Acute and Critical Care

Original Articles

Nutrition
Comparison of mNUTRIC-S2 and mNUTRIC scores to assess nutritional risk and predict intensive care unit mortality: So Jeong Kim, Hong Yeul Lee, Sun Mi Choi, Sang-Min Lee, Jinwoo Lee; Acute Crit Care. 2022;37(4):618-626. Published online October 18, 2022; DOI: https://doi.org/10.4266/acc.2022.00612

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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.

Citations

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Association of malnutrition status with 30-day mortality in patients with sepsis using objective nutritional indices: a multicenter retrospective study
Moon Seong Baek, Young Suk Kwon, Sang Soo Kang, Daechul Shim, Youngsang Yoon, Jong Ho Kim
Acute and Critical Care.2024; 39(1): 127. CrossRef

Pulmonary
Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, 216 and MPM₀ III: Mihye Ko, Miyoung Shim, Sang-Min Lee, Yujin Kim, Soyoung Yoon; Acute Crit Care. 2018;33(4):216-221. Published online November 21, 2018; DOI: https://doi.org/10.4266/acc.2018.00178

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Abstract PDF

Background
In this study, we analyze the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiology Score (SAPS) 3, and Mortality Probability Model (MPM)0 III in order to determine which system best implements data related to the severity of medical intensive care unit (ICU) patients.
Methods
The present study was a retrospective investigation analyzing the discrimination and calibration of APACHE II, APACHE IV, SAPS 3, and MPM0 III when used to evaluate medical ICU patients. Data were collected for 788 patients admitted to the ICU from January 1, 2015 to December 31, 2015. All patients were aged 18 years or older with ICU stays of at least 24 hours. The discrimination abilities of the three systems were evaluated using c-statistics, while calibration was evaluated by the Hosmer-Lemeshow test. A severity correction model was created using logistics regression analysis.
Results
For the APACHE IV, SAPS 3, MPM0 III, and APACHE II systems, the area under the receiver operating characteristic curves was 0.745 for APACHE IV, resulting in the highest discrimination among all four scoring systems. The value was 0.729 for APACHE II, 0.700 for SAP 3, and 0.670 for MPM0 III. All severity scoring systems showed good calibrations: APACHE II (chi-square, 12.540; P=0.129), APACHE IV (chi-square, 6.959; P=0.541), SAPS 3 (chi-square, 9.290; P=0.318), and MPM0 III (chi-square, 11.128; P=0.133).
Conclusions
APACHE IV provided the best discrimination and calibration abilities and was useful for quality assessment and predicting mortality in medical ICU patients.

Citations

Citations to this article as recorded by

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Martin J. Ryll, Aurelia Zodl, Toby N. Weingarten, Alejandro A. Rabinstein, David O. Warner, Darrell R. Schroeder, Juraj Sprung
Journal of Intensive Care Medicine.2024; 39(5): 455. CrossRef
Relationship between Patient Classification System and APACHE II Scores, and Mortality Prediction in a Surgical Intensive Care Unit
U Ri Go, Sung-Hyun Cho
Journal of Korean Academy of Nursing Administration.2024; 30(1): 67. CrossRef
Utilidad del uso del modelo MPM-II para predecir riesgo de mortalidad en comparación con SAPS-II en pacientes adultos en la unidad de cuidados intensivos
Perla Marlene Guzmán Ramírez
Acta Médica Grupo Ángeles.2023; 21(2): 115. CrossRef
Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU
Beth A. Davison, Christopher Edwards, Gad Cotter, Antoine Kimmoun, Étienne Gayat, Agnieszka Latosinska, Harald Mischak, Koji Takagi, Benjamin Deniau, Adrien Picod, Alexandre Mebazaa
Journal of Clinical Medicine.2023; 12(9): 3311. CrossRef
Effects of prior antiplatelet and/or nonsteroidal anti-inflammatory drug use on mortality in patients undergoing abdominal surgery for abdominal sepsis
Se Hun Kim, Ki Hoon Kim
Surgery.2023; 174(3): 611. CrossRef
Extracorporeal blood purification is associated with improvement in biochemical and clinical variables in the critically‐ill COVID‐19 patients
Vedran Premužić, Jakša Babel, Danilo Gardijan, Ivana Lapić, Rajka Gabelica, Zvonimir Ostojić, Marin Lozić, Gordana Pavliša, Maja Hrabak, Josip Knežević, Dunja Rogić, Slobodan Mihaljević
Therapeutic Apheresis and Dialysis.2022; 26(2): 316. CrossRef
Relation between red blood cell distribution width and acute kidney injury in patients with sepsis
Marina Larissa Vettorello Ramires, Manoela Fidelis Batista Leite, Daniel Zu Yow Lo, Leonardo Bonilla da Silveira, Leonardo José Rolim Ferraz, Andreia Pardini, Araci Massami Sakashita, Andrea Tiemi Kondo, Guilherme Benfatti Olivato, Marcelino de Souza Durã
Einstein (São Paulo).2022;[Epub] CrossRef
Prediction of hospital mortality in intensive care unit patients from clinical and laboratory data: A machine learning approach
Elena Caires Silveira, Soraya Mattos Pretti, Bruna Almeida Santos, Caio Fellipe Santos Corrêa, Leonardo Madureira Silva, Fabrício Freire de Melo
World Journal of Critical Care Medicine.2022; 11(5): 317. CrossRef
Reduction in the rate of mortality of moderate to severe COVID 19 infected patients with the use of remdesivir - A Tertiary Care Hospital-based retrospective observational study
Mahima Lakhanpal, Debpriya Sarkar, Ritesh Kumar, Isha Yadav
Anesthesia: Essays and Researches.2022; 16(3): 296. CrossRef
Phase Angle and Frailty are Important Prognostic Factors in Critically Ill Medical Patients: A Prospective Cohort Study
S.J. Ko, J. Cho, S.M. Choi, Y.S. Park, C.-H. Lee, S.-M. Lee, C.-G. Yoo, Y.W. Kim, Jinwoo Lee
The Journal of nutrition, health and aging.2021; 25(2): 218. CrossRef
The use of chest ultrasonography in suspected cases of COVID-19 in the emergency department
Enrico Allegorico, Carlo Buonerba, Giorgio Bosso, Antonio Pagano, Giovanni Porta, Claudia Serra, Pasquale Dolce, Valentina Minerva, Ferdinando Dello Vicario, Concetta Altruda, Paola Arbo, Teresa Russo, Chiara De Sio, Nicoletta Franco, Gianluca Ruffa, Cinz
Future Science OA.2021;[Epub] CrossRef
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Eduardo A. Trujillo Rivera, Anita K. Patel, James M. Chamberlain, T. Elizabeth Workman, Julia A. Heneghan, Douglas Redd, Hiroki Morizono, Dongkyu Kim, James E. Bost, Murray M. Pollack
Pediatric Critical Care Medicine.2021; 22(1): e33. CrossRef
Validation of the Acute Physiology and Chronic Health Evaluation (APACHE) II and IV Score in COVID-19 Patients
Jeroen Vandenbrande, Laurens Verbrugge, Liesbeth Bruckers, Laurien Geebelen, Ester Geerts, Ina Callebaut, Ine Gruyters, Liesbeth Heremans, Jasperina Dubois, Bjorn Stessel, Edward A Bittner
Critical Care Research and Practice.2021; 2021: 1. CrossRef
Relationship Between Mean Vancomycin Trough Concentration and Mortality in Critically Ill Patients: A Multicenter Retrospective Study
Yanli Hou, Jiajia Ren, Jiamei Li, Xuting Jin, Ya Gao, Ruohan Li, Jingjing Zhang, Xiaochuang Wang, Xinyu Li, Gang Wang
Frontiers in Pharmacology.2021;[Epub] CrossRef
Blood purification therapy with a hemodiafilter featuring enhanced adsorptive properties for cytokine removal in patients presenting COVID-19: a pilot study
Gianluca Villa, Stefano Romagnoli, Silvia De Rosa, Massimiliano Greco, Marco Resta, Diego Pomarè Montin, Federico Prato, Francesco Patera, Fiorenza Ferrari, Giuseppe Rotondo, Claudio Ronco
Critical Care.2020;[Epub] CrossRef

The Prognostic Utility of the Simplified Acute Physiology Score II (SAPS II) and the Sequential Organ Failure Assessment (SOFA) Score for Hemato-Oncology Patients Admitted to the Intensive Care Unit: Sunghoon Park, Won Jung Koh, Man Pyo Chung, Hojoong Kim, O Jung Kwon, Won Ki Kang, Chul Won Jung, Jin Seok Ahn, Gee Young Suh; Korean J Crit Care Med. 2009;24(1):4-10.; DOI: https://doi.org/10.4266/kjccm.2009.24.1.4

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Abstract PDF

BACKGROUND
The prognosis of hemato-oncology (HMO) patients admitted to the intensive care unit (ICU) is poor and predicting the mortality is important for decision making at the time of ICU admission and for administering aggressive treatment.
METHODS
We retrospectively reviewed 309 patients who were admitted to the medical ICU (MICU) at Samsung Medical Center from July in 2005 to June in 2006. We calculated their Simplified Acute Physiology Score II (SAPS II) and the Sequential Organ Failure Assessment (SOFA) score at the time of ICU admission and we investigated the relationship between the two scoring systems and the hospital mortality.
RESULTS
Among the 309 patients, the hospital mortality was 41.2%, and the mean SAPS II/SOFA score at ICU admission was 45.4 +/- 19.5/8.1 +/- 4.6. Seventy-nine (25.6%) patients had hemato-oncological diseases. Their hospital mortality was 65.8%, and the mean SAPS II/SOFA score at the time of ICU admission was 53.9 +/- 18.6/9.7 +/- 4.4, which was higher than that of the non-HMO patients (p = 0.00). The area under the receiver operating characteristic (ROC) curves for the SAPS II/SOFA score for predicting the mortality was 0.794 +/- 0.05/0.785 +/- 0.051 (p = 0.00/p = 0.00) for the HMO patients. There was no significant difference in discrimination ability between the two scoring systems (p > 0.05). None of the HMO patients with a SAPS II/SOFA score of 70/14 or higher survived.
CONCLUSIONS
Both the SAPS II and SOFA scores at the time of ICU admission were similarly effective for predicting the hospital mortality. The two scoring systems could be useful tools for decision making at the time of ICU admission and for administering aggressive treatment.

Citations

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Association of Peripheral Lymphocyte Subset with the Severity and Prognosis of Septic Shock
Jin Kyeong Park, Sang-Bum Hong, Chae-Man Lim, Younsuck Koh, Jin Won Huh
The Korean Journal of Critical Care Medicine.2011; 26(1): 13. CrossRef

Factors of Cardiopulmonary Resuscitation Outcome for In-hospital Adult Patients: In Byung Kim, Sang Won Chung, Dong Seok Moon, Ki Hyun Byun; Korean J Crit Care Med. 2007;22(2):83-90.

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Abstract PDF: BACKGROUND
The purpose of this study was to evaluate the factors of cardiopulmonary resuscitation (CPR) outcome for in-hospital adult patients, acquiring data with standardized reporting guideline of in-hospital cardiopulmonary resuscitation in Korea.
METHODS
All adult cardiac arrest patients from July 2004 to December 2006 in this general hospital were included. Their clinical spectrums were reviewed retrospectively using Utstein-style based template.
RESULTS
For the study time period, one hundred and forty-two patients underwent cardiac arrest in this hospital. 136 patients were performed CPR. Return of spontaneous circulation (ROSC) occurred in 42 cases, and 15 patients were survived to hospital discharge. A shorter CPR time and a lower Simplified Acute Physiology Score II (SAPS II) were significant for survivor to hospital discharge (p<0.01). Sex, age, and location in cardiac arrest were not attributed to survival to hospital discharge.
CONCLUSIONS
In-hospital CPR patients, the high rate of ROSC and survival to hospital discharge were associated to the cause of arrest, shorter time of CPR, and lesser severity of disease (SAPS II). This result can be a great implication of survivor from CPR in-hospital adult patients in Korea. Further evaluation with consistent data acquisition of CPR using Utstein-style would contribute to improve CPR practice and outcome.

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