Acute and Critical Care

Original Articles

Nephrology
Epidemiology and outcome of an acute kidney injuries in the polytrauma victims admitted at the apex trauma center in Dubai: Bhushan Sudhakar Wankhade, Zeyad Faoor Alrais, Ghaya Zeyad Alrais, Ammar Mohamed Abdel Hadi, Gopala Arun Kumar Naidu, Mohammed Shahid Abbas, Ahmed Tarek Youssef Aboul Kheir, Hasan Hadad, Sundareswaran Sharma, Mohammad Sait; Acute Crit Care. 2023;38(2):217-225. Published online May 25, 2023; DOI: https://doi.org/10.4266/acc.2023.00388

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Abstract PDF: Background
Polytrauma from road accidents is a common cause of hospital admissions and deaths, frequently leading to acute kidney injury (AKI) and impacting patient outcomes. Methods: This retrospective, single-center study included polytrauma victims with an Injury Severity Score (ISS) >25 at a tertiary healthcare center in Dubai. Results: The incidence of AKI in polytrauma victims is 30.5%, associated with higher Carlson comorbidity index (P=0.021) and ISS (P=0.001). Logistic regression shows a significant relationship between ISS and AKI (odds ratio [OR], 1.191; 95% confidence interval [CI], 1.150–1.233; P<0.05). The main causes of trauma-induced AKI are hemorrhagic shock (P=0.001), need for massive transfusion (P<0.001), rhabdomyolysis (P=0.001), and abdominal compartment syndrome (ACS; P<0.001). On multivariate logistic regression AKI can be predicated by higher ISS (OR, 1.08; 95% CI, 1.00–1.17; P=0.05) and low mixed venous oxygen saturation (OR, 1.13; 95% CI, 1.05–1.22; P<0.001). The development of AKI after polytrauma increases length of stay (LOS)-hospital (P=0.006), LOS-intensive care unit (ICU; P=0.003), need for mechanical ventilation (MV) (P<0.001), ventilator days (P=0.001), and mortality (P<0.001). Conclusions: After polytrauma, the occurrence of AKI leads to prolonged hospital and ICU stays, increased need for mechanical ventilation, more ventilator days, and a higher mortality rate. AKI could significantly impact their prognosis.

Epidemiology
Risk factors for hospital mortality in intensive care unit survivors: a retrospective cohort study: Luiza Gabriella Antonio e Silva, Claudia Maria Dantas de Maio Carrilho, Thalita Bento Talizin, Lucienne Tibery Queiroz Cardoso, Edson Lopes Lavado, Cintia Magalhães Carvalho Grion; Acute Crit Care. 2023;38(1):68-75. Published online February 27, 2023; DOI: https://doi.org/10.4266/acc.2022.01375

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Background
Deaths can occur after a patient has survived treatment for a serious illness in an intensive care unit (ICU). Mortality rates after leaving the ICU can be considered indicators of health care quality. This study aims to describe risk factors and mortality of surviving patients discharged from an ICU in a university hospital. Methods: Retrospective cohort study carried out from January 2017 to December 2018. Data on age, sex, length of hospital stay, diagnosis on admission to the ICU, hospital discharge outcome, presence of infection, and Simplified Acute Physiology Score (SAPS) III prognostic score were collected. Infected patients were considered as those being treated for an infection on discharge from the ICU. Patients were divided into survivors and non-survivors on leaving the hospital. The association between the studied variables was performed using the logistic regression model. Results: A total of 1,025 patients who survived hospitalization in the ICU were analyzed, of which 212 (20.7%) died after leaving the ICU. When separating the groups of survivors and non-survivors according to hospital outcome, the median age was higher among non-survivors. Longer hospital stays and higher SAPS III values were observed among non-survivors. In the logistic regression, the variables age, length of hospital stay, SAPS III, presence of infection, and readmission to the ICU were associated with hospital mortality. Conclusions: Infection on ICU discharge, ICU readmission, age, length of hospital stay, and SAPS III increased risk of death in ICU survivors.

Citations

Citations to this article as recorded by

Analysis of the infectious agent’s structure and antibiotic resistance parameters in patients in intensive care units of a multidisciplinary hospital
O. I. Butranova, S. K. Zyryanov, A. A. Gorbacheva, G A. Putsman
Kachestvennaya Klinicheskaya Praktika = Good Clinical Practice.2024; (4): 4. CrossRef
Interpretability-based machine learning for predicting the risk of death from pulmonary inflammation in Chinese intensive care unit patients
Yihai Zhai, Danxiu Lan, Siying Lv, Liqin Mo
Frontiers in Medicine.2024;[Epub] CrossRef

Pediatrics
Clinical implications of discrepancies in predicting pediatric mortality between Pediatric Index of Mortality 3 and Pediatric Logistic Organ Dysfunction-2: Eui Jun Lee, Bongjin Lee, You Sun Kim, Yu Hyeon Choi, Young Ho Kwak, June Dong Park; Acute Crit Care. 2022;37(3):454-461. Published online July 29, 2022; DOI: https://doi.org/10.4266/acc.2021.01480

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Abstract PDF

Background
Pediatric Index of Mortality 3 (PIM 3) and Pediatric Logistic Organ Dysfunction-2 (PELOD-2) are validated tools for predicting mortality in children. Research suggests that these tools may have different predictive performance depending on patient group characteristics. Therefore, we designed this study to identify the factors that make the mortality rates predicted by the tools different.
Methods
This retrospective study included patients (<18 years) who were admitted to a pediatric intensive care unit from July 2017 to May 2019. After defining the predicted mortality of PIM 3 minus the predicted mortality rate of PELOD-2 as “difference in mortality prediction,” the clinical characteristics significantly related to this were analyzed using multivariable regression analysis. Predictive performance was analyzed through the Hosmer-Lemeshow test and area under the receiver operating characteristic curve (AUROC).
Results
In total, 945 patients (median [interquartile range] age, 3.0 [0.0–8.0] years; girls, 44.7%) were analyzed. The Hosmer-Lemeshow test revealed AUROCs of 0.889 (χ2=10.187, P=0.313) and 0.731 (χ2=6.220, P=0.183) of PIM 3 and PELOD-2, respectively. Multivariable linear regression analysis revealed that oxygen saturation, partial pressure of CO2, base excess, platelet counts, and blood urea nitrogen levels were significant factors. Patient condition-related factors such as cardiac bypass surgery, seizures, cardiomyopathy or myocarditis, necrotizing enterocolitis, cardiac arrest, leukemia or lymphoma after the first induction, bone marrow transplantation, and liver failure were significantly related (P<0.001).
Conclusions
Both tools predicted observed mortality well; however, caution is needed in interpretation as they may show different prediction results in relation to specific clinical characteristics.

Citations

Citations to this article as recorded by

COMPARISON OF PEDIATRIC INDEX OF MORTALITY (PIM)-3 AND PEDIATRIC SEQUENTIAL ORGAN FAILURE ASSESSMENT (pSOFA) SCORES TO PREDICT MORTALITY IN PEDIATRIC INTENSIVE CARE UNIT
ANKIT KUMAR PAWAR, GAURAV KUMAR PRAJAPATI, KANCHAN CHOUBEY, RASHMI RANDA
Asian Journal of Pharmaceutical and Clinical Research.2024; : 81. 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

Predicting Hospital Survival in Patients Admitted to ICU with Pulmonary Embolism
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
Criticality: A New Concept of Severity of Illness for Hospitalized Children
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

Review

Basic science and research
The Role of Oliguria and the Absence of Fluid Administration and Balance Information in Illness Severity Scores: Neil J. Glassford, Rinaldo Bellomo; Korean J Crit Care Med. 2017;32(2):106-123. Published online May 31, 2017; DOI: https://doi.org/10.4266/kjccm.2017.00192

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Abstract PDF

Urinary examination has formed part of patient assessment since the earliest days of medicine. Current definitions of oliguria are essentially arbitrary, but duration and intensity of oliguria have been associated with an increased risk of mortality, and this risk is not completely attributable to the development of concomitant acute kidney injury (AKI) as defined by changes in serum creatinine concentration. The increased risk of death associated with the development of AKI itself may be modified by directly or indirectly by progressive fluid accumulation, due to reduced elimination and increased fluid administration. None of the currently extant major illness severity scoring systems or outcome prediction models use modern definitions of AKI or oliguria, or any values representative of fluid volumes variables. Even if a direct relationship with mortality is not observed, then it is possible that fluid balance or fluid volume variables mediate the relationship between illness severity and mortality in the renal and respiratory physiological domains. Fluid administration and fluid balance may then be an important, easily modifiable therapeutic target for future investigation. These relationships require exploration in large datasets before being prospectively validated in groups of critically ill patients from differing jurisdictions to improve prognostication and mortality prediction.

Citations

Citations to this article as recorded by

Management of oliguria
Marlies Ostermann, Andrew D. Shaw, Michael Joannidis
Intensive Care Medicine.2023; 49(1): 103. CrossRef
Nomenclature and diagnostic criteria for acute kidney injury – 2020 consensus of the Taiwan AKI-task force
Shao-Yu Yang, Terry Ting-Yu Chiou, Chih-Chung Shiao, Hugo You-Hsien Lin, Ming-Jen Chan, Che-Hsiung Wu, Chiao-Yin Sun, Wei-Jie Wang, Yen-Ta Huang, Vin-Cent Wu, Yung-Chang Chen, Ji-Tsung Fang, Shang-Jyh Hwang, Heng-Chih Pan
Journal of the Formosan Medical Association.2022; 121(4): 749. CrossRef
Haemodynamic frailty – A risk factor for acute kidney injury in the elderly
Neil G. Docherty, Christian Delles, Patrick D’Haese, Anita T. Layton, Carlos Martínez-Salgado, Benjamin A. Vervaet, Francisco J. López-Hernández
Ageing Research Reviews.2021; 70: 101408. CrossRef
Does Fluid Type and Amount Affect Kidney Function in Critical Illness?
Neil J. Glassford, Rinaldo Bellomo
Critical Care Clinics.2018; 34(2): 279. CrossRef

Original Articles

Nursing
The Inter-Rater Reliability of Simplified Acute Physiology Score 3 (SAPS3) among Intensive Care Unit Nurses: Jun Hyun Kim, Ji Yeon Kim, Wonil Kim, Kyung Woo Kim, Sang-il Lee, Kyung-Tae Kim, Jang Su Park, Won Joo Choe, Jung Won Kim; Korean J Crit Care Med. 2015;30(1):8-12. Published online February 28, 2015; DOI: https://doi.org/10.4266/kjccm.2015.30.1.8

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Abstract PDF: Background
Simplified acute physiology score 3 (SAPS3) was developed in 2005 to evaluate intensive care unit (ICU) performance and to predict patient mortality or disease severity. The score is usually calculated by doctors, but it requires substantial human resources. And many nurse-lead studies use this scoring system. In the present study, we examined the inter-rater reliability of SAPS3 among nurses in an ICU. Methods: Five ICU nurses who worked in an ICU for a mean length of 7.8 years were educated for 2 hours about SAPS3 score and its components. Each nurse scored 26 patients, and the intraclass correlation coefficient (ICC) of the total scores and each subset were evaluated. Results: The ICC (95% confidence interval) of SAPS3 score was 0.89 (0.82-0.95), that of subset I was 0.90 (0.82-0.95), subset II was 0.54 (0.35-0.73), and subset III was 0.95 (0.91-0.97). The ICC of predicted mortality was 0.91 (0.85-0.96). Conclusions: The ICC of SAPS3 score and predicted mortality among ICU nurses were reliable. According to these ICC values, SAPS3 score is a reliable scale to be used by nurses. The ICC of subset II was lower than those of the other subsets, suggesting that education of SAPS3 should focus on the definition of each subset II component.

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; Korean J Crit Care Med. 2011;26(1):13-17.; DOI: https://doi.org/10.4266/kjccm.2011.26.1.13

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Abstract PDF: BACKGROUND
A dramatic decrease in circulating lymphocyte number is observed after septic shock. In this study, we assessed whether circulating lymphocyte subpopulations influence the severity and prognosis of septic shock.
METHODS
133 patients (median 65 years, range 27-88; male 63.2%) receiving intensive care for septic shock were enrolled in this study. Flow cytometry phenotyping of circulating lymphocyte subpopulations, including helper T cells, suppressor T cells, total B cells, and natural killer (NK) cells, was performed within 24 hours after the diagnosis of septic shock. After measuring the white blood cell (WBC) and differential leukocyte count, the lymphocyte subsets were analyzed. The following data were recorded: general characteristics, severity of illness as assessed by the Sequential Organ Failure Assessment (SOFA) score, and 28-day mortality.
RESULTS
The overall mortality rate at 28 days was 33.8%. SOFA score was negatively correlated with the T cell count (r = -0.175) and helper T cell count (r = -0.223). However, only low a helper T cell count was associated with the severity of septic shock (odds ratio 0.995, 95% confidence interval 0.992-0.999, p = 0.014). Using multiple logistic regression analysis for 28-day mortality, there was no significant prognostic factor among the lymphocyte subset.
CONCLUSIONS
The low helper T cell count appeared to be associated with severity, but did not show significant association with mortality.

Severe Health-care Associated Pneumonia among the Solid Cancer Patients on Chemotherapy: Maeng Real Park, So Young Park, Kyeongman Jeon, Won Jung Koh, Man Pyo Chung, Hojoong Kim, O Jung Kwon, Gee Young Suh, Jin Seok Ahn, Myung Ju Ahn, Ho Yeong Lim; Korean J Crit Care Med. 2009;24(3):140-144.; DOI: https://doi.org/10.4266/kjccm.2009.24.3.140

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Abstract PDF: BACKGROUND
There are only inadequate studies on the characteristics of severe pneumonia in the patients who have solid cancer and who are treated with cytotoxic chemotherapy and also on the usefulness of the various severity index scores.
METHODS
We retrospectively reviewed 31 patients who were treated with cytotoxic chemotherapy because of solid cancer and who were admitted to the medical ICU at Samsung Medical Center from April 2007 to August 2008.
RESULTS
The median age of the 31 patients was 64 years old (34-79). The types of solid cancer were lung cancer (19, 61.3%), gastroesophageal cancer (4, 12.9%), breast cancer (2, 6.5%), liver cancer (1, 3.2%), ovarian cancer (1, 3.2%) and other types of cancer (4, 12.9%). The hospital mortality rate was 64.5%. We were able to determine the pathogen of 19 (61.3%) patients; S. pneumoniae (6), S. aureus (3), Candida species (3), P. aeruginosa (2), K. pneumoniae (1), Pneumocystis jiroveci (1) and others (3). There were no statistically differences of the laboratory data and severity index scores (PSI, CURB-65, APACHE II, SOFA, SAPS 3) between the survivors and nonsurvivors, except the P/F ratio.
CONCLUSIONS
The hospital mortality rate of severe pneumonia in patients who had solid cancer and who received cytotoxic chemotherapy was high. The major pathogen was S. pneumoniae. The severity indexes for general pneumonia were not useful to these patients.

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