Retrospective Study of Midazolam Protocol for Prehospital Behavioral Emergencies.

INTRODUCTION: Agitated patients in the prehospital setting pose challenges for both patient care and emergency medical services (EMS) provider safety. Midazolam is frequently used to control agitation in the emergency department setting; however, limited data exist in the prehospital setting. We describe our experience treating patients with midazolam for behavioral emergencies in a large urban EMS system. We hypothesized that using midazolam for acute agitation leads to improved clinical conditions without causing significant clinical deterioration. METHODS: We performed a retrospective review of EMS patient care reports following implementation of a behavioral emergencies protocol in a large urban EMS system from February 2014-June 2016. For acute agitation, paramedics administered midazolam 1 milligram (mg) intravenous (IV), 5 mg intramuscular (IM), or 5 mg intranasal (IN). Results were analyzed using descriptive statistics, Levene's test for assessing variance among study groups, and t-test to evaluate effectiveness based on route. RESULTS: In total, midazolam was administered 294 times to 257 patients. Median age was 30 (interquartile range 24-42) years, and 66.5% were male. Doses administered were 1 mg (7.1%) and 5 mg (92.9%). Routes were IM (52.0%), IN (40.8%), and IV (7.1%). A second dose was administered to 37 patients. In the majority of administrations, midazolam improved the patient's condition (73.5%) with infrequent adverse events (3.4%). There was no significant difference between the effectiveness of IM and IN midazolam (71.0% vs 75.4%; p = 0.24). CONCLUSION: A midazolam protocol for prehospital agitation was associated with reduced agitation and a low rate of adverse events.

Cincinnati Prehospital Stroke Scale Can Identify Large Vessel Occlusion Stroke.

OBJECTIVE: Accurate prehospital identification of patients with acute ischemic stroke (AIS) from large vessel occlusion (LVO) facilitates direct transport to hospitals that perform endovascular thrombectomy. We hypothesize that a cut-off score of the Cincinnati Prehospital Stroke Scale (CPSS), a simple assessment tool currently used by emergency medical services (EMS) providers, can be used to identify LVO. METHODS: Consecutively enrolled, confirmed AIS patients arriving via EMS between August 2012 and April 2014 at a high-volume stroke center in a large city with a single municipal EMS provider agency were identified in a prospective, single-center registry. Head and neck vessel imaging confirmed LVO. CPSS scores were abstracted from prehospital EMS records. Spearman's rank correlation, Wilcoxon rank-sum test, and Student's t-test were performed. Cohen's kappa was calculated between CPSS abstractors. The Youden index identified the optimal CPSS cut-off. Multivariate logistic regression controlling for age, sex, and race determined the odds ratio (OR) for LVO. RESULTS: Of 144 eligible patients, 138 (95.8%) had CPSS scores in the EMS record and were included for analysis. The median age was 69 (IQR 58-81) years. Vessel imaging was performed in 97.9% of patients at a median of 5.9 (IQR 3.6-10.2) hours from hospital arrival, and 43.7% had an LVO. Intravenous tissue plasminogen activator was administered to 29 patients, in whom 12 had no LVO on subsequent vessel imaging. The optimal CPSS cut-off predicting LVO was 3, with a Youden index of 0.29, sensitivity of 0.41, and specificity of 0.88. The adjusted OR for LVO with CPSS = 3 was 5.7 (95% CI 2.3-14.1). Among patients with CPSS = 3, 72.7% had an LVO, compared with 34.3% of patients with CPSS ≤ 2 (p < 0.0001). CONCLUSIONS: 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.

Identifying Key Words in 9-1-1 Calls for Stroke: A Mixed Methods Approach.

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-method, 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.