Delivery of Automated External Defibrillators via Drones in Simulated Cardiac Arrest: Users' Experiences and the Human-Drone Interaction.

BACKGROUND: Survival after out-of-hospital cardiac arrest (OHCA) in the United States is approximately 10%. Automatic external defibrillators (AEDs) are effective when applied early, yet public access AEDs are used in <2% of OHCAs. AEDs are often challenging for bystanders to locate and are rarely available in homes, where 70% of OHCAs occur. Drones have the potential to deliver AEDs to bystanders efficiently; however, little is known about the human-drone interface in AED delivery. OBJECTIVES: To describe user experiences with AED-equipped drones in a feasibility study of simulated OHCA in a community setting. METHODS: We simulated an OHCA in a series of trials with age-group/sex-matched participant pairs, with one participant randomized to search for a public access AED and the other to call a mock 9-1-1 telephone number that initiated the dispatch of an AED-equipped drone. We investigated user experience of 17 of the 35 drone recipient participants via semi-structured qualitative interviews and analyzed audio-recordings for key aspects of user experience. RESULTS: Drone recipient participants reported largely positive experiences, highlighting that this delivery method enabled them to stay with the victim and continue cardiopulmonary resuscitation. Concerns were few but included drone arrival timing and direction as well as bystander safety. Participants provided suggestions for improvements in the AED-equipped drone design and delivery procedures. CONCLUSION: Participants reported positive experiences interacting with an AED-equipped drone for a simulated OHCA in a community setting. Early findings suggest a role for drone-delivered AEDs to improve bystander AED use and improve outcomes for OHCA victims.

The Case for Drone-assisted Emergency Response to Cardiac Arrest: An Optimized Statewide Deployment Approach.

BACKGROUND Despite evidence linking rapid defibrillation to out-of-hospital cardiac arrest (OHCA) survival, bystander use of automatic external defibrillators (AEDs) remains low, due in part to AED placement and accessibility. AED-equipped drones may improve time-to-defibrillation, yet the benefits and costs are unknown.METHODS We designed drone deployment networks for the state of North Carolina using mathematical optimization models to select drone stations from existing infrastructure by specifying the number of stations and the targeted AED arrival time. Expected outcomes were evaluated over the drone's lifespan (4 years). We estimated the following parameters: proportion of OHCAs within a targeted AED delivery time, bystander utilization of AEDs, survival/neurological status, and incremental cost per quality-adjusted life year (QALY).RESULTS Statewide, 16,503 adults aged 18 or older were expected to experience OHCA with an attempted resuscitation over 4 years. Compared to no drone network, all proposed drone networks were expected to improve survival outcomes. For example, assuming 46% of OHCAs have bystanders willing to use an AED, a 500-drone network decreased the median time of defibrillator arrival from 7.7 to 2.7 minutes compared to no drone network. Expected survival rates doubled (24.5% versus 12.3%), resulting in an additional 30,267 QALYs ($858/incremental QALY). If just 4.5% of OHCAs had willing bystanders, 13.8% of victims would have survived. Sensitivity analysis demonstrated that an AED drone network remained cost-effective over a wide range of assumptions.CONCLUSIONS With proper integration into existing systems, large-scale networks for drone AED delivery have the potential to substantially improve OHCA survival rates while remaining cost-effective. Public health researchers should consider advocating for feasibility studies and policy development surrounding drones.

Sudden Cardiac Death Risk Distribution in the United States Population (from NHANES, 2005 to 2012).

Sudden cardiac death (SCD) accounts for more than half of all deaths from cardiovascular disease and is the first manifestation of heart disease in 50% of these subjects. We aimed to describe the distribution of predicted SCD risk in the general US population using a recently developed risk score. We previously developed a population-based, 10-year risk score for SCD using data from the multiracial Atherosclerosis Risk in Communities cohort, validated in the Framingham Study. We now estimate 10-year predicted SCD risk in National Health and Nutrition Examination Survey participants (pooled from cycles in 2005 to 2012) and evaluate the clinical profile of participants in lower risk (0 to 80th percentile of risk) or high risk (81st to 100th percentile of risk) strata. A total of 10,811 participants were included; the mean age of participants was 48 years, and 50% were women. The average predicted 10-year risk of SCD was 3.6% in high-risk participants (81st to 100th percentile), and 0.37% in low-risk participants (0 to 80th percentile). High-risk participants were older, had higher blood pressure, total cholesterol and body mass index, lower high-density lipoprotein, and were more likely to be men, black, smokers, and diabetic. In US adults free of cardiovascular disease, the majority of SCD risk appears confined to 10% to 20% of the population. This risk score, comprised of readily available clinical variables, identifies a subset of individuals in the population who are at an appreciably higher risk of SCD. This enriched cohort represents candidates for additional nuanced and selective screening techniques to further quantify SCD risk.

Lipid Profiles in Out-of-Hospital Sudden Unexpected Death.

OBJECTIVE: To determine the association between serum lipid measurements and the occurrence of out-of-hospital sudden unexpected death (OHSUD). PATIENTS AND METHODS: We compared 139 OHSUD cases (43 female patients [30.9%]) and 968 controls (539 female patients [55.7%]) from Wake County, North Carolina, from March 1, 2013, through February 28, 2015. Individuals were included if they were aged 18 to 64 years and had lipid measurements in the 5 years before their death (cases) or the most recent health care encounter (controls). Covariates were abstracted from medical records for all subjects, and those with triglyceride (TG) levels greater than 400 mg/dL (to convert to mmol/L, multiply by 0.0259) were excluded for low-density lipoprotein (LDL)-related analyses. RESULTS: By linear regression using age- and sex-adjusted models, cases of OHSUD had lower adjusted mean total cholesterol (170.3±52.2 mg/dL vs 188.9±39.7 mg/dL; P<.001), LDL cholesterol (90.9±39.6 mg/dL vs 109.6±35.2 mg/dL; P<.001), and non-high-density lipoprotein (HDL) (121.6±49.8 mg/dL vs 134.3±39.6 mg/dL; P<.001) levels and a higher adjusted TG/HDL-C ratio (4.7±7 vs 3±2.7; P<.001) than did controls. By logistic regression using age- and sex-adjusted models, the odds of OHSUD were elevated per unit increase in TG/HDL-C ratio (1.08; 95% CI, 1.03-1.12). CONCLUSION: Out-of-hospital sudden unexpected death cases had more favorable levels of total cholesterol, LDL cholesterol, and non-HDL, possibly indicating a lack of association between traditional lipid cardiovascular risk factors and sudden unexpected death. A comparatively elevated TG/HDL-C ratio in cases may corroborate an evolving hypothesis of how vasoactive and prothrombotic remnant-like lipoprotein particles contribute to sudden unexpected death.

Vital exhaustion and sudden cardiac death in the Atherosclerosis Risk in Communities Study.

OBJECTIVE: Vital exhaustion (VE), a construct defined as lack of energy, increased fatigue and irritability, and feelings of demoralisation, has been associated with cardiovascular events. We sought to examine the relation between VE and sudden cardiac death (SCD) in the Atherosclerosis Risk in Communities (ARIC) Study. METHODS: The ARIC Study is a predominately biracial cohort of men and women, aged 45-64 at baseline, initiated in 1987 through random sampling in four US communities. VE was measured using the Maastricht questionnaire between 1990 and 1992 among 13 923 individuals. Cox proportional hazards models were used to examine the hazard of out-of-hospital SCD across tertiles of VE scores. RESULTS: Through 2012, 457 SCD cases, defined as a sudden pulseless condition presumed due to a ventricular tachyarrhythmia in a previously stable individual, were identified in ARIC by physician record review. Adjusting for age, sex and race/centre, participants in the highest VE tertile had an increased risk of SCD (HR 1.48, 95% CI 1.17 to 1.87), but these findings did not remain significant after adjustment for established cardiovascular disease risk factors (HR 0.94, 95% CI 0.73 to 1.20). CONCLUSIONS: Among participants of the ARIC study, VE was not associated with an increased risk for SCD after adjustment for cardiovascular risk factors.

A Simple Community-Based Risk-Prediction Score for Sudden Cardiac Death.

BACKGROUND: Although sudden cardiac death is a leading cause of death in the United States, most victims of sudden cardiac death are not identified as at risk prior to death. We sought to derive and validate a population-based risk score that predicts sudden cardiac death. METHODS: The Atherosclerosis Risk in Communities (ARIC) Study recorded clinical measures from men and women aged 45-64 years at baseline; 11,335 white and 3780 black participants were included in this analysis. Participants were followed over 10 years and sudden cardiac death was physician adjudicated. Cox proportional hazards models were used to derive race-specific equations to estimate the 10-year sudden cardiac death risk. Covariates for the risk score were selected from available demographic and clinical variables. Utility was assessed by calculating discrimination (Harrell's C-index) and calibration (Hosmer-Lemeshow chi-squared test). The white-specific equation was validated among 5626 Framingham Heart Study participants. RESULTS: During 10 years' follow-up among ARIC participants (mean age 54.4 years, 52.4% women), 145 participants experienced sudden cardiac death; the majority occurred in the highest quintile of predicted risk. Model covariates included age, sex, total cholesterol, lipid-lowering and hypertension medication use, blood pressure, smoking status, diabetes, and body mass index. The score yielded very good internal discrimination (white-specific C-index 0.82; 95% confidence interval [CI], 0.78-0.85; black-specific C-index 0.75; 95% CI, 0.68-0.82) and very good external discrimination among Framingham participants (C-index 0.82; 95% CI, 0.79-0.86). Calibration plots indicated excellent calibration in ARIC (white-specific chi-squared 5.3, P = .82; black-specific chi-squared 4.1, P = .77), and a simple recalibration led to excellent fit within Framingham (chi-squared 2.1, P = 0.99). CONCLUSIONS: The proposed risk scores may be used to identify those at risk for sudden cardiac death within 10 years and particularly classify those at highest risk who may merit further screening.

Regional Evaluation of the Severity-Based Stroke Triage Algorithm for Emergency Medical Services Using Discrete Event Simulation.

BACKGROUND AND PURPOSE: The Severity-Based Stroke Triage Algorithm for Emergency Medical Services endorses routing patients with suspected large vessel occlusion acute ischemic strokes directly to endovascular stroke centers (ESCs). We sought to evaluate different specifications of this algorithm within a region. METHODS: We developed a discrete event simulation environment to model patients with suspected stroke transported according to algorithm specifications, which varied by stroke severity screen and permissible additional transport time for routing patients to ESCs. We simulated King County, Washington, and Mecklenburg County, North Carolina, distributing patients geographically into census tracts. Transport time to the nearest hospital and ESC was estimated using traffic-based travel times. We assessed undertriage, overtriage, transport time, and the number-needed-to-route, defined as the number of patients enduring additional transport to route one large vessel occlusion patient to an ESC. RESULTS: Undertriage was higher and overtriage was lower in King County compared with Mecklenburg County for each specification. Overtriage variation was primarily driven by screen (eg, 13%-55% in Mecklenburg County and 10%-40% in King County). Transportation time specifications beyond 20 minutes increased overtriage and decreased undertriage in King County but not Mecklenburg County. A low- versus high-specificity screen routed 3.7× more patients to ESCs. Emergency medical services spent nearly twice the time routing patients to ESCs in King County compared with Mecklenburg County. CONCLUSIONS: Our results demonstrate how discrete event simulation can facilitate informed decision making to optimize emergency medical services stroke severity-based triage algorithms. This is the first step toward developing a mature simulation to predict patient outcomes.

Lifetime Risk for Sudden Cardiac Death in the Community.

BACKGROUND: Sudden cardiac death (SCD) is a leading cause of death in the United States and often occurs without previous cardiac symptoms. Lifetime risk for SCD and the influence of established risk factors on lifetime risks for SCD have not been estimated previously. METHODS AND RESULTS: We followed Framingham Heart Study participants who were free of cardiovascular disease before their earliest examination. SCD was defined as death attributed to coronary heart disease within 1 hour of symptom onset without another probable cause of death, as adjudicated by a panel of 3 physicians. Lifetime risk for SCD was estimated to 85 years of age for men and women, with death attributed to other causes as the competing risk, and stratified by risk factor levels. We followed 2294 men and 2785 women for 160 396 person-years; 375 experienced SCD. At 45 years of age, lifetime risks were 10.9% (95% CI, 9.4-12.5) for men and 2.8% (95% CI, 2.1-3.5) for women. Greater aggregate burden of established risk factors was associated with a higher lifetime risk for SCD. Categorizing men and women solely by blood pressure levels resulted in a clear stratification of lifetime risk curves. CONCLUSIONS: We present the first lifetime risk estimates for SCD. Greater aggregate risk factor burden, or blood pressure level alone, is associated with higher lifetime risks for SCD. This high risk of premature death attributed to SCD (approximately 1 in 9 men and 1 in 30 women) should serve as a motivator of public health efforts in preventing and responding to SCD.