본문 바로가기
KERD
논문KCI 등재

Comparison of mNUTRIC-S2 and mNUTRIC scores to assess nutritional risk and predict intensive care unit mortality

3

조회

0

다운로드

1

인용

0

참고문헌

키워드

초록

Background: Nutritional status is associated with mortality. The modified Nutrition Risk in the Critically Ill (mNUTRIC) score is one of the most commonly used nutritional risk assessment tools in intensive care units (ICUs). The purpose of this study was to compare the mortality predictive ability of the mNUTRIC score to that of the mNUTRIC-S2 score, which uses the Simplified Acute Physiology Score (SAPS) II instead of the Acute Physiology and Chronic Health Evaluation (APACHE) II.Methods: This retrospective cohort analysis included patients admitted to the ICU between January and September 2020. Each patient’s electronic medical records were reviewed. The model discrimination for predicting ICU mortality was assessed by the area under the receiver operating characteristic (ROC) curve, and a Cox regression model was performed to confirm the relationship between the groups and mortality.Results: In total, 220 patients were enrolled. The ROC curve for predicting ICU mortality was 0.64 for the mNUTRIC score versus 0.67 for the mNUTRIC-S2 score. The difference between the areas was 0.03 (95% confidence interval [CI], –0.01 to 0.06, P=0.09). Patients with mNUTRIC-S2 score ≥5 had a greater risk of ICU mortality (hazard ratio [HR], 3.64; 95% CI, 1.85–7.14; P<0.001); however, no such relationship was observed with mNUTRIC score (HR, 1.69; 95% CI, 0.62–4.62, P=0.31).Conclusions: The mNUTRIC-S2 score was significantly associated with ICU mortality. A cutoff score of 5 was selected as most appropriate.

Abstract

Background: Nutritional status is associated with mortality. The modified Nutrition Risk in the Critically Ill (mNUTRIC) score is one of the most commonly used nutritional risk assessment tools in intensive care units (ICUs). The purpose of this study was to compare the mortality predictive ability of the mNUTRIC score to that of the mNUTRIC-S2 score, which uses the Simplified Acute Physiology Score (SAPS) II instead of the Acute Physiology and Chronic Health Evaluation (APACHE) II.Methods: This retrospective cohort analysis included patients admitted to the ICU between January and September 2020. Each patient’s electronic medical records were reviewed. The model discrimination for predicting ICU mortality was assessed by the area under the receiver operating characteristic (ROC) curve, and a Cox regression model was performed to confirm the relationship between the groups and mortality.Results: In total, 220 patients were enrolled. The ROC curve for predicting ICU mortality was 0.64 for the mNUTRIC score versus 0.67 for the mNUTRIC-S2 score. The difference between the areas was 0.03 (95% confidence interval [CI], –0.01 to 0.06, P=0.09). Patients with mNUTRIC-S2 score ≥5 had a greater risk of ICU mortality (hazard ratio [HR], 3.64; 95% CI, 1.85–7.14; P<0.001); however, no such relationship was observed with mNUTRIC score (HR, 1.69; 95% CI, 0.62–4.62, P=0.31).Conclusions: The mNUTRIC-S2 score was significantly associated with ICU mortality. A cutoff score of 5 was selected as most appropriate.

참고문헌 (33)

  1. Villet S, "Negative impact of hypocaloric feeding and energy balance on clinical outcome in ICU patients", Clin Nutr, 24, pp.502~509 (2005)
  2. Doig GS, "Effect of evidence-based feeding guidelines on mortality of critically ill adults : a cluster randomized controlled trial", JAMA, 300, pp.2731~2741 (2008)
  3. Schneider SM, "Malnutrition is an independent factor associated with nosocomial infections", Br J Nutr, 92, pp.105~111 (2004)
  4. Kyle UG, "Is nutritional depletion by Nutritional Risk Index associated with increased length of hospital stay? : a population-based study", JPEN J Parenter Enteral Nutr, 28, pp.99~104 (2004)
  5. Giner M, "In 1995 a correlation between malnutrition and poor outcome in critically ill patients still exists", Nutrition, 12, pp.23~29 (1996)
  6. Mukhopadhyay A, "Association of modified NUTRIC score with 28-day mortality in critically ill patients", Clin Nutr, 36, pp.1143~1148 (2017)
  7. McClave SA, "Guidelines for the provision and assessment of nutrition support therapy in the adult critically ill patient: Society of Critical Care Medicine (SCCM) and American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.)", JPEN J Parenter Enteral Nutr, 40, pp.159~211 (2016)
  8. Heyland DK, "Identifying critically ill patients who benefit the most from nutrition therapy : the development and initial validation of a novel risk assessment tool", Crit Care, 15, pp.R268~ (2011)
  9. Rahman A, "Identifying critically-ill patients who will benefit most from nutritional therapy : further validation of the"modified NUTRIC"nutritional risk assessment tool", Clin Nutr, 35, pp.158~162 (2016)
  10. Knaus WA, "APACHE II : a severity of disease classification system", Crit Care Med, 13, pp.818~829 (1985)
  11. Moreno RP, "Is APACHE II a useful tool for clinical research?", Rev Bras Ter Intensiva, 29, pp.264~267 (2017)
  12. Seongwook Jeong, "Scoring Systems for the Patients of Intensive Care Unit", Acute and Critical Care, 33(2), pp.102~104 (2018), 대한중환자의학회[DOI]
  13. Harrison DA, "External validation of the Intensive Care National Audit & Research Centre(ICNARC)risk prediction model in critical care units in Scotland", BMC Anesthesiol, 14, pp.116~ (2014)
  14. 박영식, "농흉 후 발생한 기관기도 연화증 환자에서 기관기도 스텐트 치험 1예 -증례 보고-", Acute and Critical Care, 26(2), pp.105~109 (2011), 대한중환자의학회
  15. Sathe PM, "Assessment of performance and utility of mortality prediction models in a single Indian mixed tertiary intensive care unit", Int J Crit Illn Inj Sci, 4, pp.29~34 (2014)
  16. Schellongowski P, "Comparison of three severity scores for critically ill cancer patients", Intensive Care Med, 30, pp.430~436 (2004)
  17. Moreno R, "Outcome prediction in intensive care : results of a prospective, multicentre, Portuguese study", Intensive Care Med, 23, pp.177~186 (1997)
  18. Castella X, "A comparison of severity of illness scoring systems for intensive care unit patients : results of a multicenter, multinational study", Crit Care Med, 23, pp.1327~1335 (1995)
  19. Seol E, "Nutritional screening tool for in-hospital patients", J Clin Nutr, 8, pp.2~10 (2016)
  20. Poole D, "Comparison between SAPS II and SAPS 3 in predicting hospital mortality in a cohort of 103 Italian ICUs : is new always better?", Intensive Care Med, 38, pp.1280~1288 (2012)
  21. Jeong DH, "Comparison of accuracy of NUTRIC and modified NUTRIC scores in predicting 28-day mortality in patients with sepsis : a single center retrospective study", Nutrients, 10, pp.911~ (2018)
  22. Jung YT, "Association of inadequate caloric supplementation with 30-day mortality in critically ill postoperative patients with high modified NUTRIC score", Nutrients, 10, pp.1589~ (2018)
  23. Im KM, "Identification of ICU patients with high nutritional risk after abdominal surgery using modified NUTRIC score and the association of energy adequacy with 90-day mortality", Nutrients, 14, pp.946~ (2022)
  24. Jeong DH, "Relationship between nutrition intake and 28-day mortality using modified NUTRIC score in patients with sepsis", Nutrients, 11, pp.1906~ (2019)
  25. Kim Y, "Comparison of the impact of malnutrition by nutritional assessment and screening tools on operative morbidity after gastric cancer surgery", J Korean Soc Parenter Enter Nutr, 4, pp.7~15 (2011)
  26. 김윤, "영양검색도구에 의한 영양불량 위험도가 위암 수술 후 합병증 발생에 미치는 영향", Annals of Surgical Treatment and Research, 80(1), pp.1~9 (2011), 대한외과학회
  27. Lee ZY, "Initial development and validation of a novel nutrition risk, sarcopenia, and frailty assessment tool in mechanically ventilated critically ill patients : the NUTRIC-SF score", JPEN J Parenter Enteral Nutr, 46, pp.499~507 (2022)
  28. Toledo DO, "NUTRIC-S proposal : using SAPS 3 for mortality prediction in nutritional risk ICU patients", Clin Nutr Exp, 31, pp.19~27 (2020)
  29. Oliveira ML, "Complementarity of modified NUTRIC score with or without C-reactive protein and subjective global assessment in predicting mortality in critically ill patients", Rev Bras Ter Intensiva, 31, pp.490~496 (2019)
  30. Ugarte H, "Procalcitonin used as a marker of infection in the intensive care unit", Crit Care Med, 27, pp.498~504 (1999)
  31. Cattani A, "Nutritional risk in critically ill patients : how it is assessed, its prevalence and prognostic value : a systematic review", Nutr Rev, 78, pp.1052~1068 (2020)
  32. Kucuk B, "NUTRIC score is not superior to mNUTRIC score in prediction of mortality of COVID-19 patients", Int J Clin Pract, 2022, pp.1864776~ (2022)
  33. Zhang P, "Use of nutrition risk in critically ill(NUTRIC)scoring system for nutrition risk assessment and prognosis prediction in critically ill neurological patients : a prospective observational study", JPEN J Parenter Enteral Nutr, 45, pp.1032~1041 (2021)

관련 논문AI추천

Effect of a nutritional support protocol on enteral nutrition and clinical outcomes of critically ill patients: a retrospective cohort study김세빈, 김소연, 박희문, 윤호일, 임성윤, Cho Young-Jae, Kim Hyung-Sook대한중환자의학회 · Acute and Critical Care2022 · 제37권 제3호Association between nutritional risk scores and timing of endotracheal intubation in COVID-19-associated acute respiratory distress syndrome: a single-center cohort study in South Korea류완호, 이광하, 장효진대한중환자의학회 · Acute and Critical Care2025 · 제40권 제4호Effect of nutrition support team on 28-day mortality in Korean patients with acute respiratory failure구미현, 김정현, 김주혜, 박소현, 방지현, 이인한, 최유림대한중환자의학회 · Acute and Critical Care2025 · 제40권 제2호Effectiveness of a multidisciplinary team for nutrition support in a trauma intensive care unit문진실, 심홍진, 연현주, 오은석, 장지영, Kang Dae Ryong대한중환자의학회 · Acute and Critical Care2020 · 제35권 제3호중환자에서 질병 중증도와 영양 상태가 예후에 미치는 효과라세희, 신증수, 안서희, 이덕철, 임현선, 장철호대한중환자의학회 · Acute and Critical Care2012 · 제27권 제2호국내 6개 상급 종합전문병원 중환자실 입원환자의 영양집중지원 실태 조사김윤, 김선형, 김은미, 백희준, 신증수, 이송미, 이승민, 이호선, 장철호대한중환자의학회 · Acute and Critical Care2012 · 제27권 제3호

이 간행물의 다른 논문 (29건)