Characteristics and Outcomes of Critically Ill Trauma Patients in Australia and New Zealand (2005-2017)

Longitudinal analysis of caloric requirements in critically ill trauma patients: a retrospective cohort study

PURPOSE

Nutrition is of paramount importance in critically ill trauma patients. However, adequate supply is difficult to achieve, as caloric requirements are unknown. This study investigated caloric requirements over time, based on indirect calorimetry, in critically ill trauma patients.

METHODS

Retrospective cohort study at a tertiary trauma center including critically ill trauma patients who underwent indirect calorimetry 2012-2019. Caloric requirements were assessed as resting energy expenditure (REE) during the intensive care unit stay up to 28 days and analyzed in patient-clustered linear regression analysis.

RESULTS

A total of 129 patients were included. Median REE per day was 2376 kcal. The caloric intake did not meet REE at any time with a median daily deficit of 1167 kcal. In univariable analysis, ISS was not significantly associated with REE over time (RC 0.03, p = 0.600). Multivariable analysis revealed a significant REE increase (RC 0.62, p < 0.001) and subsequent decrease (RC - 0.03, p < 0.001) over time. Age < 65 years (RC 2.07, p = 0.018), male sex (RC 4.38, p < 0.001), and BMI ≥ 35 kg/m2 (RC 6.94, p < 0.001) were identified as independent predictors for higher REE over time. Severe head trauma was associated with lower REE over time (RC - 2.10, p = 0.030).

CONCLUSION

In critically ill trauma patients, caloric requirements significantly increased and subsequently decreased over time. Younger age, male sex and higher BMI were identified as independent predictors for higher caloric requirements, whereas severe head trauma was associated with lower caloric requirements over time. These results support the use of IC and will help to adjust nutritional support in critically ill trauma patients.

Comparison of Intensive Care and Trauma-specific Scoring Systems in Critically Ill Patients

INTRODUCTION

Amongst critically ill trauma patients admitted to ICU and still alive and in ICU after 24 hours, it is unclear which trauma scoring system offers the best performance in predicting in-hospital mortality.

METHODS

The Australia and New Zealand Intensive Care Society Adult Patient Database and Victorian State Trauma Registry were linked using a unique patient identification number. Six scoring systems were evaluated: the Australian and New Zealand Risk of Death (ANZROD), Acute Physiology and Chronic Health Evaluation III (APACHE III) score and associated APACHE III Risk of Death (ROD), Trauma and Injury Severity Score (TRISS), Injury Severity Score (ISS), New Injury Severity Score (NISS) and the Revised Trauma Score (RTS). Patients who were admitted to ICU for longer than 24 hours were analysed. Performance of each scoring system was assessed primarily by examining the area under the receiver operating characteristic curve (AUROC) and in addition using standardised mortality ratios, Brier score and Hosmer-Lemeshow C statistics where appropriate. Subgroup assessments were made for patients aged 65 years and older, patients between 18 and 40 years of age, major trauma centre and head injury.

RESULTS

Overall, 5,237 major trauma patients who were still alive and in ICU after 24 hours were studied from 25 ICUs in Victoria, Australia between July 2008 and January 2018. Hospital mortality was 10.7%. ANZROD (AUROC 0.91; 95% CI 0.90-0.92), APACHE III ROD (AUROC 0.88; 95% CI 0.87-0.90), and APACHE III (AUROC 0.88; 95% CI 0.87-0.89) were the best performing tools for predicting hospital mortality. TRISS had acceptable overall performance (AUROC 0.78; 95% CI 0.76-0.80) while ISS (AUROC 0.61; 95% CI 0.59-0.64), NISS (AUROC 0.68; 95% CI 0.65-0.70) and RTS (AUROC 0.69; 95% CI 0.67-0.72) performed poorly. The performance of each scoring system was highest in younger adults and poorest in older adults.

CONCLUSION

In ICU patients admitted with a trauma diagnosis and still alive and in ICU after 24 hours, ANZROD and APACHE III had a superior performance when compared with traditional trauma-specific scoring systems in predicting hospital mortality. This was observed both overall and in each of the subgroup analyses. The anatomical scoring systems all performed poorly in the ICU population of Victoria, Australia.

Early Hypermetabolism is Uncommon in Trauma Intensive Care Unit Patients

BACKGROUND

Classic experiments demonstrating hypermetabolism after major trauma were performed in a different era of critical care. We aim to describe the modern posttraumatic metabolic response in the trauma intensive care unit (TICU).

METHODS

This prospective observational study enrolled TICU mechanically ventilated adults (aged ≥18) from 3/2018-2/2019. Multiple, daily resting energy expenditure (REE) measurements were recorded. Basal energy expenditure (BEE) was calculated by the Harris-Benedict equation. Hypometabolism was defined as average daily REE < 0.85*BEE and hypermetabolism defined as average daily REE > 1.15*BEE. Demographics, interventions, and clinical outcomes were abstracted. Descriptive statistics and multivariable logistical regression models evaluating demographics with the outcome variable of hypermetabolism for the first 3 days ("sustained hypermetabolism") were performed, along with group-based trajectory modeling (GBTM).

RESULTS

Fifty-five patients were analyzed: median age was 38 (28-56) years; 38 (69%) were male; body mass index (kg/m² ) was 28 (26-32); and Injury Severity Score was 27 (19-34), with (38 [71%] blunt, 8 [15%] penetrating, 7 [13%] burn) injury mechanism. Overall, 19 (35%) had hypermetabolism on day 1 ("immediate hypermetabolism"), and 11 (21%) had sustained hypermetabolism for the first 3 days. Logistic regression analysis identified penetrating mechanism (adjusted odds ratio [AOR], 16.4; 95% CI, 1.9-199.6; p = .015), burn mechanism (AOR, 11.1; 95% CI, 1.3-116.8; p =.029), and maximum temperature (AOR, 4.2; 95% CI, 1.3-20.3; p= .041) as independent predictors of sustained hypermetabolism. GBTM identified 4 nutrition phenotypes, with 2 hyperconsumptive phenotypes associated with increased risk of malnutrition at discharge.

CONCLUSION

Only a minority of injured patients is hypermetabolic in the first week after injury. Elevated temperature, penetrating mechanism, and burn mechanism are independently associated with sustained hypermetabolism. Hyperconsumptive phenotype patients are more likely to develop malnutrition during hospitalization.