five criteria (spiculations; signal intensity (SI)-time curve type; margins of the lesion; internal enhancement; and presence of edema) resulting in scores from 1 (=lowest) to 11 (=highest risk of breast cancer). Enhancement curve types (Persistent, Plateau or Wash-out) were assessed by two radiologists independently visually and using a pixel-wise color-coded computed parametric map of curve types. KS diagnostic performance differences between readings were compared by ROC analysis. RESULTS: In total 220 lesions (147 benign, 73 malignant) including mass (n = 148) and non-mass lesions (n = 72) were analyzed. KS reading performance in distinguishing benign from malignant lesions did not differ between visual analysis and parametric map (P = 0.119; visual: AUC 0.875, sensitivity 95 %, specificity 63 %; and map: AUC 0.901, sensitivity 97 %, specificity 65 %). Additionally, analyzing mass and non-mass lesions separately, showed no difference between parametric map based and visual curve type-based KS analysis as well (P = 0.130 and P = 0.787). CONCLUSIONS: The performance of the Kaiser Score is largely independent of the curve type assessment methodology, confirming its robustness as a clinical decision rule for breast MRI in any type of breast lesion in clinical routine.

The Utility of Quantitative D-Dimer Assay as a Biomarker in the Diagnosis and Exclusion of Cerebral Venous Sinus Thrombosis.

The utility and sensitivity of quantitative D-Dimer assay to rule out the diagnosis of deep vein thrombosis is well established. We extrapolated this principle to evaluate the utility of D-Dimer assay in exclusion of cerebral venous sinus thrombosis (CVST). As advanced imaging modalities required for the diagnosis of CVST might not be available everywhere, it is important to have a sensitive biomarker and a clinical decision rule which can assist in the diagnosis. Patients undergoing CT/MR Venography of the brain with the suspicion of CVST were enrolled. Quantitative D-Dimer assay was performed in those who had CVST on CT/MR Venography and was compared with those who did not. A Clinical decision rule for the diagnosis of CVST was formulated using logistic regression analysis. Receiver operating characteristic analysis evaluating the diagnostic accuracy of D Dimer for patients with CVST as compared to those who did not revealed an AUROC of 0.694. D-Dimer levels of < 300 ng/mL had a sensitivity of 90% for the exclusion of CVST. After logistic regression analysis, a clinical decision rule with a total score of 16 and individual components of Female gender (2 points), Headache (7 points), D-Dimer levels of ≥ 792 ng/mL (7 points) was proposed. D-Dimer had a poor diagnostic accuracy for differentiation of patients who had CVST from those who did not, however, had a high sensitivity at values < 300 ng/mL. The proposed clinical decision rule with a score of ≥ 9 had a good diagnostic accuracy in prediction of CVST (AUROC = 0.809).

External Validation of the Post-Concussion Symptoms Rule for Predicting Mild Traumatic Brain Injury Outcome.

Persistent symptoms are common after a mild traumatic brain injury (mTBI). The Post-Concussion Symptoms (PoCS) Rule is a newly developed clinical decision rule for the prediction of persistent post-concussion symptoms (PPCS) 3 months after an mTBI. The PoCS Rule includes assessment of demographic and clinical characteristics and headache presence in the emergency department (ED), and follow-up assessment of symptoms at 7 days post-injury using two thresholds (lower/higher) for symptom scoring. We examined the PoCS Rule in an independent sample. We analyzed a clinical trial that recruited participants with mTBI from EDs in Greater Vancouver, Canada. The primary analysis used data from 236 participants, who were randomized to a usual care control group, and completed the Rivermead Postconcussion Symptoms Questionnaire at 3 months. The primary outcome was PPCS, as defined by the PoCS authors. We assessed the overall performance of the PoCS rule (area under the receiver operating characteristic curve [AUC]), sensitivity, and specificity. More than 40% of participants (median age 38 years, 59% female) reported PPCS at 3 months. Most participants (88%) were categorized as being at medium risk based on the ED assessment, and a majority were considered as being at high risk according to the final PoCS Rule (81% using a lower threshold and 72% using a higher threshold). The PoCS Rule showed a sensitivity of 93% (95% confidence interval [CI], 88-98; lower threshold) and 85% (95% CI, 78-92; higher threshold), and a specificity of 28% (95% CI, 21-36) and 37% (95% CI, 29-46), respectively. The overall performance was modest (AUC 0.61, 95% CI 0.59, 0.65). In conclusion, the PoCS Rule was sensitive for PPCS, but had a low specificity in our sample. Follow-up assessment of symptoms can improve risk stratification after mTBI.

How to Define and Manage Low-Risk Drug Allergy Labels.

Risk stratification in drug allergy implies that specific risk categories (eg, low, moderate, and high) classify historical drug hypersensitivity reactions. These risk categories can be based on reaction phenotypic characteristics, the timing of the reaction and evaluation, the required reaction management, and individual characteristics. Although a multitude of frameworks have been described in the literature, particularly for penicillin allergy labels, there has yet to be a global consensus, and approaches continue to vary between allergy centers. Immune-mediated drug allergies can sometimes be confirmed using skin testing, but a negative drug challenge is required to demonstrate tolerance and remove the allergy from the electronic health record ("delabel" the allergy). Even for quintessential IgE-mediated drug allergy, penicillin allergy, recent data reveal that a direct oral challenge, without prior skin testing, is an appropriate diagnostic strategy in those who are considered low-risk. Drug allergy pathogenesis and clinical manifestations may vary depending on the culprit drug, and as such, the optimal approach should be based on risk stratification that considers individual patient and reaction characteristics, the likely hypersensitivity reaction phenotype, the drug class, and the patient's clinical needs. This article will describe low-risk drug allergy labels, focusing on ß-lactam and sulfonamide antibiotics, nonsteroidal anti-inflammatory drugs, iodinated contrast media, and common chemotherapeutics. This review will also address practical management approaches using currently available risk stratification and clinical decision tools.