Electrical storm treatment by percutaneous stellate ganglion block: the STAR study.

BACKGROUND AND AIMS: An electrical storm (ES) is a clinical emergency with a paucity of established treatment options. Despite initial encouraging reports about the safety and effectiveness of percutaneous stellate ganglion block (PSGB), many questions remained unsettled and evidence from a prospective multicentre study was still lacking. For these purposes, the STAR study was designed. METHODS: This is a multicentre observational study enrolling patients suffering from an ES refractory to standard treatment from 1 July 2017 to 30 June 2023. The primary outcome was the reduction of treated arrhythmic events by at least 50% comparing the 12 h following PSGB with the 12 h before the procedure. STAR operators were specifically trained to both the anterior anatomical and the lateral ultrasound-guided approach. RESULTS: A total of 131 patients from 19 centres were enrolled and underwent 184 PSGBs. Patients were mainly male (83.2%) with a median age of 68 (63.8-69.2) years and a depressed left ventricular ejection fraction (25.0 ± 12.3%). The primary outcome was reached in 92% of patients, and the median reduction of arrhythmic episodes between 12 h before and after PSGB was 100% (interquartile range -100% to -92.3%). Arrhythmic episodes requiring treatment were significantly reduced comparing 12 h before the first PSGB with 12 h after the last procedure [six (3-15.8) vs. 0 (0-1), P < .0001] and comparing 1 h before with 1 h after each procedure [2 (0-6) vs. 0 (0-0), P < .001]. One major complication occurred (0.5%). CONCLUSIONS: The findings of this large, prospective, multicentre study provide evidence in favour of the effectiveness and safety of PSGB for the treatment of refractory ES.

Emergency Department and Out-of-Hospital Emergency System (112-AREU 118) integrated response to Coronavirus Disease 2019 in a Northern Italy centre.

Since December 2019, the world has been facing the life-threatening disease, named Coronavirus disease-19 (COVID-19), recognized as a pandemic by the World Health Organization. The response of the Emergency Medicine network, integrating "out-of-hospital" and "hospital" activation, is crucial whenever the health system has to face a medical emergency, being caused by natural or human-derived disasters as well as by a rapidly spreading epidemic outbreak. We here report the Pavia Emergency Medicine network response to the COVID-19 outbreak. The "out-of-hospital" response was analysed in terms of calls, rescues and missions, whereas the "hospital" response was detailed as number of admitted patients and subsequent hospitalisation or discharge. The data in the first 5 weeks of the Covid-19 outbreak (February 21-March 26, 2020) were compared with a reference time window referring to the previous 5 weeks (January 17-February 20, 2020) and with the corresponding historical average data from the previous 5 years (February 21-March 26). Since February 21, 2020, a sudden and sustained increase in the calls to the AREU 112 system was noted (+ 440%). After 5 weeks, the number of calls and missions was still higher as compared to both the reference pre-Covid-19 period (+ 48% and + 10%, respectively) and the historical control (+ 53% and + 22%, respectively). Owing to the overflow from the neighbouring hospitals, which rapidly became overwhelmed and had to temporarily close patient access, the population served by the Pavia system more than doubled (from 547.251 to 1.135.977 inhabitants, + 108%). To minimize the possibility of intra-hospital spreading of the infection, a separate "Emergency Department-Infective Disease" was created, which evaluated 1241 patients with suspected infection (38% of total ED admissions). Out of these 1241 patients, 58.0% (n = 720) were admitted in general wards (n = 629) or intensive care unit (n = 91). To allow this massive number of admissions, the hospital reshaped many general ward Units, which became Covid-19 Units (up to 270 beds) and increased the intensive care unit beds from 32 to 60. In the setting of a long-standing continuing emergency like the present Covid-19 outbreak, the integration, interaction and team work of the "out-of-hospital" and "in-hospital" systems have a pivotal role. The present study reports how the rapid and coordinated reorganization of both might help in facing such a disaster. AREU-112 and the Emergency Department should be ready to finely tune their usual cooperation to respond to a sudden and overwhelming increase in the healthcare needs brought about by a pandemia like the current one. This lesson should shape and reinforce the future.

An Utstein-based model score to predict survival to hospital admission: The UB-ROSC score.

AIMS: To develop and validate a multi-parametric practical score to predict the probability of survival to hospital admission of an out-of-hospital cardiac arrest (OHCA) victim by using Utstein Style-based variables. METHODS: All consecutive OHCA cases occurring from 2015 to 2017 in two regions, Pavia Province (Italy) and Canton Ticino (Switzerland) were included. We used random effect logistic regression to model survival to hospital admission after an OHCA. We computed the model area under the ROC curve (AUC ROC) for discrimination and we performed both internal and external validation by considering all OHCAs occurring in the aforementioned regions in 2018. The Utstein-Based ROSC (UB-ROSC) score was derived by using the coefficients estimated in the regression model. The score value was obtained adding the pertinent score components calculated for each variable. The score was then plotted against the probability of survival to hospital admission. RESULTS: 1962 OHCAs were included (62% male, mean age 73 ± 16 years). Age, aetiology, location, witnessed OHCA, bystander CPR, EMS arrival time and shockable rhythm were independently associated with survival to hospital admission. The model showed excellent discrimination (AUC 0.83, 95%CI 0.81-0.85) for predicting survival to hospital admission, also at internal cross-validation (AUC 0.82, 95%CI 0.80-0.84). The model maintained good discrimination after external validation by using the 2018 OHCA cohort (AUC 0.77, 95%CI 0.74-0.80). CONCLUSIONS: UB-ROSC score is a novel score that predicts the probability of survival to hospital admission of an OHCA victim. UB-ROSC shall help in setting realistic expectations about sustained ROSC achievement during resuscitation manoeuvres.