Do admission glucose levels independently predict coagulopathy in multiple trauma patients? A retrospective cohort analysis

The Interaction and Implication of Stress-Induced Hyperglycemia and Cytokine Release Following Traumatic Injury: A Structured Scoping Review

INTRODUCTION

This is a structured scoping review to assess whether there is a relationship between stress-induced hyperglycemia (SIH), cytokine interactions, and mortality in trauma patients in comparison to non-diabetic normoglycemia [NDN], diabetic normoglycemia [DN], and diabetic hyperglycemia [DH].

METHODS

We conducted a literature search of MEDLINE (PubMed) databases from 2000 to 2022 using a search strategy to identify observational studies. Initially, 2879 articles were retrieved. Of these, 2869 were excluded due to insufficient variables, and non-trauma focuses.

RESULTS

Nine studies on the interaction between SIH and proinflammatory cytokines were analyzed. SIH was associated with the highest mortality rate (21.3%), followed by DH (5.4%), DN (2.8%), and NDN (2.3%) (p < 0.001). Furthermore, SIH patients exhibited an 11.28-fold higher likelihood of mortality compared to NDN patients (95% CI [9.13-13.93]; p < 0.001) and a 4.72-fold higher likelihood compared to DH patients (OR 4.72; 95% CI [3.55-6.27]; p < 0.001).

CONCLUSIONS

SIH patients had elevated IL-6 concentrations relative to NDN, DN, and DH patients. SIH is linked to higher mortality in trauma, with greater odds than NDN. However, the robustness of this association is still being determined due to statistical and clinical variability. Uncertainties about injury severity and IL-6 level similarities between SIH and DH patients require further investigation.

External Validation of Predictors of Mortality in Polytrauma Patients

INTRODUCTION

The Parkland Trauma Index of Mortality (PTIM) is an integrated, machine learning 72-h mortality prediction model that automatically extracts and analyzes demographic, laboratory, and physiological data in polytrauma patients. We hypothesized that this validated model would perform equally as well at another level 1 trauma center.

METHODS

A retrospective cohort study was performed including ∼5000 adult level 1 trauma activation patients from January 2022 to September 2023. Demographics, physiologic and laboratory values were collected. First, a test set of models using PTIM clinical variables (CVs) was used as external validation, named PTIM+. Then, multiple novel mortality prediction models were developed considering all CVs designated as the Cincinnati Trauma Index of Mortality (CTIM). The statistical performance of the models was then compared.

RESULTS

PTIM CVs were found to have similar predictive performance within the PTIM + external validation model. The highest correlating CVs used in CTIM overlapped considerably with those of the PTIM, and performance was comparable between models. Specifically, for prediction of mortality within 48 h (CTIM versus PTIM): positive prediction value was 35.6% versus 32.5%, negative prediction value was 99.6% versus 99.3%, sensitivity was 81.0% versus 82.5%, specificity was 97.3% versus 93.6%, and area under the curve was 0.98 versus 0.94.

CONCLUSIONS

This external cohort study suggests that the variables initially identified via PTIM retain their predictive ability and are accessible in a different level 1 trauma center. This work shows that a trauma center may be able to operationalize an effective predictive model without undertaking a repeated time and resource intensive process of full variable selection.