Diagnostic accuracy of 3-item stroke scale for detection of cerebral large vessel occlusion: A systematic review and meta-analysis.

BACKGROUND: Prompt identification of large vessel occlusion (LVO) in acute ischemic stroke (AIS) is crucial for expedited endovascular therapy (EVT) and improved patient outcomes. Prehospital stroke scales, such as the 3-Item Stroke Scale (3I-SS), could be beneficial in detecting LVO in suspected patients. This meta-analysis evaluates the diagnostic accuracy of 3I-SS for LVO detection in AIS. METHODS: A systematic search was conducted in Medline, Embase, Scopus, and Web of Science databases until February 2024 with no time and language restrictions. Prehospital and in-hospital studies reporting diagnostic accuracy were included. Review articles, studies without reported 3I-SS cut-offs, and studies lacking the required data were excluded. Pooled effect sizes, including area under the curve (AUC), sensitivity, specificity, diagnostic odds ratio (DOR), positive and negative likelihood ratios (PLR and NLR) with 95% confidence intervals (CI) were calculated. RESULTS: Twenty-two studies were included in the present meta-analysis. A 3I-SS score of 2 or higher demonstrated sensitivity of 76% (95% CI: 52%-90%) and specificity of 74% (95% CI: 57%-86%) as the optimal cut-off, with an AUC of 0.81 (95% CI: 0.78-0.84). DOR, PLR, and NLR, were 9 (95% CI: 5-15), 2.9 (95% CI: 2.0-4.3) and 0.32 (95% CI: 0.17-0.61), respectively. Sensitivity analysis confirmed the analyses' robustness in suspected to stroke patients, anterior circulation LVO, assessment by paramedics, and pre-hospital settings. Meta-regression analyses pinpointed LVO definition (anterior circulation, posterior circulation) and patient setting (suspected stroke, confirmed stroke) as potential sources of heterogeneity. CONCLUSION: 3I-SS demonstrates good diagnostic accuracy in identifying LVO stroke and may be valuable in the prompt identification of patients for direct transfer to comprehensive stroke centers.

Prognostic Value of Physiological Scoring Systems in COVID-19 Patients: A Prospective Observational Study.

The objective of this study was to investigate the accuracy of the Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS), Rapid Acute Physiology Score (RAPS), Worthing Physiological Scoring System (WPSS), and Revised Trauma Score (RTS) for predicting the inhospital mortality of COVID-19 patients. This diagnostic accuracy study was conducted in Tehran, Iran, from November 15, 2020, to March 10, 2021. The participants consisted of 246 confirmed cases of COVID-19 patients who were admitted to the emergency department. The patients were followed from the point of admission up until discharge from the hospital. The mortality status of patients (survivor or nonsurvivor) was reported at the discharge time, and the receiver operating characteristic curve analysis of each scoring system for predicting inhospital mortality was estimated. The area under the curve of REMS was significantly higher than other scoring systems and in cutoff value of 6 and greater had a sensitivity and specificity of 89.13% and 55.50%, respectively. Among the five scoring systems employed in this study, REMS had the best accuracy to predict the inhospital mortality rate of COVID-19 patients and RAPS had the lowest accuracy for inhospital mortality. Thus, REMS is a useful tool that can be employed in identifying high-risk COVID-19 patients.

Prognostic Value of CRASH and IMPACT Models for Predicting Mortality and Unfavorable Outcome in Traumatic Brain Injury; a Systematic Review and Meta-Analysis.

Introduction: The Corticosteroid Randomization After Significant Head injury (CRASH) and the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) are two prognostic models frequently used in predicting the outcome of patients with traumatic brain injury. There are ongoing debates about which of the two models has a better prognostic value. This study aims to compare the CRASH and IMPACT in predicting mortality and unfavorable outcome of patients with traumatic brain injury. Method: We performed a literature search using Medline (via PubMed), Embase, Scopus, and Web of Science databases until August 17, 2022. After two independent researchers screened the articles, we included all the original articles comparing the prognostic value of IMPACT and CRASH models in patients with traumatic brain injury. The outcomes evaluated were mortality and unfavorable outcome. The data of the included articles were analyzed using STATA 17.0 statistical program, and we reported an odds ratio (OR) with a 95% confidence interval (95% CI) for comparison. Results: We included the data from 16 studies. The analysis showed that the areas under the curve of the IMPACT core model and CRASH basic model do not differ in predicting the mortality of patients (OR=0.99; p=0.905) and their six-month unfavorable outcome (OR=1.01; p=0.719). Additionally, the CRASH CT model showed no difference from the IMPACT extended (OR=0.98; p=0.507) and IMPACT Lab (OR=1.00; p=0.298) models in predicting the mortality of patients with traumatic brain injury. We also observed similar findings in the six-month unfavorable outcome, showing that the CRASH CT model does not differ from the IMPACT extended (OR=1.00; p=0.990) and IMPACT Lab (OR=1.00; p=0.570) in predicting the unfavorable outcome in head trauma patients. Conclusion: Low to very low level of evidence shows that IMPACT and CRASH models have similar values in predicting mortality and unfavorable outcome in patients with traumatic brain injury. Since the discriminative power of the IMPACT Core and CRASH basic models is not different from the IMPACT extended, IMPACT Lab, and CRASH CT models, it may be possible to only use the core and basic models in examining the prognosis of patients with traumatic injuries to the brain.

Value of N-Terminal Pro-Brain Natriuretic Peptide for Embolic Events Risk Prediction in Patients with Atrial Fibrillation; a Systematic Review and Meta-Analysis.

Introduction: A comprehensive conclusion has yet to be made about the predictive value of serum N-terminal pro-brain natriuretic peptide (NT-proBNP) for stroke/systemic embolic events (SEE) in patients with atrial fibrillation (AF). This study aims to review the evidence for evaluating the value of NT-proBNP in predicting the risk of stroke/SEE in patients with AF through a systematic review and meta-analysis. Method: Two independent reviewers screened all relevant studies that were retrieved from the database of Medline, Embase, Scopus, and Web of Science until December 7th, 2021. The predictive value of NT-proBNP in the prediction of stroke/SEE was recorded as hazard ratio (HR) and 95% confidence interval (95% CI). Results: Nine articles (38,093 patients, 3.10% stroke/SEE) were included in our analysis. There was no publication bias in these studies (P=0.320). Our analysis showed that NT-proBNP can be a good predictor of stroke/SEE risk in AF patients, even at different cut-off values (HR=1.76; 95% CI: 1.51, 2.02; P < 0.001). Subgroup analysis showed that diabetes could have a possible effect on the predictive value of NT-proBNP (meta-regression coefficient = 0.042; P = 0.037). Conclusion: Measurement of NT-proBNP during the first admission could be used to assess the short- or long-term risk of stroke/SEE in patients with AF. Further studies are needed to evaluate the possible applicability of serum NT-proBNP measurement in the settings in which stroke is the sole outcome of the investigation.