Callum M Dupre1, Richard Libman2, Samuel I Dupre3, Jeffrey M Katz1, Igor Rybinnik1, Thomas Kwiatkowski4. 1. Department of Neurology, North Shore Long Island Jewish Medical Center, New Hyde Park, New York. 2. Department of Neurology, North Shore Long Island Jewish Medical Center, New Hyde Park, New York. Electronic address: rlibman@lij.edu. 3. Department of Biology, Frostburg State University, Frostburg, Maryland. 4. Department of Emergency Medicine, Hofstra North Shore-LIJ School of Medicine, New Hyde Park, New York.
Abstract
BACKGROUND: Many conditions called "stroke mimics" may resemble acute stroke. The converse of the "stroke mimic" is a presentation suggestive of another condition, which actually represents stroke. These would be "stroke chameleons." The recognition of a chameleon as stroke has implications for therapy and quality of care. METHODS: We performed a retrospective chart review, including all cases for 1 year in which patients had a stroke missed on hospital presentation. Initial erroneous diagnoses were compared for all patients correctly admitted with those diagnoses to determine positive predictive value (PPV) for each chameleon. RESULTS: Ninety-four cases were identified as chameleons where brain imaging revealed acute stroke. The common chameleons were initially diagnosed as altered mental status (AMS) (29, 31%), syncope (15, 16%), hypertensive emergency (12, 13%), systemic infection (10, 11%), and suspected acute coronary syndrome (ACS) (9, 10%). The total number of patients who were diagnosed with these conditions over the same year were AMS (393), syncope (326), hypertensive emergency (144), systemic infection (753), and suspected ACS (817) (total N = 2528). For each chameleon diagnosis, the PPV of each presentation for acute stroke was AMS (7%), syncope (4%), hypertensive emergency (8%), systemic infection (1%), and suspected ACS (1%). CONCLUSIONS: Stroke chameleons may result in patients not receiving appropriate care. The largest proportions of chameleons were AMS, syncope, hypertensive emergency, systemic infection, and suspected ACS. Patients diagnosed with hypertensive emergency or AMS had an 8% and 7% chance of having an acute stroke. Physicians should consider stroke in patients with these diagnoses with a lower threshold to obtain neuroimaging with subsequent appropriate management.
BACKGROUND: Many conditions called "stroke mimics" may resemble acute stroke. The converse of the "stroke mimic" is a presentation suggestive of another condition, which actually represents stroke. These would be "strokechameleons." The recognition of a chameleon as stroke has implications for therapy and quality of care. METHODS: We performed a retrospective chart review, including all cases for 1 year in which patients had a stroke missed on hospital presentation. Initial erroneous diagnoses were compared for all patients correctly admitted with those diagnoses to determine positive predictive value (PPV) for each chameleon. RESULTS: Ninety-four cases were identified as chameleons where brain imaging revealed acute stroke. The common chameleons were initially diagnosed as altered mental status (AMS) (29, 31%), syncope (15, 16%), hypertensive emergency (12, 13%), systemic infection (10, 11%), and suspected acute coronary syndrome (ACS) (9, 10%). The total number of patients who were diagnosed with these conditions over the same year were AMS (393), syncope (326), hypertensive emergency (144), systemic infection (753), and suspected ACS (817) (total N = 2528). For each chameleon diagnosis, the PPV of each presentation for acute stroke was AMS (7%), syncope (4%), hypertensive emergency (8%), systemic infection (1%), and suspected ACS (1%). CONCLUSIONS:Strokechameleons may result in patients not receiving appropriate care. The largest proportions of chameleons were AMS, syncope, hypertensive emergency, systemic infection, and suspected ACS. Patients diagnosed with hypertensive emergency or AMS had an 8% and 7% chance of having an acute stroke. Physicians should consider stroke in patients with these diagnoses with a lower threshold to obtain neuroimaging with subsequent appropriate management.
Authors: Tracy E Madsen; Jane Khoury; Rhonda Cadena; Opeolu Adeoye; Kathleen A Alwell; Charles J Moomaw; Erin McDonough; Matthew L Flaherty; Simona Ferioli; Daniel Woo; Pooja Khatri; Joseph P Broderick; Brett M Kissela; Dawn Kleindorfer Journal: Acad Emerg Med Date: 2016-09-27 Impact factor: 3.451
Authors: Michael P Lerario; Alexander E Merkler; Gino Gialdini; Neal S Parikh; Babak B Navi; Hooman Kamel Journal: Stroke Date: 2016-01-07 Impact factor: 7.914
Authors: Annika Berglund; Mia von Euler; Karin Schenck-Gustafsson; Maaret Castrén; Katarina Bohm Journal: BMJ Open Date: 2015-04-28 Impact factor: 2.692
Authors: Fabrício Diniz de Lima; Gustavo José Luvizutto; Arthur Oscar Schelp; Gabriel Pereira Braga; Rodrigo Bazan Journal: Case Rep Neurol Date: 2017-12-11