Comparison of APACHE III, Charlson Comorbidity Index, and SOFA Score for Prediction of Mortality Following Acute Lung Injury

CHEST Journal ◽  
2012 ◽  
Vol 142 (4) ◽  
pp. 301A
Author(s):  
Balwinder Singh ◽  
Adil Ahmed ◽  
Michelle Biehl ◽  
Pablo Franco ◽  
Guangxi Li
Keyword(s):  
Acute Lung Injury ◽  
Lung Injury ◽  
Sofa Score ◽  
Charlson Comorbidity Index ◽  
Prediction Of Mortality ◽  
Apache Iii ◽  
Comorbidity Index

PREDICTION OF MORTALITY FOLLOWING RADICAL PROSTATECTOMY BY CHARLSON COMORBIDITY INDEX

2008 ◽  
Vol 179 (4S) ◽  
pp. 559-559
Author(s):  
Paul Dluzniewski ◽  
Ryan Orosco ◽  
Elizabeth A Platz ◽  
Alan W Partin ◽  
Misop Han
Keyword(s):  
Radical Prostatectomy ◽  
Charlson Comorbidity Index ◽  
Prediction Of Mortality ◽  
Comorbidity Index

Development and Validation of the Modified Charlson Comorbidity Index in Incident Peritoneal Dialysis Patients: A National Population-Based Approach

2017 ◽  
Vol 37 (1) ◽  
pp. 94-102 ◽  
Author(s):  
Hyunjeong Cho ◽  
Myoung-Hee Kim ◽  
Hyo Jin Kim ◽  
Jae Yoon Park ◽  
Dong-Ryeol Ryu ◽  
...  
Keyword(s):  
Peritoneal Dialysis ◽  
Charlson Comorbidity Index ◽  
Clinical Decision Making ◽  
Proportional Hazards Model ◽  
Cox Regression ◽  
Relative Weight ◽  
Cox Proportional Hazards Model ◽  
Net Reclassification Improvement ◽  
Prediction Of Mortality ◽  
Comorbidity Index

Background The utility of applying the Charlson comorbidity index (CCI) to peritoneal dialysis (PD) patients is disputed because the relative weight of each comorbidity in PD patients may be different from those in other chronic diseases. We aimed to develop and validate a modified CCI in incident PD patients (mCCI-IPD) for better risk stratification and prediction of mortality. Methods The mCCI-IPD was developed using data from all Korean adult incident PD patients between 2005 and 2008 ( n = 7,606). Multivariate Cox regression was used to determine new weights for the individual comorbidities in the CCI. The prognostic performance of the mCCI-IPD was validated in an independent cohort ( n = 664) through c-statistics and continuous net reclassification improvement (cNRI). Results A total of 75.5% of the patients in the development cohort had 1 or more comorbidities. The Cox proportional hazards model provided reassigned severity weights for the 11 comorbidities that significantly predicted mortality. In the validation cohort, the CCI and mCCI-IPD scores were both correlated with survival and showed no differences in their c-statistics. However, multivariate analyses using cNRI revealed that the mCCI-IPD provided a 38.2% improvement in mortality risk assessment compared with the CCI (95% confidence interval [CI], 15.3 – 61.0; p < 0.001). These significant reclassification improvements were observed consistently in subjects with events (cNRIEvent, 28.2% [95% CI, 6.9 – 49.5; p = 0.009]) and without events (cNRINon-event, 10.0% [95% CI, 1.7 – 18.2; p = 0.019]). Conclusions Compared with the CCI, the mCCI-IPD showed better performance in mortality prediction for incident PD patients. Therefore, this tool may be used as a preferred index for statistical analysis and clinical decision-making.

The Pitt Bacteremia Score, Charlson Comorbidity Index and Chronic Disease Score are useful tools for the prediction of mortality in patients with Candida bloodstream infection

Mycoses ◽  
2017 ◽  
Vol 60 (10) ◽  
pp. 676-685 ◽  
Author(s):  
María Paz Vaquero-Herrero ◽  
Silvio Ragozzino ◽  
Fabián Castaño-Romero ◽  
María Siller-Ruiz ◽  
Rebeca Sánchez González ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Bloodstream Infection ◽  
Charlson Comorbidity Index ◽  
Disease Score ◽  
Chronic Disease Score ◽  
Prediction Of Mortality ◽  
Comorbidity Index ◽  
Candida Bloodstream Infection

scholarly journals Combination of Sequential Organ Failure Assessment (SOFA) score and Charlson Comorbidity Index (CCI) could predict the severity and prognosis of candidemia more accurately than the Acute Physiology, Age, Chronic Health Evaluation II (APACHE II) score

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nobuhiro Asai ◽  
Wataru Ohashi ◽  
Daisuke Sakanashi ◽  
Hiroyuki Suematsu ◽  
Hideo Kato ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Sequential Organ Failure Assessment ◽  
Organ Failure ◽  
Sofa Score ◽  
Charlson Comorbidity Index ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Health Evaluation ◽  
Failure Assessment ◽  
Comorbidity Index

Abstract Background Candidemia has emerged as an important nosocomial infection, with a mortality rate of 30–50%. It is the fourth most common nosocomial bloodstream infection (BSI) in the United States and the seventh most common nosocomial BSI in Europe and Japan. The aim of this study was to assess the performance of the Sequential Organ Failure Assessment (SOFA) score for determining the severity and prognosis of candidemia. Methods We performed a retrospective study of patients admitted to hospital with candidemia between September 2014 and May 2018. The severity of candidemia was evaluated using the SOFA score and the Acute Physiology, Age, Chronic Health Evaluation II (APACHE II) score. Patients’ underlying diseases were assessed by the Charlson Comorbidity Index (CCI). Results Of 70 patients enrolled, 41 (59%) were males, and 29 (41%) were females. Their median age was 73 years (range: 36–93 years). The most common infection site was catheter-related bloodstream infection (n=36, 51%).The 30-day, and in-hospital mortality rates were 36 and 43%, respectively. Univariate analysis showed that SOFA score ≥5, APACHE II score ≥13, initial antifungal treatment with echinocandin, albumin < 2.3, C-reactive protein > 6, disturbance of consciousness, and CCI ≥3 were related with 30-day mortality. Of these 7, multivariate analysis showed that the combination of SOFA score ≥5 and CCI ≥3 was the best independent prognostic indicator for 30-day and in-hospital mortality. Conclusions The combined SOFA score and CCI was a better predictor of the 30-day mortality and in-hospital mortality than the APACHE II score alone.

scholarly journals Real-Time Electronic Health Record Mortality Prediction During the COVID-19 Pandemic: A Prospective Cohort Study

2021 ◽  
Author(s):  
Peter D. Sottile ◽  
David Albers ◽  
Peter E. DeWitt ◽  
Seth Russell ◽  
J.N. Stroh ◽  
...  
Keyword(s):  
Cohort Study ◽  
Electronic Health Record ◽  
Real Time ◽  
Prospective Cohort Study ◽  
Sofa Score ◽  
Charlson Comorbidity Index ◽  
Prospective Cohort ◽  
Mortality Prediction ◽  
Health Record ◽  
Comorbidity Index

AbstractBackgroundThe SARS-CoV-2 virus has infected millions of people, overwhelming critical care resources in some regions. Many plans for rationing critical care resources during crises are based on the Sequential Organ Failure Assessment (SOFA) score. The COVID-19 pandemic created an emergent need to develop and validate a novel electronic health record (EHR)-computable tool to predict mortality.Research QuestionsTo rapidly develop, validate, and implement a novel real-time mortality score for the COVID-19 pandemic that improves upon SOFA.Study Design and MethodsWe conducted a prospective cohort study of a regional health system with 12 hospitals in Colorado between March 2020 and July 2020. All patients >14 years old hospitalized during the study period without a do not resuscitate order were included. Patients were stratified by the diagnosis of COVID-19. From this cohort, we developed and validated a model using stacked generalization to predict mortality using data widely available in the EHR by combining five previously validated scores and additional novel variables reported to be associated with COVID-19-specific mortality. We compared the area under the receiver operator curve (AUROC) for the new model to the SOFA score and the Charlson Comorbidity Index.ResultsWe prospectively analyzed 27,296 encounters, of which 1,358 (5.0%) were positive for SARS-CoV-2, 4,494 (16.5%) included intensive care unit (ICU)-level care, 1,480 (5.4%) included invasive mechanical ventilation, and 717 (2.6%) ended in death. The Charlson Comorbidity Index and SOFA scores predicted overall mortality with an AUROC of 0.72 and 0.90, respectively. Our novel score predicted overall mortality with AUROC 0.94. In the subset of patients with COVID-19, we predicted mortality with AUROC 0.90, whereas SOFA had AUROC of 0.85.InterpretationWe developed and validated an accurate, in-hospital mortality prediction score in a live EHR for automatic and continuous calculation using a novel model, that improved upon SOFA.Take Home PointsStudy QuestionCan we improve upon the SOFA score for real-time mortality prediction during the COVID-19 pandemic by leveraging electronic health record (EHR) data?ResultsWe rapidly developed and implemented a novel yet SOFA-anchored mortality model across 12 hospitals and conducted a prospective cohort study of 27,296 adult hospitalizations, 1,358 (5.0%) of which were positive for SARS-CoV-2. The Charlson Comorbidity Index and SOFA scores predicted all-cause mortality with AUROCs of 0.72 and 0.90, respectively. Our novel score predicted mortality with AUROC 0.94.InterpretationA novel EHR-based mortality score can be rapidly implemented to better predict patient outcomes during an evolving pandemic.

scholarly journals Prediction of Mortality After Radical Prostatectomy by Charlson Comorbidity Index

Urology ◽  
2010 ◽  
Vol 76 (3) ◽  
pp. 553-557 ◽  
Author(s):  
Thomas J. Guzzo ◽  
Paul Dluzniewski ◽  
Ryan Orosco ◽  
Elizabeth A. Platz ◽  
Alan W. Partin ◽  
...  
Keyword(s):  
Radical Prostatectomy ◽  
Charlson Comorbidity Index ◽  
Prediction Of Mortality ◽  
Comorbidity Index
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