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Reintam Blaser A, Rooyackers O, Bear DE. How to avoid harm with feeding critically ill patients: a synthesis of viewpoints of a basic scientist, dietitian and intensivist. Crit Care 2023; 27:258. [PMID: 37393289 PMCID: PMC10314407 DOI: 10.1186/s13054-023-04543-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 06/22/2023] [Indexed: 07/03/2023] Open
Abstract
The optimal feeding strategy in critically ill patients is a matter of debate, with current guidelines recommending different strategies regarding energy and protein targets. Several recent trials have added to the debate and question our previous understanding of the provision of nutrition during critical illness. This narrative review aims to provide a summary of interpretation of recent evidence from the view of basic scientist, critical care dietitian and intensivist, resulting in joined suggestions for both clinical practice and future research. In the most recent randomised controlled trial (RCT), patients receiving 6 versus 25 kcal/kg/day by any route achieved readiness for ICU discharge earlier and had fewer GI complications. A second showed that high protein dosage may be harmful in patients with baseline acute kidney injury and more severe illness. Lastly, a prospective observational study using propensity score matched analysis suggested that early full feeding, especially enteral, compared to delayed feeding is associated with a higher 28-day mortality. Viewpoints from all three professionals point to the agreement that early full feeding is likely harmful, whereas important questions regarding the mechanisms of harm as well as on timing and optimal dose of nutrition for individual patients remain unanswered and warrant future studies. For now, we suggest giving low dose of energy and protein during the first few days in the ICU and apply individualised approach based on assumed metabolic state according to the trajectory of illness thereafter. At the same time, we encourage research to develop better tools to monitor metabolism and the nutritional needs for the individual patient accurately and continuously.
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Affiliation(s)
- Annika Reintam Blaser
- Department of Anaesthesiology and Intensive Care, University of Tartu, Puusepa 8, 50406, Tartu, Estonia.
- Department of Intensive Care Medicine, Lucerne Cantonal Hospital, Lucerne, Switzerland.
| | - Olav Rooyackers
- Division of Anesthesiology and Intensive Care, Department of Clinical Science, Technology and Intervention, Karolinska Institutet, Huddinge, Sweden
| | - Danielle E Bear
- Department of Nutrition and Dietetics, Guy's and St Thomas' NHS Foundation Trust, London, UK
- Department of Critical Care, Guy's and St Thomas' NHS Foundation Trust, London, UK
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Zhou T, Boettger M, Knopp J, Lange M, Heep A, Chase JG. Model-based subcutaneous insulin for glycemic control of pre-term infants in the neonatal intensive care unit. Comput Biol Med 2023; 160:106808. [PMID: 37163965 DOI: 10.1016/j.compbiomed.2023.106808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 03/02/2023] [Accepted: 03/20/2023] [Indexed: 03/30/2023]
Abstract
Hyperglycaemia is a common problem in neonatal intensive care units (NICUs). Achieving good control can result in better outcomes for patients. However, good control is difficult, where poor control and resulting hypoglycaemia reduces outcomes and confounds results. Clinically validated models can provide good control, and subcutaneous insulin delivery can provide more options for insulin therapy for clinicians. However, this combination has only been significantly utilised in adult outpatient diabetes, but could hold benefit for treating NICU infants. This research combines a well-validated NICU metabolic model with subcutaneous insulin kinetics models to assess the feasibility of a model-based approach. Clinical data from 12 very/extremely pre-mature infants was collected for an average study duration of 10.1 days. Blood glucose, interstitial and plasma insulin, as well as subcutaneous and local insulin were modelled, and patient-specific insulin sensitivity profiles were identified for each patient. Modelling error was low, where the cohort median [IQR] mean percentage error was 0.8 [0.3 3.4] %. For external validation, insulin sensitivity was compared to previous NICU cohorts using the same metabolic model, where overall levels of insulin sensitivity were similar. Overall, the combined system model accurately captured observed glucose and insulin dynamics, showing the potential for a model-based approach to glycaemic control using subcutaneous insulin in this cohort. The results justify further model validation and clinical trial research to explore a model-based protocol.
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Liao Y, Zhang R, Shi S, Zhao Y, He Y, Liao L, Lin X, Guo Q, Wang Y, Chen L, Li W, Li S, Chen K, Fang Y. Triglyceride-glucose index linked to all-cause mortality in critically ill patients: a cohort of 3026 patients. Cardiovasc Diabetol 2022; 21:128. [PMID: 35804386 PMCID: PMC9270811 DOI: 10.1186/s12933-022-01563-z] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 06/30/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Triglyceride-glucose (TyG) index as a reliable surrogate of insulin resistance (IR) has been shown to be related to adverse clinical outcomes in patients with acute coronary syndrome, heart failure, ischemic stroke and so on. However, the relationship between TyG index and all-cause mortality in intensive care unit (ICU) patients remains unknown. The purpose of this study was to investigate the correlation between TyG index and all-cause mortality to evaluate the impact of IR on the prognosis of this population. METHODS This was a retrospective observational study that included 3026 patients who had an initial triglyceride and glucose data on the first day of ICU admission, and all data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. These patients were grouped into quartiles (Q1-Q4) according to TyG index. The Kaplan-Meier analysis was used to compare all-cause mortality among the above four groups. Cox proportional hazards analyses were performed to examine the association between TyG index and all-cause mortality. RESULTS During 10.46 years of follow-up, 1148 (37.9%) patients died, of which 350 (11.6%) occurred during the hospital stay and 258 (8.5%) occurred during the ICU stay. Kaplan-Meier analysis showed that the risk of all-cause mortality was significantly higher in patients with higher TyG index (log-rank P = 0.021). Multivariable Cox proportional hazards analyses showed that the TyG index was an independent risk predictor of ICU death (HR: 1.72, 95% CI 1.18-2.52, P = 0.005) and hospital death (HR: 2.19, 95% CI 1.59-3.03, P < 0.001), and each 1-unit increased in the TyG index, a 1.19-fold increase in the risk of death during the hospital stay. CONCLUSIONS TyG index is strongly related to the all-cause mortality increasing in critically ill patients. This finding indicates that the TyG index might be useful in identifying people at high risk of ICU death and hospital death.
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Affiliation(s)
- Ying Liao
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Rongting Zhang
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.,The Graduate School of Clinical Medicine, Fujian Medical University, Fuzhou, 350000, China
| | - Shanshan Shi
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.,The Graduate School of Clinical Medicine, Fujian Medical University, Fuzhou, 350000, China
| | - Yukun Zhao
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.,The Graduate School of Clinical Medicine, Fujian Medical University, Fuzhou, 350000, China
| | - Yibo He
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.,Department of Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Lihua Liao
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.,The Graduate School of Clinical Medicine, Fujian Medical University, Fuzhou, 350000, China
| | - Xueqin Lin
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.,The Graduate School of Clinical Medicine, Fujian Medical University, Fuzhou, 350000, China
| | - Qian Guo
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.,The Graduate School of Clinical Medicine, Fujian Medical University, Fuzhou, 350000, China
| | - Yani Wang
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.,The Graduate School of Clinical Medicine, Fujian Medical University, Fuzhou, 350000, China
| | - Liling Chen
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Weiguo Li
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China
| | - Shihai Li
- Department of Anesthesiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.
| | - Kaihong Chen
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.
| | - Yong Fang
- Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, China.
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