The Impact of Charlson Comorbidity Index on Mortality From SARS-CoV-2 Virus Infection

Ahmad, Jawad; Capriles, Camilo Andrés Avendaño; Capriles, Natalia M Avendaño; Mehta, Suresh L.; Khan, Nattaliea; Tariq, Sheharyar; Abbas, Ramsha; Tousif, Sohaib; Shamim, Khizer

doi:10.7759/cureus.r53

Cited by 2 publications

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“…The APACHE II and Charlson comorbidity index are known risk stratification tools and were able to predict mortality in patients with COVID-19 14 , 15 . In this study, the predictive values of IMPROVE-DD score were higher than the APACHE II score and Charlson comorbidity index.…”

Section: Discussionmentioning

confidence: 99%

Ability of IMPROVE and IMPROVE-DD scores to predict outcomes in patients with severe COVID-19: a prospective observational study

Helmy

Milad

Hasanin

et al. 2022

Sci Rep

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In this study we aimed to evaluate the ability of IMPROVE and IMPROVE-DD scores in predicting in-hospital mortality in patients with severe COVID-19. This prospective observational study included adult patients with severe COVID-19 within 12 h from admission. We recorded patients' demographic and laboratory data, Charlson comorbidity index (CCI), SpO2 at room air, acute physiology and chronic health evaluation II (APACHE II), IMPROVE score and IMPROVE-DD score. In-hospital mortality and incidence of clinical worsening (the need for invasive mechanical ventilation, vasopressors, renal replacement therapy) were recorded. Our outcomes included the ability of the IMPROVE and IMPROVE-DD to predict in-hospital mortality and clinical worsening using the area under receiver operating characteristic curve (AUC) analysis. Multivariate analysis was used to detect independent risk factors for the study outcomes. Eighty-nine patients were available for the final analysis. The IMPROVE and IMPROVE-DD score showed the highest ability for predicting in-hospital mortality (AUC [95% confidence intervals {CI}] 0.96 [0.90–0.99] and 0.96 [0.90–0.99], respectively) in comparison to other risk stratification tools (APACHE II, CCI, SpO2). The AUC (95% CI) for IMPROVE and IMPROVE-DD to predict clinical worsening were 0.80 (0.70–0.88) and 0.79 (0.69–0.87), respectively. Using multivariate analysis, IMPROVE-DD and SpO2 were the only predictors for in-hospital mortality and clinical worsening. In patients with severe COVID-19, high IMPROVE and IMOROVE-DD scores showed excellent ability to predict in-hospital mortality and clinical worsening. Independent risk factors for in-hospital mortality and clinical worsening were IMPROVE-DD and SpO2.

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Section: Discussionmentioning

confidence: 99%

Ability of IMPROVE and IMPROVE-DD scores to predict outcomes in patients with severe COVID-19: a prospective observational study

Helmy

Milad

Hasanin

et al. 2022

Sci Rep

View full text Add to dashboard Cite

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“…Comorbidity was determined using the Charlson comorbidity index (short version), a simple, validated, and readily acceptable method of determining the risk of mortality from comorbid disease. It has been used as a predictor of long-term survival and prognosis [ 20 ]. To describe the sociofamiliar situation, the results of the Gijón scale were used, made up of five items (family situation, economic situation, housing, relationships, and social support) [ 21 ].…”

Section: Methodsmentioning

confidence: 99%

Care Needs of Highly Complex Chronic Patients in the Canary Islands: An Observational Study

et al. 2022

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In the last few decades, the impact of chronic health conditions on health systems, as well as on the quality of life, frailty, and dependence of those affected, has been brought to light. The objective of this study was to describe the population care needs of highly complex chronic patients (HCCPs). Methods: An epidemiological observational study was conducted. Results: A total of 13,262 patients were identified, 51% of which were elderly women. Among all patients, 84.4% had received a nursing assessment related to health patterns. Three diagnoses were established in 25% of the sample: readiness for enhanced health management, impaired skin integrity, and risk for falls. There were significant differences according to age, most importantly in terms of impaired skin integrity (39% of patients under 80 years old). Risk for falls, social isolation, situational low self-esteem, chronic low self-esteem, impaired home maintenance, anxiety, ineffective health management, ineffective coping, impaired memory, insomnia, and self-care deficits were more common in those living alone. A total of 37 diagnoses featured differences according to frailty/dependence. Approximately 23% of HCCPs suffered from frail elderly syndrome. Conclusions: This study presents the most common care needs of HCCPs, describing the sociodemographic profile of this part of the population. The planning of HCCP care varies in nature. Factors such as the dependence level and frailty of these people should be taken into consideration.

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The Impact of Charlson Comorbidity Index on Mortality From SARS-CoV-2 Virus Infection

Cited by 2 publications

References 0 publications

Ability of IMPROVE and IMPROVE-DD scores to predict outcomes in patients with severe COVID-19: a prospective observational study

Ability of IMPROVE and IMPROVE-DD scores to predict outcomes in patients with severe COVID-19: a prospective observational study

Care Needs of Highly Complex Chronic Patients in the Canary Islands: An Observational Study

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