Identifying the factors which influence energy deficit in the adult intensive care unit
Critically ill patients frequently receive inadequate nutrition support due to under- or overestimation of nutritional needs (Reid, 2006), delays in initiating nutrition support and frequent interruptions to nutritional support (Heyland et al., 2003). The purpose of this research was to identify the significant factors which influence energy deficit in the adult intensive care unit (ICU). Methods:
ICU patients with a length of stay of ≥3 days were studied for 30 days over two consecutive years at a large university teaching hospital. Fifty-six patients were studied with a total of 530 records of feeding days. The following information was collected: day feeding was initiated, age, length of stay, Acute Physiology & Chronic Health Evaluation score (APACHE II), fed within 24 h (yes/no) gender, speciality, type of ventilation (endotracheal tube (ETT), tracheostomy, non-invasive (NIV), self), feeding route, outcome (survived/died), diarrhoea, aspirate volume, dietitian observed nutritional status (at risk or not), sedation, estimated energy requirements and energy received. The statistical method used was mixed linear models for longitudinal data with energy deficit (energy received – energy requirements) as the dependent variable. Results:
The model showed that factors which significantly affected energy deficit were: day feeding was initiated (P < 0.001), whether fed within 24 h (P < 0.001) and whether sedated (P < 0.001). Energy deficit was greatest during the first week but this reduced and became more stable thereafter. Furthermore, three combined effects were found:
Ventilation mode and aspirate volume (P < 0.007); in patients with larger aspirate volumes the type of ventilation really affected energy deficit, particularly with ETT.
Fed within 24 h and sedation (P < 0.017); Patients who were fed within 24 h had lower energy deficits and sedation had little effect on this. However, in the group who were not fed within 24 h, sedated patients had much greater deficits than non-sedated.
Fed within 24 h and ventilation mode (P < 0.001); Patients not fed within the first 24 h and ventilated with ETT or NIV had much higher energy deficits compared to other forms of ventilation. Discussion:
The time on ICU prior to commencing feeding and whether fed in the first 24 h will obviously affect overall energy deficit. Sedation can affect gastric motility and the decision to feed, which could lead to the observed effect on energy deficit. These findings confirm those of previous studies (Heyland et al., 2003; Reid, 2006). In addition this study also showed that aspirate volume, type of ventilation and sedation were involved in combined effects. A plausible explanation for these findings is that sedated and ventilated patients are the sickest patients on ICU and their nutrition support is frequently interrupted by procedures, surgery and poor feed tolerance. Interestingly baseline APACHE II score, specialty, feeding route, presence of diarrhoea and nutritional status were not included in the final model which best predicted energy deficit, probably due to correlations with the included variables. Conclusions:
Day when feeding was initiated, fed within 24 h and sedation have been identified as independent factors which predict energy deficit during ICU stay. More focus can therefore be given to the patients most at risk to try and ensure that adequate energy intakes are achieved. References
Heyland, D.K., Schroter-Neppe, D., Drover, J.W., Jain, M., Keefe, L., Dhaliwal, R. & Day, A. (2003) Nutrition support in the critical care setting: current practice in Canadian ICU's – opportunities for improvement? J. Parenter. Enteral. Nutr. 27, 74–83.
Reid, C. (2006) Frequency of under- and overfeeding in mechanically ventilated ICU patients: causes and possible consequences. J. Hum. Nutr. Diet.19, 13–22.
Document Type: Research Article
Affiliations: 1: Imperial College Healthcare NHS Trust, Department of Nutrition and Dietetics, Charing Cross Hospital, London, UK 2: Statistical Advisory Service, Imperial College, London, UK, Email: firstname.lastname@example.org
Publication date: August 1, 2008