Abstract
Introduction:
Out-of-hospital cardiac arrest (OHCA) is a time-sensitive medical emergency. There is international evidence to suggest that rural regions experience worse OHCA outcomes, such as reduced survival rates. The aim of this study was to quantitatively review and compare the OHCA response, treatment and pre-hospital outcomes in a single-centre ambulance service over a 1-year period in urban and rural areas.
Methods:
This study used retrospective OHCA audit data from the North East Ambulance Service NHS Foundation Trust, from April 2018 to April 2019, comparing OHCA response, treatment and return of spontaneous circulation (ROSC) data in relation to urban or rural classification status, using the UK government urban–rural classification tool.
Results:
A total of 1295 urban cases and 319 rural cases were compared. Bystander public-access defibrillator (PAD) use was higher in rural areas in comparison to urban areas (20/319 (6.3%) vs 47/1295 (3.6%); p = 0.03). The mean ambulance response time was slower in rural areas (10:43 minutes (n = 319) (SD ± 8.2) vs 07:35 minutes (n = 1295) (SD ± 7.1); p = < 0.01). Despite this, overall ROSC rates at hospital were similar between the groups, with no statistically significant difference (rural: 87/319 (27.3%) vs urban: 409/1295 (31.6%); p = 0.14).
A further sub-group analysis of initially shockable OHCA cases showed slower ambulance response times in rural areas (10:45 minutes (n = 68) (SD ± 12.3) vs 07:55 minutes (n = 245) (SD ± 5.5); p = < 0.01) and that rural cases experienced lower ROSC at hospital rates (31/68 (45.6%) vs 151/245 (61.6%); p = 0.02).
Conclusion:
This report showed differences in OHCA response and outcomes between rural and urban settings. In the shockable OHCA sub-group analysis, rural areas had slower ambulance response times and lower ROSC rates. The longer ambulance response times in the rural shockable OHCA group could be a factor in the reduced ROSC rates. Linking hospital survival data should be used in future research to explore this area further.
Keywords: EMS, out-of-hospital cardiac arrest, urban–rural
Introduction
Out-of-hospital cardiac arrest (OHCA) is a time-sensitive medical emergency requiring urgent treatment (Drennan et al., 2021). NHS ambulance services treat 30,000 OHCA patients annually in the United Kingdom. Return of spontaneous circulation (ROSC) rates at any time during the resuscitation were reported at 30% nationwide in 2021, but vary across UK regions (Perkins & Brace-McDonnell, 2015; Perkins et al., 2021).
The chain of survival for OHCA highlights the importance of key factors to improve OHCA survival, such as early defibrillation (Nolan et al., 2006). Public access defibrillators (PADs) are defibrillators that can be accessed and used by bystanders prior to an ambulance arriving (Smith et al., 2017). Bystander PAD use and rapid ambulance response times are associated with improved OHCA survival outcomes (Torney et al., 2020).
There is international evidence to suggest that rural areas experience worse OHCA outcomes, for example survival due to geospatial factors such as delayed ambulance response times (Connolly et al., 2022; Masterson et al., 2015; Mathiesen et al., 2018; Peters et al., 2023). However, there is also evidence to show that this is not the case in all countries (Ringgren et al., 2022). There is minimal evidence to explore rural OHCA outcomes against urban OHCA outcomes in the United Kingdom.
Methods
Aims
The primary aim of this study was to quantitatively review and compare the OHCA response, treatment and pre-hospital outcomes in a single-centre ambulance service over a 1-year period, for both urban and rural groups.
Objectives
To describe the baseline characteristics of OHCA in both urban and rural areas.
To compare the ambulance response, treatment and pre-hospital resuscitation success of both urban and rural OHCA groups.
Study design
This study was a retrospective cohort study using routinely collected OHCA audit data from April 2018 to April 2019. The OHCA audit data were requested and released by the North East Ambulance Service NHS Foundation Trust (NEAS) for research in May 2021, after ethical approval. The dataset was selected from before the COVID-19 pandemic and over a financial year, to ensure a large and reliable sample that reflected an accurate OHCA response prior to the COVID-19 pandemic.
Study population
The dataset came from NEAS, which provides emergency and urgent care over 3230 square miles and for over 2.7 million people (North East Ambulance Service NHS Foundation Trust, 2011). The data included both adult and paediatric OHCA patients who had resuscitation attempted by NEAS during the study timeframe.
The dataset contained detailed OHCA audit data (Table 1). It is important to note that the dataset did not include survival from hospital information, and ROSC data (at scene and at hospital) were used as a measure of pre-hospital resuscitation success. Lastly, the dataset only included OHCA cases where emergency medical services (EMS) resuscitation occurred.
Table 1.
Original dataset variables.
| Variable | Data type |
| Date | Long date (01/01/1900) |
| Time | HH:MM:SS format |
| Postcode | Standard UK postcode format |
| Aetiology | Cause of cardiac arrest (e.g. cardiac) |
| Age | Number format / Unknown response |
| Sex | Male or female |
| Ambulance response time | HH:MM:SS format |
| PAD used | YES / NO / Unknown response |
| Bystander CPR | YES / NO / Unknown response |
| Witnessed arrest | EMS / Bystander / No / Unknown response |
| DNACPR form | YES / NO / Unknown response |
| Defibrillator used by EMS | YES / NO / Unknown response |
| Initial rhythm | VF and/or VT/ Asystole / PEA / Unknown |
| EMS CPR | YES / NO / Unknown response |
| Advanced airway management | YES / NO / Unknown response |
| ALS drugs | YES / NO / Unknown response |
| ROLE | YES / NO / Unknown response |
| ROSC at any time | YES / NO / Unknown response |
| Leave scene to hospital time | HH:MM:SS format |
| Conveyed to hospital | YES / NO / Unknown response |
| ROSC on arrival at hospital | YES / NO / Unknown response |
| Receiving destination | Hospital name |
| Cardiac arrest witnessed by someone | YES / NO / Unknown response |
| Initial call category: Category 1: life-threatening illness and injury Category 2: emergency or a potentially serious condition Category 3: urgent Category 4: not urgent but needs assessment* |
C1 / C2 / C3 / C4 |
*Taken from Goddard (2022).
ALS: advanced life support; CPR: cardiopulmonary resuscitation; DNACPR: do not attempt cardiopulmonary resuscitation; EMS: emergency medical services; PAD: public access defibrillator; PEA: pulseless electrical activity; ROLE: recognition of life extinct; ROSC: return of spontaneous circulation; VF: ventricular fibrillation; VT: ventricular tachycardia.
Advanced airway management was defined by the ambulance service as the use of a supraglottic or endotracheal tube, and advanced life support (ALS) drugs were defined as any administration of adrenaline and/or amiodarone.
Inclusion and exclusion criteria
An OHCA case was included in the data transformation stage if it met the following eligibility criteria:
full location data available; and
initially coded as a cardiac arrest by the ambulance service (C1).
Exclusion criteria were:
OHCA cases that were initially coded as non-life-threatening (C2, C3 and C4); and
OHCA cases with missing location data.
Data transformation
The postcode of the OHCA incident was categorised into urban or rural classification using the UK government urban–rural classification tool (Figure 1). This tool allows locations to be coded into whether they are rural or urban, and further subtypes (e.g. rural village in a sparse setting). Rural areas were defined as per the UK classification tool, which uses multiple factors, for example settlements with a population under 10,000 residents (Department for Environment, Food & Rural Affairs, 2021). The principal researcher manually inputted each included case into the tool.
Figure 1. Office for National Statistics urban–rural classification tool.
Source: Office for National Statistics, licensed under the Open Government Licence v.3.0. Contains OS data © Crown copyright and database right 2017. https://geoportal.statistics.gov.uk/documents/rural-urban-classification-2011-map-of-the-oas-in-the-north-east-region-1/explore.
Data analysis
The data were divided into the two cohorts of urban and rural. Descriptive statistics were used to summarise both cohorts. Chi-square testing was used to test statistical significance for categorical data, such as ROSC rate differences. Mann-Whitney U testing was used to test whether ambulance response times were statistically different. A p-value of 0.05 was set to determine statistically significant differences with all tests. The study also explored the sub-group of shockable cardiac arrest cases. This was to gain further insight into this unique patient group, where time to defibrillation is an important factor in resuscitation success.
Results
A total of 1923 unique OHCA cases were available in the dataset. After applying the inclusion and exclusion criteria, a final 1614 OHCA incidents were included in the analysis; of these, there were 1295 urban OHCA cases and 319 rural OHCA cases (Figure 2). The results can be seen in Table 2.
Figure 2. Study flow diagram.
OHCA: out-of-hospital cardiac arrest.
Table 2.
Results.
| Variable | Urban (n = 1295) | Rural (n = 319) | P-value |
| Total OHCA cases | < 0.001* | ||
| Result | 1295 | 319 | |
| Percentage | (80.2%) | (19.8%) | |
| Urban and rural sub-classification breakdown | A1 (urban major conurbation): | D1 (rural town and fringe): | N/A |
| 688 | 199 | ||
| (53.1%) | (62.4%) | ||
| C1 (urban city and town): | D2 (rural town and fringe in a sparse setting): | ||
| 598 | 16 | ||
| (46.2%) | (5.0%) | ||
| C2 (urban city and town in a sparse setting): | E1 (rural village): | ||
| 9 | 4 | ||
| (0.7%) | (1.3%) | ||
| E2 (rural village in a sparse setting): | |||
| 13 | |||
| (4.1%) | |||
| F1 (rural hamlets and isolated dwellings): | |||
| 33 | |||
| (10.3%) | |||
| F2 (rural hamlets and isolated dwellings in a sparse setting): | |||
| 15 | |||
| (4.7%) | |||
| Age (years) | 0.093 | ||
| Mean | 64.3 | 66.4 | |
| SD | 19.1 | 18.7 | |
| Male sex | 0.627 | ||
| Amount | 801 | 202 | |
| Percentage | (61.9%) | (63.3%) | |
| Aetiology breakdown | Asphyxia | 0.028* | |
| 40 | 18 | ||
| (3.1%) | (5.6%) | ||
| Cardiac | 0.314 | ||
| 1124 | 270 | ||
| (86.8%) | (84.6%) | ||
| Drug overdose | 0.023* | ||
| 55 | 5 | ||
| (4.2%) | (1.6%) | ||
| Exsanguination | N/A | ||
| 2 | 0 | ||
| (0.2%) | (0%) | ||
| Other (non-cardiac) | 0.316 | ||
| 42 | 14 | ||
| (3.2%) | (4.4%) | ||
| Submersion | 0.403 | ||
| 4 | 2 | ||
| (0.3%) | (0.6%) | ||
| Trauma | 0.304 | ||
| 28 | 10 | ||
| (2.2%) | (3.1%) | ||
| Initial rhythm | Asystole | 0.485 | |
| 768 | 196 | ||
| (59.3%) | (61.4%) | ||
| PEA | 0.097 | ||
| 211 | 40 | ||
| (16.3%) | (12.5%) | ||
| VF/VT | 0.331 | ||
| 245 | 68 | ||
| (18.9%) | (21.3%) | ||
| Unknown / Unrecorded / Other | 0.578 | ||
| 71 | 15 | ||
| (5.5%) | (4.7%) | ||
| PAD use | 47 | 20 | 0.03* |
| (3.6%) | (6.3%) | ||
| Bystander CPR | 969 | 253 | 0.09 |
| (74.8%) | (79.3%) | ||
| Mean ambulance response time (MM:SS): | < 0.001* (mean) | ||
| Mean time | 07:35 | 10:43 | |
| SD | 7.10 | 8.19 | |
| Median | 6.52 | 9.17 | |
| IQR | 4.6–9.0 | 6.1–13.1 | |
| Advanced airway management | 1186 | 291 | 0.84 |
| (91.6%) | (91.2%) | ||
| ALS drug administration | 1069 | 272 | 0.25 |
| (82.5%) | (85.3%) | ||
| ROSC at anytime | 518 | 118 | 0.32 |
| (40.0%) | (37.0%) | ||
| ROSC at hospital | 409 | 87 | 0.14 |
| (31.6%) | (27.3%) |
*Statistically significant result p = < 0.05.
ALS: advanced life support; CPR: cardiopulmonary resuscitation; IQR: interquartile range; OHCA: out-of-hospital cardiac arrest; PAD: public access defibrillator; PEA: pulseless electrical activity; ROSC: return of spontaneous circulation; SD: standard deviation; VF: ventricular fibrillation; VT: ventricular tachycardia.
Patient demographics and out-of-hospital cardiac arrest characteristics
The demographics of both cohorts were similar, with no difference between age and sex. Furthermore, the aetiology and initial rhythm were also similar in both cohorts, with cardiac aetiology and asystole electrocardiogram rhythm as the most common findings in both cohorts. However, asphyxia aetiology was more common in the rural group, and drug overdose aetiology was more common in the urban group.
Bystander interventions
Bystander cardiopulmonary resuscitation (CPR) rates were similar; however, bystander PAD use was higher in rural areas in comparison to urban areas.
Ambulance response
The mean ambulance response time was significantly slower in the rural cohort in comparison to the urban cohort.
Ambulance treatment
Both advanced airway management and ALS drug administration rates were similar in both cohorts.
Pre-hospital resuscitation success
There was no statistically significant difference in ROSC at hospital or ROSC at any time rates in either cohort.
Sub-group analysis
In shockable OHCA cases, there were lower rates of ROSC at hospital in the rural cohort. There were also slower ambulance response times in the rural cohort (Table 3).
Table 3.
Sub-group analysis of initially shockable out-of-hospital cardiac arrest cases.
| Variable | Urban (n = 245) | Rural (n = 68) | P-value |
| Age (years) | 0.378 | ||
| Mean | 64.5 | 66.8 | |
| SD | 15.8 | 14.5 | |
| Male sex | 0.02* | ||
| Amount | 185 | 60 | |
| Percentage | (75.5%) | (88.2%) | |
| Aetiology breakdown | Asphyxia | N/A | |
| 1 | 0 | ||
| (3.1%) | (0%) | ||
| Cardiac | 0.98 | ||
| 238 | 66 | ||
| (86.8%) | (97.0%) | ||
| Drug overdose | N/A | ||
| 1 | 0 | ||
| (4.2%) | (0%) | ||
| Exsanguination | N/A | ||
| 0 | 0 | ||
| (0%) | (0%) | ||
| Other (non-cardiac) | N/A | ||
| 2 | 0 | ||
| (3.2%) | (0%) | ||
| Submersion | 0.33 | ||
| 1 | 1 | ||
| (0.3%) | (1.5%) | ||
| Trauma | 0.62 | ||
| 2 | 1 | ||
| (2.2%) | (1.5%) | ||
| Bystander PAD | 18 | 8 | 0.24 |
| (7.3%) | (11.8%) | ||
| Bystander CPR | 200 | 56 | 0.89 |
| (81.6%) | (82.4%) | ||
| Mean ambulance response time (MM:SS) | < 0.001* (mean) | ||
| Mean time | 07:55 | 10:45 | |
| SD | 5.5 | 12.3 | |
| Median | 6.7 | 9.5 | |
| IQR | 4.7–8.5 | 6.9–14.0 | |
| Advanced airway management | 224 | 61 | 0.66 |
| (91.4%) | (89.7%) | ||
| ALS drugs | 170 | 51 | 0.37 |
| (69.4%) | (75.0%) | ||
| ROSC at anytime | 171 | 39 | 0.05* |
| (69.8%) | (57.4%) | ||
| ROSC at hospital | 151 | 31 | 0.02* |
| (61.6%) | (45.6%) |
*Statistically significant result p = < 0.05.
ALS: advanced life support; CPR: cardiopulmonary resuscitation; IQR: interquartile range; PAD: public access defibrillator; ROSC: return of spontaneous circulation; SD: standard deviation.
Discussion
This study quantitatively reviewed OHCA audit data to describe and compare the OHCA response, treatment and pre-hospital success outcomes in the North East of England over a 1-year period, comparing urban and rural location groups. This study has shown differences in the OHCA response, treatment and outcomes between urban and rural areas. In the shockable OHCA sub-group analysis, rural areas had slower ambulance response times and lower ROSC rates.
Shockable out-of-hospital cardiac arrest sub-group
In the shockable cardiac arrest sub-group, there were significantly lower ROSC rates in the rural group compared to the urban group. The other variables showed that the demographics (apart from male sex), OHCA characteristics, bystander interventions and ambulance treatment were similar in this sub-group, with the only significant difference being seen in ambulance response time. It has been reported in other research that slower ambulance response times negatively affect OHCA outcomes (Bürger et al., 2018). This study provides observational data to support this.
Bystander interventions
A promising finding from the data was that overall bystander CPR rates were high, with around 3/4 OHCA cases receiving CPR prior to EMS arrival. This rate is higher than the 54.9%–60.8% rates reported by Connolly et al. (2022) in Canada or 55%–70% reported by Masterson et al. (2015) in Ireland.
Bystander PAD use remained low in both urban and rural areas (3.6%–6.3%), which is similar to other research findings in Europe and North America. PAD use has been reported between 3.1% and 4.7% in other studies (Connolly et al., 2022; Masterson et al., 2015). Furthermore, this study reports similar findings to Masterson et al. (2015), in that rural areas had higher rates of PAD use. However, Connolly et al. (2022) found that urban areas received higher rates of PAD use in comparison to rural areas. In their urban areas, PADs were located on average 6632 metres closer to OHCA cases than their rural areas (Connolly et al., 2022). Research has shown that there are multiple barriers affecting PAD use around the world, such as willingness to use a PAD, where to find a PAD and how to use a PAD (Smith et al., 2017).
Recommendations
This study recommends further service evaluations of each UK ambulance service to review their unique geographical situations. Linking hospital survival data to urban and rural OHCA care would provide better data to enable better analysis of the observations seen in this study. The study also recommends the use of proven schemes to improve OHCA outcomes, such as the use of first-responder schemes to augment OHCA response, especially in rural areas (Oving et al., 2021). An exciting intervention that has gained attention in the last five years is the use of drones to deliver defibrillators to OHCA emergencies, as seen in Sweden (Schierbeck et al., 2022). The utility of this intervention could be evaluated in the United Kingdom.
Lastly, future research could explore PAD use barriers in the study region by using mathematical modelling to calculate the average distance to the nearest PAD in both urban and rural areas, and to interview the public to understand their experience and behaviours when accessing a PAD.
Limitations
The authors acknowledge that there were limitations for this research. There were no data on survival from hospital available. This limits the strength of the conclusions that can be drawn from the ROSC data, as ROSC does not necessarily equate to long-term survival. From a pre-hospital point of view, ROSC at hospital data provide the best available data to indicate pre-hospital resuscitation success. Furthermore, some OHCA cases were not applicable due to the ambulance service system initially reporting the patient condition as a non-life-threatening call. These were removed as they reduced validity of the ambulance response times (n = 302). Information bias was considered due to reporting systems from the ambulance service being linked to inaccuracies, such as poor memory recall from paramedics during stressful situations (LeBlanc et al., 2012). To mitigate against this, a large, real-world and pragmatic sampling technique was used.
Conclusion
This short report has shown differences in the OHCA response, treatment and outcomes between urban and rural areas. In the shockable OHCA sub-group analysis, rural areas had slower ambulance response times and lower ROSC rates. The longer ambulance response times in the rural shockable OHCA group could be a factor in the reduced ROSC rates. This study recommends further research of a similar nature to explore urban and rural outcomes in other UK regions. Linking hospital survival data should also be used in future research to explore this area further.
Acknowledgements
Thank you to Graham McClelland for providing feedback and encouragement throughout the project.
Author contributions
OF conceptualised the project, designed the study, applied for ethical approval, collected the data, analysed the data, contributed to the statistical analysis, interpreted the results and wrote the manuscript. HS analysed the data, performed the majority of the statistical testing and assisted in the drafts of the projects. All authors approved the final draft. OF acts as the guarantor for this article.
Conflict of interest
None declared.
Ethics
Favourable ethical opinion was gained from the North East – Newcastle & North Tyneside 2 Research Ethics Committee (REC reference: 21/NE/0057). The research protocol and guidance from this approval were followed throughout.
Funding
None.
Contributor Information
Owen Finney, North East Ambulance Service NHS Foundation Trust ORCID iD: https://orcid.org/0000-0003-3744-2710.
Hayley Stagg, North East Ambulance Service NHS Foundation Trust.
References
- Bürger A., Wnent J., Bohn A., Jantzen T., Brenner S., Lefering R., Seewald S., Gräsner J.-T. & Fischer M. (2018). The effect of ambulance response time on survival following out-of-hospital cardiac arrest. Deutsches Ärzteblatt International, 115(33–34), 541–548. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Connolly M. S., Goldstein J. P., Currie M., Carter A. J. E., Doucette S. P., Giddens K., Allan K. S., Travers A. H., Ahrens B., Rainham D., & Sapp J. L. (2022). Urban–rural differences in cardiac arrest outcomes: A retrospective population-based cohort study. CJC Open, 4(4), 383–389. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Department for Environment, Food & Rural Affairs. (2021). Rural urban classification: Definition of rural areas using the rural urban classification. https://www.gov.uk/government/collections/rural-urban-classification.
- Drennan I. R., Geri G., Brooks S., Couper K., Hatanaka T., Kudenchuk P., Olasveengen T., Pellegrino J., Schexnayder S. M., Morley P., Basic Life Support (BLS), Pediatric Life Support (PLS) and Education, Implementation and Teams (EIT) Taskforces of the International Liaison Committee on Resuscitation (ILCOR), BLS Task Force, Pediatric Task Force, & EIT Task Force. (2021). Diagnosis of out-of-hospital cardiac arrest by emergency medical dispatch: A diagnostic systematic review. Resuscitation, 159, 85–96. [DOI] [PubMed] [Google Scholar]
- Goddard J. (2022). Ambulance response times in England: An emergency? House of Lords Library, UK Parliament. https://lordslibrary.parliament.uk/ambulance-response-times-in-england-an-emergency/. [Google Scholar]
- LeBlanc V. R., Regehr C., Tavares W., Scott A. K., Macdonald R., & King K. (2012). The impact of stress on paramedic performance during simulated critical events. Prehospital and Disaster Medicine, 27(4), 369–374. [DOI] [PubMed] [Google Scholar]
- Masterson S., Wright P., O’Donnell C., Vellinga A., Murphy A. W., Hennelly D., Sinnott B., Egan J., O’Reilly M., Keaney J., Bury G., & Deasy C. (2015). Urban and rural differences in out-of-hospital cardiac arrest in Ireland. Resuscitation, 91, 42–47. [DOI] [PubMed] [Google Scholar]
- Mathiesen W., Bjørshol C., Kvaløy J., & Søreide E. (2018). Effects of modifiable prehospital factors on survival after out-of-hospital cardiac arrest in rural versus urban areas. Critical Care, 22, (1), 99. https://doi.org/10.1186/s13054-018-2017-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Nolan J., Soar J., & Eikeland H. (2006). The chain of survival. Resuscitation, 71(3), 270–271. [DOI] [PubMed] [Google Scholar]
- North East Ambulance Service NHS Foundation Trust. (2011). Who we are and what we do. https://www.neas.nhs.uk/about-us/who-we-are-and-what-we-do.aspx.
- Oving I., de Graaf C., Masterson S., Koster R. W., Zwinderman A. H., Stieglis R., AliHodzic H., Baldi E., Betz S., Cimpoesu D., Folke F., Rupp D., Semeraro F., Truhlar A., Tan H. L., Blom M. T., for the ESCAPE-NET Investigators. (2021). European first responder systems and differences in return of spontaneous circulation and survival after out-of-hospital cardiac arrest: A study of registry cohorts. The Lancet Regional Health – Europe, 1, 100004. https://doi.org/10.1016/j.lanepe.2020.100004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Perkins G. D., & Brace-McDonnell S. J. (2015). The UK out-of-hospital cardiac arrest outcome (OHCAO) project. BMJ Open, 5(10), e008736. https://doi.org/10.1136/bmjopen-2015-008736. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Perkins G. D., Nolan J. P., Soar J., Hawkes C., Wyllie J., Skellett S., Lockey A., & Hampshire S. (2021). Epidemiology of cardiac arrest guidelines. Resuscitation Council UK. https://www.resus.org.uk/library/2021-resuscitation-guidelines/epidemiology-cardiac-arrest-guidelines. [Google Scholar]
- Peters G., Ordoobadi A., Panchal A., & Cash R. (2023). Differences in out-of-hospital cardiac arrest management and outcomes across urban, suburban, and rural settings. Prehospital Emergency Care, 27(2), 162–169. [DOI] [PubMed] [Google Scholar]
- Ringgren K. B., Kragholm K. H., Lindgren F. L., Jacobsen P. A., Jørgensen A. J., Christensen H. C., Mills E. H. A., Jakobsen L. K., Yonis H., Folke F., Lippert F., & Torp-Pedersen C. (2022). Out-of-hospital cardiac arrest: Does rurality decrease chances of survival? Resuscitation Plus, 9, 100208. https://doi.org/10.1016/j.resplu.2022.100208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schierbeck S., Svensson L., & Claesson A. (2022). Use of a drone-delivered automated external defibrillator in an out-of-hospital cardiac arrest. New England Journal of Medicine, 386(20), 1953–1954. [DOI] [PubMed] [Google Scholar]
- Smith C. M., Lim Choi Keung S. N., Khan M. O., Arvanitis T. N., Fothergill R., Hartley-Sharpe C., Wilson M. H., & Perkins G. D. (2017). Barriers and facilitators to public access defibrillation in out-of-hospital cardiac arrest: A systematic review. European Heart Journal, 3(4), 264–273. [DOI] [PubMed] [Google Scholar]
- Torney H., McAlister O., Harvey A., Kernaghan A., Funston R., McCartney B., Davis L., Bond R., McEneaney D., & Adgey J. (2020). Real-world insight into public access defibrillator use over five years. Open Heart, 7(1), e001251. https://doi.org/10.1136/openhrt-2020-001251. [DOI] [PMC free article] [PubMed] [Google Scholar]