Dataset Information

Accuracy of prehospital transport time estimation.

ABSTRACT: Estimates of prehospital transport times are an important part of emergency care system research and planning; however, the accuracy of these estimates is unknown. The authors examined the accuracy of three estimation methods against observed transport times in a large cohort of prehospital patient transports.This was a validation study using prehospital records in King County, Washington, and southwestern Pennsylvania from 2002 to 2006 and 2005 to 2011, respectively. Transport time estimates were generated using three methods: linear arc distance, Google Maps, and ArcGIS Network Analyst. Estimation error, defined as the absolute difference between observed and estimated transport time, was assessed, as well as the proportion of estimated times that were within specified error thresholds. Based on the primary results, a regression estimate was used that incorporated population density, time of day, and season to assess improved accuracy. Finally, hospital catchment areas were compared using each method with a fixed drive time.The authors analyzed 29,935 prehospital transports to 44 hospitals. The mean (± standard deviation [±SD]) absolute error was 4.8 (±7.3) minutes using linear arc, 3.5 (±5.4) minutes using Google Maps, and 4.4 (±5.7) minutes using ArcGIS. All pairwise comparisons were statistically significant (p < 0.01). Estimation accuracy was lower for each method among transports more than 20 minutes (mean [±SD] absolute error was 12.7 [±11.7] minutes for linear arc, 9.8 [±10.5] minutes for Google Maps, and 11.6 [±10.9] minutes for ArcGIS). Estimates were within 5 minutes of observed transport time for 79% of linear arc estimates, 86.6% of Google Maps estimates, and 81.3% of ArcGIS estimates. The regression-based approach did not substantially improve estimation. There were large differences in hospital catchment areas estimated by each method.Route-based transport time estimates demonstrate moderate accuracy. These methods can be valuable for informing a host of decisions related to the system organization and patient access to emergency medical care; however, they should be employed with sensitivity to their limitations.

SUBMITTER: Wallace DJ

PROVIDER: S-EPMC4251659 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Accuracy of prehospital transport time estimation.

Wallace David J DJ Kahn Jeremy M JM Angus Derek C DC Martin-Gill Christian C Callaway Clifton W CW Rea Thomas D TD Chhatwal Jagpreet J Kurland Kristen K Seymour Christopher W CW

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine 20140101 1

<h4>Objectives</h4>Estimates of prehospital transport times are an important part of emergency care system research and planning; however, the accuracy of these estimates is unknown. The authors examined the accuracy of three estimation methods against observed transport times in a large cohort of prehospital patient transports.<h4>Methods</h4>This was a validation study using prehospital records in King County, Washington, and southwestern Pennsylvania from 2002 to 2006 and 2005 to 2011, respec ...[more]

PMID: 24552519

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Project description:Background and purposeAcute stroke treatment outcomes are predicated on reperfusion timeliness which can be improved by better prehospital stroke identification. We aimed to assess the effect of interactive emergency medical services (EMS) training on stroke recognition and prehospital care performance in a very high-risk cardiovascular risk population in Lithuania.MethodsWe conducted a single-center interrupted time-series study between March 1, 2019 and March 15, 2020. Two-hour small-group interactive stroke training sessions were organized for 166 paramedics serving our stroke network. We evaluated positive predictive value (PPV) and sensitivity for stroke including transient ischemic attack identification, onset-to-door time, and hospital-based outcomes during 6-months prior and 3.5 months after the training. The study outcomes were compared between EMS providers in urban and suburban areas.ResultsIn total, 677 suspected stroke cases and 239 stroke chameleons (median age 75 years, 54.8% women) were transported by EMS. After the training, we observed improved PPV for stroke recognition (79.8% vs. 71.8%, p = 0.017) and a trend of decreased in-hospital mortality (7.8% vs. 12.3, p = 0.070). Multivariable logistic regression models adjusted for age, gender, EMS location, and stroke subtype showed an association between EMS stroke training and improved odds of stroke identification (adjusted odds ratio [aOR] 1.6 [1.1-2.3]) and onset-to-door ≤ 90 min (aOR 1.6 [1.1-2.5]). The improvement of PPV was observed in urban EMS (84.9% vs. 71.2%, p = 0.003), but not in the suburban group (75.0% vs. 72.6%, p = 0.621).ConclusionsThe interactive EMS training was associated with a robust improvement of stroke recognition, onset to hospital transport time, and a trend of decreased in-hospital mortality. Adapted training strategies may be needed for EMS providers in suburban areas. Future studies should evaluate the long-term effects of the EMS training and identify optimal retraining intervals.

Project description:Survival after major trauma is considered to be time dependent. Efficient prehospital care with rapid transport is the norm in developed countries, which is not available in many lower middle and low-income countries. The aim of this study was to assess the effect of prehospital time and primary treatment given on survival of major trauma patients in a setting without prehospital care.This prospective observational study was carried out in a university hospital in Mumbai, from January to December 2014. The hospital has a trauma service but no organized prehospital care or defined interhospital transfer protocols. All patients with life- and/or limb-threatening injuries were included in the study. Injury time and arrival time were noted and the interval was defined as "prehospital time" for the directly arriving patients and as "time to tertiary care" for those transferred. Primary outcome measure was in-hospital death (or discharge).Of 1181 patients, 352 were admitted directly from the trauma scene and 829 were transferred from other hospitals. In-hospital mortality was associated with age, mechanism and mode of injury, shock, Glasgow Coma Score <9, Injury Severity Score ≥16, need for intubation, and ventilatory support on arrival; but neither with prehospital time nor with time to tertiary care. Transferred patients had a significantly higher mortality (odds ratio = 1.869, 95% confidence interval = 1.233-2.561, P = 0.005) despite fewer patients with severe injury. Two hundred and ninety-four (35%) of these needed airway intervention while 108 (13%) needed chest tube insertion on arrival to the trauma unit suggesting inadequate care at primary facility.Mortality is not associated with prehospital time but with transfers from primary care; probably due to deficient care. To improve survival after major trauma, enhancement of resources for resuscitation and capacity building of on-duty doctors in primary centers should be a priority in countries with limited resources.

Project description:INTRODUCTION:Increased out-of-hospital time is associated with worse outcomes in trauma. Sparse literature exists comparing prehospital scene and transport time management intervals between adult and pediatric trauma patients. National Emergency Medical Services guidelines recommend that trauma scene time be less than 10 minutes. The objective of this study was to examine prehospital time intervals in adult and pediatric trauma patients. METHODS:We performed a retrospective cohort study of blunt and penetrating trauma patients in a five-county region in North Carolina using prehospital records. We included patients who were transported emergency traffic directly from the scene by ground ambulance to a Level I or Level II trauma center between 2013-2018. We defined pediatric patients as those less than 16 years old. Urbanicity was controlled for using the Centers for Medicare and Medicaid's Ambulance Fee Schedule. We performed descriptive statistics and linear mixed-effects regression modeling. RESULTS:A total of 2179 records met the study criteria, of which 2077 were used in the analysis. Mean scene time was 14.2 minutes (95% confidence interval [CI], 13.9-14.5) and 35.3% (n = 733) of encounters had a scene time of 10 minutes or less. Mean transport time was 17.5 minutes (95% CI, 17.0-17.9). Linear mixed-effects regression revealed that scene times were shorter for pediatric patients (p<0.0001), males (p=0.0016), penetrating injury (p<0.0001), and patients with blunt trauma in rural settings (p=0.005), and that transport times were shorter for males (p = 0.02), non-White patients (p<0.0001), and patients in urban areas (p<0.0001). CONCLUSION:This study population largely missed the 10-minute scene time goal. Demographic and patient factors were associated with scene and transport times. Shorter scene times occurred with pediatric patients, males, and among those with penetrating trauma. Additionally, suffering blunt trauma while in a rural environment was associated with shorter scene time. Males, non-White patients, and patients in urban environments tended to have shorter transport times. Future studies with outcomes data are needed to identify factors that prolong out-of-hospital time and to assess the impact of out-of-hospital time on patient outcomes.

Project description:BackgroundFoamy viruses (FVs) are the most genetically stable viruses of the retrovirus family. This is in contrast to the in vitro error rate found for recombinant FV reverse transcriptase (RT). To investigate the accuracy of FV genome copying in vivo we analyzed the occurrence of mutations in HEK 293T cell culture after a single round of reverse transcription using a replication-deficient vector system. Furthermore, the frequency of FV recombination by template switching (TS) and the cross-packaging ability of different FV strains were analyzed.ResultsWe initially sequenced 90,000 nucleotides and detected 39 mutations, corresponding to an in vivo error rate of approximately 4 x 10-4 per site per replication cycle. Surprisingly, all mutations were transitions from G to A, suggesting that APOBEC3 activity is the driving force for the majority of mutations detected in our experimental system. In line with this, we detected a late but significant APOBEC3G and 3F mRNA by quantitative PCR in the cells. We then analyzed 170,000 additional nucleotides from experiments in which we co-transfected the APOBEC3-interfering foamy viral bet gene and observed a significant 50% drop in G to A mutations, indicating that APOBEC activity indeed contributes substantially to the foamy viral replication error rate in vivo. However, even in the presence of Bet, 35 out of 37 substitutions were G to A, suggesting that residual APOBEC activity accounted for most of the observed mutations. If we subtract these APOBEC-like mutations from the total number of mutations, we calculate a maximal intrinsic in vivo error rate of 1.1 x 10-5 per site per replication. In addition to the point mutations, we detected one 49 bp deletion within the analyzed 260000 nucleotides.Analysis of the recombination frequency of FV vector genomes revealed a 27% probability for a template switching (TS) event within a 1 kilobase (kb) region. This corresponds to a 98% probability that FVs undergo at least one additional TS event per replication cycle. We also show that a given FV particle is able to cross-transfer a heterologous FV genome, although at reduced efficiency than the homologous vector.ConclusionOur results indicate that the copying of the FV genome is more accurate than previously thought. On the other hand recombination among FV genomes appears to be a frequent event.

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Accuracy of prehospital transport time estimation.

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Accuracy of prehospital transport time estimation.

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