Monitoring / Diagnostics

#### MONITORING / DIAGNOSTICS

Br J Anaesth. 2018 Dec;121(6):1215-1217

# Venous air embolism: ultrasonographic diagnosis and treatment with hyperbaric oxygen therapy.

Brodbeck A, Bothma P, Pease J

A man with neuromuscular respiratory failure requiring intubation and ventilation suffered a venous air embolism during inadvertent administration of 5 ml of air. Ultrasound (US) imaging confirmed an air embolus in the left subclavian vein, which was only partially treated by US-guided aspiration. The embolus completely resolved on US imaging during hyperbaric oxygen therapy, and the patient recovered with no complications secondary to the embolism. Venous air embolism is under-recognised, and can cause siginificant neurological morbidity and death if untreated. When available, urgent hyperbaric oxygen therapy appears to be an effective approach.

J Trauma Acute Care Surg. 2019; Epub ahead of print

# Thromboelastography On-the-Go: Evaluation of the TEG 6s Device During Ground and High-Altitude Aeromedical Evacuation with Extracorporeal Life Support.

Roberts T, Jones J, Choi J, Sieck K, Harea G, Wendorff D, Beely B, Karaliou V, Cap A, Davis M, Cancio L, Sams V, Batchinsky A

BACKGROUND: Coagulation monitoring capabilities during transport are limited. Thromboelastography (TEG) is a whole-blood clotting test measuring clot formation, stabilization and fibrinolysis; and is traditionally performed in a laboratory. We evaluated a new point-of-care TEG analyzer, TEG 6s (Haemonetics; Braintree, MA), in a large animal model of combat-relevant trauma managed with extracorporeal life support (ECLS) during ground and high-altitude aeromedical evacuation. The objective was to compare TEG 6s used during transport vs. the predicate device, TEG 5000, used in the laboratory. We hypothesized that TEG 6s would be comparable to TEG 5000 during dynamically changing transport conditions.

METHODS: TEG parameters (R, K, Angle, MA, LY30) derived by TEG 6s and TEG 5000 were compared during transport of 8 swine. TEG 6s was transported with animals during ground transport and flight. TEG 5000 was stationary in an adjacent building. TEG 6s activated clotting time (ACT) was compared to a Hemochron Junior ACT analyzer (Accriva Diagnostics; San Diego, CA). Statistics were performed using SAS 9.4 with Deming regressions, Spearman correlations and average differences compared.

RESULTS: Correlation between devices was stronger at sea-level (R r=0.7413, K r=0.7115, Angle r=0.7192, MA r=0.8386, LY30 r=0.9099) than during high-altitude transport (R r=0.4787, K r=0.4007, Angle r =0.3706, MA r=0.6573, LY30 r=0.8481). Method agreement was comparable during stationary operation (R r=0.7978, K r=0.7974, Angle r=0.7574, MA r=0.7841, LY30 r=0.9140) vs. ground transport (R r=0.7927, K r=0.6246, Angle r=0.6967, MA r=0.9163, LY30 r=0.8603). TEG 6s ACT trended higher than Hemochron ACT when subjects were heparinized (average difference=1442±1703 sec) without a methodological difference by Deming regression.

CONCLUSIONS: Mobile TEG 6s during ground and altitude transport is feasible and provides unprecedented information to guide coagulation management. Future studies should assess the precision and accuracy of TEG 6s during transport of critically ill.

LEVEL OF EVIDENCE: Basic science paper, does not require level of evidence.

Sci Rep. 2019 Sep 24;9(1):13755

# Prehospital lactate improves prediction of the need for immediate interventions for hemorrhage after trauma.

Fukuma H, Nakada T, Shimada T, Shimazui T, Aizimu T, Nakao S, Watanabe H, Mizushima Y, Matsuoka T

The blood lactate level is used to guide the management of trauma patients with circulatory disturbance. We hypothesized that blood lactate levels at the scene (Lac scene) could improve the prediction for immediate interventions for hemorrhage. We prospectively measured blood lactate levels and assessed retrospectively in 435 trauma patients both at the scene and on arrival at the emergency room (ER) of a level I trauma center. Primary outcome was immediate intervention for hemorrhage defined as surgical/radiological intervention and/or blood transfusion within 24 h. Physiological variables plus Lac scene significantly increased the predictive value for immediate intervention (area under the curve [AUC] 0.882, 95% confidence interval [CI] 0.839-0.925) compared to that using physiological variables only (AUC 0.837, 95% CI 0.787-0.887, P = 0.0073), replicated in the validation cohort (n = 85). There was no significant improvement in predicting value of physiological variables plus Lac scene for massive transfusion compared to physiological variables (AUC 0.903 vs 0.895, P = 0.32). The increased blood lactate level per minute from scene to ER was associated with increased probability for immediate intervention (P < 0.0001). Both adding Lac scene to physiological variables and the temporal elevation of blood lactate levels from scene to ER could improve the prediction of the immediate intervention.

Am J Emerg Med. 2019 Jul 15;Epub ahead of print

# The utility of iPhone oximetry apps: A comparison with standard pulse oximetry measurement in the emergency department.

Jordan T, Meyers C, Schrading W, Donnelly J

OBJECTIVES: To determine if a correlation exists between 3 iphone pulse ox applications' measurements and the standard pulse oximetry (SpO2) and whether these applications can accurately determine hypoxia.

METHODS: Three applications reportedly measuring SpO2 were downloaded onto an iPhone 5s. Two of these applications used the onboard light and camera lens "Pulse Oximeter" (Pox) and "Heart Rate and Pulse Oximeter" (Ox) and one used an external device that plugged into the iphone (iOx). Patients in the ED were enrolled with chief complaints of cardiac/pulmonary origin or a SpO2 ≤ 94%. All measurements were compared to controls. Concordance correlation coefficients, sensitivity, and specificity were calculated.

RESULTS: A total of 191 patients were enrolled. The concordance correlation of iOx with control was 0.55 (CI 0.46, 0.63), POx was 0.01 (CI -0.09, 0.11), and Ox was 0.07 (CI -0.02, 0.15). 68/191 patients (35%) were found to have hypoxemia. Sensitivities for detecting hypoxia were 69%, 0%, and 7% for iOx, POx, and Ox, respectively. Specificities were 89%, 100%, and 89%. Even iOx (the most accurate) 21 (11%) were incorrectly classified nonhypoxic, and 22 (12%) were incorrectly classified hypoxic.

CONCLUSIONS: While iOx has modest concordance with control, Ox and POx showed almost none. The iOx device was best in correctly identifying hypoxia patients, but almost 1/4 of patients were incorrectly classified. The three apps provided inaccurate SpO2 measurements and had limited to no ability to accurately detect hypoxia. These apps should not be relied upon to provide accurate SpO2 measurements in emergent, even austere conditions.