INTRODUCTIONInappropriate fluid management during patient transport may lead to casualty morbidity. Percent systolic pressure variation (%SPV) is one of several technologies that perform a dynamic assessment of fluid responsiveness (FT-DYN). Trained anesthesia providers can visually estimate and use %SPV to limit the incidence of erroneous volume management decisions to 1-4%. However, the accuracy of visually estimated %SPV by other specialties is unknown. The aim of this article is to determine the accuracy of estimated %SPV and the incidence of erroneous volume management decisions for Critical Care Air Transport (CCAT) team members before and after training to visually estimate and utilize %SPV.MATERIAL AND METHODSIn one sitting, CCAT team providers received didactics defining %SPV and indicators of fluid responsiveness and treatment with %SPV ≤7 and ≥14.5 defining a fluid nonresponsive and responsive patient, respectively; they were then shown ten 45-second training arterial waveforms on a simulated Propaq M portable monitor's screen. Study subjects were asked to visually estimate %SPV for each arterial waveform and queried whether they would treat with a fluid bolus. After each training simulation, they were told the true %SPV. Seven days post-training, the subjects were shown a different set of ten 45-second testing simulations and asked to estimate %SPV and choose to treat, or not. Nonparametric limits of agreement for differences between true and estimated %SPV were analyzed using Bland-Altman graphs. In addition, three errors were defined: (1) %SPV visual estimate errors that would label a volume responsive patient as nonresponsive, or vice versa; (2) incorrect treatment decisions based on estimated %SPV (algorithm application errors); and (3) incorrect treatment decisions based on true %SPV (clinically significant treatment errors). For the training and testing simulations, these error rates were compared between, and within, provider groups.RESULTSSixty-one physicians (MDs), 64 registered nurses (RNs), and 53 respiratory technicians (RTs) participated in the study. For testing simulations, the incidence and 95% CI for %SPV estimate errors with sufficient magnitude to result in a treatment error were 1.4% (0.5%, 3.2%), 1.6% (0.6%, 3.4%), and 4.1% (2.2%, 6.9%) for MDs, RNs, and RTs, respectively. However, clinically significant treatment errors were statistically more common for all provider types, occurring at a rate of 7%, 10%, and 23% (all P < .05). Finally, students did not show clinically relevant reductions in their errors between training and testing simulations.CONCLUSIONSAlthough most practitioners correctly visually estimated %SPV and all students completed the training in interpreting and applying %SPV, all groups persisted in making clinically significant treatment errors with moderate to high frequency. This suggests that the treatment errors were more often driven by misapplying FT-DYN algorithms rather than by inaccurate visual estimation of %SPV. Furthermore, these errors were not responsive to training, suggesting that a decision-making cognitive aid may improve CCAT teams' ability to apply FT-DYN technologies.

INTRODUCTION:Understanding usage patterns of current paper-based documentation can inform the development of electronic documentation forms for en route care. The primary objective was to analyze the frequency of use of each field within the 3899 L Patient Movement Record documented by en route Critical Care Air Transport Teams. Secondary objectives were to identify rarely utilized form fields and to analyze the proportion of verifiable major events documented within the 3899 L form.MATERIALS AND METHODS:We performed a retrospective review of 3899 L patient movement records for patients transported via Critical Care Air Transport Teams from January 2019 to December 2019. Scanned 3899 L forms were manually transcribed into a Microsoft Access database for evaluation and analysis. Proportions were calculated for completed fields. Major vital sign event frequency was compared for checkbox fields versus the vital sign flow sheet for each patient. We performed descriptive analyses for the proportion of charts with completed documentation in each evaluated field and the proportion of flow sheet events documented in major event fields.RESULTS:We analyzed 130 records. Fourteen of 18 (77.8%) demographic fields had a 75% or greater completion ratio. Sections with the largest proportion of rarely or never utilized fields (<1.5% completed) were procedures (77.8% of fields) and major events (63.9% of fields). Major event checkboxes had low sensitivity for documented events in the flow sheet: Change in heart rate greater than 20% (1 of 28 patients); increase in the fraction of inspired oxygen requirement of greater than 10% (6 of 23 patients); decrease in mean arterial pressure of greater than 20% (1 in 12 patients); and temperature less than 35.6°C (1 in 13 patients).CONCLUSIONS:Many of the current 3899 L fields are highly utilized, but some 3899 L sections contain high proportions of rarely utilized fields. Major event checkboxes did not consistently capture events documented within the in-flight vital sign flow sheet.

BACKGROUND:The majority of critical care air transport (CCAT) flights are regulated, meaning that a theater-validating flight surgeon has confirmed that the patient is medically cleared for flight and that evacuation is appropriate. If the conditions on the ground do not allow for this process, the flight is unregulated. Published data are limited regarding CCAT unregulated missions to include the period of troop drawdown at the end of the Afghanistan conflict. The objective of our study was to characterize the unregulated missions within Afghanistan during troop drawdown and compare them to regulated missions during the same timeframe.STUDY DESIGN:We performed a retrospective review of all CCAT medical records of patients transported via CCAT within Afghanistan between January 2017 and December 2019. We abstracted data from the records, including mission characteristics, patient demographics, injury descriptors, preflight military treatment facility procedures, CCAT procedures, in-flight CCAT treatments, in-flight events, and equipment issues. Following descriptive and comparative analysis, a Cochran-Armitage test was performed to evaluate the statistical significance of the trend in categorical data over time. Multivariable regression was used to assess the association between vasopressors and preflight massive transfusions, preflight surgical procedures, injury patterns, and age.RESULTS:We reviewed 147 records of patients transported via CCAT: 68 patients were transported in a regulated fashion and 79 on an unregulated flight. The number of patients evacuated increased year-over-year (n = 22 in 2017, n = 57 in 2018, and n = 68 in 2019, P < .001), and the percentage of missions that were unregulated grew geometrically (14%, n = 3 in 2017; 37%, n = 21 in 2018; and 81%, n = 55 in 2019, P < .001). During the time studied, CCAT teams were being used more to decompress forward surgical teams (FST) and, therefore, they were transporting patients just hours following initial damage control surgery in an unregulated fashion. In 2 instances, CCAT decompressed an FST following a mass casualty, during which aeromedical evacuation (AE) crews assisted with patient care. For the regulated missions, the treatments that were statistically more common were intravenous fluids, propofol, norepinephrine, any vasopressors, and bicarbonate. During unregulated missions, the statistically more common treatments were ketamine, fentanyl, and 3% saline. Additional analysis of the mechanically ventilated patient subgroup revealed that vasopressors were used twice as often on regulated (38%) vs. unregulated (13%) flights. Multivariable regression analysis demonstrated that traumatic brain injury (TBI) was the only significant predictor of in-flight vasopressor use (odds ratio = 3.53, confidence interval [1.22, 10.22], P = .02).CONCLUSION:During the troop drawdown in Afghanistan, the number of unregulated missions increased geometrically because the medical footprint was decreasing. During unregulated missions, CCAT providers used ketamine more frequently, consistent with Tactical Combat Casualty Care guidelines. In addition, TBI was the only predictor of vasopressor use and may reflect an attempt to adhere to unmonitored TBI clinical guidelines. Interoperability between CCAT and AE teams is critical to meet mass casualty needs in unregulated mission environments and highlights a need for joint training. It remains imperative to evaluate changes in mission requirements to inform en route combat casualty care training.

Introduction: Inappropriate fluid management during patient transport may lead to combat causality morbidity. We hypothesize that one brief training episode on the visual estimation of percent systolic pressure variation (%SPV) and % SPV-based fluid administration decision making will result in less than 10% fluid administration errors. Methods: CCAT teams received didactic training defining %SPV and were shown Propaq M portable monitor screen simulator containing arterial waveforms. Subjects were asked to visually estimate %SPV for 10 45-second simulations and queried whether they would treat with a fluid bolus; they were told the calculated %SPV after each simulation. After 7 days, subjects were shown a different set of 10 45-second simulations, order randomized, and again asked to estimate %SPV and decide whether they wanted to treat with fluid. Limits of agreement (LOA) for the non-parametric distributed differences between the calculated and estimated %SPV were analyzed using Bland-Altman graphs. Treatment errors were defined as patients with calculated %SPV < 7 and >14.5 receiving fluid and no fluid bolus, respectively. The percentage of incorrect treatment decisions was analyzed using a binomial proportion confidence interval; clinical utility was assessed using a clinical significance analysis. Results: 61 physicians (MDs), 64 nurses (RNs), and 53 respiratory (RTs) participated in this study. In the post-training groups, the percentage and 95% confidence interval [CI] for the %SPV estimate errors with sufficient magnitude to result in a treatment error were 3.3% [1.7%, 5.7%], 1.6% [0.6%, 3.4%], and 4.1% [2.2%, 6.9%], for MDs, RNs, and RTs, respectively; the corresponding fluid treatment errors were 6.6% [4.3%, 9.6%], 9.6% [6.9%, 13.0%], and 23.3% [18%, 28.3%]. All specialty groups had significantly higher fluid treatment errors compared to their %SPV estimate errors. Conclusions: CCAT MDs and RNs performed the best, their incorrect fluid treatments occurred 6.6-9.6% of the time; the largest component of their errors resulted from choosing an incorrect fluid therapy after an estimate of %SPV was made. Further research is required to determine knowledge retention and operational environment effects.