Prehospital emergency care : official journal of the National Association of EMS Physicians and the National Association of State EMS Directors
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Background: The objective of this study was to develop and validate machine learning models for data entry error detection in a national out-of-hospital cardiac arrest (OHCA) prehospital patient care report database. Methods: Adult OHCAs of presumed cardiac etiology were included. Data entry errors were defined as discrepancies between the coded data and the free-text note documenting the intervention or event; for example, information that was recorded as "absent" in the coded data but "present" in the free-text note. ⋯ Machine learning models detected errors most efficiently for outcome place and initial rhythm errors; 82.6% of place errors and 93.8% of initial rhythm errors could be detected while checking 11 and 35% of data, respectively, compared to the strategy of checking all data. Conclusion: Machine learning models can detect data entry errors in care reports of emergency medical services (EMS) clinicians with acceptable performance and likely can improve the efficiency of the process of data quality control. EMS organizations that provide more prehospital interventions for OHCA patients could have higher error rates and may benefit from the adoption of error-detection models.
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Prehospital traumatic cardiac arrest (TCA) is associated with a poor prognosis and requires urgent interventions to address its potentially reversible causes. Resuscitative efforts of TCA in the prehospital setting may entail significant resource allocation and impose added tolls on caregivers. The Israel Defense Forces Medical Corps (IDF-MC) instructs clinicians to perform a set protocol in the case of TCA, providing prompt oxygenation, chest decompression and volume resuscitation. This study investigates the settings, interventions, and outcomes of TCA resuscitation by IDF-MC teams over 25 years in both combat and civilian settings. ⋯ The prognosis of prehospital TCA is poor, and efforts to address its potentially reversible causes may often be futile. These notions may be further emphasized in military settings, where resources are limited, and extensive penetrating injuries are more common.
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Background: The opioid epidemic is an ongoing public health emergency, exacerbated in recent years by the introduction and rising prevalence of synthetic opioids. The National EMS Scope of Practice Model was changed in 2017 to recommend allowing basic life support (BLS) clinicians to administer intranasal (IN) naloxone. This study examines local IN naloxone administration rates for 4 years after the new recommendation, and Glasgow Coma Scale (GCS) scores and respiratory rates before and after naloxone administration. ⋯ Mean respiratory rates before (mean = 12.6 - 12.6, r = -0.04, 95% CI: -0.09 - 0.01; p = 0.1) and after (mean = 15.2 - 14.9, r = -0.03, 95% CI: -0.08 - 0.01; p = 0.172) naloxone administration have not changed. While initial GCS scores have become significantly lower, GCS scores after administration of naloxone have not changed (initial median GCS 10 - 6, p < 0.001; final median GCS 15 - 15, p = 0.23). Conclusions: Current dosing protocols of naloxone appear effective in the era of synthetic opioids in our region, although patients may be marginally more likely to require repeat naloxone doses.
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Rearrest after successful resuscitation from out-of-hospital cardiac arrest (OHCA) is common and is associated with worse patient outcomes. However, little is known about the effect of interventions designed to prevent rearrest. We assessed the association between a prehospital care protocol for immediate management after return of spontaneous circulation (ROSC) and rates of field rearrest and survival to discharge in patients with prehospital ROSC. ⋯ Introduction of a post-ROSC care protocol for patients with prehospital ROSC after OHCA was not associated with reduced odds of field rearrest. When elements of the care bundle were considered individually, push-dose epinephrine was associated with decreased odds of rearrest.
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Association between First-pass Intubation Success and Enhanced PPE Use during the COVID-19 Pandemic.
We evaluated first-pass endotracheal intubation (ETI) success within the critical care transport (CCT) environment using a natural experiment created by the COVID-19 pandemic. Our primary objective was to evaluate if the use of personal protective equipment (PPE) or the COVID-19 time period was associated with differences in first-pass success rates of ETI within a large CCT system with a high baseline ETI first-pass success rate. We hypothesized that pandemic-related challenges would be associated with decreased first-pass success rates. ⋯ In a large regional CCT system with a high ETI first-pass success rate, neither PPE use nor the COVID-19 time period were associated with differences in ETI first-pass success while controlling for relevant patient and operational factors. Other emergency medical services (EMS) systems may have encountered different effects of pandemic-related PPE use on intubation success rates. Further studies are needed to evaluate the influence of sustained use of enhanced PPE or changes in training or procedural experience on post-pandemic ETI first-pass success rates for non-CCT EMS clinicians.