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Background: Italy, France and New York City have reported an increase in out-of-hospital cardiac arrest (OHCA) incidence during the COVID-19 pandemic. The purpose of our study was to assess the effect of COVID-19 on OHCA cases in Chicago. Method: Cardiac Arrest Registry to Enhance Survival (CARES) database was used. Bivariate analysis was conducted to assess changes in demographic and other characteristics. We excluded the cases that occurred in a healthcare facility or a nursing home. We compared the cases reported in 2020 to 2019 (and prior years). ArcGIS was used to geocode incident addresses and to show the temporal distribution by community areas. Bivariate analysis was done using chi-square tests. Results: A total of 3221 OHCA cases were reported in Chicago in 2020, which is 31.5% higher than those reported in 2019 (n=2450 cases). This increase was higher than what has been noticed historically (for instance, the increase from 2018 to 2019 was only 17%). There was an increase in Hispanic OHCA cases (17.3% in 2020 vs. 13.5% in 2019, p Conclusion: A better understanding of the causes of the excess cardiac arrest numbers will be important to help plan and better prepare for future public health interventions. The effect of COVID-19 on OHCA survival needs to be examined further in future studies.

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 PARTICIPANTS: This retrospective, multicenter preimplementation-postimplementation 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 (EMS) transport from December 1, 2017, to May 31, 2019 (9 months before and after implementation in September 2018). Data were analyzed from December 1, 2017, to May 31, 2019. INTERVENTIONS: Prehospital EMS transport policy to triage patients with suspected LVO stroke, using a 3-item stroke scale, to comprehensive stroke centers. MAIN OUTCOMES AND MEASURES: Rates of EVT before and after implementation among EMS-transported patients within 6 hours of AIS onset. RESULTS: Among 7709 patients with stroke, 663 (mean [SD] age, 68.5 [14.9] years; 342 women [51.6%] and 321 men [48.4%]; and 348 Black individuals [52.5%]) with AIS arrived within 6 hours of stroke onset by EMS transport: 310 of 2603 (11.9%) in the preimplementation period and 353 of 2637 (13.4%) in the postimplementation period. The EVT rate increased overall among all patients with AIS (preimplementation, 4.9% [95% CI, 4.1%-5.8%]; postimplementation, 7.4% [95% CI, 7.5%-8.5%]; P

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.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.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.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.

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-type 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

Introduction: Early revascularization improves outcomes in patients with acute stroke, and prehospital identification of patients with large vessel occlusions can result in preferential transport to centers with endovascular capability. Several stroke severity scales have been developed to assist with prehospital triage, but emergency medical services (EMS) provider training on new assessment scales presents challenges. Hypothesis: A dichotomized Cincinnati Prehospital Stroke Scale (CPSS) with a cut-off of 2 correlates with acute stroke revascularization in a large US city. Methods: Patients with confirmed stroke arriving via EMS between August 2012 and April 2014 at a high-volume stroke center in a large urban city with a single municipal EMS provider were identified. Demographics, prehospital CPSS, initial NIH stroke scale score (NIHSS) at hospital arrival, and type of revascularization (intravenous tissue plasminogen activator [IVtPA] or endovascular) were captured. Spearman’s rank correlation and Mann-Whitney U Test were performed after applying skewness/kurtosis tests. The Youden index was used to identify the optimal cut-off for the dichotomized CPSS. Multivariate logistic regression controlling for age, sex, and race determined the odds ratio (OR) for revascularization. Results: A total of 144 patients were included; 51% were male, 57% were white, and 33% were black. The mean age was 68.8 years (SD 16.1). A total of 31 patients (21.5%) underwent revascularization, most often with IVtPA alone (n=30). CPSS was ≥2 in 42% of patients, and the median NIHSS in patients with CPSS Conclusions: Prehospital dichotomized CPSS with a cut-off of 2 is well correlated with acute stroke revascularization in a large US city. Further studies should investigate how the dichotomized CPSS performs in the prehospital identification of stroke patients with large vessel occlusions.

Background and objective: Immediate access to emergency medical services (EMS) is critical in stroke. Correct dispatcher diagnosis may be influenced by caller recognition of stroke symptoms. In a study of 9-1-1 calls, we hypothesized that the word "stroke" is infrequently used by EMS callers when reporting strokes. Methods: From 3 hospitals, we identified 62 patients with confirmed stroke who arrived by EMS during the period of January - June 2013 and analyzed the 9-1-1 audio recordings. We used an evaluation form to identify words used to describe stroke symptoms by the callers. We compared the association between dispatcher diagnosis and caller use of “stroke” and call duration between those that used “stroke” versus to those that did not. Results: Of the 62 patients in the study, "stroke" was mentioned by 20 (32.3%) callers. The average duration of 9-1-1 calls was 55 seconds (IQR 40-78 seconds) and did not differ in calls that used “stroke” vs. those that did not (56 vs. 54 seconds; p=0.47). The dispatcher suspected stroke in 20 cases (32.3%) of which 18 were instances where the caller used the word “stroke” (p Conclusion: The word "stroke" was used by only one-third of the EMS callers. The most common reported symptom that correlated with use of the word “stroke” was weakness. Use of the word “stroke” by callers was strongly associated with dispatcher diagnosis of stroke. Effective educational intervention with emphasis on communicating stroke symptoms and indicating stroke may help facilitate immediate and correct action by the EMS.

Objectives Telecommunicators 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. Methods We 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. Results Among 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. Conclusion A single-question arrest identification algorithm may not achieve a favorable balance of risk and benefit.