The Ability of Military Critical Care Air Transport Members to Visually Estimate Percent Systolic Pressure Variation

Introduction: Inappropriate 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 methods: In 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.

Results: Sixty-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.

Conclusions: Although 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.