Prehospital Emergency Care最新文献

Objectives: Extracorporeal cardiopulmonary resuscitation (eCPR) is a promising treatment that could improve survival for refractory out-of-hospital (OHCA) patients. Healthcare systems may choose to start eCPR in the prehospital setting to optimize time to eCPR initiation and decrease low-flow time. We used geospatial modeling to evaluate different eCPR catchment strategies for a forthcoming prehospital eCPR program in Houston, Texas.

Methods: We studied OHCAs treated by the Houston Fire Department from 2013 to 2021. We included OHCA patients aged 18-65 years old with an initial shockable rhythm that did not have prehospital return of spontaneous circulation (ROSC). Based on the geolocation that each OHCA occurred, we used geospatial modeling to identify eCPR candidates using four mapping strategies based on distance/drive time from the eCPR center: 1) 15-minute drive time, 20-minute drive time, 10-mile drive distance, and 15-mile drive distance.

Results: Of 18,501 OHCAs during the study period, 881 met the eCPR inclusion criteria. Compared to non-eCPR candidates, eCPR candidates were younger (median age 52.3 years vs 62.7 years, p < 0.01) and had a higher proportion of males (76.6% v 59.8%, p < 0.01). Of eCPR candidate OHCAs, OHCAs occurred more frequently during the weekdays and the daytime, with 5:00 PM being the most common time. Using geospatial modeling and based on drive time, 219 OHCAs (24.9% of 881) were within a 15-minute drive, and 454 (51.5%) were within a 20-minute drive. Using drive distance, 383 eCPR candidates (43.5%) were within 10 miles, and 703 (79.8%) were within 15 miles.

Conclusions: Using geospatial modeling, we demonstrated a process to estimate potential eCPR patient volumes for a geographic region. Geospatial modeling represents a viable strategy for healthcare systems to delineate eCPR catchment areas.

Objectives: Many American police organizations respond to out-of-hospital cardiac arrest (OHCA). This study sought to: 1) explore variation in the role of police in OHCA across emergency medical systems and 2) identify factors influencing this variation.

Methods: We conducted a qualitative multisite case study analysis using data collected through semi-structured key informant interviews and multidisciplinary focus groups with telecommunicators, fire, police, emergency medical services, and hospital personnel across nine Michigan emergency systems of care. Sites were sampled based on return of spontaneous circulation rates, trauma region, geography, rurality, and population density. Data were analyzed to examine police role in OHCA and the organizational factors that contribute to these roles. Transcripts and coded data were explored using iterative thematic analysis and matrices.

Results: Interviews included approximately 160 public safety informants of varying administrative levels (i.e., field staff, mid-level managers, and leadership). Across systems, police played four on-scene roles in OHCA response: 1) early responder, 2) resuscitation team member, 3) security, and 4) information gathering. Less consistently, police performed supplementary roles as telecommunicators and cardiac arrest educators. We found that factors including administrative structure of the police agency, resources (e.g., human and material), organizational culture, medical training, deployment and response policies, nature of response environment, and relationships with other prehospital stakeholders contributed to the degree certain roles were present.

Conclusions: Police serve numerous on-scene and supplementary roles in OHCA response across jurisdictions. Their roles were influenced by multiple factors at each site. Future studies may help to better understand the value of and how to optimize police engagement in OHCA response.

Objectives: Early defibrillation with an automated external defibrillator (AED) can effectively improve the survival rate of patients with out-of-hospital cardiac arrest (OHCA). Placing AEDs in public locations can reduce the defibrillation response interval from collapse to defibrillation. Most public AEDs are currently placed in a stationary way (S-AED) with limited coverage area. Bus mounted AED (B-AED) can be delivered directly to the demand point. Although B-AEDs are only available during bus operating hours, they provide greater coverage area. When the number of available AEDs is insufficient, better coverage may be achieved by placing a portion of AEDs as B-AEDs. Our purpose is developing a model to determine the optimal locations of B-AEDs and S-AEDs with a predetermined number of available AEDs. The goal is to maximize the total coverage level of all demand points.

Methods: We proposed a joint location model to place B-AEDs and S-AEDs based on the p-median problem (JPMP). Using data from Chang'an District, Xi'an City, China, we determined the optimal AED deployment. The performance of JPMP was compared with several other models. The coverage results of JPMP are analyzed in details, including the quantity assignment, coverage level, and geographical location of B-AEDs and S-AEDs. The impact of the bus departure intervals on coverage was also discussed.

Results: The use of B-AEDs results in an average 98.43% increase in the number of covered demand points, and an average 74.05% increase in total coverage level. In optimal AED deployment, B-AEDs coverage follows an inverted U-shaped curve with increasing number of available AEDs. It begins to decrease when all demand points during the operating hours are covered. With a constant number of available AEDs, the total coverage level increases and then decreases as the bus departure interval increases. The larger the number of available AEDs, the smaller the optimal departure interval.

Conclusions: With a given number of available AEDs, combinational deployment of B-AEDs and S-AEDs significantly improves the coverage level. B-AEDs are recommended when AEDs are insufficient. If more AEDs are available, better coverage can be obtained with reasonable location of S-AEDs and B-AEDs.

Objectives: Data suggest patients suffering acute coronary occlusion myocardial infarction (OMI) benefit from prompt primary percutaneous intervention (PPCI). Many emergency medical services (EMS) activate catheterization labs to reduce time to PPCI, but suffer a high burden of inappropriate activations. Artificial intelligence (AI) algorithms show promise to improve electrocardiogram (ECG) interpretation. The primary objective was to evaluate the potential of AI to reduce false positive activations without missing OMI.

Methods: Electrocardiograms were categorized by (1) STEMI criteria, (2) ECG integrated device software and (3) a proprietary AI algorithm (Queen of Hearts (QOH), Powerful Medical). If multiple ECGs were obtained and any one tracing was positive for a given method, that diagnostic method was considered positive. The primary outcome was OMI defined as an angiographic culprit lesion with either TIMI 0-2 flow; or TIMI 3 flow with either peak high sensitivity troponin-I > 5000 ng/L or new wall motion abnormality. The primary analysis was per-patient proportion of false positives.

Results: A total of 140 patients were screened and 117 met criteria. Of these, 48 met the primary outcome criteria of OMI. There were 80 positives by STEMI criteria, 88 by device algorithm, and 77 by AI software. All approaches reduced false positives, 27% for STEMI, 22% for device software, and 34% for AI (p < 0.01 for all). The reduction in false positives did not significantly differ between STEMI criteria and AI software (p = 0.19) but STEMI criteria missed 6 (5%) OMIs, while AI missed none (p = 0.01).

Conclusions: In this single-center retrospective study, an AI-driven algorithm reduced false positive diagnoses of OMI compared to EMS clinician gestalt. Compared to AI (which missed no OMI), STEMI criteria also reduced false positives but missed 6 true OMI. External validation of these findings in prospective cohorts is indicated.

Objectives: Although the proximal tibia is a common site for intraosseous (IO) line placement in pediatric patients, previously published data indicate high malposition rates in infants and children at this location. Although distal femur IO lines generally demonstrate higher flow rates than those at the proximal tibia, to date, there have been no published studies assessing distal femur IO access in pediatric patients. Thus, we aimed to compare the success rates of pediatric IO line insertion attempts between the proximal tibia and the distal femur in a prehospital setting.

Methods: We conducted a retrospective chart review of prehospital pediatric patients who underwent at least one IO line placement attempt by Palm Beach County Fire Rescue from May 2015 to January 2024. We excluded records lacking specific documentation of IO attempt location. We compared the unadjusted success rates of distal femur to proximal tibia, and we also compared success rates after propensity score matching and multivariable logistic regression. Secondarily, we assessed the prehospital complication rate of the IO lines at each anatomical site.

Results: We identified 163 pediatric patients who had an IO attempt and were eligible for analysis. Median age was 1.9 years (IQR: 0.46 to 4.2 years). Among those 163 patients, there were 234 vascular access attempts, including 82 IO attempts at the distal femur and 72 at the proximal tibia. The unadjusted success rate of distal femur attempts was 89.0%, compared to 84.7% for proximal tibia attempts, a difference of 4.3% (95% CI -6.4 to 15.0%). After propensity score matching, we found an adjusted odds ratio of 2.0 (95% CI 0.66 to 6.8), favoring the distal femur for successful placement. Prehospital complication rates were similar for distal femur (5.5%) and proximal tibia (4.9%).

Conclusions: This retrospective analysis of pediatric patients in a prehospital setting suggests that IO line placement at the distal femur might offer a marginally higher success rate compared to the proximal tibia. Despite not reaching statistical significance, these findings support the consideration of distal femur as a viable option for IO placement in the pediatric population.

Objectives: Transcutaneous cardiac pacing (TCP) is a potentially lifesaving therapy for patients who present in the prehospital setting with bradycardia that is causing hemodynamic compromise. Our objective was to examine the outcomes of patients who received prehospital TCP and identify predictors of TCP failure.

Methods: We utilized the 2018-2021 ESO Data Collaborative public use research datasets for this study. All patients without a documented TCP attempt were excluded. Mortality was derived from hospital disposition data. TCP failure was defined as the initiation of CPR following the first TCP attempt among patients who did not receive CPR prior to the first TCP attempt. Multivariable logistic regression models using age and sex as covariables were used to explore the association between prehospital vital signs and TCP failure.

Results: During the study period, 13,270 patients received transcutaneous pacing and 2560 of these patients had outcome data available. Overall, the mortality rate following TCP was 63.4%. Among patients who did not receive CPR prior to the first TCP attempt (n = 7930), TCP failure (progression to cardiac arrest) occurred 20.4% of the time. Factors associated with TCP failure included increased body weight (>100 vs. 60-100 kg, aOR: 1.33 (1.15, 1.55)), a pre-pacing non-bradycardic heart rate (>50 vs. <40 bpm, aOR: 2.87 (2.39, 3.44)), and pre-TCP hypoxia (<80% vs. >90% SpO₂, aOR: 6.01 (4.96, 7.29)).

Conclusions: Patients who undergo prehospital TCP are at high risk of mortality. Progression to cardiac arrest is common and associated with factors including increased weight, a non-bradycardic initial heart rate and pre-TCP hypoxia.