scholarly journals PERFORMANCE OF PROGNOSTIC SCORES IN AKI POPULATION IN ICU

2020 ◽  
pp. 1-4
Author(s):  
Jasmin das
Keyword(s):  
Hospital Mortality ◽  
Goodness Of Fit ◽  
Characteristic Curve ◽  
Prognostic Score ◽  
Apache Ii ◽  
Prognostic Scores ◽  
Apache Ii Score ◽  
P Value ◽  
Goodness Of Fit Test ◽  
Good For

Acute kidney injury in hospitalized patients is associated with high mortality rates and increased length of hospital stay. Prognostication of patients with AKI is of immense value in making decisions regarding the optimal type and intensity of treatment, patient selection, and clinical discussions on prognosis and in assessment of the quality of an ICU. Prognostic scores are comprised of relevant clinical and laboratory variables of patients associated to the clinical endpoint. There are limited studies that have evaluated which prognostic score may be used in patients with AKI. Studies have shown that APACHE II underestimates hospital mortality whereas AKI specific Liano score has better statistical correlation with mortality. Materials and methods: All patients admitted to the ICU fulfilling the inclusion criteria during the study period were recruited and evaluated for AKI by both RIFLE and AKI criteria. Prognostic scores, APACHE II and Liano were used in predicting hospital mortality. Assessment of score performance was made through analysis of the discrimination and calibration using area under a receiver operating characteristic curve (AUROC) and Hosmer and Lemeshow goodness of fit test. Results: Mean APACHE II score was higher in AKI subjects compared to non AKI and was statistically significant and it increased with the severity of AKI. The AUROC for APACHE II score was 0.739 and 0.706 for AKIN and RIFLE respectively and signifies APACHE II score increases with AKI. An AUROC curve of prognostic scores for predicting mortality was 0.677 and 0.639 for Liano and APACHE II respectively and on comparison showed insignificant p value (0.6331). Assessment of calibration showed that the calibration was good for specific score. Conclusion:Assessment of performance of both the prognostic scores APACHE II and Liano had poor discrimination but calibration was good for Liano model

scholarly journals Dynamic APACHE II Score to Predict Outcome Among Intensive Care Unit Patients

2021 ◽  
Author(s):  
Yao Tian ◽  
Yang YAO ◽  
Jing Zhou ◽  
Xin Diao ◽  
Hui Chen ◽  
...  
Keyword(s):  
Intensive Care ◽  
Hospital Mortality ◽  
Goodness Of Fit ◽  
Apache Ii ◽  
Secondary Outcome ◽  
Apache Ii Score ◽  
Optimal Timing ◽  
Goodness Of Fit Test ◽  
Icu Patients ◽  
Mimic Iii

Abstract Purpose: The Acute Physiology and Chronic Health Evaluation II (APACHE II) score is used to determine disease severity and predict outcomes in critically ill patients. However, there is no dynamic APACHE II score for predicting outcomes among ICU patients.The aim of this study is to explore the optimal timing to predict the outcomes of ICU patients by dynamically evaluating APACHE II score.Methods: Study data of demographics and comorbidities from the first 24 h after ICU admission were retrospectively extracted from MIMIC-III, a multiparameter intensive care database. The primary outcome was hospital mortality. 90-day mortality was a secondary outcome. APACHE II scores on days 1, 2, 3, 5, 7, 14 and 28 were compared using area under the receiver operating characteristic (AUROC) analysis. Hospital survival was visualised using Kaplan-Meier Curves.Results:A total of 6374 eligible subjects were extracted from the MIMIC-III. Mean APACHE II score on day 1 were 18.4±6.3, hospital and 90-day mortality was 19.1% and 25.8%, respectively.The optimal timing where predicted hospital mortality was on day 3 with an area under the cure of 0.666 (0.607-0.726)(P＜0.0001). The best tradeoff for preciction was found at 17 score, more than 17 score predicted mortality of non-survivors with a sensitivity of 92.8% and PPV of 23.1%. Hosmer-lemeshow goodness of fit test showed that APACHE II 3 has a good predictive calibration ability (X2 =6.198, P=0.625) and consistency of predicted death and actual death was 79.4%. The calibration of APACHE II 1 was poor (X2=294.898, P<0.001).Conclusions: APACHE II on 3 dayis the optimal prognostic marker and 17 score provided the best dignostic accuracy to predict outcomes for ICU patients. These finding will help medical make clinical judgment.

scholarly journals A transformation of oxygen saturation (the saturation virtual shunt) to improve clinical prediction model calibration and interpretation

2018 ◽  
Author(s):  
Guohai Zhou ◽  
Walter Karlen ◽  
Rollin Brant ◽  
Matthew Wiens ◽  
Niranjan Kissoon ◽  
...  
Keyword(s):  
Oxygen Saturation ◽  
Disease Severity ◽  
Goodness Of Fit ◽  
Prediction Models ◽  
Characteristic Curve ◽  
Approximation Formula ◽  
P Value ◽  
Clinical Prediction ◽  
Goodness Of Fit Test ◽  
Peripheral Oxygen Saturation

ABSTRACTBackgroundThe relationship between peripheral oxygen saturation (SpO2) and the inspired oxygen concentration is non-linear. SpO2 is frequently used as a dichotomized predictor, to manage this non-linearity. We propose the saturation virtual shunt (VS) as a transformation of SpO2 to a continuous linear variable to improve interpretation of disease severity within clinical prediction models.MethodWe calculate the saturation VS based on an empirically derived approximation formula between physiological VS and SpO2. We evaluated the utility of the saturation VS in a clinical study predicting the need for facility admission in children in a low resource health-care setting.ResultsThe transformation was saturation VS = 68.864*log10(103.711 − SpO2) −52.110. The ability to predict hospital admission based on a dichotomized SpO2 produced an area under the receiver operating characteristic curve of 0.57, compared to 0.71 based on the untransformed SpO2 and saturation VS. However, the untransformed SpO2 demonstrated a lack of fit compared to the saturation VS (goodness-of-fit test p-value <0.0001 versus 0.098). The observed admission rates varied non-linearly with the untransformed SpO2 but varied linearly with the saturation VS.ConclusionThe saturation VS estimates a continuous linearly interpretable disease severity based on SpO2 and improves clinical prediction.

scholarly journals Prognostic Value of Charlton’s Weighted Index of Capabilities Combined with Chronic Health Evaluation II Score in COVID-19：a retrospective cohort study

2020 ◽  
Author(s):  
Yali Qian ◽  
Zhuo Li ◽  
Ziqiang Du ◽  
Yanfang Zhu ◽  
Hongjun Miao
Keyword(s):  
Hospital Mortality ◽  
Characteristic Curve ◽  
Chronic Health Evaluation ◽  
Apache Ii ◽  
P Value ◽  
Health Evaluation ◽  
Joint Detection ◽  
Chronic Health ◽  
Weighted Index ◽  
Underlying Diseases

Abstract Background: Since December 2019, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread across the world. Age and underlying diseases have been reported as predictors of mortality in 2019-nCoV infection. Charlson's weighted index of comorbidities (WIC) and acute physiology and chronic health evaluation (APACHE) II are two frequently-used measures of comorbidity. In this study, we have assessed the performance of WIC and APACHE II in predicting the mortality of COVID-19 patients.Methods: A total of 76 adult patients with COVID-19 were admitted to a designated hospital in Huangshi province from 1 January 2020 to 29 February 2020. Clinical data including age, gender, underlying diseases, and hospital mortality were collected. The APACHE II and WIC scores were assessed within the first 24 hours of admission. Univariate and multiple logistic regression analyses were used to compare the performance of WIC, APACHE II, and joint detection. The area under the receiver operating characteristic curve (AUC) was used to predict the hospital mortality. Results: Of the 76 enrolled patients, 57 patients survived, and 19 died. The surviving patients had significantly lower WIC and APACHE II than the non-surviving patients (p-value < 0.05). The AUC for the hospital mortality was 0.814 (95% confidence interval (CI) 0.705-0.923) of WIC, 0.854 (95% CI 0.705-0.956) of APACHE II and 0.891(95% CI 0.830-0.966) for the joint detection. The diagnostic value of the joint detection was found to be better than that of WIC (p-value= 0.002) or APACHE II (p-value = 0.042). Conclusions: The WIC and APACHE II scores might serve as independent determinants for the hospital mortality associated with COVID-19 patients. The combined use of WIC and APACHE II is more predictive than individuals．

scholarly journals Impact of Operator Expertise on Collection of the APACHE II Score and on the Derived Risk of Death and Standardized Mortality Ratio

2005 ◽  
Vol 33 (5) ◽  
pp. 585-590 ◽  
Author(s):  
D. Ledoux ◽  
S. Finfer ◽  
S. Mckinley
Keyword(s):  
Goodness Of Fit ◽  
Characteristic Curve ◽  
Receiver Operator Characteristic Curve ◽  
Clinical Staff ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Standardized Mortality Ratio ◽  
Risk Of Death ◽  
Mortality Ratio ◽  
The Impact

We assessed the impact of operator expertise on collection of the APACHE II score, the derived risk of death and standardized mortality ratio in 465 consecutive patients admitted to a multi-disciplinary tertiary hospital ICU. Research coordinators and junior clinical staff independently collected the APACHE II variables; experts (senior clinical staff) rescored 20 % of the records. Agreement was moderate between junior clinical staff and research coordinators or senior clinical staff for most variables of the acute physiology score (weighted κ<0.6); agreement between research coordinators and senior clinical staff data collectors was good (weighted κ >0.75). The APACHE II score and its derived risk of death (ROD) were significantly lower using the junior clinical staff dataset compared to research coordinators and senior clinical staff (APACHE II score: 13.4±9.2 vs 16.8±8.5 vs 17.1±7.7, P<0.001; ROD: 14.7%±22.4% vs 21.6%±22.6% vs 20.8%±22.4%, P<0.01 respectively). The discriminative capacity was not altered by the lack of agreement (area under Receiver Operator Characteristic curve >0.8) but calibration of ROD from the junior clinical staff dataset was poor (Goodness-of-fit: P=0.001). The standardized mortality ratio (SMR) was higher with the junior clinical staff dataset (SMR: 1.22, 95% CI: 0.96-1.52 vs 0.87, 95% CI: 0.70-1.06 vs 0.76, 95% CI: 0.40-1.3 calculated from junior clinical staff, research coordinators and senior clinical staff data-sets respectively). We conclude that the expertise of data collectors significantly influences the APACHE II score, the derived risk of death and the standardized mortality ratio. Given the importance of such scores, ICUs should be provided with sufficient resources to train and employ dedicated data collectors.

scholarly journals Combining Sequential Organ Failure Assessment (SOFA) Score with Acute Physiology and Chronic Health Evaluation (APACHE) II Score to Predict Hospital Mortality of Critically Ill Patients

2007 ◽  
Vol 35 (4) ◽  
pp. 515-521 ◽  
Author(s):  
K. M. Ho
Keyword(s):  
Hospital Mortality ◽  
Critically Ill ◽  
Sofa Score ◽  
Critically Ill Patients ◽  
Characteristic Curve ◽  
Apache Ii ◽  
Brier Score ◽  
Apache Ii Score ◽  
Failure Assessment ◽  
Predict Hospital Mortality

The ability to accurately adjust for the severity of illness in outcome studies of critically ill patients is essential. Previous studies have showed that Sequential Organ Failure Assessment (SOFA) score and Acute Physiology and Chronic Health Evaluation (APACHE) II score can predict hospital mortality of critically ill patients. The effects of combining these two scores to predict hospital mortality of critically ill patients has not been evaluated. This cohort study evaluated the performance of combining the APACHE II score with SOFA score in predicting hospital mortality of critically ill patients. A total of 1,311 consecutive adult patients admitted to a tertiary 22-bed multidisciplinary intensive care unit (ICU) in Western Australia were considered. The APACHE II, Admission SOFA, Delta SOFA and maximum SOFA score were all related to hospital survival in the univariate analyses. Combining Max SOFA (area under receiver operating characteristic curve 0.875 vs. 0.858, P=0.014; Nagelkerke R2: 0.411 vs. 0.371; Brier Score: 0.086 vs. 0.090) or Delta SOFA score (area under receiver operating characteristic curve 0.874 vs. 0.858, P=0.003; Nagelkerke R2: 0.412 vs. 0.371; Brier Score: 0.086 vs. 0.090) with the APACHE II score improved the discrimination and overall performance of the predictions when compared with using the APACHE II score alone, especially in the emergency ICU admissions. Combining Max SOFA or Delta SOFA score with the APACHE II score may improve the accuracy of risk adjustment in outcome studies of critically ill patients.

Cohort study of the APACHE II score and mortality for different types of intensive care unit patients

2021 ◽  
pp. postgradmedj-2021-140376
Author(s):  
Veli Sungono ◽  
Hori Hariyanto ◽  
Tri Edhi Budhi Soesilo ◽  
Asri C Adisasmita ◽  
Syahrizal Syarif ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Goodness Of Fit ◽  
Characteristic Curve ◽  
Secondary Data ◽  
Apache Ii ◽  
Surgical Patients ◽  
Medical Emergency ◽  
Apache Ii Score ◽  
Icu Patients

ObjectivesFind the discriminant and calibration of APACHE II (Acute Physiology And Chronic Health Evaluation) score to predict mortality for different type of intensive care unit (ICU) patients.MethodsThis is a cohort retrospective study using secondary data of ICU patients admitted to Siloam Hospital of Lippo Village from 2014 to 2018 with minimum age ≥17 years. The analysis uses the receiver operating characteristic curve, student t-test and logistic regression to find significant variables needed to predict mortality.ResultsA total of 2181 ICU patients: men (55.52%) and women (44.48%) with an average age of 53.8 years old and length of stay 3.92 days were included in this study. Patients were admitted from medical emergency (30.5%), neurosurgical (52.1%) and surgical (17.4%) departments, with 10% of mortality proportion. Patients admitted from the medical emergency had the highest average APACHE score, 23.14±8.5, compared with patients admitted from neurosurgery 15.3±6.6 and surgical 15.8±6.8. The mortality rate of patients from medical emergency (24.5%) was higher than patients from neurosurgery (3.5%) or surgical (5.3%) departments. Area under curve of APACHE II score showed 0.8536 (95% CI 0.827 to 0.879). The goodness of fit Hosmer-Lemeshow show p=0.000 with all ICU patients’ mortality; p=0.641 with medical emergency, p=0.0001 with neurosurgical and p=0.000 with surgical patients.ConclusionAPACHE II has a good discriminant for predicting mortality among ICU patients in Siloam Hospital but poor calibration score. However, it demonstrates poor calibration in neurosurgical and surgical patients while demonstrating adequate calibration in medical emergency patients.

scholarly journals Feasibility of transitioning from APACHE II to SAPS III as prognostic model in a Brazilian general intensive care unit. A retrospective study

2014 ◽  
Vol 133 (3) ◽  
pp. 199-205 ◽  
Author(s):  
Ary Serpa Neto ◽  
Murillo Santucci Cesar de Assunção ◽  
Andréia Pardini ◽  
Eliézer Silva
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Retrospective Study ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Predictive Models ◽  
Critically Ill Patients ◽  
Goodness Of Fit ◽  
Apache Ii ◽  
Goodness Of Fit Test

CONTEXT AND OBJECTIVE: Prognostic models reflect the population characteristics of the countries from which they originate. Predictive models should be customized to fit the general population where they will be used. The aim here was to perform external validation on two predictive models and compare their performance in a mixed population of critically ill patients in Brazil.DESIGN AND SETTING: Retrospective study in a Brazilian general intensive care unit (ICU).METHODS: This was a retrospective review of all patients admitted to a 41-bed mixed ICU from August 2011 to September 2012. Calibration (assessed using the Hosmer-Lemeshow goodness-of-fit test) and discrimination (assessed using area under the curve) of APACHE II and SAPS III were compared. The standardized mortality ratio (SMR) was calculated by dividing the number of observed deaths by the number of expected deaths.RESULTS: A total of 3,333 ICU patients were enrolled. The Hosmer-Lemeshow goodness-of-fit test showed good calibration for all models in relation to hospital mortality. For in-hospital mortality there was a worse fit for APACHE II in clinical patients. Discrimination was better for SAPS III for in-ICU and in-hospital mortality (P = 0.042). The SMRs for the whole population were 0.27 (confidence interval [CI]: 0.23 - 0.33) for APACHE II and 0.28 (CI: 0.22 - 0.36) for SAPS III.CONCLUSIONS: In this group of critically ill patients, SAPS III was a better prognostic score, with higher discrimination and calibration power.

Comparative Prognostic Accuracy of Risk Prediction Models for Cardiogenic Shock

2019 ◽  
Vol 35 (12) ◽  
pp. 1513-1519
Author(s):  
Robert J. H. Miller ◽  
Danielle Southern ◽  
Stephen B. Wilton ◽  
Matthew T. James ◽  
Bryan Har ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Cardiogenic Shock ◽  
Prediction Models ◽  
Tertiary Care ◽  
Apache Ii ◽  
Risk Scores ◽  
Apache Ii Score ◽  
World Population ◽  
Goodness Of Fit Test ◽  
Prognostic Accuracy

Objectives: Despite advances in medical therapy, reperfusion, and mechanical support, cardiogenic shock remains associated with excess morbidity and mortality. Accurate risk stratification may improve patient management. We compared the accuracy of established risk scores for cardiogenic shock. Methods: Patients admitted to tertiary care center cardiac care units in the province of Alberta in 2015 were assessed for cardiogenic shock. The Acute Physiology and Chronic Health Evaluation-II (APACHE-II), CardShock, intra-aortic balloon pump (IABP) Shock II, and sepsis-related organ failure assessment (SOFA) risk scores were compared. Receiver operating characteristic curves were used to assess discrimination of in-hospital mortality and compared using DeLong’s method. Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test. Results: The study included 3021 patients, among whom 510 (16.9%) had cardiogenic shock. Patients with cardiogenic shock had longer median hospital stays (median 11.0 vs 4.1 days, P < .001) and were more likely to die (29.0% vs 2.5%, P < .001). All risk scores were adequately calibrated for predicting hospital morality except for the APACHE-II score (Hosmer-Lemeshow P < .001). Discrimination of in-hospital mortality with the APACHE-II (area under the curve [AUC]: 0.72, 95% confidence interval [CI]: 0.66-0.76) and IABP-Shock II (AUC: 0.73, 95% CI: 0.68-0.77) scores were similar, while the CardShock (AUC: 0.76, 95% CI: 0.72-0.81) and SOFA (AUC: 0.76, 95%CI: 0.72-0.81) scores had better discrimination for predicting in-hospital mortality. Conclusions: In a real-world population of patients with cardiogenic shock, existing risk scores had modest prognostic accuracy, with no clear superior score. Further investigation is required to improve the discriminative abilities of existing models or establish novel methods.

The Relationship of the ACCP/SCCM Consensus Conference Classification of Sepsis to Mortality and Multiorgan Dysfunction among Medical ICU Patients

1996 ◽  
Vol 11 (6) ◽  
pp. 326-334 ◽  
Author(s):  
Marin H. Kollef ◽  
Paul R. Eisenberg
Keyword(s):  
Septic Shock ◽  
Severe Sepsis ◽  
Hospital Mortality ◽  
Consensus Conference ◽  
Organ System ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Icu Patients ◽  
Multiorgan Dysfunction

To determine the relation between the proposed ACCP/SCCM Consensus Conference classification of sepsis and hospital outcomes, we conducted a single-center, prospective observational study at Barnes Hospital, St. Louis, MO, an academic tertiary care hospital. A total of 324 consecutive patients admitted to the medical intensive care unit (ICU) were studied for prospective patient surveillance and data collection. The main outcome measures were the number of acquired organ system derangements and hospital mortality. Fifty-seven (17.6%) patients died during the study period. The proposed classifications of sepsis (e.g., systemic inflammatory response syndrome [SIRS], sepsis, severe sepsis, septic shock) correlated with hospital mortality ( r = 0.330; p < 0.001) and development of an Organ System Failure Index (OSFI) of 3 or greater ( r = 0.426; p < 0.001). Independent determinants of hospital mortality for this patient cohort ( p < 0.05) were development of an OSFI of 3 or greater (adjusted odds ratio [AOR], 13.9; 95% confidence interval [CI], 6.4–30.2; p < 0.001); presence of severe sepsis or septic shock (AOR, 2.6; 95% CI, 1.2–5.6; p = 0.002), and an APACHE II score ≥ of 18 or greater (AOR, 2.4; 95% CI, 1.0–5.8; p = 0.045). Intra-abdominal infection (AOR, 19.1; 95% CI, 1.6–230.1; p = 0.011), an APACHE II score ≥ of 18 or greater (AOR, 8.9; 95% CI, 4.2–18.6; p < 0.001), and presence of severe sepsis or septic shock (AOR, 2.9; 95% CI, 1.5–5.4; p = 0.001) were independently associated with development of an OSFI of 3 or greater. These data confirm that acquired multiorgan dysfunction is the most important predictor of mortality among medical ICU patients. In addition, they identify the proposed ACCP/SCCM Consensus Conference classification of sepsis as an additional independent determinant of both hospital mortality and multiorgan dysfunction.

scholarly journals APHACHE Score as a Predictive Indices for Weanability from Mechanical Ventilation

2013 ◽  
Vol 1 (1) ◽  
pp. 18-22 ◽  
Author(s):  
Md Sayedul Islam
Keyword(s):  
Mechanical Ventilation ◽  
Respiratory Failure ◽  
Private Hospital ◽  
Total Duration ◽  
Apache Ii ◽  
Apache Ii Score ◽  
P Value ◽  
Apache Score ◽  
Number Of Patients ◽  
Weaning Outcome

Objective: To determine the significance of acute physiology and chronic health evaluation (APACHE) score as an important parameter of weaning outcome for mechanical ventilation. Design: prospective, observational. Setting: The medical ICU of a modernized private hospital, Dhaka. Method: The study was carried out during the period of 2008 to 2009 in a specialized private hospital Dhaka. Critical care physicians were asked to filled up the data sheets having detail problem of the patients including the APACHE II score. The APACHE II score is divided into three steps High score>25, Medium score 20-24 and Low score < 20. The clinicians were suggested to predict whether it would take < 3 days or 4to 7days or >8days to wean each patients from mechanical ventilation. The cause of respiratory failure and total duration of weaning were recorded. The significance was set at p<.05. Result: Total number of patients included in this study were 40. Male were 22 (55%) and female were 18 (45%), the mean age of the patients were 51.1±13.9. The most common cause of respiratory failure were COPD 11(24.5%) and next common were pneumonia and ARDS due to sepsis 8 (20%) each. Among the studied population 20 (50%) having low APACHE score (<20), 12 (30%) were medium score (20-24) and 8 (20%) patients were high score (>25). Total 25 (62.5%) of the patients were successfully weaned from mechanical ventilation, 10 (25%) of the patient died and 5 (12.5%) of the patent were shifted to other low cost hospital. The successfully weaned groups 17 (68%) had lower APACHE II score than the unsuccessfully (failure) group which were statistically significant ÷2 =.8546, df =2, p-value >.005. Conclusions: The overall severity of illness as assessed by APACHE II score correlates better with weaning outcome. DOI: http://dx.doi.org/10.3329/bccj.v1i1.14360 Bangladesh Crit Care J March 2013; 1: 18-22

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