Effect of ferritin, INR, and D-dimer immunological parameters levels as predictors of COVID-19 mortality: A strong prediction with the decision trees

Huyut, Mehmet Tahir; Huyut, Zübeyir

doi:10.1016/j.heliyon.2023.e14015

Cited by 18 publications

(15 citation statements)

References 84 publications

(169 reference statements)

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“…Our results are in line with partial results obtained by previous studies, as the variables identified in our research correspond to subgroups reported across different studies in the literature. Specifically, our findings on LDH, age, red blood cell distribution standard deviation, neutrophils, basophils, and C-reactive protein for severe and non-severe COVID-19 cases are supported by the results obtained across various prior investigations [48] , [49] , [87] , [88] , [89] . However, the difference in weight across the variables could be due to variations among different populations or settings [90] .…”

Section: Discussionsupporting

confidence: 84%

Developing an interpretable machine learning model for predicting COVID-19 patients deteriorating prior to intensive care unit admission using laboratory markers

Reina-Reina,

Barrera,

Maté

et al. 2023

Heliyon

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Section: Discussionsupporting

confidence: 84%

Developing an interpretable machine learning model for predicting COVID-19 patients deteriorating prior to intensive care unit admission using laboratory markers

Reina-Reina,

Barrera,

Maté

et al. 2023

Heliyon

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“…Overall, our findings are consistent with those previously reported [ [27] , [28] , [29] , [30] ]. Regarding other laboratory parameters, consistent associations have been documented between increased levels of C-reactive protein [ 31 , 32 ], ferritin [ 32 , 33 ], INR [ 33 ], and NLR [ 34 ] in patients with negative COVID-19 outcomes, such as severity or death. However, these associations were not observed in our study.…”

Section: Discussionmentioning

confidence: 90%

Cytokine expression and mortality risk among COVID-19 hospitalized patients over 60 years of age in a referral hospital in Cartagena, Colombia

Ramos-González,

Cano-Pérez,

Loyola

et al. 2024

Heliyon

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“…Ferritin was associated with severity and death due to COVID [ 37 , 38 ]. It increases in several inflammatory conditions and has an important immunomodulatory effect on mortality and inflammatory processes.…”

Section: Discussionmentioning

confidence: 99%

New score to predict COVID-19 progression in vaccine and early treatment era: the COVID-19 Sardinian Progression Score (CSPS)

De Vito,

Saderi,

Colpani

et al. 2024

Eur J Med Res

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Background Several scores aimed at predicting COVID-19 progression have been proposed. As the variables vaccination and early SARS-CoV-2 treatment were systematically excluded from the prognostic scores, the present study's objective was to develop a new model adapted to the current epidemiological scenario. Methods We included all patients evaluated by the Infectious Disease Unit in Sassari, with SARS-CoV-2 infection and without signs of respiratory failure at the first evaluation (P/F > 300). Disease progression was defined by the prescription of supplemental oxygen. In addition, variables related to demographics, vaccines, comorbidities, symptoms, CT scans, blood tests, and therapies were collected. Multivariate logistic regression modelling was performed to determine factors associated with progression; any variable with significant univariate test or clinical relevance was selected as a candidate for multivariate analysis. Hosmer–Lemeshow (HL) goodness of fit statistic was calculated. Odds ratio values were used to derive an integer score for developing an easy-to-use progression risk score. The discrimination performance of the risk index was determined using the AUC, and the best cut-off point, according to the Youden index, sensitivity, specificity, predictive value, and likelihood ratio, was chosen. Results 1145 patients [median (IQR) age 74 (62–83) years; 53.5% males] were enrolled; 336 (29.3%) had disease progression. Patients with a clinical progression were older and showed more comorbidities; furthermore, they were less vaccinated and exposed to preventive therapy. In the multivariate logistic regression analysis, age ≥ 60 years, COPD, dementia, haematological tumours, heart failure, exposure to no or one vaccine dose, fever, dyspnoea, GGO, consolidation, ferritin, De Ritis ≥ 1.2, LDH, and no exposure to early anti-SARS-CoV-2 treatment were associated with disease progression. The final risk score ranged from 0 to 45. The ROC curve analysis showed an AUC of 0.92 (95% CI 0.90–0.93) with a 93.7% specificity and 72.9% sensitivity. Low risk was defined when the cut-off value was less than 23. Three risk levels were identified: low (0–23 points), medium (24–35), and high (≥ 36). Conclusions The proportion of patients with progression increases with high scores: the assessment of the risk could be helpful for clinicians to plan appropriate therapeutic strategies.

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Effect of ferritin, INR, and D-dimer immunological parameters levels as predictors of COVID-19 mortality: A strong prediction with the decision trees

Cited by 18 publications

References 84 publications

Developing an interpretable machine learning model for predicting COVID-19 patients deteriorating prior to intensive care unit admission using laboratory markers

Developing an interpretable machine learning model for predicting COVID-19 patients deteriorating prior to intensive care unit admission using laboratory markers

Cytokine expression and mortality risk among COVID-19 hospitalized patients over 60 years of age in a referral hospital in Cartagena, Colombia

New score to predict COVID-19 progression in vaccine and early treatment era: the COVID-19 Sardinian Progression Score (CSPS)

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