After 800 Mtp Events, Mortality Due to Hemorrhagic Shock Remains High and Unchanged Despite Several In-Hospital Hemorrhage Control Advancements

PROSPECTIVE EXAMINATION OF THE K/ICA RATIO AS A PREDICTOR FOR MORTALITY IN SEVERE HEMORRHAGE

ABSTRACT

Background: Patients receiving massive transfusion protocol (MTP) are at risk for posttransfusion hypocalcemia and hyperkalemia. Previous retrospective analysis has suggested the potassium/ionized calcium (K/iCa) ratio as a prognostic indicator of mortality. This prospective study sought to validate the value of the K/iCa ratio as a predictor for mortality in patients receiving MTP. Methods: This was a prospective analysis of adult trauma patients who underwent MTP activation from May 2019 to March 2021 at an urban level 1 trauma center. Serum potassium and iCa levels within 0 to 1 h of MTP initiation were used to obtain K/iCa. Receiver operator characteristic curve analysis assessed predictive capacity of K/iCa on mortality. Kaplan-Meier survival analysis and Cox regression examined the effect of K/iCa ratio on survival. Results: A total of 110 of 300 MTP activation patients met inclusion criteria. Overall mortality rate was 31.8%. No significant differences between the elevated K/iCa and lower K/iCa groups were found for prehospital or emergency department initial vitals, shock index, or injury severity. However, nonsurvivors had a significantly higher median K/iCa ratio compared with those who survived ( P < 0.01). Multivariable logistic regression revealed the total number of blood products to be significantly associated with elevated K/iCa (odds ratio, 1.02; 95% CI, 1.01-1.04; P = 0.01). The Kaplan Meier survival curve demonstrated a significantly increased rate of survival for those with an elevated K/iCa ratio ( P < 0.01). Multivariable Cox regression adjusted for confounders showed a significant association between K/iCa and mortality (Hazard Ratio, 4.12; 95% CI, 1.89-8.96; P < 0.001). Conclusion: This evidence further highlights the importance of the K/iCa ratio in predicting mortality among trauma patients receiving MTP. Furthermore, it demonstrates that posttransfusion K levels along with iCa levels should be carefully monitored in the MTP setting. Level of Evidence: Level II. Study Type: Prognostic/epidemiological.

Change in outcomes for trauma patients over time: Two decades of a state trauma system

BACKGROUND

Trauma center mortality rates are benchmarked to expected rates of death based on patient and injury characteristics. The expected mortality rate is recalculated from pooled outcomes across a trauma system each year, obscuring system-level change across years. We hypothesized that risk-adjusted mortality would decrease over time within a state-wide trauma system.

METHODS

We identified adult trauma patients presenting to Level I and II Pennsylvania trauma centers, 1999-2018, using the Pennsylvania Trauma Outcomes Study. Multivariable logistic regression generated risk-adjusted models for mortality in all patients, and in key subgroups: penetrating torso injury, blunt multisystem trauma, and patients presenting in shock.

RESULTS

Of 162,646 included patients, 123,518 (76.1%) were white and 108,936 (67.0%) were male. The median age was 49 (interquartile range [IQR] 29-70), median injury severity score was 16 (IQR 10-24), and 87.5% of injuries were blunt. Overall, 9.9% of patients died, and compared to 1999, no year had significantly higher adjusted odds of mortality. Overall mortality was significantly lower in 2007-2009 and 2011-2018. Of patients with blunt, multisystem injuries, 17.7% died, and adjusted mortality improved over time. Mortality rates were 24.9% for penetrating torso injury, and 56.9% for shock, with no significant change. Mortality improved for patients with ISS < 25, but not for the most severely injured.

CONCLUSIONS

Over 20 years, Pennsylvania trauma centers demonstrated improved risk-adjusted mortality rates overall, but improvement remains lacking in high-risk groups despite numerous innovations and practice changes in this time period. Identifying change over time can help guide focus to these critical gaps.