INTRODUCTION The Out-of-Hospital Cardiac Arrest (OHCA) Outcomes project is a national research registry. One of its aims is to explore sources of variation in OHCA survival outcomes. This study reports the development and validation of risk prediction models for return of spontaneous circulation (ROSC) at hospital handover and survival to hospital discharge. METHODS AND RESULTS The study included OHCA patients who were treated during 2014 and 2015 by emergency medical services (EMS) from 7 English National Health Service ambulance services. The 2014 data were used to identify important variables and to develop the risk prediction models, which were validated using the 2015 data. Model prediction was measured by area under the curve (AUC), Hosmer-Lemeshow test, Cox calibration regression and Brier score. All analyses were conducted using mixed effects logistic regression models. Important factors included age, gender, witness/bystander cardiopulmonary resuscitation (CPR) combined, aetiology and initial rhythm. Interaction effects between witness/bystander CPR with gender, aetiology and initial rhythm and between aetiology and initial rhythm were significant in both models. The survival model achieved better discrimination and overall accuracy compared with the ROSC model (AUC=0.86 vs 0.67, Brier score=0.072 vs 0.194, respectively). Calibration tests showed over- and under-estimation for the ROSC and survival models, respectively. A sensitivity analysis individually assessing Index of Multiple Deprivation scores and location in the final models substantially improved overall accuracy with inconsistent impact on discrimination. CONCLUSION Our risk prediction models identified and quantified important pre-EMS intervention factors determining survival outcomes in England. The survival model had excellent discrimination.

Background Health care planners need to predict demand for hospital beds to avoid deterioration in health care. Seasonal demand can be affected by respiratory illnesses which in England are monitored using syndromic surveillance systems. Therefore, we investigated the relationship between syndromic data and daily emergency hospital admissions. Methods We compared the timing of peaks in syndromic respiratory indicators and emergency hospital admissions, between 2013 and 2018. Furthermore, we created forecasts for daily admissions and investigated their accuracy when real-time syndromic data were included. Results We found that syndromic indicators were sensitive to changes in the timing of peaks in seasonal disease, especially influenza. However, each year, peak demand for hospital beds occurred on either 29th or 30th December, irrespective of the timing of syndromic peaks. Most forecast models using syndromic indicators explained over 70% of the seasonal variation in admissions (adjusted R square value). Forecast errors were reduced when syndromic data were included. For example, peak admissions for December 2014 and 2017 were underestimated when syndromic data were not used in models. Conclusion Due to the lack of variability in the timing of the highest seasonal peak in hospital admissions, syndromic surveillance data do not provide additional early warning of timing. However, during atypical seasons syndromic data did improve the accuracy of forecast intensity.

Dear Editor, Those classed as homeless have a greatly reduced life expectancy compared to the population average:at 44 years for men and 42 years for women. New legislation has come into force that gives a powerful tool for emergency front-line staff to break down the cycle of disadvantage and help reduce attendances from this group. Clinicians working in urgent and emergency care settings may well be the first and only health professionals that someone who is homeless see. It must therefore be recognised that this healthcare encounter could be the key opportunity to improve the life course for this person. It is important to note that ‘homelessness’ does …

Journal of Paramedic PracticeVol. 11, No. 2 CommentHomelessness: implications for paramedic practiceSammer Tang, Gemma Dovey, James MapstoneSammer TangSearch for more papers by this author, Gemma DoveySearch for more papers by this author, James MapstoneSearch for more papers by this authorSammer Tang; Gemma Dovey; James MapstonePublished Online:4 Feb 2019https://doi.org/10.12968/jpar.2019.11.2.52AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References Deloitte. Healthcare for the Homeless. Homelessness is Bad for your Health. 2012. https://tinyurl.com/y9c6xu9v (accessed 26 January 2019) Google ScholarGallagher J. Homelessness Reduction Act 2017. Housing Matters. 2017; 119:4–5 Google ScholarHomeless Link. Health Needs Audit – explore the data. 2016. https://tinyurl.com/y8fz5mhc (accessed 26 January 2019) Google ScholarHomelessness Reduction Act 2017. https://tinyurl.com/y8r3y5vm (accessed 26 January 2019) Google ScholarMinistry of Housing, Community and Local Government. A guide to the duty to refer. 2018. https://tinyurl.com/ydxysjgk (accessed 26 January 2019) Google ScholarMinistry of Housing, Community and Local Government. Homelessness statistics. 2018. https://tinyurl.com/q9utptw (accessed 26 January 2019) Google ScholarPublic Health England. Evidence review: Adults with complex needs (with a particular focus on street begging and street sleeping). 2018. https://tinyurl.com/y9b8xsav (accessed 26 January 2019) Google ScholarQuilgars D, Pleace N. Delivering Health Care to Homeless People: An Effectiveness Review. 2003. https://tinyurl.com/y7tgdbmv (accessed 26 January 2019) Google ScholarThomas B. Homelessness kills: An analysis of the mortality of homeless people in early twenty-first century England. London: Crisis; 2012 Google Scholar FiguresReferencesRelatedDetailsCited byHomelessness in the aftermath of COVID-19Philippa Jane Nilsen9 November 2021 | Journal of Paramedic Practice, Vol. 13, No. 11 2 February 2019Volume 11Issue 2ISSN (print): 1759-1376ISSN (online): 2041-9457 Metrics History Published online 4 February 2019 Published in print 2 February 2019 Information© MA Healthcare LimitedPDF download

Introduction This study reports the epidemiology and outcomes from out-of-hospital cardiac arrest (OHCA) in England during 2014. Methods Prospective observational study from the national OHCA registry. The incidence, demographic and outcomes of patients who were treated for an OHCA between 1st January 2014 and 31st December 2014 in 10 English ambulance service (EMS) regions, serving a population of almost 54 million, are reported in accordance with Utstein recommendations. Results 28,729 OHCA cases of EMS treated cardiac arrests were reported (53 per 100,000 of resident population). The mean age was 68.6 (SD=19.6) years and 41.3% were female. Most (83%) occurred in a place of residence, 52.7% were witnessed by either the EMS or a bystander. In non-EMS witnessed cases, 55.2% received bystander CPR whilst public access defibrillation was used rarely (2.3%). Cardiac aetiology was the leading cause of cardiac arrest (60.9%). The initial rhythm was asystole in 42.4% of all cases and was shockable (VF or pVT) in 20.6%. Return of spontaneous circulation at hospital transfer was evident in 25.8% (n=6302) and survival to hospital discharge was 7.9%. Conclusion Cardiac arrest is an important cause of death in England. With less than one in ten patients surviving, there is scope to improve outcomes. Survival rates were highest amongst those who received bystander CPR and public access defibrillation.

AimsThe aim of the project was to identify the neighbourhood characteristics of areas in England where out-of-hospital cardiac arrest (OHCA) incidence was high and bystander cardiopulmonary resuscitation (BCPR) was low using registry data.Methods and resultsAnalysis was based on 67 219 cardiac arrest events between 1 April 2013 and 31 December 2015. Arrest locations were geocoded to give latitude/longitude. Postcode district was chosen as the proxy for neighbourhood. High-risk neighbourhoods, where OHCA incidence based on residential population was >127.6/100 000, or based on workday population was >130/100 000, and BCPR in bystander witnessed arrest was <60% were observed to have: a greater mean residential population density, a lower workday population density, a lower rural-urban index, a higher proportion of people in routine occupations and lower proportion in managerial occupations, a greater proportion of population from ethnic minorities, a greater proportion of people not born in UK, and greater level of deprivation. High-risk areas were observed in the North-East, Yorkshire, South-East, and Birmingham.ConclusionThe study identified neighbourhood characteristics of high-risk areas that experience a high incidence of OHCA and low bystander resuscitation rate that could be targeted for programmes of training in cardiopulmonary resuscitation and automated external defibrillator use.

The first documented British outbreak of Shiga toxin-producing Escherichia coli (STEC) O55:H7 began in the county of Dorset, England, in July 2014. Since then, there have been a total of 31 cases of which 13 presented with haemolytic uraemic syndrome (HUS). The outbreak strain had Shiga toxin (Stx) subtype 2a associated with an elevated risk of HUS. This strain had not previously been isolated from humans or animals in England. The only epidemiological link was living in or having close links to two areas in Dorset. Extensive investigations included testing of animals and household pets. Control measures included extended screening, iterative interviewing and exclusion of cases and high risk contacts. Whole genome sequencing (WGS) confirmed that all the cases were infected with similar strains. A specific source could not be identified. The combination of epidemiological investigation and WGS indicated, however, that this outbreak was possibly caused by recurrent introductions from a local endemic zoonotic source, that a highly similar endemic reservoir appears to exist in the Republic of Ireland but has not been identified elsewhere, and that a subset of cases was associated with human-to-human transmission in a nursery.