Acute Physiology and Chronic Health Evaluation II score for the assessment of mortality prediction in the intensive care unit: a single‐centre study from Iran

Abstract

Background: The Acute Physiology and Chronic Health Evaluation (APACHE) II is still commonly used as an index of illness severity in patients admitted to intensive care unit (ICU) and has been validated for many research and clinical audit purposes. Aims and objectives: To investigate the diagnostic value of the APACHE II score for predicting mortality rate of critically ill patients. Design: This was a single-centre, retrospective study of 200 Iranian patients admitted in the medical-surgical adult ICU from June 2012 to May 2013. Methods: Demographic data, pre-existing comorbidities and variables required for calculating the APACHE II score were recorded. Receiver operating characteristic (ROC) curves were constructed, and the area under the ROC curves was calculated to assess the predictive value of the APACHE II score. Results: Of the 200 patients with a mean age of 55⋅27 ± 21⋅59 years enrolled in the study, 112 (54%) were admitted in the medical ICU and 88 (46%) in the surgical ICU. Finally, 116 patients (58%) died, and 84 patients (42%) survived. The overall actual and predicted ICU mortality were 58% and 25⋅16%, respectively. The mean APACHE II score was 16⋅31 in total patients, 17⋅78 in medical ICU and 14⋅45 in surgical ICU patients (P = 0⋅003). Overall, the APACHE II score had the highest prognostic value for predicting the mortality rate of critically ill patients with an area under the cure of 0⋅88, and with a cut-off value of 15, the APACHE II score predicted mortality of patients with a sensitivity of 85⋅3%, a specificity of 77⋅4%, a positive predictive value of 83⋅9% and a negative predictive value of 73⋅9%. Conclusion: This study shows that an APACHE II score of 15 provides the best diagnostic accuracy to predict mortality of critically ill patients. Our observed mortality rate was greater than the predicted death rate, in comparison to the other prestigious centres in the world. Therefore, it appears that we must improve our intensive care to reduce mortality. Relevance to clinical practice: There is a need to create a suitable scoring system to predict the mortality rate of critically ill patients in accordance with the advanced technological equipment and experienced physicians and nurses in that ICU.

Factors Associated with In-Hospital Mortality after Continuous Renal Replacement Therapy for Critically Ill Patients: A Systematic Review and Meta-Analysis

“…This system consists of three components: Twelve physiological variables, the previous state of the patient's health, and their age [35]. The SOFA score is a simpler system and is usually used to assess the severity of multiple organ failure, including the respiratory, circulation, renal, neurologic, hepatogenic, and coagulation systems [36]. AKI is a common cause of complex multiple organ failure syndromes among ICU patients [37].…”

Sex differences in immune responses to SARS-CoV-2 in patients with COVID-19

“…Within the first 24 hours of patient admittance, the worst value for each physiological variable is calculated into an integer score from 0 to 71. Higher scores represent a more severe disease and a higher hospital mortality risk [25]. APACHE II can be Downloaded from http://portlandpress.com/bioscirep/article-pdf/doi/10.1042/BSR20202074/900629/bsr-2020-2074-t.pdf by guest on 28 December 2020 6 used to assess the severity of COVID-19 patients.…”

SOFA score is superior to APACHE-II score in predicting the prognosis of critically ill patients with acute kidney injury undergoing continuous renal replacement therapy

“…Currently available scoring systems such as acute physiology and chronic health evaluation (APACHE), Marshall method (MOF), and MOD score [10,11] are used to calculate the prediction values in ICU patients. APACHE-II is the most widely used; however, this score is not able to predict multiple organ failure [12]. The sequential organ failure assessment (SOFA) score was developed and used to describe multiple organ dysfunction using a limited number of routinely measured variables [13].…”