Developing an adapted Charlson comorbidity index for ischemic stroke outcome studies.
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ABSTRACT:
SUBMITTER: Hall RE
PROVIDER: S-EPMC6892203 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature
Publications
Developing an adapted Charlson comorbidity index for ischemic stroke outcome studies.
Hall Ruth E RE Porter Joan J Quan Hude H Reeves Mathew J MJ
BMC health services research 20191203 1
<h4>Background</h4>The Charlson comorbidity index (CCI) is commonly used to adjust for patient casemix. We reevaluated the CCI in an ischemic stroke (IS) cohort to determine whether the original seventeen comorbidities and their weights are relevant.<h4>Methods</h4>We identified an IS cohort (N = 6988) from the Ontario Stroke Registry (OSR) who were discharged from acute hospitals (N = 100) between April 1, 2012 and March 31, 2013. We used hospital discharge ICD-10-CA data to identify Charlson c ...[more]
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Project description:BACKGROUND:The Charlson Comorbidity Index (CCI) can be automatically calculated from the International Classification of Disease (ICD) code. However, the feasibility of this transformation has not been acknowledged, particularly in hospitals without a qualified ICD coding system. Here, we investigated the utility of coding-based CCI in China. METHODS:A multi-center, population-based, retrospective observational study was conducted, using a dataset incorporating 2,464,395 adult subjects from 15 hospitals. CCI was calculated using both ICD-10-based and diagnosis-based method, according to the transformation rule reported previously and to the literal description from discharge diagnosis, respectively. A ? coefficient of variation was used as a measure of agreement between the above two methods for each hospital. The discriminative abilities of the two methods were compared using the receiver-of-operating characteristic curve (ROC) for prediction of in-hospital mortality. RESULTS:Total agreement between the ICD-based and diagnosis-based CCI for each index ranged from 86.1 to 100%, with ? coefficients from 0.210 [95% confidence interval (CI) 0.208-0.212] to 0.932 (95% CI 0.924-0.940). None of the 19 indices of CCI had a ? coefficient?>?0.75 in all the hospitals included for study. The area under the curve of ROC for in-hospital mortality of all 15 hospitals was significantly lower for ICD-based than diagnosis-based CCI [0.735 (0.732, 0.739) vs 0.760 (0.757, 0.764)], indicative of more limited discriminative ability of the ICD-based calculation. CONCLUSIONS:CCI calculated using ICD-10 coding did not agree with diagnosis-based CCI. ICD-based CCI displayed diminished discrimination performance in terms of in-hospital mortality, indicating that this method is not promising for CCI scoring in China under the present circumstances.
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Project description:This retrospective study investigated the association between the Charlson comorbidity index (CCI) score and the survival of patients with stage IIIB-IV (advanced, non-resectable) non-small cell lung cancer (NSCLC) who also did not have gene mutations in epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK).The records of 165 patients (28-80 y, median 61 y) who met the above criteria and were admitted to Beijing Friendship Hospital Capital Medical University from 1 May 2010 to 1 October 2014were reviewed. Associations between baseline variables and the CCI score were assessed via univariate and multivariate logistic regression analysis. Overall survival was defined as the time from the first clinic visit to death from any cause, or to the end of follow-up. Survival curves were estimated via the Kaplan-Meier method and compared with the log-rank test.Logistic regression analyses indicated that smoking and performance status were independently associated with the CCI score. Smoking was associated with an increased risk of mortality (odds ratio (OR) 4.12 (95% confidence interval [CI] 1.92-8.84) compared to non-smokers), as was performance status 2 (ambulatory, capable of self-care, unable to perform any work activities; active for >50% of waking hours) (OR 2.22 (95% CI, 1.14-4.33) compared to performance status 1). Univariate Cox's regression analyses showed that the hazard ratios were significantly associated with the CCI score (P = 0.009), smoking (P = 0.042), and male gender (P = 0.021).The CCI score is an important prognostic factor for the prediction of overall survival in patients with stage IIIB-IV NSCLC who are negative for EGFR and ALK gene mutations.
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Project description:AbstractAged population with comorbidities demonstrated high mortality rate and severe clinical outcome in the patients with coronavirus disease 2019 (COVID-19). However, whether age-adjusted Charlson comorbidity index score (CCIS) predict fatal outcomes remains uncertain.This retrospective, nationwide cohort study was performed to evaluate patient mortality and clinical outcome according to CCIS among the hospitalized patients with COVID-19 infection. We included 5621 patients who had been discharged from isolation or had died from COVID-19 by April 30, 2020. The primary outcome was composites of death, admission to intensive care unit, use of mechanical ventilator or extracorporeal membrane oxygenation. The secondary outcome was mortality. Multivariate Cox proportional hazard model was used to evaluate CCIS as the independent risk factor for death.Among 5621 patients, the high CCIS (≥ 3) group showed higher proportion of elderly population and lower plasma hemoglobin and lower lymphocyte and platelet counts. The high CCIS group was an independent risk factor for composite outcome (HR 3.63, 95% CI 2.45-5.37, P < .001) and patient mortality (HR 22.96, 95% CI 7.20-73.24, P < .001). The nomogram showed that CCIS was the most important factor contributing to the prognosis followed by the presence of dyspnea (hazard ratio [HR] 2.88, 95% confidence interval [CI] 2.16-3.83), low body mass index < 18.5 kg/m2 (HR 2.36, CI 1.49-3.75), lymphopenia (<0.8 x109/L) (HR 2.15, CI 1.59-2.91), thrombocytopenia (<150.0 x109/L) (HR 1.29, CI 0.94-1.78), anemia (<12.0 g/dL) (HR 1.80, CI 1.33-2.43), and male sex (HR 1.76, CI 1.32-2.34). The nomogram demonstrated that the CCIS was the most potent predictive factor for patient mortality.The predictive nomogram using CCIS for the hospitalized patients with COVID-19 may help clinicians to triage the high-risk population and to concentrate limited resources to manage them.
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Project description:PurposeComorbidity in stroke is common, but comprehensive reports are sparse. We describe prevalence of comorbidity and the prognostic impact on mortality and functional outcome in a large national ischemic stroke cohort.MethodsWe used outcome data from a long-term follow-up survey conducted in 2016 by the Swedish Stroke Register (Riksstroke). Those included in the study were 11 775 pre-stroke functionally independent patients with first-ever ischemic stroke followed up at three months and 12?months (all patients), and three years (2013 cohort) or five years (2011 cohort). Pre-stroke comorbidity data for 16 chronic conditions were obtained from the Swedish National Patient Register, the Swedish Prescribed Drugs Register and the Riksstroke register. Individuals were grouped according to number of conditions: none (0), low (1), moderate (2-3) or high (?4). Co-occurrence was analysed using hierarchical clustering, and multivariable analyses were used to estimate the prognostic significance of individual conditions.ResultsThe proportion of patients without comorbidity was 24.8%; 31.8% had low comorbidity; 33.5% had moderate comorbidity and 9.9% had high comorbidity. At 12?months, the proportion of poor outcome (dead or dependent: mRS ?3) was 24.8% (no comorbidity), 34.7% (low), 45.2% (moderate) and 59.4% (high). At five years, these proportions were 37.7%, 50.3%, 64.3%, and 81.7%, respectively. There was clustering of cardiovascular conditions and substantial negative effects of dementia, kidney, and heart failure.ConclusionComorbidity is common and has a strong impact on mortality and functional outcome. Our results highlight the need for health systems to shift focus to a comprehensive approach in stroke care that includes multimorbidity as a key component.
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Project description:Hyperhomocysteinemia or systemic elevation of the amino acid homocysteine is a common metabolic disorder that is considered to be a risk factor for ischemic stroke. However, it is still unclear whether predisposition to hyperhomocysteinemia could contribute to the severity of stroke outcome. This review highlights the advantages and limitations of the current rodent models of hyperhomocysteinemia, describes the consequence of mild hyperhomocysteinemia on the severity of ischemic brain damage in preclinical studies and summarizes the mechanisms involved in homocysteine induced neurotoxicity. The findings provide the premise for establishing hyperhomocysteinemia as a comorbidity for ischemic stroke and should be taken into consideration while developing potential therapeutic agents for stroke treatment.
| S-EPMC7856041 | biostudies-literature