A CPSS score of 3 reliably identifies LVO in AIS patients. EMS providers may be able to use the CPSS, a simple, widely adopted prehospital stroke assessment tool, with a cut-off score to screen for patients with suspected LVO.

IMPORTANCE Endovascular therapy (EVT) improves functional outcomes in acute ischemic stroke (AIS) with large vessel occlusion (LVO). Whether implementation of a regional prehospital transport policy for comprehensive stroke center triage increases use of EVT is uncertain.OBJECTIVE To evaluate the association of a regional prehospital transport policy that directly triages patients with suspected LVO stroke to the nearest comprehensive stroke center with rates of EVT. DESIGN, SETTING, AND PARTICIPANTSThis retrospective, multicenter preimplementationpostimplementation study used an interrupted time series analysis to compare treatment rates before and after implementation in patients with AIS arriving at 15 primary stroke centers and 8 comprehensive stroke centers in Chicago, Illinois, via emergency medical services (

Objectives Identifying stroke during a 9–1-1 call is critical to timely prehospital care. However, emergency medical dispatchers (EMDs) recognize stroke in less than half of 9–1-1 calls, potentially due to the words used by callers to communicate stroke signs and symptoms. We hypothesized that callers do not typically use words and phrases considered to be classical descriptors of stroke, such as focal neurologic deficits, but that a mixed-methods approach can identify words and phrases commonly used by 9–1-1 callers to describe acute stroke victims. Methods We performed a mixed-methods, retrospective study of 9–1-1 call audio recordings for adult patients with confirmed stroke who were transported by ambulance in a large urban city. Content analysis, a qualitative methodology, and computational linguistics, a quantitative methodology, were used to identify key words and phrases used by 9–1-1 callers to describe acute stroke victims. Because a caller’s level of emotional distress contributes to the communication during a 9–1-1 call, the Emotional Content and Cooperation Score was scored by a multidisciplinary team. Results A total of 110 9–1-1 calls, received between June and September 2013, were analyzed. EMDs recognized stroke in 48% of calls, and the emotional state of most callers (95%) was calm. In 77% of calls in which EMDs recognized stroke, callers specifically used the word “stroke”; however, the word “stroke” was used in only 38% of calls. Vague, non-specific words and phrases were used to describe stroke victims’ symptoms in 55% of calls, and 45% of callers used distractor words and phrases suggestive of non-stroke emergencies. Focal neurologic symptoms were described in 39% of calls. Computational linguistics identified 9 key words that were more commonly used in calls where the EMD identified stroke. These words were concordant with terms identified through qualitative content analysis. Conclusions Most 9–1-1 callers used vague, non-specific, or distractor words and phrases and infrequently provide classic stroke descriptions during 9–1-1 calls for stroke. Both qualitative and quantitative methodologies identified similar key words and phrases associated with accurate EMD stroke recognition. This study suggests that tools incorporating commonly used words and phrases could potentially improve EMD stroke recognition.

ObjectivesTelecommunicators use a two-question algorithm to identify cardiac arrest: Is the individual conscious? Is the individual breathing normally? Although this approach increases arrest identification and consequently bystander CPR, the strategy does not identify all arrests and requires time to complete. We evaluated the implications of a one-question strategy that inquired only about consciousness.MethodsWe undertook a 3-month observational study of consecutive cases identified as unconscious by the telecommunicator prior to EMS arrival who were not receiving bystander CPR. We evaluated the extent that a one-question strategy could increase arrest identification and reduce the identification interval; and the trade-off whereby additional persons without arrest could potentially receive CPR.ResultsAmong 679 eligible cases, 20% (n = 135) were in arrest and 80% (n = 544) were not in arrest. The two-question algorithm identified 90% (121/135) as true arrest. Of the 135 in arrest, 70% (n = 95) received compressions. The median interval from call to arrest identification was 72 seconds, with a median of 14 seconds for the breathing normally question. Using the two-question algorithm, telecommunicators incorrectly classified 30% (n = 164/544) of non-arrests as arrest. Bystanders proceeded to compressions in 16% (n = 85/544) of persons not in arrest. A one-question approach that inquired only about consciousness could potentially increase the arrest identification by 10% (14/135) and reduce the interval to compressions by a median of 14 seconds; however the strategy would potentially triple the number of non-arrest cases (544 versus 164) eligible for CPR instructions.ConclusionA single-question arrest identification algorithm may not achieve a favorable balance of risk and benefit.

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