Characteristics, Prehospital Management, and Outcomes in Patients Assessed for Hypoglycemia: Repeat Access to Prehospital or Emergency Care.

BACKGROUND: In Ontario, Canada, there currently are no prehospital treat-and-release protocols and the safety of this practice remains unclear. We sought to describe the characteristics, management, and outcomes of patients with hypoglycemia treated by paramedics, and to determine the predictors of repeat access to prehospital or emergency department (ED) care within 72 hours of initial paramedic assessment. METHODS: We performed a health record review of paramedic call reports and ED records over a 12-month period. We queried prehospital databases to identify cases, which included all adult patients (≥ 18 years) with a prehospital glucose reading of <72mg/dl (4.0mmol/L) and excluded terminally ill and cardiac arrest patients. We developed and piloted a standardized data collection tool and obtained consensus on all data definitions before initiation of data extraction by trained investigators. Data analyses include descriptive statistics with standard deviations, Chi-square, t-tests, and logistic regression with adjusted odds ratios (AdjOR). RESULTS: There were 791 patients with the following characteristics: mean age 56.2, male 52.3%, known diabetic 61.6%, on insulin 46.1%, mean initial glucose 50.0 dl/mg (2.8 mmol/L), from home 56.3%. They were treated by an Advanced Care Paramedic 80.1%, received IV D50W 38.0%, IM glucagon 18.3%, PO complex carbs 26.6%, and accepted transport to hospital 69.4%. Of those transported, 134/556 (24.3%) were admitted and 9 (1.6%) died in the ED. Overall, 43 patients (5.4%) had repeat access to prehospital/ED care, among those, 8 (18.6%) were related to hypoglycemia. Patients on insulin were less likely to have repeat access to prehospital/ED care (AdjOR 0.4; 95%CI 0.2-0.9). This was not impacted by initial (or refusal of) transport (AdjOR 1.1; 95%CI 0.5-2.4). CONCLUSION: Although risk of repeat access to prehospital/ED care for patients with hypoglycemia exists, it was less common among patients taking insulin and was not predicted by an initial refusal of transport.

Hospital Variation in the Utilization and Implementation of Targeted Temperature Management in Out-of-Hospital Cardiac Arrest.

Background Targeted temperature management (TTM) for out-of-hospital cardiac arrest is associated with improved functional survival and is a class I recommendation in resuscitation guidelines. However, patterns of utilization of TTM and adherence to recommended TTM guidelines in contemporary practice are unknown. Methods and Results In a multicenter, prospective cohort of consecutive adults with non-traumatic out-of-hospital cardiac arrest in the Resuscitation Outcomes Consortium in 2012 to 2015, we identified all adults (≥18 years) who were potential candidates for TTM. Of 37 898 out-of-hospital cardiac arrest patients at 186 hospitals across 10 Resuscitation Outcomes Consortium sites, 8313 survived for ≥4 hours after hospital arrival, of which, 2878 (34.6%) received TTM. Mean age was 61.5 years and 36.3% were women. Median hospital rate of TTM use was 27% (interquartile range [IQR]: 14%, 45%), with an over 2-fold difference across sites after accounting for differences in presentation characteristics (median odds ratio, 2.10 [1.83-2.26]). Notably, TTM utilization decreased during the study period (57.5% [2012] to 26.5% [2015], P<0.001) including among shockable out-of-hospital cardiac arrest (73.4% to 46.3%, P<0.001). When administered, the median rate of deviation from one or more recommended practices was 60% (IQR: 40%, 78%). The median rate for delayed onset of TTM was 13% (IQR: 0%, 25%), varying by 70% for identical patients across 2 randomly chosen hospitals (median odds ratio 1.70 [1.39-1.97]). Similarly, the median rate for TTM <24 hours was 20% (IQR: 0%, 34%) and for achieved temperature <32°C was 18% (IQR: 0%, 39%), with marked variation across sites (median odds ratios of 1.44 [1.18-1.64] and 1.98 [1.62-2.31], respectively). Conclusions There has been a substantial decline in the utilization of TTM with significant variation in its real-world implementation. Further standardization of contemporary post-resuscitation practices, like TTM, is critical to ensure that their potential survival benefit is realized.

Safety and clinically important events in PCP-initiated STEMI bypass in Ottawa.

OBJECTIVE: The aim of this study was to determine what clinically important events occur in ST-elevation myocardial infarction (STEMI) patients transported for primary percutaneous coronary intervention (PCI) via a primary care paramedic (PCP) crew, and what proportion of such events could only be treated by advanced care paramedic (ACP) protocols. METHODS: We conducted a health record review of STEMI transports by PCP-only crews and those transferred from PCP to ACP crews (ACP-intercept) from 2011 to 2015. A piloted data collection form was used to extract clinically important events, interventions during transport, and mortality. RESULTS: We identified 214 STEMI bypass cases (118 PCP-only and 96 ACP-intercept). Characteristics were mean age 61.4 years; 44.4% inferior infarcts; mean response time 6 minutes, 19 seconds; total paramedic contact time 29 minutes, 40 seconds; and, in cases of ACP-intercept, 7 minutes, 46 seconds of PCP-only contact time. A clinically important event occurred in 127 (59.3%) of cases: SBP < 90 mm Hg (26.2%), HR < 60 (30.4%), HR > 100 (20.6%), arrhythmias 7.5%, altered mental status 6.5%, airway intervention 2.3%. Two patients (0.9%) arrested, both survived. Of the events identified, 42.5% could be addressed differently by ACP protocols. The majority related to fluid boluses for hypotension (34.6%). In the ACP-intercept group, ACPs acted on 51.6% of events. There were six (2.8%) in-hospital deaths. CONCLUSIONS: Although clinically important events are common in STEMI bypass patients, a smaller proportion of events would be addressed differently by ACP compared with PCP protocols. The majority of clinically important events were transient and of limited clinical significance. PCP-only crews can safely transport STEMI patients directly to primary PCI.

Time to Epinephrine Administration and Survival From Nonshockable Out-of-Hospital Cardiac Arrest Among Children and Adults.

BACKGROUND: Previous studies have demonstrated that earlier epinephrine administration is associated with improved survival from out-of-hospital cardiac arrest (OHCA) with shockable initial rhythms. However, the effect of epinephrine timing on patients with nonshockable initial rhythms is unclear. The objective of this study was to measure the association between time to epinephrine administration and survival in adults and children with emergency medical services (EMS)-treated OHCA with nonshockable initial rhythms. METHODS: We performed a secondary analysis of OHCAs prospectively identified by the Resuscitation Outcomes Consortium network from June 4, 2011, to June 30, 2015. We included patients of all ages with an EMS-treated OHCA and an initial nonshockable rhythm. We excluded those with return of spontaneous circulation in <10 minutes. We conducted a subgroup analysis involving patients <18 years of age. The primary exposure was time (minutes) from arrival of the first EMS agency to the first dose of epinephrine. Secondary exposure was time to epinephrine dichotomized as early (<10 minutes) or late (≥10 minutes). The primary outcome was survival to hospital discharge. We adjusted for Utstein covariates and Resuscitation Outcomes Consortium study site. RESULTS: From 55 568 EMS-treated OHCAs, 32 101 patients with initial nonshockable rhythms were included. There were 12 238 in the early group, 14 517 in the late group, and 5346 not treated with epinephrine. After adjusting for potential confounders, each minute from EMS arrival to epinephrine administration was associated with a 4% decrease in odds of survival for adults, odds ratio=0.96 (95% confidence interval, 0.95-0.98). A subgroup analysis (n=13 290) examining neurological outcomes showed a similar association (adjusted odds ratio, 0.94 per minute; 95% confidence interval, 0.89-0.98). When epinephrine was given late in comparison with early, odds of survival were 18% lower (odds ratio, 0.82; 95% confidence interval, 0.68-0.98). In a pediatric analysis (n=595), odds of survival were 9% lower (odds ratio, 0.91; 95% confidence interval, 0.81-1.01) for each minute delay in epinephrine. CONCLUSIONS: Among OHCAs with nonshockable initial rhythms, the majority of patients were administered epinephrine >10 minutes after EMS arrival. Each minute delay in epinephrine administration was associated with decreased survival and unfavorable neurological outcomes. EMS agencies should consider strategies to reduce epinephrine administration times in patients with initial nonshockable rhythms.

Habitat fragmentation and its lasting impact on Earth's ecosystems.

We conducted an analysis of global forest cover to reveal that 70% of remaining forest is within 1 km of the forest's edge, subject to the degrading effects of fragmentation. A synthesis of fragmentation experiments spanning multiple biomes and scales, five continents, and 35 years demonstrates that habitat fragmentation reduces biodiversity by 13 to 75% and impairs key ecosystem functions by decreasing biomass and altering nutrient cycles. Effects are greatest in the smallest and most isolated fragments, and they magnify with the passage of time. These findings indicate an urgent need for conservation and restoration measures to improve landscape connectivity, which will reduce extinction rates and help maintain ecosystem services.

Predicting species distributions for conservation decisions.

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

Predictive vegetation modeling for conservation: impact of error propagation from digital elevation data.

The effect of digital elevation model (DEM) error on environmental variables, and subsequently on predictive habitat models, has not been explored. Based on an error analysis of a DEM, multiple error realizations of the DEM were created and used to develop both direct and indirect environmental variables for input to predictive habitat models. The study explores the effects of DEM error and the resultant uncertainty of results on typical steps in the modeling procedure for prediction of vegetation species presence/absence. Results indicate that all of these steps and results, including the statistical significance of environmental variables, shapes of species response curves in generalized additive models (GAMs), stepwise model selection, coefficients and standard errors for generalized linear models (GLMs), prediction accuracy (Cohen's kappa and AUC), and spatial extent of predictions, were greatly affected by this type of error. Error in the DEM can affect the reliability of interpretations of model results and level of accuracy in predictions, as well as the spatial extent of the predictions. We suggest that the sensitivity of DEM-derived environmental variables to error in the DEM should be considered before including them in the modeling processes.