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

Ahmed, 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.19937

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…Hazard ratios (HR) with 95% confidence intervals (95% CI) were reported, along with the accompanying slope, Wald statistic and p values. Even though COPD is one of the variables used for calculating the Charlson comorbidity index, it was employed as a joint measurement of comorbidity burden because of its longstanding validity in the previous literature in both COVID-19 and other clinical settings [ 35 – 38 ].…”

Section: Methodsmentioning

confidence: 99%

Investigating the role of obstructive pulmonary diseases and eosinophil count at admission on all-cause mortality in SARS-CoV-2 patients

Salai

Vražić

Kovačević

et al. 2023

Wien Klin Wochenschr

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Introduction The impact of asthma and chronic obstructive pulmonary disease (COPD) in the setting of severe acute respiratory syndrome coronavirus 2 (SARS-CoV‑2) infection is not clearly defined. Blood eosinophil count is a standard diagnostic test which, according to the previously published literature, might have a potential prognostic role on mortality in patients with SARS-CoV‑2 infection. Aim To investigate the potential prognostic value of peripheral blood eosinophil count on all-cause mortality of patients hospitalized with SARS-CoV‑2 infection, as well as to assess the impact of asthma or COPD premorbidity on all-cause mortality. Material and methods We conducted a retrospective registry-based cohort study. Survival analysis was performed by employing the Cox proportional hazards regression model at 30 days of follow-up. Prognostic value of eosinophil count on all-cause mortality was assessed using receiver-operating characteristic (ROC) curve analysis. Results A total of 5653 participants were included in the study. Our model did not reveal that pre-existing asthma or COPD is a statistically significant covariate for all-cause mortality but, indicated that higher eosinophil count at admission might have a protective effect (hazard ratio, HR 0.13 (95% confidence interval, CI 0.06–0.27), p = 0.0001). ROC curve analysis indicates cut-off value of 20 cells/mm 3 (81% specificity; 30.9% sensitivity). Conclusion Our results indicate that eosinophil count at hospital admission might have a potential prognostic role for all-cause mortality at 30 days of follow-up; however this was not demonstrated for pre-existing obstructive lung diseases.

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Section: Methodsmentioning

confidence: 99%

Investigating the role of obstructive pulmonary diseases and eosinophil count at admission on all-cause mortality in SARS-CoV-2 patients

Salai

Vražić

Kovačević

et al. 2023

Wien Klin Wochenschr

View full text Add to dashboard Cite

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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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Charlson comorbidity index, neutrophil-to-lymphocyte ratio and undertreatment with renin-angiotensin-aldosterone system inhibitors predict in-hospital mortality of hospitalized COVID-19 patients during the omicron dominant period

et al. 2022

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PurposeTo investigate the clinical predictors of in-hospital mortality in hospitalized patients with Coronavirus disease 2019 (COVID-19) infection during the Omicron period.MethodsAll consecutive hospitalized laboratory‐confirmed COVID-19 patients between January and May 2022 were retrospectively analyzed. All patients underwent accurate physical, laboratory, radiographic and echocardiographic examination. Primary endpoint was in-hospital mortality.Results74 consecutive COVID-19 patients (80.0 ± 12.6 yrs, 45.9% males) were included. Patients who died during hospitalization (27%) and those who were discharged alive (73%) were separately analyzed. Compared to patients discharged alive, those who died were significantly older, with higher comorbidity burden and greater prevalence of laboratory, radiographic and echographic signs of pulmonary and systemic congestion. Charlson comorbidity index (CCI) (OR 1.76, 95%CI 1.07-2.92), neutrophil-to-lymphocyte ratio (NLR) (OR 1.24, 95%CI 1.10-1.39) and absence of angiotensin-converting enzyme inhibitors (ACEI)/angiotensin II receptor blockers (ARBs) therapy (OR 0.01, 95%CI 0.00-0.22) independently predicted the primary endpoint. CCI ≥7 and NLR ≥9 were the best cut-off values for predicting mortality. The mortality risk for patients with CCI ≥7, NLR ≥9 and not in ACEI/ARBs therapy was high (86%); for patients with CCI <7, NLR ≥9, with (16.6%) or without (25%) ACEI/ARBs therapy was intermediate; for patients with CCI <7, NLR <9 and in ACEI/ARBs therapy was of 0%.ConclusionsHigh comorbidity burden, high levels of NLR and the undertreatment with ACEI/ARBs were the main prognostic indicators of in-hospital mortality. The risk stratification of COVID-19 patients at hospital admission would help the clinicians to take care of the high-risk patients and reduce the mortality.

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

Cited by 4 publications

References 16 publications

Investigating the role of obstructive pulmonary diseases and eosinophil count at admission on all-cause mortality in SARS-CoV-2 patients

Investigating the role of obstructive pulmonary diseases and eosinophil count at admission on all-cause mortality in SARS-CoV-2 patients

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

Charlson comorbidity index, neutrophil-to-lymphocyte ratio and undertreatment with renin-angiotensin-aldosterone system inhibitors predict in-hospital mortality of hospitalized COVID-19 patients during the omicron dominant period

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