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“If it looks like a stroke, walks like a stroke, could it still be a stroke?”

Presentation of Stroke Mimics in the Emergency Department




CASE

History


64-year-old female with a past medical history of a prior middle cerebral artery (MCA) stroke with left hemiplegia (2021), and cardiovascular risk factors of hypertension, hyperlipidaemia, type 2 diabetes complicated by gastroparesis and peripheral neuropathy. Patient has been brought in by ambulance, after having been found with new-onset left facial droop, left upper extremity flaccidity, and aphasia. Last known normal was >24 hours, evidenced in notes retrieved from the patient’s nursing home. Issues with neglect were raised, as to why it had been well over >12 hours between the nursing notes on the patient. Staff had reported that the patient had woken up in the morning mumbling and weaker on the left side. At the patient’s baseline, they are able to ambulate using a wheelchair, has normal strength in bilateral upper extremities, has weakness of left lower extremity but is able to move it. Patient is normally alert and oriented. Unable to perform a thorough Review of Systems due to acuity of condition.

Physical Examination

Vitals on arrival: BP 112/76, P 82, RR 22, T 36.6C, O2 Sat 100% on 2L.

Constitutional: No apparent distress, and is comfortable at rest.

HEENT: Atraumatic. Normocephalic. PERRL. EOMI without nystagmus. Normal Sclera without injection, normal pinnae without drainage, no nasal deformity. Neck Supple.


No remarkable findings on cardiovascular, respiratory, abdominal or MSK examinations.


Neurological Examination: Awake, alert, aphasic on arrival.


Cranial Nerve Examination: (II) Partial Left-sided Hemianopia; (VII) Partial Paralysis of the left upper and lower face.

In order to assess and quantify the extent of neurological deficit, the Total National Institutes of Health Stroke Scale (NIHSS) Score was taken in the Critical Care Bay.

This was 20/42, suggestive of moderate stroke.

Patient lost points on loss of consciousness (-1 for questions, -2 for commands), with left-sided hemianopsia (-2), partial gaze palsy (-1), and dysarthria (-2). No movement was elicited in the left upper extremity (-4) and left lower extremity (-4).

Fine touch was also absent on LUE and LLE. Co-ordination was unable to be assessed.


ED Management


  • CBC notable for WBC 15.34 (normal 4.5 to 11.0 × 109/L)

  • CMP notable for Creatinine 1.68 mg/dL (normal 0.7 to 1.3 mg/dL); Glucose 47 mg/dL (normal 70 to 120 mg/dL)

  • Patient’s Aspirin and Clopidogrel were held, in sight of possible neurosurgical intervention.

  • Initiated therapeutic and supportive interventions, including 1l IV fluids bolus to correct creatinine, providing analgesia and antiemetics as needed.

  • Initial CT Head demonstrated mixed chronic and acute findings; CT imaging reported a loss of grey-white differentiation in the right paramedian occipital lobe, reflecting an acute/subacute infarction

  • Patient received Dextrose 50% (D50) and was followed up with 4-hourly point of care (POC) glucose testing.

  • Patient’s NIHSS improved to 17 (increased movement in the LUE and LLE, regained some sensation in the LUE) after the administration of dextrose. Patient also seemed more alert. This had led the team to believe there is a possibility that these symptoms could have been in the setting of recrudescence of the stroke due to hypoglycemia.

  • Low-dose Sliding Scale of Insulin was given to maintain euglycemia; Acetaminophen was given PRN to maintain normothermia. However, her right MCA cerebrovascular accident in 2021 gave an NIHSS score of 8; acute stroke was not ruled out, and an MRI/ MRA were obtained for further clarification.

  • Brain MRI with and without contrast confirmed large right acute ischemic infarct involving the entire right MCA and ACA territory.

  • The patient was >24 hours since they were last known normal; IV tPA was considered and contraindicated due to presentation outside the 4½ hour time window.

  • Consulted with neurology and admitted to Neurosciences Critical Care Unit (NCCU) for evaluation and management of ischemic stroke, with concerns of oedema and progression to malignant cerebral infarction.

Clinical Question: Before use of imaging, are there clinical characteristics we can use to distinguish stroke patients from stroke mimics in the Emergency Department?


Defined first by Libman et al., (1995), Stroke Mimics are an umbrella term referring to non-ischemic clinical syndromes which are initially suggestive of stroke.


A systematic review of 61 studies, comprising 62,664 participants, found the rate of stroke mimic being 24.8% (15,595 participants), comparing the mimic types, risk factors and clinical findings between the two groups (Pohl et al., 2021).


Using prospective and retrospective cohort study designs, appropriate for calculating incidence of pathology, the large sample size of Pohl et al., (2021) provides us robust generalizable findings, helping us to identify outliers that may have been present had the study had fewer participants.

In view of its strong external validity, we can find reliability in its distribution of stroke mimic types, and clinical characteristics, having been similarly showcased by Buck et al., (2021).


Stroke mimic etiology as reported by Pohl et al., (2021) has been illustrated on the right.


They find that when compared to stroke patients, stroke mimic patients are significantly more likely (P<0.05) to present with headache (28.5% vs. 9.8%), vomiting (28.5% vs. 18.8%), loss of consciousness (14.7% vs. 10.2%). The ability to walk was seen less in stroke patients compared to stroke mimics (37.5% vs. 51.4%) although this was based on only one study (Hand et al., 2006).


Stroke mimic patients were found to have had significantly lower NIHSS score (4.99 ± 5.65 vs. 8.06 ± 6.37, p < 0.001), and more likely to be female (68 vs 56 %, p < 0.001). Stroke mimic patients were found to have a lower average blood pressure reading (154/86mmHg vs. 140/83mmHg, p < 0.001), explained by the lack of cerebrovascular etiology.


Pohl et al., (2021) further report that the following risk factors were significantly more common (p < 0.001) in ischemic stroke patients compared to stroke mimics: smoking; hypertension; dyslipidaemia; diabetes; atrial fibrillation; peripheral vascular disease.


In contrast, stroke mimic patients were more likely to have cognitive impairment (25.4% vs. 11.1%, p<0.001), and migraine (16.5% vs. 11.3%, p<0.001) as risk factors, possibly contributing to the higher likelihood of headache and loss of consciousness seen in patients with stroke.


Tu et al., (2020) externally validated the performance of the following four stroke mimic prediction scales in the setting of the emergency department:

  • the FABS score (Goyal et al., 2016), which assesses if the age <50 years, the absence of facial droop, absence of atrial fibrillation, a systolic blood pressure of <150mmHg at presentation, a history of seizures, and the presence of an isolated sensory symptom

  • the simplified FABS score, which does not look at sensory deficit or seizure disorder, validated by Qin et al., (2017)

  • the TeleStroke mimic (TM) score (Ali et al., 2014), which assesses age, medical history of atrial fibrillation/ hypertension/ seizures, facial weakness, and an NIHSS >14

  • the 9-point Khan score (Khan et al., 2018), assessing age, presence of hypertension, hyperlipidemia/ diabetes mellitus in the absence of atrial fibrillation, and a history of migraine, epilepsy and psychiatric illness.

  • Tu et al., (2020) found the TM score having the highest sensitivity at 91.3%, with the Khan score having the highest specificity (88.2%). Their AUROC analysis found a novel algorithm, using only age greater than 45 years, the absence of migraine and a previous psychiatric history having a 96.9% certainty in prediction of a true ischemic stroke.

These findings are however limited by the study design of Tu et al., (2020), who have only included patients administered intravenous thrombolysis (IVT), and not all patients presenting to the ED. Furthermore, these scales have not been validated by a comparison to an external stroke cohort, and as such we cannot comment on the generalizability of this study.

A recent retrospective observational study by Kim et al., (2022) aimed to investigate the specific neurological characteristics and examination findings used to differentiate stroke and stroke mimics in ‘code-stroke’ patients the emergency department between January to December 2019.

The protocol to determine ‘code-stroke’ was outlined as those patients suspected with stroke after clinical evaluation by an emergency physician, or all patients with an onset of symptoms within 24 hours. After brain CT and MRI, a neurologist would diagnose whether a stroke had occurred, with cases of TIA and cerebral hemorrhage also being coded as stroke.


Kim et al., (2022) reported that, of a total of 409 ‘code-stroke’ patients presenting to the ED, 125 (31%) were diagnosed with stroke mimics.


Statistically significant difference between neurological symptoms has been tabulated below. Kim et al., (2022) found that while hemiparesis and dysarthria were significantly more common in the stroke, dizziness, seizure-like movements, memory disturbance and altered mental status were increasingly present in stroke mimic patients. This supports the review of and mimic types found by Pohl et al., (2021).


When comparing the individual NIHSS items between stroke and stroke mimic patients, the mimic patients were significantly (p<0.001) less likely to present with facial palsy and sensory change, with neglect (p<0.04), visual disturbance (p<0.014) and upper limb monoparesis (p<0.025) being more common in stroke mimic patients, though not significantly so.

Though the NIHSS score was reportedly higher in the stroke group, the difference between these two was found to be smaller than in the older studies of Brunser et al., (2013) and Chernyshev et al., (2010).


Collating a set of seven focal neurological symptoms (unilateral limb weakness, unilateral limb sensory change, facial palsy, dysarthria, aphasia, diplopia, and visual disturbance), Kim et al., (2022) found that as the number of focal deficits increased, so did the likelihood (p<0.001) of an ischaemic stroke diagnosis.





RECOMMENDATIONS


Being such a “heterogenous group of non-vascular aetiologies” (Nguyen and Chang, 2015) with ranging criteria and parameters available to make the final consensus of a stroke mimic, we are posed with a diagnostic challenge for what should be a time-dependent therapeutic intervention. Given that over a third of patients with suspected stroke have an alternative diagnosis (Buck et al., 2021), there are clinical characteristics beyond the focal neurological deficits we should be aware of when evaluating our patients.


With delay in stroke diagnosis having devastating consequences for our patient, we should, as emergency physicians, complement our low index of suspicion for ischemic stroke with regular usage of stroke mimic scales.

As an example: peripheral vertigo accounted for roughly a quarter of all mimics (Pohl et al., 2021), whereas only 5% of emergency vertigo/dizziness complaints were diagnosed as stroke syndromes (Atzema et al., 2016). The bedside H.I.N.T.S. oculomotor exam could prove beneficial as a regular feature in assessments of stroke patients to support a mimic diagnosis of vertigo syndromes.

In order to be clinically useful, our stroke mimic scales should ideally have a high specificity, ensuring we are never missing a true stroke, and as such should be informed by research assessing features characteristics of strokes that are, if true, largely absent in stroke-mimics.


Metabolic and toxic disturbances should also be actively in the list of differentials, which can be supported by blood test results and point-of-care tests.


This increased awareness of stroke mimics must not deter us from actively investigating where ischemic causes are strongly clinically suggested, rather should allow us to broaden treatment outcomes in that misdiagnosed third of patients.


As the literature suggests a stroke mimic demographic tending towards younger female patients, as well as patients commonly presenting with migraines, dizziness, loss of consciousness and associated psychiatric histories, further studies can help compare the incidence of symptoms in stroke mimics – with the hope of approaching a highly-specific standardized stroke-mimic scale that can be performed alongside neurological evaluation to decisively determine whether a presentation is a stroke or not.


REFERENCES


Ali, S. F., Viswanathan, A., Singhal, A. B., Rost, N. S., Forducey, P. G., Davis, L. W., Schindler, J., Likosky, W., Schlegel, S., Solenski, N., Schwamm, L. H., & Partners Telestroke Network (2014). The TeleStroke mimic (TM)-score: a prediction rule for identifying stroke mimics evaluated in a Telestroke Network. Journal of the American Heart Association, 3(3), e000838. https://doi.org/10.1161/JAHA.114.000838


Atzema, C. L., Grewal, K., Lu, H., Kapral, M. K., Kulkarni, G., & Austin, P. C. (2016). Outcomes among patients discharged from the emergency department with a diagnosis of peripheral vertigo. Annals of neurology, 79(1), 32–41. https://doi.org/10.1002/ana.24521


Brunser, A. M., Illanes, S., Lavados, P. M., Muñoz, P., Cárcamo, D., Hoppe, A., Olavarria, V. V., Delgado, I., & Díaz, V. (2013). Exclusion criteria for intravenous thrombolysis in stroke mimics: an observational study. Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 22(7), 1140–1145. https://doi.org/10.1016/j.jstrokecerebrovasdis.2012.10.019


H Buck, B., Akhtar, N., Alrohimi, A., Khan, K., & Shuaib, A. (2021). Stroke mimics: incidence, aetiology, clinical features and treatment. Annals of medicine, 53(1), 420–436. https://doi.org/10.1080/07853890.2021.1890205


Chernyshev, O. Y., Martin-Schild, S., Albright, K. C., Barreto, A., Misra, V., Acosta, I., Grotta, J. C., & Savitz, S. I. (2010). Safety of tPA in stroke mimics and neuroimaging-negative cerebral ischemia. Neurology, 74(17), 1340–1345. https://doi.org/10.1212/WNL.0b013e3181dad5a6


Goyal, N., Tsivgoulis, G., Male, S., Metter, E. J., Iftikhar, S., Kerro, A., Chang, J. J., Frey, J. L., Triantafyllou, S., Papadimitropoulos, G., Abedi, V., Alexandrov, A. W., Alexandrov, A. V., & Zand, R. (2016). FABS: An Intuitive Tool for Screening of Stroke Mimics in the Emergency Department. Stroke, 47(9), 2216–2220. https://doi.org/10.1161/STROKEAHA.116.013842


Hand, P. J., Kwan, J., Lindley, R. I., Dennis, M. S., & Wardlaw, J. M. (2006). Distinguishing between stroke and mimic at the bedside: the brain attack study. Stroke, 37(3), 769–775. https://doi.org/10.1161/01.STR.0000204041.13466.4c


Khan, N. I., Chaku, S., Goehl, C., Endris, L., Mueller-Luckey, G., & Siddiqui, F. M. (2018). Novel Algorithm to Help Identify Stroke Mimics. Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 27(3), 703–708. https://doi.org/10.1016/j.jstrokecerebrovasdis.2017.09.067


Kim, T., Jeong, H. Y., & Suh, G. J. (2022). Clinical Differences Between Stroke and Stroke Mimics in Code Stroke Patients. Journal of Korean medical science, 37(7), e54. https://doi.org/10.3346/jkms.2022.37.e54


Libman, R. B., Wirkowski, E., Alvir, J., & Rao, T. H. (1995). Conditions that mimic stroke in the emergency department. Implications for acute stroke trials. Archives of neurology, 52(11), 1119–1122. https://doi.org/10.1001/archneur.1995.00540350113023


Nguyen, P. L., & Chang, J. J. (2015). Stroke Mimics and Acute Stroke Evaluation: Clinical Differentiation and Complications after Intravenous Tissue Plasminogen Activator. The Journal of emergency medicine, 49(2), 244–252. https://doi.org/10.1016/j.jemermed.2014.12.072


Pohl, M., Hesszenberger, D., Kapus, K., Meszaros, J., Feher, A., Varadi, I., Pusch, G., Fejes, E., Tibold, A., & Feher, G. (2021). Ischemic stroke mimics: A comprehensive review. Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia, 93, 174–182. https://doi.org/10.1016/j.jocn.2021.09.025


Qin, X., Zhao, S., Yin, L., Dou, H., Fu, J., Wang, Y., Li, M., Chen, R., Chen, J., Liu, W., Yang, G., Liu, X., Wang, R., Jia, X., Bu, S., Ma, D., Wang, B., & Li, S. (2017). Validation of simplified FABS scale to predict stroke mimics in a Chinese population undergoing intravenous thrombolysis. Clinical neurology and neurosurgery, 161, 1–5. https://doi.org/10.1016/j.clineuro.2017.07.013


Tu, T. M., Tan, G. Z., Saffari, S. E., Wee, C. K., Chee, D. J. M. S., Tan, C., & Lim, H. C. (2020). External validation of stroke mimic prediction scales in the emergency department. BMC neurology, 20(1), 269. https://doi.org/10.1186/s12883-020-01846-6







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