scholarly journals Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

2022 ◽  
Vol 91 (1) ◽  
pp. 8-35
Author(s):  
Mary E. Charlson ◽  
Danilo Carrozzino ◽  
Jenny Guidi ◽  
Chiara Patierno
Keyword(s):  
Critical Review ◽  
Charlson Comorbidity Index ◽  
Concurrent Validity ◽  
Assessment Tool ◽  
Self Report ◽  
Surgical Intensive Care Unit ◽  
Surgical Intensive Care ◽  
Comorbidity Index ◽  
Long Term Mortality

The present critical review was conducted to evaluate the clinimetric properties of the Charlson Comorbidity Index (CCI), an assessment tool designed specifically to predict long-term mortality, with regard to its reliability, concurrent validity, sensitivity, incremental and predictive validity. The original version of the CCI has been adapted for use with different sources of data, ICD-9 and ICD-10 codes. The inter-rater reliability of the CCI was found to be excellent, with extremely high agreement between self-report and medical charts. The CCI has also been shown either to have concurrent validity with a number of other prognostic scales or to result in concordant predictions. Importantly, the clinimetric sensitivity of the CCI has been demonstrated in a variety of medical conditions, with stepwise increases in the CCI associated with stepwise increases in mortality. The CCI is also characterized by the clinimetric property of incremental validity, whereby adding the CCI to other measures increases the overall predictive accuracy. It has been shown to predict long-term mortality in different clinical populations, including medical, surgical, intensive care unit (ICU), trauma, and cancer patients. It may also predict in-hospital mortality, although in some instances, such as ICU or trauma patients, the CCI did not perform as well as other instruments designed specifically for that purpose. The CCI thus appears to be clinically useful not only to provide a valid assessment of the patient’s unique clinical situation, but also to demarcate major diagnostic and prognostic differences among subgroups of patients sharing the same medical diagnosis.

scholarly journals Charlson Comorbidity Index does not predict long-term mortality in elderly subjects with chronic heart failure

2009 ◽  
Vol 38 (6) ◽  
pp. 734-740 ◽  
Author(s):  
G. Testa ◽  
F. Cacciatore ◽  
G. Galizia ◽  
D. Della-Morte ◽  
F. Mazzella ◽  
...  
Keyword(s):  
Heart Failure ◽  
Chronic Heart Failure ◽  
Charlson Comorbidity Index ◽  
Elderly Subjects ◽  
Comorbidity Index ◽  
Long Term Mortality

Aspartate transaminase/alanine transaminase ratio as a significant prognostic factor in patients with sepsis: a retrospective analysis

2020 ◽  
Author(s):  
Pengyue Zhao ◽  
Renqi Yao ◽  
Chao Ren ◽  
Songyan Li ◽  
Yuxuan Li ◽  
...  
Keyword(s):  
Prognostic Value ◽  
Cox Regression ◽  
Alanine Transaminase ◽  
Receiver Operating Curve ◽  
Surgical Intensive Care Unit ◽  
Significant Prognostic Factor ◽  
Aspartate Transaminase ◽  
Surgical Intensive Care ◽  
Long Term Mortality

Abstract Background: The study was performed to investigate the relationship between aspartate transaminase/alanine transaminase ratio (DRR) and long-term mortality among patients diagnosed with sepsis or septic shock. Methods: We conducted a retrospective study among adult septic patients who were admitted to surgical intensive care unit (ICU) of the Chinese People's Liberation Army (PLA) General Hospital from January 2014 to December 2018. Baseline characteristics were compared between survivors and non-survivors. We applied univariate as well as multivariate Cox regression analyses to evaluate DRR in relation to 180-day mortality. The potential prognostic value of DRR in predicting mortality rate was assessed by receiver operating curve (ROC) analysis. Besides, we conducted subgroup analysis by stratifying patients via optimal DRR cut-off value. Results: We included a total number of 183 patients in the current study, 44 (24%) patients died within 180-day hospitalization. Univariate and multivariate Cox analysis revealed that DRR was an independent predictor of 180-day mortality (hazard ratio [HR] 1.421, 95% confidence interval [CI] 1.073-1.883, P = 0.014). The predicting accuracy of 180-day mortality for DRR was presented as ROC with an area under the curve (AUC) of 0.708 (95% CI 0.629–0.786, P < 0.001). As we stratified all enrolled patients into two groups by using the optimal cut-off value of 1.29, we observed a significantly higher mortality in patients with relatively high DRR. Conclusions: An elevated DRR was associated with higher 180-day mortality among septic patients, and DRR might be an optimal marker for predicting the long-term mortality of sepsis. More prospective and randomized trials are needed to confirm the prognostic value of DRR.

scholarly journals Lipid and lipoprotein predictors of functional outcomes and long-term mortality after surgical sepsis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Faheem W. Guirgis ◽  
Christiaan Leeuwenburgh ◽  
Lyle Moldawer ◽  
Gabriela Ghita ◽  
Lauren Page Black ◽  
...  
Keyword(s):  
Cox Regression ◽  
Performance Status ◽  
Density Lipoprotein ◽  
Poor Performance ◽  
Lipid Biomarkers ◽  
Surgical Intensive Care Unit ◽  
Poor Performance Status ◽  
Surgical Intensive Care ◽  
Long Term Mortality

Abstract Rationale Sepsis is a life-threatening, dysregulated response to infection. Lipid biomarkers including cholesterol are dynamically regulated during sepsis and predict short-term outcomes. In this study, we investigated the predictive ability of lipid biomarkers for physical function and long-term mortality after sepsis. Methods Prospective cohort study of sepsis patients admitted to a surgical intensive-care unit (ICU) within 24 h of sepsis bundle initiation. Samples were obtained at enrollment for lipid biomarkers. Multivariate regression models determined independent risk factors predictive of poor performance status (Zubrod score of 3/4/5) or survival at 1-year follow-up. Measurements and main results The study included 104 patients with surgical sepsis. Enrollment total cholesterol and high-density lipoprotein (HDL-C) levels were lower, and myeloperoxidase (MPO) levels were higher for patients with poor performance status at 1 year. A similar trend was seen in comparisons based on 1-year mortality, with HDL-C and ApoA-I levels being lower and MPO levels being higher in non-survivors. However, multivariable logistic regression only identified baseline Zubrod and initial SOFA score as significant independent predictors of poor performance status at 1 year. Multivariable Cox regression modeling for 1-year survival identified high Charlson comorbidity score, low ApoA-I levels, and longer vasopressor duration as predictors of mortality over 1-year post-sepsis. Conclusions In this surgical sepsis study, lipoproteins were not found to predict poor performance status at 1 year. ApoA-I levels, Charlson comorbidity scores, and duration of vasopressor use predicted 1 year survival. These data implicate cholesterol and lipoproteins as contributors to the underlying pathobiology of sepsis.

Patients’ Characteristics Associated With Readmission to a Surgical Intensive Care Unit

2012 ◽  
Vol 21 (6) ◽  
pp. e120-e128 ◽  
Author(s):  
T. K. Timmers ◽  
M. H. J. Verhofstad ◽  
K. G. M. Moons ◽  
L. P. H. Leenen
Keyword(s):  
Quality Of Life ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Severity Of Illness ◽  
Total Sample ◽  
Surgical Intensive Care Unit ◽  
Surgical Intensive Care ◽  
Term Survival

Background Readmission within 48 hours is a leading performance indicator of the quality of care in an intensive care unit. Objective To investigate variables that might be associated with readmission to a surgical intensive care unit. Methods Demographic characteristics, severity-of-illness scores, and survival rates were collected for all patients admitted to a surgical intensive care unit between 1995 and 2000. Long-term survival and quality of life were determined for patients who were readmitted within 30 days after discharge from the unit. Quality of life was measured with the EuroQol-6D questionnaire. Multivariate logistic analysis was used to calculate the independent association of expected covariates. Results Mean follow-up time was 8 years. Of the 1682 patients alive at discharge, 141 (8%) were readmitted. The main causes of readmission were respiratory decompensation (48%) and cardiac conditions (16%). Compared with the total sample, patients readmitted were older, mostly had vascular (39%) or gastrointestinal (26%) disease, and had significantly higher initial severity of illness (P = .003, .007) and significantly more comorbid conditions (P = .005). For all surgical classifications except general surgery, readmission was independently associated with type of admission and need for mechanical ventilation. Long-term mortality was higher among patients who were readmitted than among the total sample. Nevertheless, quality-of-life scores were the same for patients who were readmitted and patients who were not. Conclusion The adverse effect of readmission to the intensive care unit on survival appears to be long-lasting, and predictors of readmission are scarce.

Utility of the Charlson Comorbidity Index Computed from Routinely Collected Hospital Discharge Diagnosis Codes

2000 ◽  
Vol 39 (01) ◽  
pp. 7-11 ◽  
Author(s):  
L. L.-Y. Lim ◽  
R. L. O’Connell
Keyword(s):  
Charlson Comorbidity Index ◽  
Model Fit ◽  
Ratio Test ◽  
Discharge Diagnosis ◽  
Term Survival ◽  
Additional Information ◽  
Diagnosis Codes ◽  
Comorbidity Index ◽  
Informed Patient

Abstract:This study aims to determine whether the Charlson comorbidity index computed from ICD-9-CM discharge diagnosis codes adds additional information to a model containing adjustment for more informed patient details (e.g., disease severity and history), besides solely age and sex, when predicting long-term survival. We conducted a retrospective cohort study of patients admitted to hospital for suspected acute myocardial infarction. Index scores were calculated by applying the D’Hoore et al. algorithm (1993). The index significantly improved the model fit (likelihood ratio test: p <0.001). The D’Hoore-adapted Charlson index is a useful comorbidity risk adjustment tool when applied to AMI and angina patients.

scholarly journals QT prolongation predicts short-term mortality independent of comorbidity

EP Europace ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 1254-1260 ◽  
Author(s):  
Charlotte Gibbs ◽  
Jacob Thalamus ◽  
Doris Tove Kristoffersen ◽  
Martin Veel Svendsen ◽  
Øystein L Holla ◽  
...  
Keyword(s):  
Main Diagnosis ◽  
Short Term ◽  
Significant Difference ◽  
All Cause Mortality ◽  
Short Term Mortality ◽  
Comorbidity Index ◽  
Short And Long Term ◽  
Mortality Hazard Ratio ◽  
Long Term Mortality

Abstract Aims A prolonged corrected QT interval (QTc) ≥500 ms is associated with high all-cause mortality in hospitalized patients. We aimed to explore any difference in short- and long-term mortality in patients with QTc ≥500 ms compared with patients with QTc <500 ms after adjustment for comorbidity and main diagnosis. Methods and results Patients with QTc ≥500 ms who were hospitalized at Telemark Hospital Trust, Norway between January 2007 and April 2014 were identified. Thirty-day and 3-year all-cause mortality in 980 patients with QTc ≥500 ms were compared with 980 patients with QTc <500 ms, matched for age and sex and adjusting for Charlson comorbidity index (CCI), previous admissions, and main diagnoses. QTc ≥500 ms was associated with increased 30-day all-cause mortality [hazard ratio (HR) 1.90, 95% confidence interval (CI) 1.38–2.62; P < 0.001]. There was no significant difference in mortality between patients with QTc ≥500 ms and patients with QTc <500 ms who died between 30 days and 3 years; 32% vs. 29%, P = 0.20. Graded CCI was associated with increased 3-year all-cause mortality (CCI 1–2: HR 1.62, 95% CI 1.34–1.96; P < 0.001; CCI 3–4: HR 2.50, 95% CI 1.95–3.21; P < 0.001; CCI ≥5: HR 3.76, 95% CI 2.85–4.96; P < 0.001) but was not associated with 30-day all-cause mortality. Conclusion QTc ≥500 ms is a powerful predictor of short-term mortality overruling comorbidities. QTc ≥500 ms also predicted long-term mortality, but this effect was mainly caused by the increased short-term mortality. For long-term mortality, comorbidity was more important.

scholarly journals Bleeding during critical illness: A prospective cohort study using a new measurement tool

2007 ◽  
Vol 30 (2) ◽  
pp. 93 ◽  
Author(s):  
Donald M. Arnold ◽  
Laura Donahoe ◽  
France J. Clarke ◽  
Andrea J. Tkaczyk ◽  
Diane Heels-Ansdell ◽  
...  
Keyword(s):  
Risk Factors ◽  
Critical Illness ◽  
Major Bleeding ◽  
Proportional Hazards Model ◽  
Assessment Tool ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Surgical Intensive Care Unit ◽  
Measurement Tool ◽  
Surgical Intensive Care

Purpose: To estimate the incidence, severity, duration and consequences of bleeding during critical illness, and to test the performance characteristics of a new bleeding assessment tool. Methods: Clinical bleeding assessments were performed prospectively on 100 consecutive patients admitted to a medical-surgical intensive care unit (ICU) using a novel bleeding measurement tool called HEmorrhage MEasurement (HEME). Bleeding assessments were done daily in duplicate and independently by blinded, trained assessors. Inter-rater agreement and construct validity of the HEME tool were calculated using φ. Risk factors for major bleeding were identified using a multivariable Cox proportional hazards model. Results: Overall, 90% of patients experienced a total of 480 bleeds of which 94.8% were minor and 5.2% were major. Inter-rater reliability of the HEME tool was excellent (φ = 0.98, 95% CI: 0.96 to 0.99). A decrease in platelet count and a prolongation of partial thromboplastin time were independent risk factors for major bleeding but neither were renal failure nor prophylactic anticoagulation. Patients with major bleeding received more blood transfusions and had longer ICU stays compared to patients with minor or no bleeding. Conclusions: Bleeding, although primarily minor, occurred in the majority of ICU patients. One of five patients experienced a major bleed which was associated with abnormal coagulation tests but not with prophylactic anticoagulants. These baseline bleeding rates can inform the design of future clinical trials in critical care that use bleeding as an outcome and HEME is a useful tool to measure bleeding in critically ill patients.

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