scholarly journals Improvement of APACHE II score system for disease severity based on XGBoost algorithm

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yan Luo ◽  
Zhiyu Wang ◽  
Cong Wang
Keyword(s):  
Intensive Care ◽  
Hospital Mortality ◽  
Patient Outcomes ◽  
External Validation ◽  
Apache Ii ◽  
Validation Dataset ◽  
Apache Ii Score ◽  
Severity Scores ◽  
The Impact ◽  
Improve Patient

Abstract Background Prognostication is an essential tool for risk adjustment and decision making in the intensive care units (ICUs). In order to improve patient outcomes, we have been trying to develop a more effective model than Acute Physiology and Chronic Health Evaluation (APACHE) II to measure the severity of the patients in ICUs. The aim of the present study was to provide a mortality prediction model for ICUs patients, and to assess its performance relative to prediction based on the APACHE II scoring system. Methods We used the Medical Information Mart for Intensive Care version III (MIMIC-III) database to build our model. After comparing the APACHE II with 6 typical machine learning (ML) methods, the best performing model was screened for external validation on anther independent dataset. Performance measures were calculated using cross-validation to avoid making biased assessments. The primary outcome was hospital mortality. Finally, we used TreeSHAP algorithm to explain the variable relationships in the extreme gradient boosting algorithm (XGBoost) model. Results We picked out 14 variables with 24,777 cases to form our basic data set. When the variables were the same as those contained in the APACHE II, the accuracy of XGBoost (accuracy: 0.858) was higher than that of APACHE II (accuracy: 0.742) and other algorithms. In addition, it exhibited better calibration properties than other methods, the result in the area under the ROC curve (AUC: 0.76). we then expand the variable set by adding five new variables to improve the performance of our model. The accuracy, precision, recall, F1, and AUC of the XGBoost model increased, and were still higher than other models (0.866, 0.853, 0.870, 0.845, and 0.81, respectively). On the external validation dataset, the AUC was 0.79 and calibration properties were good. Conclusions As compared to conventional severity scores APACHE II, our XGBoost proposal offers improved performance for predicting hospital mortality in ICUs patients. Furthermore, the TreeSHAP can help to enhance the understanding of our model by providing detailed insights into the impact of different features on the disease risk. In sum, our model could help clinicians determine prognosis and improve patient outcomes.

Outcomes of Critically Ill Gynecological Cancer Patients Admitted to Intensive Care Unit

2012 ◽  
Vol 30 (1) ◽  
pp. 7-11 ◽  
Author(s):  
Silvio A. Ñamendys-Silva ◽  
María O. González-Herrera ◽  
Julia Texcocano-Becerra ◽  
Angel Herrera-Gómez
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Prognostic Factors ◽  
Mortality Rate ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Gynecological Cancer ◽  
Apache Ii ◽  
Apache Ii Score

Purpose: To assess the characteristics of critically ill patients with gynecological cancer, and to evaluate their prognosis. Methods: Fifty-two critically ill patients with gynecological cancer admitted to intensive care unit (ICU) were included. Univariate and multivariate logistic regressions were used to identify factors associated with hospital mortality. Results: Thirty-five patients (67.3%) had carcinoma of the cervix uteri and 11 (21.2%) had ovarian cancer. The mortality rate in the ICU was 17.3% (9 of 52) and hospital mortality rate were 23%(12 of 52). In the multivariate analysis, independent prognostic factors for hospital mortality were vasopressor use (odds ratio [OR] = 8.60, 95% confidence interval [CI] 2.05-36; P = .03) and the Acute Physiology and Chronic Health Evaluation (APACHE) II score (OR = 1.43, 95% CI 1.01-2.09; P = .048). Conclusions: The independent prognostic factors for hospital mortality were the need for vasopressors and the APACHE II score.

The Utility of Acute Physiology and Chronic Health Evaluation II Scores for Prediction of Mortality among Intensive Care Unit (ICU) and Non-ICU Patients with Methicillin-Resistant Staphylococcus aureus Bacteremia

2012 ◽  
Vol 33 (6) ◽  
pp. 558-564 ◽  
Author(s):  
Vanessa Stevens ◽  
Thomas P. Lodise ◽  
Brian Tsuji ◽  
Meagan Stringham ◽  
Jill Butterfield ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Staphylococcus Aureus ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Chronic Health Evaluation ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Health Evaluation ◽  
Icu Patients ◽  
Time Points

Objective.Bloodstream infections due to methicillin-resistant Staphylococcus aureus (MRSA) have been associated with significant risk of in-hospital mortality. The acute physiology and chronic health evaluation (APACHE) II score was developed and validated for use among intensive care unit (ICU) patients, but its utility among non-ICU patients is unknown. The aim of this study was to determine the ability of APACHE II to predict death at multiple time points among ICU and non-ICU patients with MRSA bacteremia.Design.Retrospective cohort study.Participants.Secondary analysis of data from 200 patients with MRSA bacteremia at 2 hospitals.Methods.Logistic regression models were constructed to predict overall in-hospital mortality and mortality at 48 hours, 7 days, 14 days, and 30 days using APACHE II scores separately in ICU and non-ICU patients. The performance of APACHE II scores was compared with age adjustment alone among all patients. Discriminatory ability was assessed using the c-statistic and was compared at each time point using X2 tests. Model calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test.Results.APACHE II was a significant predictor of death at all time points in both ICU and non-ICU patients. Discrimination was high in all models, with c-statistics ranging from 0.72 to 0.84, and was similar between ICU and non-ICU patients at all time points. APACHE II scores significantly improved the prediction of overall and 48-hour mortality compared with age adjustment alone.Conclusions.The APACHE II score may be a valid tool to control for confounding or for the prediction of death among ICU and non-ICU patients with MRSA bacteremia.

Glucose Disturbances and Atypical Antipsychotic Use in the Intensive Care Unit

2016 ◽  
Vol 29 (6) ◽  
pp. 534-538 ◽  
Author(s):  
Amy Bishara ◽  
Stephanie V. Phan ◽  
Henry N. Young ◽  
T. Vivian Liao
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Patient Outcomes ◽  
Atypical Antipsychotic ◽  
Atypical Antipsychotics ◽  
Apache Ii Score ◽  
Icu Patients ◽  
Acute Hyperglycemia ◽  
The Impact ◽  
Chronic Use

Purpose: Chronic use of atypical antipsychotics may lead to metabolic abnormalities including hyperglycemia. Although evidence supports acute hyperglycemic episodes associated with atypical antipsychotic use, the acute use of atypical antipsychotics in the intensive care unit (ICU) setting has not been studied. The purpose of this study is to evaluate the occurrence of hyperglycemia in ICU patients receiving newly prescribed atypical antipsychotic. Summary: Of the 273 patient charts reviewed, 50 patients were included in this study. Approximately 45% of patients experienced at least 1 hyperglycemic episode (blood glucose >180 mg/dL) after the initiation of an atypical antipsychotic in the ICU. Of the patients experiencing at least 1 hyperglycemic episode, 60% experienced multiple distinct hyperglycemic episodes. In this study, quetiapine was the most commonly used atypical antipsychotic, 19 (38%) patients were discharged from the ICU on the atypical antipsychotic, 6 (12%) patients died in the ICU, and 31 (62%) patients were treated with an antihyperglycemic agent. Logistic regression analysis showed that women and ICU patients with a higher Acute Physiology and Chronic Health Evaluation II (APACHE II) score were significantly more likely to have multiple hyperglycemic episodes. Conclusion: Patients admitted to the ICU and initiated on an atypical antipsychotic may develop hyperglycemia independent of other glucose-elevating factors. The direct correlation of these agents to resulting acute hyperglycemia is unknown. Further studies are needed to investigate the link between atypical antipsychotics and acute hyperglycemia and the clinical significance of the impact on patient outcomes.

scholarly journals Influence of time elapsed from end of emergency surgery until admission to intensive care unit, on Acute Physiology and Chronic Health Evaluation II (APACHE II) prediction and patient mortality rate

2005 ◽  
Vol 123 (4) ◽  
pp. 167-174 ◽  
Author(s):  
Paulo Antonio Chiavone ◽  
Samir Rasslan
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Mortality Rate ◽  
Length Of Stay ◽  
Hospital Mortality ◽  
Emergency Surgery ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Death Risk ◽  
Expected Mortality

CONTEXT AND OBJECTIVE: Patients are often admitted to intensive care units with delay in relation to when this service was indicated. The objective was to verify whether this delay influences hospital mortality, length of stay in the unit and hospital, and APACHE II prediction. DESIGN AND SETTING: Prospective and accuracy study, in intensive care unit of Santa Casa de São Paulo, a tertiary university hospital. METHODS: We evaluated all 94 patients admitted following emergency surgery, from August 2002 to July 2003. The variables studied were APACHE II, death risk, length of stay in the unit and hospital, and hospital mortality rate. The patients were divided into two groups according to the time elapsed between end of surgery and admission to the unit: up to 12 hours and over 12 hours. RESULTS: The groups were similar regarding gender, age, diagnosis, APACHE II score and hospital stay. The death risk factors were age, APACHE II and elapsed time (p < 0.02). The mortality rate for the over 12-hour group was higher (54% versus 26.1%; p = 0.018). For the over 12-hour group, observed mortality was higher than expected mortality (p = 0.015). For the up to 12-hour group, observed and expected mortality were similar (p = 0.288). CONCLUSION: APACHE II foresaw the mortality rate among patients that arrived faster to the intensive care unit, while the mortality rate was higher among those patients whose admission to the intensive care unit took longer.

scholarly journals Clostridioides difficile infections in the intensive care unit: a monocentric cohort study

Infection ◽  
2020 ◽  
Vol 48 (3) ◽  
pp. 421-427
Author(s):  
Rebeca Cruz Aguilar ◽  
Jon Salmanton-García ◽  
Jonathan Carney ◽  
Boris Böll ◽  
Matthias Kochanek ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Financial Burden ◽  
Apache Ii ◽  
University Hospital ◽  
Apache Ii Score ◽  
High Risk Population ◽  
Cure Rate ◽  
Clostridioides Difficile ◽  
Severity Scores

Abstract Introduction Patient-level data from Clostridioides difficile infections (CDI) treated in an intensive care setting is limited, despite the growing medical and financial burden of CDI. Methods We retrospectively analyzed data from 100 medical intensive care unit patients at the University Hospital Cologne with respect to demography, diagnostics, severity scores, treatment, and outcome. To analyze factors influencing response to treatment and death, a backward-stepwise multiple logistic regression model was applied. Results Patients had significant comorbidities including 26% being immunocompromised. The mean Charlson Comorbidity Index was 6.3 (10-year survival rate of 2.25%). At the time of diagnosis, the APACHE II was 17.4±6.3 (predicted mortality rate of 25%), and the ATLAS score was 5.2±1.9 (predicted cure rate of 75%). Overall, 47% of CDI cases were severe, 35% were complicated, and 23% were both. At least one concomitant antibiotic was given to 74% of patients. The cure rate after 10 and 90 days was 56% and 51%, respectively. Each unit increment in APACHE II score was associated with poorer treatment response (OR 0.931; 95% CI 0.872–0.995; p = 0.034). Age above 65 years was associated with death (OR 2.533; 95% CI 1.031–6.221; p = 0.043), and overall mortality at 90 days was 56%. Conclusions CDI affects a high-risk population, in whom predictive scoring tools are not accurate, and outcomes are poor despite intensive treatment. Further research in this field is warranted to improve prediction scoring and patient outcomes.

Prognostic factors for patients with lymphoma requiring intensive care

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 17519-17519
Author(s):  
A. Scheliga ◽  
F. M. Vieira ◽  
N. Spector ◽  
S. Romano ◽  
J. I. Salluh ◽  
...  
Keyword(s):  
Intensive Care ◽  
Hospital Mortality ◽  
Hodgkin’S Lymphoma ◽  
Male Gender ◽  
Apache Ii ◽  
Hodgkin's Lymphoma ◽  
Apache Ii Score ◽  
Non Hodgkin’S Lymphoma ◽  
Non Hodgkin's Lymphoma ◽  
Organ Failures

17519 Background: Prognosis of patients (pts) with hematological malignancies (HM) in the intensive care unit (ICU) seems to be improving, despite different biological behaviors and outcomes. The study of homogenous groups of pts might provide useful clinical insights. The aim of this study was to evaluate the outcomes of critically ill patients with lymphomas (CIPL). Methods: During 66 months, all consecutive CIPL admitted to an oncologic ICU were studied. Variables collected were: age, gender, performance status, type and status of lymphoma, neutropenia, infection at admission, use of mechanical ventilation (MV), the Acute Physiology and Chronic Health Evaluation (APACHE) II score, comorbidities and number of acute organ failures (AOF). Variables selected in the univariate analysis (p < 0.25) and those clinically relevant were entered in a multivariable logistic regression analysis [results expressed as odds-ratios (OR), 95% confidence interval (CI)]. The end-point was hospital mortality. Results: A total of 120 CIPL were studied. Mean age was 51 ± 20 years and 54% were males. APACHE II was 19 ± 7 points. Diagnoses were High Grade Non-Hodgkin’s Lymphoma (77.5%), Hodgkin’s disease (17.5%) and Low Grade Non-Hodgkin’s Lymphoma (5%). Reasons for ICU admission were severe sepsis (62%) and acute respiratory failure (22%). During ICU stay 90% pts received MV, 71% vasopressors and 27.5% dialysis. Twenty-three (19%) pts had neutropenia. End-of-life decisions were implemented in 31% pts and all of them died at the ICU. The ICU and hospital mortality rates were 53% and 67% respectively, with no difference among the groups of lymphomas (p = 0.877). Variables identified in the multivariate analysis were: age [OR = 1.03 (95% CI = 1.01–1.06)], male gender [3.72 (1.27–10.90)], uncontrolled disease [OR = 6.28 (1.80–21.95), for pts with newly diagnosed disease and OR = 5.33 (1.45–19.47), for those with recurrence/progression, sepsis [OR = 5.31 (1.62–17.37)] and AOF [OR = 2.35 (1.53–3.61)]. Conclusions: Higher age, male gender, the severity of organ failures, sepsis and disease status were the main adverse factors. Type of lymphoma and neutropenia had no impact in the outcome. The appropriate use of such easily available clinical characteristics may avoid forgoing intensive care for lymphoma pts with a chance of survival. No significant financial relationships to disclose.

Interrater Reliability of APACHE II Scores for Medical-Surgical Intensive Care Patients: A Prospective Blinded Study

2007 ◽  
Vol 16 (4) ◽  
pp. 378-383 ◽  
Author(s):  
Michelle E. Kho ◽  
Ellen McDonald ◽  
Paul W. Stratford ◽  
Deborah J. Cook
Keyword(s):  
Intensive Care ◽  
Interrater Reliability ◽  
Intraclass Correlation ◽  
Illness Severity ◽  
Apache Ii ◽  
Surgical Intensive Care Unit ◽  
Apache Ii Score ◽  
Surgical Intensive Care ◽  
Chronic Health ◽  
Severity Scores

Background Despite widespread use of the Acute Physiology and Chronic Health Evaluation II (APACHE II), its interrater reliability has not been well studied. Objective To determine interrater reliability of APACHE II scores among 1 intensive care nurse and 2 research clerks. Methods In a prospective, blinded, observational study, 3 raters collected APACHE II scores on 37 consecutive patients in a medical-surgical intensive care unit. One research clerk was blinded to the study’s start date to minimize observer bias. The nurse and the other research clerk were blinded to each other’s scores and did not communicate with the first research clerk about the study. The data analyst was blinded to the identity and source of all 3 raters’ scores. Intraclass correlation coefficients and 95% confidence intervals were assessed. Results Mean (standard deviation) APACHE II scores were 21.8 (9.2) for the nurse, 20.4 (7.7) for research clerk 1, and 20.5 (8.1) for research clerk 2. Among the 3 raters, the intraclass correlation coefficient (95% confidence interval) was 0.90 (0.84, 0.94) for the APACHE II total score. Within APACHE II score components, the highest reliability was for age (0.98 [0.97, 0.99]), with lower reliabilities for the Chronic Health Index (0.64 [0.50, 0.80]) and the verbal component of the Glasgow Coma Scale (0.40 [0.20, 0.60]). Results were similar between pairs of raters. Conclusions Use of trained nonmedical personnel to collect illness severity scores for clinical, research, and administrative purposes is reasonable. This method could be used to assess reliability of other illness severity scores.

scholarly journals Why the surgical patients are so critical in their intensive care unit arrival?

2013 ◽  
Vol 28 (suppl 1) ◽  
pp. 48-53 ◽  
Author(s):  
Anibal Basile-Filho ◽  
Mayra Gonçalves Menegueti ◽  
Maria Auxiliadora-Martins ◽  
Edson Antonio Nicolini
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Negative Impact ◽  
Survival Rates ◽  
Severity Of Illness ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Death Risk ◽  
Icu Transfer ◽  
The Impact

PURPOSE: To assess the ability of the Acute Physiology and Chronic Health Evaluation II (APACHE II) to stratify the severity of illness and the impact of delay transfer to an Intensive Care Unit (ICU) on the mortality of surgical critically ill patients. METHODS: Five hundred and twenty-nine patients (60.3% males and 39.7% females; mean age of 52.8 ± 18.5 years) admitted to the ICU were retrospectively studied. The patients were divided into survivors (n=365) and nonsurvivors (n=164). APACHE II and death risk were analysed by generation of receiver operating characteristic (ROC) curves. The interval time between referral and ICU arrival was also registered. The level of significance was 0.05. RESULTS: The mean APACHE II and death risk was 19.9 ± 9.6 and 37.7 ± 28.9%, respectively. The area under the ROC curve for APACHE II and death risk was 0.825 (CI = 0.765-0.875) and 0.803 (CI = 0.741-0.856). The overall mortality (31%) increased progressively with the delay time to ICU transfer, as also evidencied by the APACHE II score and death risk. CONCLUSION: This investigation shows that the longer patients wait for ICU transfer the higher is their criticallity upon ICU arrival, with an obvious negative impact on survival rates.

scholarly journals Impact of Intensive Care Unit Readmissions on Patient Outcomes and the Evaluation of the National Early Warning Score to Prevent Readmissions: Literature Review

10.2196/13782 ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. e13782
Author(s):  
Heidi Mcneill ◽  
Saif Khairat
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Literature Review ◽  
Hospital Mortality ◽  
Patient Outcomes ◽  
Early Warning ◽  
Early Warning Score ◽  
Risk Stratification Tool ◽  
National Early Warning Score ◽  
The Impact

Background Intensive care unit (ICU) readmissions have been shown to increase a patient’s in-hospital mortality and length of stay (LOS). Despite this, no methods have been set in place to prevent readmissions from occurring. Objective The aim of this literature review was to evaluate the impact of ICU readmission on patient outcomes and to evaluate the effect of using a risk stratification tool, the National Early Warning Score (NEWS), on ICU readmissions. Methods A database search was performed on PubMed, Cumulative Index of Nursing and Allied Health Literature, Google Scholar, and ProQuest. In the initial search, 2028 articles were retrieved; after inclusion and exclusion criteria were applied, 12 articles were ultimately used in this literature review. Results This literature review found that patients readmitted to the ICU have an increased mortality rate and LOS at the hospital. The sample sizes in the reviewed studies ranged from 158 to 745,187 patients. Readmissions were most commonly associated with respiratory issues about 18% to 59% of the time. The NEWS has been shown to detect early clinical deterioration in a patient within 24 hours of transfer, with a 95% CI of 0.89 to 0.94 (P<.001), a sensitivity of 93.6% , and a specificity of 82.2%. Conclusions ICU readmissions are associated with worse patient outcomes, including hospital mortality and increased LOS. Without the use of an objective screening tool, the provider has been solely responsible for the decision of patient transfer. Assessment with the NEWS could be helpful in decreasing the frequency of inappropriate transfers and ultimately ICU readmission.

scholarly journals Impact of Intensive Care Unit Readmissions on Patient Outcomes and the Evaluation of the National Early Warning Score to Prevent Readmissions: Literature Review (Preprint)

2019 ◽  
Author(s):  
Heidi Mcneill ◽  
Saif Khairat
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Literature Review ◽  
Hospital Mortality ◽  
Patient Outcomes ◽  
Early Warning ◽  
Early Warning Score ◽  
Risk Stratification Tool ◽  
National Early Warning Score ◽  
The Impact

BACKGROUND Intensive care unit (ICU) readmissions have been shown to increase a patient’s in-hospital mortality and length of stay (LOS). Despite this, no methods have been set in place to prevent readmissions from occurring. OBJECTIVE The aim of this literature review was to evaluate the impact of ICU readmission on patient outcomes and to evaluate the effect of using a risk stratification tool, the National Early Warning Score (NEWS), on ICU readmissions. METHODS A database search was performed on PubMed, Cumulative Index of Nursing and Allied Health Literature, Google Scholar, and ProQuest. In the initial search, 2028 articles were retrieved; after inclusion and exclusion criteria were applied, 12 articles were ultimately used in this literature review. RESULTS This literature review found that patients readmitted to the ICU have an increased mortality rate and LOS at the hospital. The sample sizes in the reviewed studies ranged from 158 to 745,187 patients. Readmissions were most commonly associated with respiratory issues about 18% to 59% of the time. The NEWS has been shown to detect early clinical deterioration in a patient within 24 hours of transfer, with a 95% CI of 0.89 to 0.94 (<i>P</i>&lt;.001), a sensitivity of 93.6% , and a specificity of 82.2%. CONCLUSIONS ICU readmissions are associated with worse patient outcomes, including hospital mortality and increased LOS. Without the use of an objective screening tool, the provider has been solely responsible for the decision of patient transfer. Assessment with the NEWS could be helpful in decreasing the frequency of inappropriate transfers and ultimately ICU readmission.

Sign in / Sign up

Export Citation Format

Share Document