Dataset Information

Spatio-temporal prediction model of out-of-hospital cardiac arrest: Designation of medical priorities and estimation of human resources requirement.

ABSTRACT: AIMS:To determine the out-of-hospital cardiac arrest (OHCA) rates and occurrences at municipality level through a novel statistical model accounting for temporal and spatial heterogeneity, space-time interactions and demographic features. We also aimed to predict OHCAs rates and number at municipality level for the upcoming years estimating the related resources requirement. METHODS:All the consecutive OHCAs of presumed cardiac origin occurred from 2005 until 2018 in Canton Ticino region were included. We implemented an Integrated Nested Laplace Approximation statistical method for estimation and prediction of municipality OHCA rates, number of events and related uncertainties, using age and sex municipality compositions. Comparisons between predicted and real OHCA maps validated our model, whilst comparisons between estimated OHCA rates in different yeas and municipalities identified significantly different OHCA rates over space and time. Longer-time predicted OHCA maps provided Bayesian predictions of OHCA coverages in varying stressful conditions. RESULTS:2344 OHCAs were analyzed. OHCA incidence either progressively reduced or continuously increased over time in 6.8% of municipalities despite an overall stable spatio-temporal distribution of OHCAs. The predicted number of OHCAs accounts for 89% (2017) and 90% (2018) of the yearly variability of observed OHCAs with prediction error ?1OHCA for each year in most municipalities. An increase in OHCAs number with a decline in the Automatic External Defibrillator availability per OHCA at region was estimated. CONCLUSIONS:Our method enables prediction of OHCA risk at municipality level with high accuracy, providing a novel approach to estimate resource allocation and anticipate gaps in demand in upcoming years.

SUBMITTER: Auricchio A

PROVIDER: S-EPMC7458314 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatio-temporal prediction model of out-of-hospital cardiac arrest: Designation of medical priorities and estimation of human resources requirement.

Auricchio Angelo A Peluso Stefano S Caputo Maria Luce ML Reinhold Jost J Benvenuti Claudio C Burkart Roman R Cianella Roberto R Klersy Catherine C Baldi Enrico E Mira Antonietta A

PloS one 20200831 8

<h4>Aims</h4>To determine the out-of-hospital cardiac arrest (OHCA) rates and occurrences at municipality level through a novel statistical model accounting for temporal and spatial heterogeneity, space-time interactions and demographic features. We also aimed to predict OHCAs rates and number at municipality level for the upcoming years estimating the related resources requirement.<h4>Methods</h4>All the consecutive OHCAs of presumed cardiac origin occurred from 2005 until 2018 in Canton Ticino ...[more]

PMID: 32866165

Similar Datasets

Project description:There is substantial observational evidence that long-term exposure to particulate air pollution is associated with premature death in urban populations. Estimates of the magnitude of these effects derive largely from cross-sectional comparisons of adjusted mortality rates among cities with varying pollution levels. Such estimates are potentially confounded by other differences among the populations correlated with air pollution, for example, socioeconomic factors. An alternative approach is to study covariation of particulate matter and mortality across time within a city, as has been done in investigations of short-term exposures. In either event, observational studies like these are subject to confounding by unmeasured variables. Therefore the ability to detect such confounding and to derive estimates less affected by confounding are a high priority. In this article, we describe and apply a method of decomposing the exposure variable into components with variation at distinct temporal, spatial, and time by space scales, here focusing on the components involving time. Starting from a proportional hazard model, we derive a Poisson regression model and estimate two regression coefficients: the "global" coefficient that measures the association between national trends in pollution and mortality; and the "local" coefficient, derived from space by time variation, that measures the association between location-specific trends in pollution and mortality adjusted by the national trends. Absent unmeasured confounders and given valid model assumptions, the scale-specific coefficients should be similar; substantial differences in these coefficients constitute a basis for questioning the model. We derive a backfitting algorithm to fit our model to very large spatio-temporal datasets. We apply our methods to the Medicare Cohort Air Pollution Study (MCAPS), which includes individual-level information on time of death and age on a population of 18.2 million for the period 2000-2006. Results based on the global coefficient indicate a large increase in the national life expectancy for reductions in the yearly national average of PM2.5. However, this coefficient based on national trends in PM2.5 and mortality is likely to be confounded by other variables trending on the national level. Confounding of the local coefficient by unmeasured factors is less likely, although it cannot be ruled out. Based on the local coefficient alone, we are not able to demonstrate any change in life expectancy for a reduction in PM2.5. We use additional survey data available for a subset of the data to investigate sensitivity of results to the inclusion of additional covariates, but both coefficients remain largely unchanged.

Project description:BackgroundAlthough studies have reported variation in out-of-hospital cardiac arrest (OHCA) survival by geographic location, little is known about variation in OHCA survival at the level of emergency medical service (EMS) agencies-which may have modifiable practices, unlike counties and regions. We quantified the variation in OHCA survival across EMS agencies and explored whether variation in 2 specific EMS resuscitation practices were associated with survival to hospital admission.MethodsWithin the Cardiac Arrest Registry to Enhance Survival, a prospective registry representing ≈51% of the US population, we identified 258 342 OHCAs from 764 EMS agencies with >10 OHCA cases annually during 2015 to 2019. Using hierarchical logistic regression, risk-standardized rates of survival to hospital admission were computed for each EMS agency. We quantified inter-agency variation in survival with median odds ratios and assessed the association of 2 resuscitation practices (EMS response time and the proportion of OHCAs with termination of resuscitation without meeting futility criteria) with EMS agency survival rates to hospital admission.ResultsAcross 764 EMS agencies comprising 258 342 OHCAs, the median risk-standardized rate of survival to hospital admission was 27.3% (interquartile range, 24.5%-30.1%; range: 16.0%-45.6%). The adjusted median odds ratio was 1.35 (95% CI, 1.32-1.39), denoting that the odds of survival of 2 patients with identical covariates varied by 35% at 2 randomly selected EMS agencies. EMS agencies in the lowest quartile of risk-standardized survival had longer EMS response times when compared with the highest quartile (12.0±3.4 versus 9.0±2.6 minutes; P<0.001), and a higher proportion of OHCAs with termination of resuscitation without meeting futility criteria (27.9±16.1% versus 18.9±11.4%; P<0.001).ConclusionsSurvival after OHCA varies widely across EMS agencies. EMS response times and termination of resuscitation practices were associated with agency-level rates of survival to hospital admission, suggesting potentially modifiable practices which can improve OHCA survival.

Project description:ImportanceDespite evidence that therapeutic hypothermia improves patient outcomes for out-of-hospital cardiac arrest, use of this therapy remains low.ObjectiveTo determine whether the use of therapeutic hypothermia and patient outcomes have changed after publication of the Targeted Temperature Management trial on December 5, 2013, which supported more lenient temperature management for out-of-hospital cardiac arrest.Design, setting, and participantsA retrospective cohort was conducted between January 1, 2013, and December 31, 2016, of 45 935 US patients in the Cardiac Arrest Registry to Enhance Survival who experienced out-of-hospital cardiac arrest and survived to hospital admission.ExposuresCalendar time by quarter year.Main outcomes and measuresUse of therapeutic hypothermia and patient survival to hospital discharge.ResultsAmong 45 935 patients (17 515 women and 28 420 men; mean [SD] age, 59.3 [18.3] years) who experienced out-of-hospital cardiac arrest and survived to admission at 649 US hospitals, overall use of therapeutic hypothermia during the study period was 46.4%. In unadjusted analyses, the use of therapeutic hypothermia dropped from 52.5% in the last quarter of 2013 to 46.0% in the first quarter of 2014 after the December 2013 publication of the Targeted Temperature Management trial. Use of therapeutic hypothermia remained at or below 46.5% through 2016. In segmented hierarchical logistic regression analysis, the risk-adjusted odds of use of therapeutic hypothermia was 18% lower in the first quarter of 2014 compared with the last quarter of 2013 (odds ratio, 0.82; 95% CI, 0.71-0.94; P = .006). Similar point-estimate changes over time were observed in analyses stratified by presenting rhythm of ventricular tachycardia or ventricular fibrillation (odds ratio, 0.89; 95% CI, 0.71-1.13, P = .35) and pulseless electrical activity or asystole (odds ratio, 0.75; 95% CI, 0.63-0.89; P = .001). Overall risk-adjusted patient survival was 36.9% in 2013, 37.5% in 2014, 34.8% in 2015, and 34.3% in 2016 (P < .001 for trend). In mediation analysis, temporal trends in use of hypothermia did not consistently explain trends in patient survival.Conclusions and relevanceIn a US registry of patients who experienced out-of-hospital cardiac arrest, the use of guideline-recommended therapeutic hypothermia decreased after publication of the Targeted Temperature Management trial, which supported more lenient temperature thresholds. Concurrent with this change, survival among patients admitted to the hospital decreased, but was not mediated by use of hypothermia.

Project description:Importance:Emergency medical services (EMS) deliver essential initial care for patients with out-of-hospital cardiac arrest (OHCA), but the extent to which patient outcomes vary between different EMS agencies is not fully understood. Objective:To quantify variation in patient outcomes after OHCA across EMS agencies. Design, Setting, and Participants:This observational cohort study was conducted in the Resuscitation Outcomes Consortium (ROC) Epistry, a prospective multicenter OHCA registry at 10 sites in North America. Any adult with OHCA treated by an EMS from April 2011 through June 2015 was included. Data analysis occurred from May 2017 to March 2018. Exposure:Treating EMS agency. Main Outcomes and Measures:The primary outcome was survival to hospital discharge. Secondary outcomes were return of spontaneous circulation at emergency department arrival and favorable functional outcome at hospital discharge (defined as a modified Rankin scale score ≤3). Multivariable hierarchical logistic regression models were used to adjust confounders and clustering of patients within EMS agencies, and calculated median odds ratios (MORs) were used to quantify the extent of residual variation in outcomes between EMS agencies. Results:We identified 43 656 patients with OHCA treated by 112 EMS agencies. At EMS agency level, we observed large variations in survival to hospital discharge (range, 0%-28.9%; unadjusted MOR, 1.43 [95% CI, 1.34-1.54]), return of spontaneous circulation on emergency department arrival (range, 9.0%-57.1%; unadjusted MOR, 1.53 [95% CI, 1.43-1.65]), and favorable functional outcome (range, 0%-20.4%; unadjusted MOR, 1.54 [95% CI, 1.40-1.73]). This variation persisted despite adjustment for patient-level and EMS agency-level factors known to be associated with outcomes (adjusted MOR for survival 1.56 [95% CI 1.44-1.73]; adjusted MOR for return of spontaneous circulation at emergency department arrival, 1.50 [95% CI, 1.41-1.62]; adjusted MOR for functionally favorable survival, 1.53 [95% CI, 1.37-1.78]). After restricting analysis to those who survived more than 60 minutes after hospital arrival and including hospital treatment characteristics, the variation persisted (adjusted MOR for survival, 1.49 [95% CI, 1.36-1.69]; adjusted MOR for functionally favorable survival, 1.34 [95% CI, 1.20-1.59]). Conclusions and Relevance:We found substantial variations in patient outcomes after OHCA between a large group of EMS agencies in North America that were not explained by documented patient-level and EMS agency-level variables.

Dataset Information

Spatio-temporal prediction model of out-of-hospital cardiac arrest: Designation of medical priorities and estimation of human resources requirement.

Publications

Spatio-temporal prediction model of out-of-hospital cardiac arrest: Designation of medical priorities and estimation of human resources requirement.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets