ABSTRACT
BACKGROUND: Prehospital identification of the injured patient likely to require emergent care remains a challenge. End-tidal carbon dioxide (ETCO2) has been used in the prehospital setting to monitor respiratory physiology and confirmation of endotracheal tube placement. Low levels of ETCO2 have been demonstrated to correlate with injury severity and mortality in a number of in-hospital studies. We hypothesized that prehospital ETCO2 values would be predictive of mortality and need for massive transfusion (MT) in intubated patients. METHODS: This was a retrospective multicenter trial with 24 participating centers. Prehospital, emergency department, and hospital values were collected. Receiver operating characteristic curves were created and compared. Massive transfusion defined as >10 U of blood in 6 hours or death in 6 hours with at least 1 U of blood transfused. RESULTS: A total of 1,324 patients were enrolled. ETCO2 (area under the receiver operating characteristic curve [AUROC], 0.67; confidence interval [CI], 0.63-0.71) was better in predicting mortality than shock index (SI) (AUROC, 0.55; CI, 0.50-0.60) and systolic blood pressure (SBP) (AUROC, 0.58; CI, 0.53-0.62) (p < 0.0005). Prehospital lowest ETCO2 (AUROC, 0.69; CI, 0.64-0.75), SBP (AUROC, 0.75; CI, 0.70-0.81), and SI (AUROC, 0.74; CI, 0.68-0.79) were all predictive of MT. Analysis of patients with normotension demonstrated lowest prehospital ETCO2 (AUROC, 0.66; CI, 0.61-0.71), which was more predictive of mortality than SBP (AUROC, 0.52; CI, 0.47-0.58) or SI (AUROC, 0.56; CI, 0.50-0.62) (p < 0.001). Lowest prehospital ETCO2 (AUROC, 0.75; CI, 0.65-0.84), SBP (AUROC, 0.63; CI, 0.54-0.74), and SI (AUROC, 0.64; CI, 0.54-0.75) were predictive of MT in normotensive patients. ETCO2 cutoff for MT was 26 mm Hg. The positive predictive value was 16.1%, and negative predictive value was high at 98.1%. CONCLUSION: Prehospital ETCO2 is predictive of mortality and MT. ETCO2 outperformed traditional measures such as SBP and SI in the prediction of mortality. ETCO2 may outperform traditional measures in predicting need for transfusion in occult shock. LEVEL OF EVIDENCE: Diagnostic test, level III.
Subject(s)
Blood Component Transfusion/statistics & numerical data , Carbon Dioxide/metabolism , Emergency Medical Services , Wounds and Injuries/mortality , Adolescent , Adult , Aged , Female , Hospital Mortality , Humans , Injury Severity Score , Male , Middle Aged , Predictive Value of Tests , Retrospective Studies , Tidal Volume , United States , Vital SignsABSTRACT
BACKGROUND: Studies have individually reported the relationship of age, cardiac risk factors, and history of preexisting coronary artery disease (CAD) for predicting acute coronary syndromes in chest pain patients undergoing cardiac stress testing. In this study, we investigate the interplay of all these factors on the incidence of acute coronary syndromes to develop a tool that may assist physicians in the selection of appropriate chest pain patients for stress testing. METHODS: Retrospective analysis of a prospectively acquired database of consecutive chest pain patients undergoing nuclear stress testing. Backward stepwise logistic regression was used to develop a model for predicting risk of 30-day acute coronary events (ACE) using information obtained from age, sex, cardiac risk factors, and history of preexisting CAD. RESULTS: A total of 800 chest pain patients underwent nuclear stress testing. ACE occurred in 74 patients (9.3%). Logistic regression analysis found only 6 factors predictive of ACE: age, male sex, preexisting CAD, diabetes, and hyperlipidemia. Area under the receiver operator characteristic curve of this model for predicting ACE was 0.767 (95% confidence interval, 0.719-0.815). There were no cases of ACE in the 173 patients with predicted probability estimates ≤2.5% (95% confidence interval, 0%-2.1%). CONCLUSIONS: A regression model using age, sex, preexisting CAD, diabetes, and hyperlipidemia is predictive of 30-day ACE in chest pain patients undergoing nuclear stress testing. Prospective studies need to be performed to determine whether this model can assist physicians in the selection of appropriate low-to-intermediate risk chest pain patients for nuclear stress testing.
