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The Value of Predictive Instruments in the Screening of Acute Stroke: An Umbrella Review on Previous Systematic Reviews Publisher



Baratloo A1, 2 ; Mohamadi M3 ; Mohammadi M3 ; Toloui A4 ; Neishaboori AM4 ; Alavi SNR4 ; Nahiyeh A5 ; Yousefifard M4
Authors
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Authors Affiliations
  1. 1. Research Center for Trauma in Police Operation, Directorate of Health, Rescue and Treatment, Police Headquarter, Tehran, Iran
  2. 2. Prehospital and Hospital Emergency Research Center, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Student Research Committee, Iran University of Medical Sciences, Tehran, Iran
  4. 4. Physiology Research Center, Iran University of Medical Sciences, Tehran, Iran
  5. 5. Faculty of Medicine, University of Central Lancashire, Preston, United Kingdom

Source: Frontiers in Emergency Medicine Published:2022


Abstract

Objective: Although various predictive instruments have been introduced for early stroke diagnosis, there is no consensus on their performance. Therefore, we decided to assess the value of predictive instruments in the detection of stroke by conducting an umbrella review. Method: A search was performed in the Medline, Embase, Scopus and Web of Science databases by the end of August 2021 for systematic reviews and meta-analyses. Original articles included in the systematic reviews were retrieved, summarized and pooled sensitivity, specificity and diagnostic odds ratio were calculated. The level of evidence was divided into five groups: convincing (class I), highly suggestive (class II), suggestive (class III), weak (class IV) and non-significant. Results: The value of 33 predictive instruments was evaluated. The sample size included in these scoring systems’ assessments varied between 182 and 47072 patients. The level of evidence was class I in one tool, class II in 18 tools, class III in 2 tools, class IV in 11 tools, and non-significant in one tool. Apart from Med PACS, which had a low diagnostic value, other tools appeared to be able to detect a stroke. The optimum performance for diagnosis of stroke was for ROSIER, NIHSS, PASS, FAST, LAMS, RACE and CPSS. Conclusion: Convincing to suggestive evidence shows that ROSIER, NIHSS, PASS, FAST, LAMS, RACE and CPSS have the optimum performance in identifying stroke. Since ROSIER’s calculation is simple and has the highest sensitivity and specificity among those predictive instruments, it is recommended for stroke diagnosis in pre-hospital and in-hospital settings. © 2022 Tehran University of Medical Sciences.
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