Clinical Predictors of Accurate Prehospital Stroke Recognition

Introduction

Among patients with acute ischemic stroke (IS), transport by emergency medical services (EMS) has been associated with earlier arrival,¹ faster emergency department (ED) evaluations,^2–4 and improved rates and speed of tissue-type plasminogen activator (tPA) delivery.³ These benefits stem, at least in part, from prearrival activation of stroke teams as a result of hospital prenotification by EMS.^5,6 Stroke recognition by EMS providers in the field is therefore a critical step in the stroke chain of recovery. However, accurate stroke identification in the field is challenging because of variable and often nonspecific clinical presentations of patients with stroke and transient ischemic attack (TIA), as well as the high prevalence of stroke mimics.^7–9 In response to this, many prehospital stroke scales, such as the Los Angeles Prehospital Stroke Screen,¹⁰ the Melbourne Ambulance Stroke Screen,¹¹ the Ontario Prehospital Stroke Screening Tool,¹² and the Cincinnati Prehospital Stroke Scale (CPSS),¹³ have been developed to improve the accuracy of prehospital stroke recognition. Despite endorsement by national guideline recommendations,¹⁴ validation studies have reported variable accuracy of these tools—particularly with respect to false positives resulting in low specificity.¹⁵ Furthermore, the degree to which these scales are incorporated into current EMS practice is not well documented.

We recently established a cohort study to identify and link EMS and hospital records for patients transported by EMS with suspected, confirmed, or missed IS or TIA to determine the accuracy of prehospital stroke recognition. We sought to measure the prevalence of CPSS in this cohort, analyze the relationship between CPSS use and EMS diagnostic accuracy, and describe errors in prehospital stroke recognition.

Methods

The methods used to establish the registry have been published previously.¹⁶ Briefly, this observational registry was conducted in a single county in Southwest Michigan, which is served by 3 independent advanced life support transporting EMS agencies that collectively provide >50 000 transports per year. Patients who were transported by EMS with an impression of suspected stroke or who were diagnosed with IS or TIA after hospital arrival were included, thus capturing EMS-suspected (false positive), confirmed (true positive), and missed (false negative) stroke transports. Patients who were transported by EMS to either of 2 participating primary stroke center hospitals with a primary or secondary impression of suspected stroke/TIA were identified from electronic EMS records. We captured EMS-missed strokes by searching hospital records for patients with a final hospital discharge diagnosis of stroke or TIA who were transported by EMS. Hemorrhagic strokes were excluded. All EMS and hospital medical records were then manually linked. We abstracted data on patient demographics, prehospital care, ED diagnostic testing and treatment, in-hospital mortality, discharge disposition, and discharge diagnosis. Because the local stroke transport protocol directs EMS providers to conduct a CPSS, we recorded the explicit documentation of the CPSS in the EMS record. This study was approved by the Spectrum Health Institutional Review Board.

The final diagnosis for all cases was based on the final hospital discharge diagnosis. Two authors (J.A.O. and T.C.) independently validated the final hospital discharge diagnoses based on review of medical records. Inter-rater agreement for a stroke/TIA diagnosis was high (κ=0.89). The sensitivity and positive predictive value (PPV) of EMS stroke recognition were calculated using a final hospital discharge diagnosis as the gold standard. Because of the fact that the number of true negatives could not be ascertained from our design, specificity and negative predictive value could not be calculated.

To characterize the role of the CPSS in EMS stroke recognition, we compared the accuracy of EMS stroke recognition between cohorts of patients with and without a documented CPSS. The differences in sensitivity and PPV were compared using χ² tests. To determine the independent association between CPSS use and the sensitivity of EMS stroke recognition, we used multivariable logistic regression to calculate the adjusted odds ratio (OR) for accurate prehospital stroke recognition given CPSS documentation among confirmed stroke or TIA cases. We adjusted for potential confounders, including age, National Institute of Health Stroke Scale (NIHSS), sex, dispatch reason (stroke versus others), and time from symptom onset. We then applied the same model among EMS-suspected stroke cases to measure the relationship between CPSS documentation and the PPV of EMS stroke suspicion.

Finally, we examined errors in EMS stroke recognition. To evaluate EMS-missed IS cases, we abstracted clinical characteristics and patient history obtained from the initial ED evaluation of cases that were subsequently confirmed as having IS. The documented NIHSS was used to assess for the presence of specific neurological deficits because physical examination descriptions were highly variable in the ED notes. Because patients with TIA are not candidates for acute intervention and >55% of confirmed TIA cases in our data set lacked a documented NIHSS or had an NIHSS of 0 by the time of presentation in the ED, we excluded patients with TIA from this part of the analysis. We compared the clinical characteristics of EMS-recognized cases with EMS-missed cases using χ² tests for categorical variables, Mann–Whitney U tests for ordinal variables, and Student t-tests for continuous variables. We then compared the prevalence of stroke symptoms and signs among EMS-recognized and missed strokes. We also identified the most common EMS transport impressions among missed stroke and TIA cases and the most common final discharge diagnoses among the patients without stroke transported by EMS as suspected stroke.

Results

During a 1-year period, 371 cases were transported by EMS as suspected stroke or TIA, whereas another 70 stroke cases were transported by EMS for other reasons and so were designated as missed cases. Characteristics of all 441 cases are summarized in Table 1. The median age was 78 years, and 59% were women. A total of 264 cases (59.9%) were confirmed as having a final discharge diagnosis of either IS (n=186) or TIA (n=78). Use of the CPSS was documented in the EMS record in 347 (79%) cases.

The overall sensitivity of EMS stroke recognition was 73.5% (95% confidence interval, 67.7–78.7), and PPV was 52.3% (95% confidence interval, 47.1–57.5; Figure 1). Among the 347 cases with a CPSS documented, the sensitivity of EMS provider stroke recognition was higher than that among the 94 cases where a CPSS was not documented (84.7% versus 30.9%; P<0.0001). The PPV among cases with a documented CPSS was also higher (56.2% versus 30.4%; P=0.0004).

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In multivariable logistic regression analysis conducted among the 264 subjects with confirmed IS or TIA, we found that CPSS documentation was independently associated with the sensitivity of EMS stroke recognition after adjustment for patient age, sex, stroke severity (NIHSS), dispatch reason, and time from symptom onset (OR, 12.02; 95% confidence interval, 5.66–25.51; Table 2). Other factors significantly associated with increased sensitivity of EMS recognition included whether the subjects were evaluated within 120 minutes of symptom onset (OR, 2.22) and higher NIHSS (OR, 1.09). CPSS documentation was also independently associated with higher PPV of EMS stroke suspicion (2.47; 95% confidence interval, 1.30–4.69) among the 371 EMS-suspected stroke cases.

The clinical characteristics of the 141 EMS-recognized IS cases and the 45 missed IS cases are described in Table 3. Demographics and past medical history were similar between the 2 groups. A complaint of unilateral weakness (73.8% versus 48.9%; P=0.002) and unilateral weakness on examination (73.8% versus 53.3%; P=0.01) was more common among EMS-recognized than missed IS, whereas vertigo (5.7% versus 16.3%; P=0.034) and ataxia (12.8% versus 30.2%; P=0.02) were more common among EMS-missed strokes. The sensitivity of EMS stroke recognition was the highest among patients who presented with symptoms and signs included in the CPSS (Table I in the online-only Data Supplement). EMS-recognized strokes had faster door-to-computed tomographic times (34.6 versus 84.7 minutes; P<0.001), and there was a trend toward greater likelihood of tPA delivery (14.9% versus 4.4%; P=0.074). EMS-recognized stroke cases had higher stroke severity (median NIHSS 10 versus 4; Mann–Whitney U test; P<0.001). The frequency distribution of NIHSS categories is shown in Figure 2.

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The most common EMS impressions among the 70 missed stroke transports included generalized weakness (22.9%), altered mental status (14.3%), and dizziness (10.0%; Table 4). Seven EMS-missed cases (10%) were transported for a focal neurological complaint, such as unilateral weakness or aphasia without explicitly identifying the patient as a suspected stroke. The final diagnoses of the 177 cases transported by EMS as suspected strokes who were subsequently given a nonstroke diagnosis are also shown in Table 4. Discharge diagnoses were highly varied among EMS false-positive cases, and more than 1 quarter received a nonspecific, symptom-based discharge diagnosis after diagnostic workup failed to identify a specific cause. The most common stroke mimics were infections (12.4%), seizures (11.3%), and syncope (10.2%).

Discussion

Transportation by EMS is an important predictor of improved in-hospital stroke response and use of tPA for patients with acute IS.^1–3 These benefits likely stem in part from earlier activation of hospital stroke code processes through prearrival notification.⁵ Therefore, accurate prehospital stroke recognition is a critical link in the stroke chain of recovery. Although prehospital stroke scales are endorsed by national guidelines,¹⁷ their real-world effect on EMS stroke recognition is unclear. A recent meta-analysis of 3 validation studies of the CPSS found sensitivities ranging from 79% to 95%¹⁵; however, a recently published study conducted in New York demonstrated EMS sensitivity of only 50% despite CPSS education and incorporation into local stroke protocols.¹⁸

In our cohort of EMS-transported cases, EMS sensitivity for stroke recognition was 74%, slightly lower than the observed range in previous CPSS validation studies.¹⁵ Furthermore, PPV of EMS suspicion of stroke was only 52%, suggesting that there is opportunity for improvement by reducing both the over- and under-recognition of stroke by EMS providers.

Our analysis suggests that a strong relationship exists between documentation of the CPSS and the sensitivity (adjusted OR, 12.02) and PPV (adjusted OR, 2.47) of prehospital stroke recognition. These relationships were independent of stroke severity, dispatch reason, and time from symptom onset, age, and sex. Our results corroborate those of a recently published analysis of prehospital stroke recognition, which reported a similarly strong association between CPSS use and sensitivity.¹⁸ To our knowledge, this is the first study to report higher PPV among EMS cases with a documented CPSS as opposed to no documented stroke scale. Although this supports the hypothesis that use of CPSS improves overall diagnostic accuracy, we suspect that paramedics may use and document a CPSS preferentially among patients with more obvious stroke signs who are already recognized as suspect stroke/TIA cases.

Symptoms and signs not included in the CPSS, such as vertigo (16%) and limb ataxia (30%), were more common among missed stroke cases. Nevertheless, over half of the EMS-missed strokes demonstrated unilateral weakness in the ED and only 30% (11/37) of those cases had a documented CPSS, suggesting that more consistent application of the CPSS in the prehospital setting could improve EMS sensitivity. Because nearly half of EMS-missed strokes were transported with EMS impressions of generalized weakness, altered mental status, or dizziness, increased use of the CPSS among these populations may improve EMS stroke recognition sensitivity.

Other factors associated with EMS sensitivity were early presentation (OR, 2.22) and increasing NIHSS (OR, 1.09 for each 1 point increase). These findings have also been described previously¹⁸ and suggest that paramedics are more likely to recognize patients with more obvious stroke presentations or those perceived to be possible candidates for tPA therapy. An emergency dispatcher impression of possible stroke was also associated with a marginally significant increased likelihood of accurate EMS provider stroke recognition in the multivariable analysis (OR, 1.94). This finding might suggest that dispatch reasons provide a degree of priming for paramedics to consider stroke. If so, this may be another potential target for intervention. Recent studies of the accuracy of emergency dispatcher stroke recognition suggest fairly low sensitivities^19–21; however, incorporation of the CPSS into dispatcher protocols may improve this.^22,23 Future studies are needed to determine whether improved dispatcher recognition translates into improved EMS provider stroke recognition, prehospital notification, and thus downstream in-hospital stroke care.

Historically, the prehospital links in the stroke chain of recovery have received less attention than in-hospital care. Substantial evidence suggests that EMS use is associated with faster ED stroke evaluations^2,4 and increased opportunity for treatment with tPA.³ Our results identified opportunity to improve EMS provider recognition by reducing the rate of missed strokes and false positives through more consistent application of the CPSS. Given the critical role EMS stroke recognition plays in providing high-quality prehospital stroke care,¹⁶ future studies should focus on refinement and implementation of prehospital stroke screening tools and measure the effect of improvements in recognition on patient outcomes.

Footnotes