Cincinnati Prehospital Stroke Scale. Its role in Emergency Department

Stroke is the second leading global cause of death after heart disease and the third leading cause of disability. That’s why the Cincinnati Prehospital Stroke Scale is a very important instrument to evaluate the stroke on patients.

The stroke is not a disease to undervalue. Many people can suffer from stroke, like people who work too much and also some veterans. The Cincinnati Prehospital Stroke Scale (CPSS) is a medical rating scale to diagnose stroke in patients. It is used by doctors and nurses both in the emergency department and in pre-hospital care.

Cincinnati Prehospital Stroke Scale: how does it work?

Hereunder the three aspects of the evaluation of the scale:

  • Facial mimic: make the patient smile or ask him/her showing the teeth; if both sides of the face move in the same way, the situation is ok. Otherwise, if one side of the face moves differently from the other, the situation is abnormal.
  • Movement of arms: invite the patient to close his eyes and raise his arms); the situation is normal if both limbs move in the same way, it is abnormal when one limb falls or moves differently from the other
  • Language: enabling the patient to pronounce a sentence. If the patient pronounces the sentence correctly, the situation is normal. If the patient misses the words, does not pronounce them well or just cannot speak,  it is abnormal.

In particular, the National Center for Biotechnology Information reported the study and the conclusions of the role of the Cincinnati Prehospital Stroke Scale in the emergency department: evidence from a systematic review and meta-analysis.

BELOW A PART OF THE PAPER ABOUT STROKE SCALE:

” In 2015, an estimated 6.3 million deaths occurred because of cerebrovascular disease: a total of 3 million people died because of ischemic stroke and 3.3 million because of hemorrhagic stroke. In high-income countries such as Europe, in the last decades, a decreasing trend in stroke mortality rate was reported; for instance, in Italy, from 1990 to 2016, the number of deaths decreased by 17% (from 60,000 to 50,000), and a remarkable decrease by approximately 45% resulted in Denmark from 1994 to 2011. Despite this declining trend in mortality, stroke incidence increased globally by 5% between 2005 and 2015.
Furthermore, in 2010, stroke ranked in the top 18 diseases that contributed to years lived with disability worldwide and, among them, it is the only one that significantly increased from 1990 to 2010. A significant improvement in patient outcomes is reported by several studies that showed that shorter treatment times increase the chance of returning to good function (ie, being independent and having slight disability or less) when treated within 4.5 hrs from symptoms onset. For this reason, numerous efforts to aid clinicians and Emergency Medical Staff (EMS) to fastly identify this pathology, either in hospital and prehospital settings, were carried out, and several stroke prediction scales were elaborated.

The Cincinnati Prehospital Stroke Scale (CPSS), the Face-Arm-Speech-Time (FAST), the FAST-ED, the Rapid Arterial Occlusion Evaluation Scale, the Los Angeles Prehospital Stroke Screen (LAPSS) are stroke impairment scales developed to quickly assess possible stroke in patients in the prehospital setting. The NIHSS, the Recognition Of Stroke in the Emergency Room, 3-item Stroke Scale, the Cincinnati Prehospital Stroke Severity Scale (CPSSS or C-STAT), were designed for hospital use with the aim of detecting stroke and its severity.

In 2013, Jauch et al reported that the best door-to-physician time should be less than 10 mins, and door-to-stroke unit admission time less than 3 hrs. Moreover, EMS is recommended to reach the target time of fewer than 20 mins from hospital arrival to CT scan, and less than 60 mins door-to-needle time.

For this reason, emergency medical systems should activate a prehospital stroke prenotification, which is associated both with earlier door-to imaging time (25 mins reduction) and door-to-needle time (60 mins reduction). Currently, the CPSS, the FAST, and the LAPSS scales are recommended by the American Heart Association/American Stroke Association guidelines as validated and standardized tools for stroke screening, even if there is no strong evidence that suggests a higher accuracy of one over the other.

The CPSS, proposed by Kothari et al (1999), in particular, is a short, practical, and easy-to-use scale developed extracting 3 of the 15 symptoms from the NIHSS, the gold standard for the assessment of stroke severity. The CPSS assesses facial palsy, asymmetric arm weakness, and speech disturbances, and each item can be scored as normal or not; if any of three is abnormal, the patient is suspected of having a stroke.

In the last two decades, reviews were published with the aim of comparing existing scales, but none of them focused only on the validity of the CPSS in terms of sensitivity and specificity, even if it is one of the most commonly used prehospital tools, included in several stroke emergency medical systems protocols and national recommendations. The aim of this study is to systematically review the role of the CPSS, globally assessing its sensitivity and specificity in prehospital and hospital settings.

Stroke Scale: methods

Study design and literature search

A systematic review and meta-analysis of the scientific literature were conducted. Literature search was carried out querying the following electronic databases: EMBASE, PubMed, Web Of Science, Cochrane, and Scopus from their commencements to December 2018, without language restrictions. The search string was created using the elements of the PICO model (P, population/patient; I, intervention/indicator; C, comparator/control; and O, outcome) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses check-list and flow diagram were used to collect and report data.

The following search terms were used:

  1. Terms related to Population: “brain ischemia”, “carotid artery diseases”, “intracranial embolism and thrombosis”, “intracranial haemorrhages”, “stroke”, “acute cerebrovascular disease”, “transient ischemic attack”, “cerebrovascular accident”, “cerebrovascular diseases”, “cerebrovascular disorders”, “brain vascular accident”, “brain ischemia”, “cerebrovascular occlusion”;

  2. Terms linked to intervention: “Cincinnati Prehospital Stroke Scale”;

  3. Terms related to measured outcomes: “sensitivity”, “specificity”, “positive predictive value”, “negative predictive value”, “reproducibility”.

Boolean operators “OR” and “AND” were used to link the keywords.

References of individual studies were also back-checked for relevant studies, and hand search was used to identify missing articles. Two investigators independently screened titles and abstracts of all records to identify potentially relevant publications.

The following inclusion criteria were used: articles published in English, where the accuracy of the CPSS was assessed using as reference standard the hospital discharge diagnosis of stroke (ischemic, hemorrhagic, or transient ischemic attack).

Articles were excluded if they met at least one of the following criteria: pediatric population, studies without original data (reviews, editorials, practice guidelines, book reviews and chapters, meeting abstracts), quantitative analysis not reported.

Full texts of all potentially eligible studies that met the inclusion criteria were obtained and assessed in duplicate. At all levels, disagreements were resolved by discussion, and by involving a third reviewer when consensus could not be reached.

 

Quality assessment

Two independent researchers evaluated the validity of the selected studies using the Revised Quality Assessment of Diagnostic Accuracy Studies −2 (QUADAS-2) tool, a specific validated tool for the quality assessment of diagnostic accuracy studies.

The QUADAS-2 rates the risk of bias in four domains:

  1. Patient selection assesses methods of patient selection and inappropriate exclusions;

  2. Index test describes how the index test was conducted and interpreted;

  3. Reference standard investigates how the reference standard was conducted and interpreted;

  4. Flow and timing describes any patients who did not receive the index test(s) and/or reference standard or who were excluded from the TP, TN, FN, FN tables.

The applicability form that follows the first three domains evaluates the correspondence between the study design and the purpose of the specific review to be carried out.

If at least one of the answer in each domain or in the concern regarding applicability was deemed at “high risk of bias”, the final risk of bias of the relative domain or in the relative applicability item figures as “High”. If the article did not provide sufficient information, the risk of bias figures as “Unclear”. Otherwise, if no question found any risk of bias, the domain or the applicability form is scored as “low risk of bias”.

Two investigators independently tested the tool for a small number of articles and, once validated, it was used to assess the quality of the included studies.

 

Data extraction and data analysis

From each study, data were manually extracted by two authors using a standardized form including the following information: first author’s last name, year of publication, country, study design, setting, training in stroke scale of hospital and prehospital staff, administrator of the CPSS, population characteristics, type of stroke evaluated and if CPSS was derived from other source or directly performed. An overall estimation of sensitivity and specificity was achieved using a diagnostic test accuracy meta-analysis of the studies that included data on true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN); when these latter not directly reported, they were derived from available data of the included studies.

Pooled and stratified sensitivity and specificity of CPSS (95% confidence interval) and summary receiver operating characteristic (sROC) curves were obtained using STATA 13.0 and Cochrane RevMan 5.3. Stratified analyses were performed according to the study design, setting, scale administrator, and type of stroke investigated.

Diagnostic odds ratio (DOR), pooled positive and negative likelihood ratios (LR+ and LR–), were obtained to assess the informative power of the tests.

Results

Study selection

From a total of 448 articles, 386 were excluded after duplicates removal, and title and abstract reading. The remaining 62 articles were selected for full-text review, 44 were excluded because they did not meet the inclusion criteria of this study. A total of 18 articles were qualitatively synthesized, and eventually, 11 were included in the meta-analysis.”

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