Association between Malnutrition and 28-Day Mortality and Intensive Care Length-of-Stay in the Critically ill: A Prospective Cohort Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Collection
2.2. Nutrition Assessment
2.3. Statistical Analysis
3. Results
4. Discussion
4.1. Future Research
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Lew, C.C.H.; Yandell, R.; Fraser, R.J.; Chua, A.P.; Chong, M.F.F.; Miller, M. Association between malnutrition and clinical outcomes in the intensive care unit: A systematic review. J. Parenter. Enter. Nutr. 2017, 41, 744–758. [Google Scholar] [CrossRef] [PubMed]
- Cederholm, T.; Bosaeus, I.; Barazzoni, R.; Bauer, J.; Van Gossum, A.; Klek, S.; Muscaritoli, M.; Nyulasi, I.; Ockenga, J.; Schneider, S.M.; et al. Diagnostic criteria for malnutrition—An ESPEN consensus statement. Clin. Nutr. 2015, 34, 335–340. [Google Scholar] [CrossRef] [PubMed]
- White, J.V.; Guenter, P.; Jensen, G.; Malone, A.; Schofield, M.; AcademyMalnutrition Work Group; American Society for Parenteral and Enteral Nutrition Malnutrition Task Force; The American Society for Parenteral and Enteral Nutrition Board of Directors. Consensus statement: Academy of nutrition and dietetics and american society for parenteral and enteral nutrition: Characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). J. Parenter. Enter. Nutr. 2012, 36, 275–283. [Google Scholar] [CrossRef] [PubMed]
- Kondrup, J.; Rasmussen, H.H.; Hamberg, O.; Stanga, Z. Nutritional risk screening (NRS 2002): A new method based on an analysis of controlled clinical trials. Clin. Nutr. 2003, 22, 321–336. [Google Scholar] [CrossRef]
- Elia, M. The ‘Must’ Report. Nutritional Screening for Adults: A Multidisciplinary Responsibility. Development and Use of the ‘Malnutrition Universal Screening Tool’ (Must) for Adults; BAPEN: Worcestershire, UK, 2003. [Google Scholar]
- Detsky, A.S.; McLaughlin, J.R.; Baker, J.P.; Johnston, N.; Whittaker, S.; Mendelson, R.A.; Jeejeebhoy, K.N. What is subjective global assessment of nutritional status? J. Parenter. Enter. Nutr. 1987, 11, 8–13. [Google Scholar] [CrossRef] [PubMed]
- Moons, K.G.; Royston, P.; Vergouwe, Y.; Grobbee, D.E.; Altman, D.G. Prognosis and prognostic research: What, why, and how? BMJ 2009, 338, b375. [Google Scholar] [CrossRef] [PubMed]
- Knaus, W.A.; Draper, E.A.; Wagner, D.P.; Zimmerman, J.E. APACHE II: A severity of disease classification system. Crit. Care Med. 1985, 13, 818–829. [Google Scholar] [CrossRef] [PubMed]
- Ho, K.M.; Knuiman, M.; Finn, J.; Webb, S.A. Estimating long-term survival of critically ill patients: The predict model. PLoS ONE 2008, 3, e3226. [Google Scholar] [CrossRef] [PubMed]
- Waterer, G.W.; Somes, G.W.; Wunderink, R.G. Monotherapy may be suboptimal for severe bacteremic pneumococcal pneumonia. Arch. Intern. Med. 2001, 161, 1837–1842. [Google Scholar] [CrossRef] [PubMed]
- Moons, K.G.; Altman, D.G.; Reitsma, J.B.; Ioannidis, J.P.; Macaskill, P.; Steyerberg, E.W.; Vickers, A.J.; Ransohoff, D.F.; Collins, G.S. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): Explanation and elaborationthe tripod statement: Explanation and elaboration. Ann. Intern. Med. 2015, 162, W1–W73. [Google Scholar] [CrossRef] [PubMed]
- Heyland, D.K.; Dhaliwal, R.; Jiang, X.; Day, A.G. Identifying critically ill patients who benefit the most from nutrition therapy: The development and initial validation of a novel risk assessment tool. Crit. Care 2011, 15, R268. [Google Scholar] [CrossRef] [PubMed]
- Salluh, J.I.; Soares, M. ICU severity of illness scores: APACHE, SAPS and MPM. Curr. Opin. Crit. Care 2014, 20, 557–565. [Google Scholar] [CrossRef] [PubMed]
- Vincent, J.-L.; Moreno, R.; Takala, J.; Willatts, S.; De Mendonça, A.; Bruining, H.; Reinhart, C.; Suter, P.; Thijs, L. The sofa (sepsis-related organ failure assessment) score to describe organ dysfunction/failure. Intensive Care Med. 1996, 22, 707–710. [Google Scholar] [CrossRef] [PubMed]
- Charlson, M.E.; Pompei, P.; Ales, K.L.; MacKenzie, C.R. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J. Chronic Dis. 1987, 40, 373–383. [Google Scholar] [CrossRef]
- Churchill, D. Adequacy of dialysis and nutrition in continuous peritoneal dialysis: Association with clinical outcomes. J. Am. Soc. Nephrol. 1996, 7, 198–207. [Google Scholar]
- Lim, S.L.; Lin, X.H.; Daniels, L. Seven-point subjective global assessment is more time sensitive than conventional subjective global assessment in detecting nutrition changes. J. Parenter. Enter. Nutr. 2016, 40, 966–972. [Google Scholar] [CrossRef] [PubMed]
- Lee, J.; Tan, C.S.; Chia, K.S. A practical guide for multivariate analysis of dichotomous outcomes. Ann. Acad. Med. Singap. 2009, 38, 714–719. [Google Scholar] [PubMed]
- Brock, G.N.; Barnes, C.; Ramirez, J.A.; Myers, J. How to handle mortality when investigating length of hospital stay and time to clinical stability. BMC Med. Res. Methodol. 2011, 11, 144. [Google Scholar] [CrossRef] [PubMed]
- Fontes, D.; Generoso, S.d.V.; Toulson Davisson Correia, M.I. Subjective global assessment: A reliable nutritional assessment tool to predict outcomes in critically ill patients. Clin. Nutr. 2014, 33, 291–295. [Google Scholar] [CrossRef] [PubMed]
- Sheean, P.M.; Peterson, S.J.; Chen, Y.; Liu, D.; Lateef, O.; Braunschweig, C.A. Utilizing multiple methods to classify malnutrition among elderly patients admitted to the medical and surgical intensive care units (ICU). Clin. Nutr. 2013, 32, 752–757. [Google Scholar] [CrossRef] [PubMed]
- Mukhopadhyay, A.; Henry, J.; Ong, V.; Leong, C.S.-F.; Teh, A.L.; van Dam, R.M.; Kowitlawakul, Y. Association of modified nutric score with 28-day mortality in critically ill patients. Clin. Nutr. 2017, 36, 1143–1148. [Google Scholar] [CrossRef] [PubMed]
- Caporossi, F.S.; Caporossi, C.; Borges Dock-Nascimento, D.; de Aguilar-Nascimento, J.E. Measurement of the thickness of the adductor pollicis muscle as a predictor of outcome in critically ill patients. Nutr. Hosp. 2012, 27, 490–495. [Google Scholar] [PubMed]
- Sheean, P.M.; Peterson, S.J.; Gurka, D.P.; Braunschweig, C.A. Nutrition assessment: The reproducibility of subjective global assessment in patients requiring mechanical ventilation. Eur. J. Clin. Nutr. 2010, 64, 1358–1364. [Google Scholar] [CrossRef] [PubMed]
- Schmidt, C.O.; Kohlmann, T. When to use the odds ratio or the relative risk? Int.J. Public Health 2008, 53, 165–167. [Google Scholar] [CrossRef] [PubMed]
- Arabi, Y.M.; Casaer, M.P.; Chapman, M.; Heyland, D.K.; Ichai, C.; Marik, P.E.; Martindale, R.G.; McClave, S.A.; Preiser, J.-C.; Reignier, J.; et al. The intensive care medicine research agenda in nutrition and metabolism. Intensive Care Med. 2017, 43, 1239–1256. [Google Scholar] [CrossRef] [PubMed]
- Ferrie, S.; Allman-Farinelli, M.; Daley, M.; Smith, K. Protein requirements in the critically ill: A randomized controlled trial using parenteral nutrition. J. Parenter. Enter. Nutr. 2016, 40, 795–805. [Google Scholar] [CrossRef] [PubMed]
Parameters | Well-Nourished | Malnourished | p-Value | Survivor | Non-Survivor | p-Value |
---|---|---|---|---|---|---|
(n = 316) | (n = 123) | (n = 316) | (n = 123) | |||
Age (years) | 59.8 (15.7) | 65.6 (15.3) | 0.001 | 59.3 (15.9) | 66.8 (14.1) | < 0.001 |
Male | 188 (59.5) | 69 (56.1) | 0.517 | 191 (60.4) | 67 (54.5) | 0.254 |
BMI (kg/m2) | 26.2 (5.8) | 22.6 (5.8) | <0.001 | 25.2 (6.0) | 25.1 (6.2) | 0.960 |
Location before adm | ||||||
ED/HD/OT | 263 (83.2) | 94 (76.4) | 0.100 | 268 (84.8) | 89 (72.4) | 0.003 |
Wards | 53 (16.8) | 29 (23.6) | 48 (15.2) | 34 (27.6) | ||
Type of adm | ||||||
No surgery | 210 (66.5) | 83 (67.5) | 0.974 | 199 (63.0) | 94 (76.4) | 0.027 |
Elective surgery | 10 (3.2) | 4 (3.3) | 11 (3.5) | 3 (2.4) | ||
Emergency surgery | 96 (30.4) | 36 (29.3) | 106 (33.5) | 26 (21.1) | ||
Charlson morbidity index | 1.0 (0.0, 3.0) | 1.0 (1.0, 3.0) | 0.054 | 1.0 (0.0, 3.0) | 1.0 (0.0, 3.0) | 0.320 |
LOS before ICU adm (days) | 0.0 (0.0, 1.0) | 1.0 (0.0, 3.0) | <0.001 | 0.0 (0.0, 1.0) | 1.0 (0.0, 3.0) | 0.008 |
APACHE II | 23.7 (8.0) | 26.9 (7.9) | <0.001 | 22.6 (7.4) | 29.5 (7.7) | <0.001 |
SOFA | 8.3 (3.6) | 9.5 (4.2) | 0.009 | 7.9 (3.5) | 10.7 (3.8) | <0.001 |
Predicted mortality risk (%) a | 47.7 (25.8) | 59.7 (24.9) | <0.001 | 44.1 (24.2) | 68.8 (22.2) | <0.001 |
Vasoactives before ICU adm | 134 (42.4) | 59 (48.0) | 0.292 | 127 (40.2) | 66 (53.7) | 0.011 |
CPR before ICU adm | 35 (11.1) | 18 (14.6) | 0.304 | 17 (5.4) | 36 (29.3) | <0.001 |
Length of MV (days) | 2.0 (1.0, 5.0) | 2.0 (1.0, 5.0) | 0.734 | 2.0 (1.0, 4.0) | 3.0 (2.0, 6.0) | <0.001 |
ICU LOS (days) | 2.0 (2.0, 5.0) | 3.0 (2.0, 5.0) | 0.981 | 2.0 (1.0, 4.0) | 3.0 (2.0, 6.0) | 0.001 |
Hospital LOS (days) | 13.0 (6.3, 24.0) | 16.0 (9.0, 27.0) | 0.120 | 15.0 (9.0, 33.0) | 9.0 (4.0, 16.0) | <0.001 |
28-day mortality | 72 (22.8) | 51 (41.5) | <0.001 | |||
Malnutrition | 72 (22.8) | 51 (41.5) | <0.001 | |||
SGA Sub-Categories | ||||||
SGA-7 | 217 (68.7) | 165 (52.2) | 52 (42.3) | |||
SGA-6 | 99 (31.3) | 79 (25.0) | 20 (16.3) | |||
SGA-5 | 59 (48.0) | 38 (12.0) | 21 (17.1) | |||
SGA-4 | 32 (26.0) | 16 (5.1) | 16 (13.0) | |||
SGA-3 | 19 (15.4) | 9 (2.8) | 10 (8.1) | |||
SGA-2 | 12 (9.8) | 9 (2.8) | 3 (2.4) | |||
SGA-1 | 1 (0.8) | 0 (0.0) | 1 (0.2) |
Parameters | Risk Estimates a | p-Value | |
---|---|---|---|
Malnourished b | Crude RR | 1.82 (95%CI: 1.36, 2.44) | <0.001 |
Adj-RR | 1.33 (95% CI: 1.05, 1.69) | 0.019 | |
Every 1-point decrease in the 7-point SGA c | Crude RR | 1.18 (95%CI: 1.08, 1.30) | <0.001 |
Adj-RR | 1.08 (95% CI: 1.00, 1.16) | 0.039 |
Patient Characteristics (n = 363) | Standardized Beta Weight | 95% Confidence Interval | p-Value |
---|---|---|---|
Age (years) | −0.100 b | −0.105, 0.001 | 0.057 |
BMI (kg/m2) | 0.052 b | −0.072, 0.220 | 0.318 |
Admitted from the wards | 0.005 | −2.247, 2.479 | 0.923 |
No surgery | −0.200 | −1.875, 1.230 | 0.700 |
Charlson morbidity index | −0.100 b | −0.870, 0.011 | 0.056 |
LOS before ICU admission (days) | 0.001 b | −0.180, 0.182 | 0.063 |
APACHE II | −0.025 b | −0.140, 0.085 | 0.632 |
SOFA | 0.031 b | −0.175, 0.324 | 0.559 |
Predicted Mortality Risk (%) a | −0.042 b | −0.049, 0.020 | 0.424 |
Given vasoactives before ICU admission | 0.001 | −1.726, 1.745 | 0.991 |
Given CPR before ICU admission | 0.006 | −2.980, 3.364 | 0.905 |
Length of MV (days) | 0.068 b | −0.213, 5.825 | 0.068 |
Malnutrition | −0.015 | −2.245, 1.665 | 0.771 |
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Lew, C.C.H.; Wong, G.J.Y.; Cheung, K.P.; Chua, A.P.; Chong, M.F.F.; Miller, M. Association between Malnutrition and 28-Day Mortality and Intensive Care Length-of-Stay in the Critically ill: A Prospective Cohort Study. Nutrients 2018, 10, 10. https://doi.org/10.3390/nu10010010
Lew CCH, Wong GJY, Cheung KP, Chua AP, Chong MFF, Miller M. Association between Malnutrition and 28-Day Mortality and Intensive Care Length-of-Stay in the Critically ill: A Prospective Cohort Study. Nutrients. 2018; 10(1):10. https://doi.org/10.3390/nu10010010
Chicago/Turabian StyleLew, Charles Chin Han, Gabriel Jun Yung Wong, Ka Po Cheung, Ai Ping Chua, Mary Foong Fong Chong, and Michelle Miller. 2018. "Association between Malnutrition and 28-Day Mortality and Intensive Care Length-of-Stay in the Critically ill: A Prospective Cohort Study" Nutrients 10, no. 1: 10. https://doi.org/10.3390/nu10010010
APA StyleLew, C. C. H., Wong, G. J. Y., Cheung, K. P., Chua, A. P., Chong, M. F. F., & Miller, M. (2018). Association between Malnutrition and 28-Day Mortality and Intensive Care Length-of-Stay in the Critically ill: A Prospective Cohort Study. Nutrients, 10(1), 10. https://doi.org/10.3390/nu10010010