Ruling out coronary heart disease in primary care: external validation of a clinical prediction rule.

BACKGROUND: The Marburg Heart Score (MHS) aims to assist GPs in safely ruling out coronary heart disease (CHD) in patients presenting with chest pain, and to guide management decisions. AIM: To investigate the diagnostic accuracy of the MHS in an independent sample and to evaluate the generalisability to new patients. DESIGN AND SETTING: Cross-sectional diagnostic study with delayed-type reference standard in general practice in Hesse, Germany. METHOD: Fifty-six German GPs recruited 844 males and females aged ≥ 35 years, presenting between July 2009 and February 2010 with chest pain. Baseline data included the items of the MHS. Data on the subsequent course of chest pain, investigations, hospitalisations, and medication were collected over 6 months and were reviewed by an independent expert panel. CHD was the reference condition. Measures of diagnostic accuracy included the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, likelihood ratios, and predictive values. RESULTS: The AUC was 0.84 (95% confidence interval [CI] = 0.80 to 0.88). For a cut-off value of 3, the MHS showed a sensitivity of 89.1% (95% CI = 81.1% to 94.0%), a specificity of 63.5% (95% CI = 60.0% to 66.9%), a positive predictive value of 23.3% (95% CI = 19.2% to 28.0%), and a negative predictive value of 97.9% (95% CI = 96.2% to 98.9%). CONCLUSION: Considering the diagnostic accuracy of the MHS, its generalisability, and ease of application, its use in clinical practice is recommended.

Clinical predictors for Legionella in patients presenting with community-acquired pneumonia to the emergency department.

BACKGROUND: Legionella species cause severe forms of pneumonia with high mortality and complication rates. Accurate clinical predictors to assess the likelihood of Legionella community-acquired pneumonia (CAP) in patients presenting to the emergency department are lacking. METHODS: We retrospectively compared clinical and laboratory data of 82 consecutive patients with Legionella CAP with 368 consecutive patients with non-Legionella CAP included in two studies at the same institution. RESULTS: In multivariate logistic regression analysis we identified six parameters, namely high body temperature (OR 1.67, p < 0.0001), absence of sputum production (OR 3.67, p < 0.0001), low serum sodium concentrations (OR 0.89, p = 0.011), high levels of lactate dehydrogenase (OR 1.003, p = 0.007) and C-reactive protein (OR 1.006, p < 0.0001) and low platelet counts (OR 0.991, p < 0.0001), as independent predictors of Legionella CAP. Using optimal cut off values of these six parameters, we calculated a diagnostic score for Legionella CAP. The median score was significantly higher in Legionella CAP as compared to patients without Legionella (4 (IQR 3-4) vs 2 (IQR 1-2), p < 0.0001) with a respective odds ratio of 3.34 (95%CI 2.57-4.33, p < 0.0001). Receiver operating characteristics showed a high diagnostic accuracy of this diagnostic score (AUC 0.86 (95%CI 0.81-0.90), which was better as compared to each parameter alone. Of the 191 patients (42%) with a score of 0 or 1 point, only 3% had Legionella pneumonia. Conversely, of the 73 patients (16%) with > or =4 points, 66% of patients had Legionella CAP. CONCLUSION: Six clinical and laboratory parameters embedded in a simple diagnostic score accurately identified patients with Legionella CAP. If validated in future studies, this score might aid in the management of suspected Legionella CAP.

A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin κ C as a compatible prognostic marker in human solid tumors.

PURPOSE: Although the central role of the immune system for tumor prognosis is generally accepted, a single robust marker is not yet available. EXPERIMENTAL DESIGN: On the basis of receiver operating characteristic analyses, robust markers were identified from a 60-gene B cell-derived metagene and analyzed in gene expression profiles of 1,810 breast cancer; 1,056 non-small cell lung carcinoma (NSCLC); 513 colorectal; and 426 ovarian cancer patients. Protein and RNA levels were examined in paraffin-embedded tissue of 330 breast cancer patients. The cell types were identified with immunohistochemical costaining and confocal fluorescence microscopy. RESULTS: We identified immunoglobulin κ C (IGKC) which as a single marker is similarly predictive and prognostic as the entire B-cell metagene. IGKC was consistently associated with metastasis-free survival across different molecular subtypes in node-negative breast cancer (n = 965) and predicted response to anthracycline-based neoadjuvant chemotherapy (n = 845; P < 0.001). In addition, IGKC gene expression was prognostic in NSCLC and colorectal cancer. No association was observed in ovarian cancer. IGKC protein expression was significantly associated with survival in paraffin-embedded tissues of 330 breast cancer patients. Tumor-infiltrating plasma cells were identified as the source of IGKC expression. CONCLUSION: Our findings provide IGKC as a novel diagnostic marker for risk stratification in human cancer and support concepts to exploit the humoral immune response for anticancer therapy. It could be validated in several independent cohorts and carried out similarly well in RNA from fresh frozen as well as from paraffin tissue and on protein level by immunostaining.

Combining bone resorption markers and heel quantitative ultrasound to discriminate between fracture cases and controls.

This nested case-control analysis of a Swiss ambulatory cohort of elderly women assessed the discriminatory power of urinary markers of bone resorption and heel quantitative ultrasound for non-vertebral fractures. The tests all discriminated between cases and controls, but combining the two strategies yielded no additional relevant information. INTRODUCTION: Data are limited regarding the combination of bone resorption markers and heel quantitative bone ultrasound (QUS) in the detection of women at risk for fracture. METHODS: In a nested case-control analysis, we studied 368 women (mean age 76.2 +/- 3.2 years), 195 with low-trauma non-vertebral fractures and 173 without, matched for age, BMI, medical center, and follow-up duration, from a prospective study designed to predict fractures. Urinary total pyridinolines (PYD) and deoxypyridinolines (DPD) were measured by high performance liquid chromatography. All women underwent bone evaluations using Achilles+ and Sahara heel QUS. RESULTS: Areas under the receiver operating-characteristic curve (AUC) for discriminative models of the fracture group, with 95% confidence intervals, were 0.62 (0.56-0.68) and 0.59 (0.53-0.65) for PYD and DPD, and 0.64 (0.58-0.69) and 0.65 (0.59-0.71) for Achilles+ and Sahara QUS, respectively. The combination of resorption markers and QUS added no significant discriminatory information to either measurement alone with an AUC of 0.66 (0.60-0.71) for Achilles+ with PYD and 0.68 (0.62-0.73) for Sahara with PYD. CONCLUSIONS: Urinary bone resorption markers and QUS are equally discriminatory between non-vertebral fracture patients and controls. However, the combination of bone resorption markers and QUS is not better than either test used alone.

Improvement of cardiovascular risk prediction: time to review current knowledge, debates, and fundamentals on how to assess test characteristics.

Cardiovascular risk assessment might be improved with the addition of emerging, new tests derived from atherosclerosis imaging, laboratory tests or functional tests. This article reviews relative risk, odds ratios, receiver-operating curves, posttest risk calculations based on likelihood ratios, the net reclassification improvement and integrated discrimination. This serves to determine whether a new test has an added clinical value on top of conventional risk testing and how this can be verified statistically. Two clinically meaningful examples serve to illustrate novel approaches. This work serves as a review and basic work for the development of new guidelines on cardiovascular risk prediction, taking into account emerging tests, to be proposed by members of the 'Taskforce on Vascular Risk Prediction' under the auspices of the Working Group 'Swiss Atherosclerosis' of the Swiss Society of Cardiology in the future.

Measuring brain perfusion with intravoxel incoherent motion (IVIM): Initial clinical experience.

PURPOSE: To evaluate the feasibility of intravoxel incoherent motion (IVIM) perfusion measurements in the brain with currently available imaging systems. MATERIALS AND METHODS: We acquired high in-plane resolution (1.2 × 1.2 mm(2) ) diffusion-weighted images with 16 different values of b ranging from 0 to 900 s/mm(2) , in three orthogonal directions, on 3T systems with a 32-multichannel receiver head coil. IVIM perfusion maps were extracted by fitting a double exponential model of signal amplitude decay. Regions of interest were drawn in pathological and control regions, where IVIM perfusion parameters were compared to the corresponding dynamic susceptibility contrast (DSC) parameters. RESULTS: Hyperperfusion was found in the nonnecrotic or cystic part of two histologically proven glioblastoma multiforme and in two histologically proven glioma WHO grade III, as well as in a brain metastasis of lung adenocarcinoma, in a large meningioma, and in a case of ictal hyperperfusion. A monoexponential decay was found in a territory of acute ischemia, as well as in the necrotic part of a glioblastoma. The IVIM perfusion fraction f correlated well with DSC CBV. CONCLUSION: Our initial report suggests that high-resolution brain perfusion imaging is feasible with IVIM in the current clinical setting. J. Magn. Reson. Imaging 2014;39:624-632. © 2013 Wiley Periodicals, Inc.

Full-waveform inversion of cross-hole ground-penetrating radar data to characterize a gravel aquifer close to the Thur River, Switzerland

Cross-hole radar tomography is a useful tool for mapping shallow subsurface electrical properties viz. dielectric permittivity and electrical conductivity. Common practice is to invert cross-hole radar data with ray-based tomographic algorithms using first arrival traveltimes and first cycle amplitudes. However, the resolution of conventional standard ray-based inversion schemes for cross-hole ground-penetrating radar (GPR) is limited because only a fraction of the information contained in the radar data is used. The resolution can be improved significantly by using a full-waveform inversion that considers the entire waveform, or significant parts thereof. A recently developed 2D time-domain vectorial full-waveform crosshole radar inversion code has been modified in the present study by allowing optimized acquisition setups that reduce the acquisition time and computational costs significantly. This is achieved by minimizing the number of transmitter points and maximizing the number of receiver positions. The improved algorithm was employed to invert cross-hole GPR data acquired within a gravel aquifer (4-10 m depth) in the Thur valley, Switzerland. The simulated traces of the final model obtained by the full-waveform inversion fit the observed traces very well in the lower part of the section and reasonably well in the upper part of the section. Compared to the ray-based inversion, the results from the full-waveform inversion show significantly higher resolution images. At either side, 2.5 m distance away from the cross-hole plane, borehole logs were acquired. There is a good correspondence between the conductivity tomograms and the natural gamma logs at the boundary of the gravel layer and the underlying lacustrine clay deposits. Using existing petrophysical models, the inversion results and neutron-neutron logs are converted to porosity. Without any additional calibration, the values obtained for the converted neutron-neutron logs and permittivity results are very close and similar vertical variations can be observed. The full-waveform inversion provides in both cases additional information about the subsurface. Due to the presence of the water table and associated refracted/reflected waves, the upper traces are not well fitted and the upper 2 m in the permittivity and conductivity tomograms are not reliably reconstructed because the unsaturated zone is not incorporated into the inversion domain.

Development and validation of a clinical prediction rule for chest wall syndrome in primary care.

ABSTRACT: BACKGROUND: Chest wall syndrome (CWS), the main cause of chest pain in primary care practice, is most often an exclusion diagnosis. We developed and evaluated a clinical prediction rule for CWS. METHODS: Data from a multicenter clinical cohort of consecutive primary care patients with chest pain were used (59 general practitioners, 672 patients). A final diagnosis was determined after 12 months of follow-up. We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS. We used data from a German cohort (n = 1212) for external validation. RESULTS: From bivariate analyses, we identified six variables characterizing CWS: thoracic pain (neither retrosternal nor oppressive), stabbing, well localized pain, no history of coronary heart disease, absence of general practitioner's concern, and pain reproducible by palpation. This last variable accounted for 2 points in the clinical prediction rule, the others for 1 point each; the total score ranged from 0 to 7 points. The area under the receiver operating characteristic (ROC) curve was 0.80 (95% confidence interval 0.76-0.83) in the derivation cohort (specificity: 89%; sensitivity: 45%; cut-off set at 6 points). Among all patients presenting CWS (n = 284), 71% (n = 201) had a pain reproducible by palpation and 45% (n = 127) were correctly diagnosed. For a subset (n = 43) of these correctly classified CWS patients, 65 additional investigations (30 electrocardiograms, 16 thoracic radiographies, 10 laboratory tests, eight specialist referrals, one thoracic computed tomography) had been performed to achieve diagnosis. False positives (n = 41) included three patients with stable angina (1.8% of all positives). External validation revealed the ROC curve to be 0.76 (95% confidence interval 0.73-0.79) with a sensitivity of 22% and a specificity of 93%. CONCLUSIONS: This CWS score offers a useful complement to the usual CWS exclusion diagnosing process. Indeed, for the 127 patients presenting CWS and correctly classified by our clinical prediction rule, 65 additional tests and exams could have been avoided. However, the reproduction of chest pain by palpation, the most important characteristic to diagnose CWS, is not pathognomonic.

A multicentre, retrospective case-control study assessing the role of trabecular bone score (TBS) in menopausal Caucasian women with low areal bone mineral density (BMDa): Analysing the odds of vertebral fracture.

INTRODUCTION: The trabecular bone score (TBS) is a new parameter that is determined from grey level analysis of DXA images. It relies on the mean thickness and volume fraction of trabecular bone microarchitecture. This was a preliminary case-control study to evaluate the potential diagnostic value of TBS, both alone and combined with bone mineral density (BMDa), in the assessment of vertebral fracture. METHODS: Out of a subject pool of 441 Caucasian, postmenopausal women between the ages of 50 and 80 years, we identified 42 women with osteoporosis-related vertebral fractures, and compared them with 126 age-matched women without any fractures (1 case: 3 controls). Primary outcomes were BMDa and TBS. Inter-group comparisons were undertaken using Student's t-tests and Wilcoxon signed ranks tests for parametric and non-parametric data, respectively. Odds ratios for vertebral fracture were calculated for each incremental one standard deviation decrease in BMDa and TBS, and areas under the receiver operating curve (AUC) calculated and sensitivity analysis were conducted to compare BMDa alone, TBS alone, and the combination of BMDa and TBS. Subgroup analyses were performed specifically for women with osteopenia, and for women with T-score-defined osteoporosis. RESULTS: Across all subjects (n=42, 126) weight and body mass index were greater and BMDa and TBS both less in women with fractures. The odds of vertebral fracture were 3.20 (95% CI, 2.01-5.08) for each incremental decrease in TBS, 1.95 (1.34-2.84) for BMDa, and 3.62 (2.32-5.65) for BMDa + TBS combined. The AUC was greater for TBS than for BMDa (0.746 vs. 0.662, p=0.011). At iso-specificity (61.9%) or iso-sensitivity (61.9%) for both BMDa and TBS, TBS + BMDa sensitivity or specificity was 19.1% or 16.7% greater than for either BMDa or TBS alone. Among subjects with osteoporosis (n=11, 40) both BMDa (p=0.0008) and TBS (p=0.0001) were lower in subjects with fractures, and both OR and AUC (p=0.013) for BMDa + TBS were greater than for BMDa alone (OR=4.04 [2.35-6.92] vs. 2.43 [1.49-3.95]; AUC=0.835 [0.755-0.897] vs. 0.718 [0.627-0.797], p=0.013). Among subjects with osteopenia, TBS was lower in women with fractures (p=0.0296), but BMDa was not (p=0.75). Similarly, the OR for TBS was statistically greater than 1.00 (2.82, 1.27-6.26), but not for BMDa (1.12, 0.56-2.22), as was the AUC (p=0.035), but there was no statistical difference in specificity (p=0.357) or sensitivity (p=0.678). CONCLUSIONS: The trabecular bone score warrants further study as to whether it has any clinical application in osteoporosis detection and the evaluation of fracture risk.

INTERMED predicts non-return to work in an occupational rehabilitation setting for individuals with orthopaedic trauma-part 2

Introduction.- The model presented in part I (19 predictors) had good predictive values for non-return to work 2 years after vocational rehabilitation for orthopaedic trauma. However, the number of predictors is high for the detection of patients at risk in a clinic. For example, the INTERMED for itself consists of 20 questions and needs 20 minutes to be filled in. For this reason, the aim of this study was to compare the predictive value of different models for the prediction of non-return to work.Patients and methods.- In this longitudinal prospective study, the cohort consisted of 2156 included inpatients with orthopaedic trauma attending a rehabilitation hospital after a work, traffic, sport or leisure related injury. Two years after discharge, 1502 patients returned a questionnaire regarding return to work. We compared the area under the receiver-operator-characteristics curve (ROC) between different models: INTERMED total score, the 4 partial INTERMED scores, the items of the most predictive partial score; with or without confounders.Results.- The ROC for the total score of the INTERMED plus the five confounders of the of the part one (qualified work, speaking French, lesion of upper extremity, education and age) was 0.72. The sole partial INTERMED score to predict return to work was the social sub score. The ROC for the five items of the latter sub score of the INTERMED was 0.69. The ROC for the five items of the social subscale of the INTERMED combined with five predictors was 0.73. This was significantly better than the use of only the five items from INTERMED alone (delta 0.034; 95% CI 0.017 to .050). The model presented in part I (INTERMED total score plus 18 predictors) was not significantly better than the five items INTERMED social score plus five confounders.Discussion.- The use of a model with ten variables (INTERMED social five items plus five confounders) has good predictive value to detect patients not returning to work after vocational rehabilitation after orthopaedic trauma. The parsimony of this model facilitates its use in a clinic for the detection of patients at risk.

An integer-based score to predict functional outcome in acute ischemic stroke: The ASTRAL score.

OBJECTIVE: To develop and validate a simple, integer-based score to predict functional outcome in acute ischemic stroke (AIS) using variables readily available after emergency room admission. METHODS: Logistic regression was performed in the derivation cohort of previously independent patients with AIS (Acute Stroke Registry and Analysis of Lausanne [ASTRAL]) to identify predictors of unfavorable outcome (3-month modified Rankin Scale score >2). An integer-based point-scoring system for each covariate of the fitted multivariate model was generated by their β-coefficients; the overall score was calculated as the sum of the weighted scores. The model was validated internally using a 2-fold cross-validation technique and externally in 2 independent cohorts (Athens and Vienna Stroke Registries). RESULTS: Age (A), severity of stroke (S) measured by admission NIH Stroke Scale score, stroke onset to admission time (T), range of visual fields (R), acute glucose (A), and level of consciousness (L) were identified as independent predictors of unfavorable outcome in 1,645 patients in ASTRAL. Their β-coefficients were multiplied by 4 and rounded to the closest integer to generate the score. The area under the receiver operating characteristic curve (AUC) of the score in the ASTRAL cohort was 0.850. The score was well calibrated in the derivation (p = 0.43) and validation cohorts (0.22 [Athens, n = 1,659] and 0.49 [Vienna, n = 653]). AUCs were 0.937 (Athens), 0.771 (Vienna), and 0.902 (when pooled). An ASTRAL score of 31 indicates a 50% likelihood of unfavorable outcome. CONCLUSIONS: The ASTRAL score is a simple integer-based score to predict functional outcome using 6 readily available items at hospital admission. It performed well in double external validation and may be a useful tool for clinical practice and stroke research.

Peritoneal carcinomatosis due to ovarian cancer: comparison between MDCT, MRI and 18F-FDG PET/CT

Purpose: To compare MDCT, MRI and 18F-FDG PET/CT for the detection of peritoneal carcinomatosis due to ovarian cancerMethods and Materials: Fifteen women (mean age 65±) with clinical suspicion of ovarian cancer and peritoneal carcinomatosis underwent MDCT, MRI and 18F-FDG PET/CT, simultaneously and shortly performed before surgery (delay 8.1± days). According to the peritoneal cancer index nine abdominopelvic regions were defined. We applied four scores of lesion size on MDCT and MR images, while the maximal standard uptake value (SUVmax) was measured on 18F-FDG PET/CT. Three sites of lymphadenopathy and posterobasal pleural carcinomatosis were also analyzed. First, one radiologist blindly and separately read MDCT and MR images, while one nuclear physician blindly read PET/CT images grading each lesion according to four diagnostic certitudes. Secondly, all the images were reviewed jointly and compared with histopathology. Receiver operating characteristics (ROC) analysis was performed.Results: Peritoneal implants were proven in ten women (75%). Altogether, 228 abdominopelvic sites were compared. Sensitivity and specificity for MDCT was 90.2% and 90.6%, for MRI 93.5% and 86.3%, and for 18F-FDG PET/CT 92.7% and 95.7%, respectively. ROC area under the curve were 0.93 for MDCT and MRI, and 0.96 for 18F-FDG PET/CT respectively. No significant differences (p=0.11) were found between the three modalities.Conclusion: Although MRI revealed to be the most sensitive and 18F-FDG PET/CT the most specific modality, no significant differences were shown between the three techniques.

Discordances in the application of different criteria for quantification of paediatric abdominal obesity: an analysis of two Swiss studies.

Several definitions of paediatric abdominal obesity have been proposed but it is unclear whether they lead to similar results. We assessed the prevalence of abdominal obesity using five different waist circumference-based definitions and their agreement with total body fat (TBF) and abdominal fat (AF). Data from 190 girls and 162 boys (Ballabeina), and from 134 girls and 113 boys (Kinder-Sportstudie, KISS) aged 5-11 years were used. TBF was assessed by bioimpedance (Ballabeina) or dual energy X-ray absorption (KISS). On the basis of the definition used, the prevalence of abdominal obesity varied between 3.1 and 49.4% in boys, and 4.7 and 55.5% in girls (Ballabeina), and between 1.8 and 36.3% in boys and 4.5 and 37.3% in girls (KISS). Among children considered as abdominally obese by at least one definition, 32.0 (Ballabeina) and 44.7% (KISS) were considered as such by at least two (out of five possible) definitions. Using excess TBF or AF as reference, the areas under the receiver operating curve varied between 0.577 and 0.762 (Ballabeina), and 0.583 and 0.818 (KISS). We conclude that current definitions of abdominal obesity in children lead to wide prevalence estimates and should not be used until a standard definition can be proposed.

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies.

ABSTRACT: BACKGROUND: Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. METHODS: We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. RESULTS: We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. CONCLUSIONS: We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

Symptomatic intracranial hemorrhage after stroke thrombolysis: comparison of prediction scores.

BACKGROUND AND PURPOSE: Several prognostic scores have been developed to predict the risk of symptomatic intracranial hemorrhage (sICH) after ischemic stroke thrombolysis. We compared the performance of these scores in a multicenter cohort. METHODS: We merged prospectively collected data of patients with consecutive ischemic stroke who received intravenous thrombolysis in 7 stroke centers. We identified and evaluated 6 scores that can provide an estimate of the risk of sICH in hyperacute settings: MSS (Multicenter Stroke Survey); HAT (Hemorrhage After Thrombolysis); SEDAN (blood sugar, early infarct signs, [hyper]dense cerebral artery sign, age, NIH Stroke Scale); GRASPS (glucose at presentation, race [Asian], age, sex [male], systolic blood pressure at presentation, and severity of stroke at presentation [NIH Stroke Scale]); SITS (Safe Implementation of Thrombolysis in Stroke); and SPAN (stroke prognostication using age and NIH Stroke Scale)-100 positive index. We included only patients with available variables for all scores. We calculated the area under the receiver operating characteristic curve (AUC-ROC) and also performed logistic regression and the Hosmer-Lemeshow test. RESULTS: The final cohort comprised 3012 eligible patients, of whom 221 (7.3%) had sICH per National Institute of Neurological Disorders and Stroke, 141 (4.7%) per European Cooperative Acute Stroke Study II, and 86 (2.9%) per Safe Implementation of Thrombolysis in Stroke criteria. The performance of the scores assessed with AUC-ROC for predicting European Cooperative Acute Stroke Study II sICH was: MSS, 0.63 (95% confidence interval, 0.58-0.68); HAT, 0.65 (0.60-0.70); SEDAN, 0.70 (0.66-0.73); GRASPS, 0.67 (0.62-0.72); SITS, 0.64 (0.59-0.69); and SPAN-100 positive index, 0.56 (0.50-0.61). SEDAN had significantly higher AUC-ROC values compared with all other scores, except for GRASPS where the difference was nonsignificant. SPAN-100 performed significantly worse compared with other scores. The discriminative ranking of the scores was the same for the National Institute of Neurological Disorders and Stroke, and Safe Implementation of Thrombolysis in Stroke definitions, with SEDAN performing best, GRASPS second, and SPAN-100 worst. CONCLUSIONS: SPAN-100 had the worst predictive power, and SEDAN constantly the highest predictive power. However, none of the scores had better than moderate performance.