Evaluation of an Artificial Neural Network to Predict Urea Nitrogen Appearance for Critically Ill Multiple-Trauma Patients

Which criteria is a better predictor of ICU admission in trauma patients? An artificial neural network approach

PURPOSE

One of the most critical concerns in the intensive care unit (ICU) section is identifying the best criteria for entering patients to this part. This study aimed to predict the best compatible criteria for entering trauma patients in the ICU section.

METHOD

The present study was a historical cohort study. The data were collected from 2448 trauma patients referring to Shahid Rajaee Hospital between January 2015 and January 2017 in Shiraz, Iran. The artificial neural network (ANN) models with cross-validation and logistic regression (LR) with a backward method was used for data analysis. The final analysis was performed on a total of 958 patients who were transferred to the ICU section.

RESULTS

Based on the present results, the motor component of the GCS score at each cutoff point had the highest importance. The results also showed better performance for the AUC and accuracy rate for ANN compared with LR.

CONCLUSION

The most critical indicators in predicting the optimal use of ICU services in this study were the Motor component of the GCS. Results revealed that the ANN had a better performance than the LR in predicting the main outcomes of the traumatic patients in both the accuracy and AUC index. Trauma section surgeons and ICU specialists will benefit from this study's results and can assist them in making decisions to predict the patient outcomes before entering the ICU.

Nitrogen Balance and Protein Requirements for Critically Ill Older Patients

Critically ill older patients with sarcopenia experience greater morbidity and mortality than younger patients. It is anticipated that unabated protein catabolism would be detrimental for the critically ill older patient. Healthy older subjects experience a diminished response to protein supplementation when compared to their younger counterparts, but this anabolic resistance can be overcome by increasing protein intake. Preliminary evidence suggests that older patients may respond differently to protein intake than younger patients during critical illness as well. If sufficient protein intake is given, older patients can achieve a similar nitrogen accretion response as younger patients even during critical illness. However, there is concern among some clinicians that increasing protein intake in older patients during critical illness may lead to azotemia due to decreased renal functional reserve which may augment the propensity towards worsened renal function and worsened clinical outcomes. Current evidence regarding protein requirements, nitrogen balance, ureagenesis, and clinical outcomes during nutritional therapy for critically ill older patients is reviewed.

Using an Artificial Neural Networks (ANNs) Model for Prediction of Intensive Care Unit (ICU) Outcome and Length of Stay at Hospital in Traumatic Patients

INTRODUCTION

Currently applications of artificial neural network (ANN) models in outcome predicting of patients have made considerable strides in clinical medicine. This project aims to use a neural network for predicting survival and length of stay of patients in the ward and the intensive care unit (ICU) of trauma patients and to obtain predictive power of the current method.

MATERIALS AND METHODS

We used Neuro-Solution software (NS), a leading-edge neural network software for data mining to create highly accurate and predictive models using advanced preprocessing techniques, intelligent automated neural network topology through cutting-edge distributed computing. This ANN model was used based on back-propagation, feed forward, and fed by Trauma and injury severity score (TRISS) components, biochemical findings, risk factors and outcome of 95 patients. In the next step a trained ANN was used to predict outcome, ICU and ward length of stay for 30 test group patients by processing primary data.

RESULTS

The sensitivity and specificity of an ANN for predicting the outcome of traumatic patients in this study calculated 75% and 96.26%, respectively. 93.33% of outcome predictions obtained by ANN were correct. In 3.33% of predictions, results of ANN were optimistic and 3.33% of cases predicted ANN results were worse than the actual outcome of patients. Neither difference in average length of stay in the ward and ICU with predicted ANN results, were statistically significant. Correlation coefficient of two variables of ANN prediction and actual length of stay in hospital was equal to 0.643.

CONCLUSION

Using ANN model based on clinical and biochemical variables in patients with moderate to severe traumatic injury, resulted in satisfactory outcome prediction when applied to a test set.

Influence of aging on nitrogen accretion during critical illness

BACKGROUND

Aging adversely affects nitrogen accretion during health, but its effect during critical illness is unknown. Nitrogen balance (NB) response to varying protein intakes was compared between critically ill, older and younger patients.

METHODS

Adult patients admitted to the trauma intensive care unit, given enteral or parenteral nutrition, and who had a NB determination within 5-14 days after injury were evaluated. Patients with renal or hepatic disease were excluded. Patients were categorized as older (≥60 years) or younger (18-59 years of age). Data are given as mean ± SD or median [interquartile range].

RESULTS

Fifty-four older (69 [65, 77] years) and 195 younger (35 [27, 47] years) patients were evaluated. NB was blunted for the older patients with an observed trending improvement in NB from -13.5 ± 5.5 to -5.6 ± 8.8 g/d (P = NS) noted at 1.5-1.99 g/kg/d. NB improved from -22.2 ± 8.2 to -11.8 ± 9.9 g/d (P = .05) at 1-1.49 g/kg/d and modestly thereafter for each 0.5-g/kg/d increase in protein intake for the younger patients. Serum urea nitrogen concentration during the NB was highly variable but overall greater for the older patients (20 [14, 33] vs 15 [10, 20] mg/dL, P = .001).

CONCLUSIONS

Improvement in nitrogen accretion was blunted at lower protein intakes in critically ill, older patients compared with younger patients. Individualization of protein intake is warranted.