ABSTRACT
INTRODUCTION: Effective response to a mass-casualty incident (MCI) entails the activation of hospital MCI plans. Unfortunately, there are no tools available in the literature to support hospital responders in predicting the proper level of MCI plan activation. This manuscript describes the scientific-based approach used to develop, test, and validate the PEMAAF score (Proximity, Event, Multitude, Overcrowding, Temporary Ward Reduction Capacity, Time Shift Slot [Prossimità, Evento, Moltitudine, Affollamento, Accorpamento, Fascia Oraria], a tool able to predict the required level of hospital MCI plan activation and to facilitate a coordinated activation of a multi-hospital network. METHODS: Three study phases were performed within the Metropolitan City of Milan, Italy: (1) retrospective analysis of past MCI after action reports (AARs); (2) PEMAAF score development; and (3) PEMAAF score validation. The validation phase entailed a multi-step process including two retrospective analyses of past MCIs using the score, a focus group discussion (FGD), and a prospective simulation-based study. Sensitivity and specificity of the score were analyzed using a regression model, Spearman's Rho test, and receiver operating characteristic/ROC analysis curves. RESULTS: Results of the retrospective analysis and FGD were used to refine the PEMAAF score, which included six items-Proximity, Event, Multitude, Emergency Department (ED) Overcrowding, Temporary Ward Reduction Capacity, and Time Shift Slot-allowing for the identification of three priority levels (score of 5-6: green alert; score of 7-9: yellow alert; and score of 10-12: red alert). When prospectively analyzed, the PEMAAF score determined most frequent hospital MCI plan activation (>10) during night and holiday shifts, with a score of 11 being associated with a higher sensitivity system and a score of 12 with higher specificity. CONCLUSIONS: The PEMAAF score allowed for a balanced and adequately distributed response in case of MCI, prompting hospital MCI plan activation according to real needs, taking into consideration the whole hospital response network.
Subject(s)
Disaster Planning , Mass Casualty Incidents , Humans , Retrospective Studies , Emergency Service, Hospital , Hospitals , TriageABSTRACT
BACKGROUND: Return of spontaneous circulation (ROSC) is achieved in 25% of out-of-hospital cardiac arrest (OHCA) patients. Mechanical chest compression (mechCPR) may maintain better perfusion during transport, allowing hospital treatments like extracorporeal circulation life support (ECLS). We aim to assess the effectiveness of a pre-hospital protocol introduction. METHODS: Observational, retrospective study assessing all OHCA patients aged 12-75, with no-flow time <20 min in a metropolitan area (Milan, Italy, 2013-2016). PRIMARY OUTCOMES: ROSC and Cerebral Performance Category score (CPC) ≤2 at hospital discharge. Logistic regressions with multiple comparison adjustments balanced with propensity scores calculated with inverse probability of treatment weighting were performed. RESULTS: 1366 OHCA were analysed; 305 received mechCPR, 1061 manual chest compressions (manCPR), and 108 ECLS. ROSC and CPC ≤2 were associated with low-flow minutes (odds ratio [95% confidence interval] 0.90 [0.88-0.91] and 0.90 [0.87-0.93]), shockable rhythm (2.52 [1.71-3.72] and 10.68 [5.63-20.28]), defibrillations number (1.15 [1.07-1.23] and 1.15 [1.04-1.26]), and mechCPR (1.86 [1.17-2.96] and 2.06 [1.11-3.81]). With resuscitation times >13 min, mechCPR achieved more frequently ROSC compared to manCPR. Among ECLS patients, 70% had time exceeding protocol: 8 (7.5%) had CPC ≤2 (half of them with low-flow times between 45 and 90 min), 2 (1.9%) survived with severe neurological disabilities, and 13 brain-dead (12.0%) became organ donors. CONCLUSIONS: MechCPR patients achieved ROSC more frequently than manual CPR patients; mechCPR was a crucial factor in an ECLS protocol for refractory OHCA. ECLS offered a chance of survival to patients who would otherwise die.