Purpose: While fever may be a presenting symptom of COVID-19, fever at hospital admission has not been identified as a predictor of mortality. However, hyperthermia during critical illness among ventilated COVID-19 patients in the ICU has not yet been studied. We sought to determine mortality predictors among ventilated COVID-19 ICU patients and we hypothesized that fever in the ICU is predictive of mortality. Materials and Methods: We conducted a retrospective cohort study of 103 ventilated COVID-19 patients admitted to the ICU between March 14 and May 27, 2020. Final follow-up was June 5, 2020. Patients discharged from the ICU or who died were included. Patients still admitted to the ICU at final follow-up were excluded. Results: 103 patients were included, 40 survived and 63(61.1%) died. Deceased patients were older {66 years[IQR18] vs 62.5[IQR10], ( p = 0.0237)}, more often male {48(68%) vs 22(55%), ( p = 0.0247)}, had lower initial oxygen saturation {86.0%[IQR18] vs 91.5%[IQR11.5], ( p = 0.0060)}, and had lower pH nadir than survivors {7.10[IQR0.2] vs 7.30[IQR0.2] ( p < 0.0001)}. Patients had higher peak temperatures during ICU stay as compared to hospital presentation {103.3°F[IQR1.7] vs 100.0°F[IQR3.5], ( p < 0.0001)}. Deceased patients had higher peak ICU temperatures than survivors {103.6°F[IQR2.0] vs 102.9°F[IQR1.4], ( p = 0.0008)}. Increasing peak temperatures were linearly associated with mortality. Febrile patients who underwent targeted temperature management to achieve normothermia did not have different outcomes than those not actively cooled. Multivariable analysis revealed 60% and 75% higher risk of mortality with peak temperature greater than 103°F and 104°F respectively; it also confirmed hyperthermia, age, male sex, and acidosis to be predictors of mortality. Conclusions: This is one of the first studies to identify ICU hyperthermia as predictive of mortality in ventilated COVID-19 patients. Additional predictors included male sex, age, and acidosis. With COVID-19 cases increasing, identification of ICU mortality predictors is crucial to improve risk stratification, resource management, and patient outcomes.

Venous thromboembolism (VTE) is a major issue in trauma patients. Without prophylaxis, the rate of deep venous thrombosis approaches 60% and even with chemoprophylaxis may be nearly 30%. Advances in VTE reduction are imperative to reduce the burden of this issue in the trauma population. Novel approaches in VTE prevention may include new medications, dosing regimens, and extending prophylaxis to the postdischarge phase of care. Standard dosing regimens of low-molecular-weight heparin are insufficient in trauma, shifting our focus toward alternative dosing strategies to improve prophylaxis. Mixed data suggest that anti-Xa-guided dosage, weight-based dosing, and thromboelastography are among these potential strategies. The concern for VTE in trauma does not end upon discharge, however. The risk for VTE in this population extends well beyond hospitalization. Variable extended thromboprophylaxis regimens using aspirin, low-molecular-weight heparin, and direct oral anticoagulants have been suggested to mitigate this prolonged VTE risk, but the ideal approach for outpatient VTE prevention is still unclear. As part of the 2022 Consensus Conference to Implement Optimal Venous Thromboembolism Prophylaxis in Trauma, a multidisciplinary array of participants, including physicians from multiple specialties, pharmacists, nurses, advanced practice providers, and patients met to attack these issues. This paper aims to review the current literature on novel approaches for optimizing VTE prevention in injured patients and identify research gaps that should be investigated to improve VTE rates in trauma. (

D-CTH in elderly trauma patients taking antithrombotic agents shows no statistically significant or clinical benefit for diagnosing delayed intracranial hemorrhage after minor head injury. In those with delayed imaging showing new ICH, management was not significantly altered. Not enough data were available to predict which patients would develop D-ICH, even if asymptomatic.