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4C mortality score and COVID-19 mortality risk score: an analysis in four different age groups of an Italian population

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Abstract

To evaluate the prognostic stratification ability of 4C Mortality Score and COVID-19 Mortality Risk Score in different age groups. Retrospective study, including all patients, presented to the Emergency Department of the University Hospital Careggi, between February, 2020 and May, 2021, and admitted for SARS-CoV2. Patients were divided into four subgroups based on the quartiles of age distribution: patients < 57 years (G1, n = 546), 57–71 years (G2, n = 508), 72–81 years (G3, n = 552), and > 82 years (G4, n = 578). We calculated the 4C Mortality Score and COVID-19 Mortality Risk Score. The end-point was in-hospital mortality. In the whole population (age 68 ± 16 years), the mortality rate was 19% (n = 424), and increased with increasing age (G1: 4%, G2: 11%, G3: 22%, and G4: 39%, p < 0.001). Both scores were higher among non-survivors than survivors in all subgroups (4C-MS, G1: 6 [3–7] vs 3 [2–5]; G2: 10 [7–11] vs 7 [5–8]; G3: 11 [10–14] vs 10 [8–11]; G4: 13 [12–15] vs 11 [10–13], all p < 0.001; COVID-19 MRS, G1: 8 [7–9] vs 9 [9–11], G2: 10 [8–11] vs 11 [10–12]; G3: 11 [10–12] vs 12 [11–13]; G4: 11 [10–13] vs 13 [12–14], all p < 0.01). The ability of both scores to identify patients at higher risk of in-hospital mortality, was similar in different age groups (4C-MS: G1 0.77, G2 0.76, G3 0.68, G4 0.72; COVID-19 MRS: G1 0.67, G2 0.69, G3 0.69, G4 0.72, all p for comparisons between subgroups = NS). Both scores confirmed their good performance in predicting in-hospital mortality in all age groups, despite their different mortality rate.

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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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References

  1. Rahman S, Montero MTV, Rowe K, Kirton R, Kunik F Jr (2021) Epidemiology, pathogenesis, clinical presentations, diagnosis and treatment of COVID-19: a review of current evidence. Expert Rev Clin Pharmacol 14(5):601–621. https://doi.org/10.1080/17512433.2021.1902303

    Article  CAS  PubMed  Google Scholar 

  2. Lynch SM, Guo G, Gibson DS, Bjourson AJ, Rai TS (2021) Role of senescence and aging in SARS-CoV-2 infection and COVID-19 disease. Cells. https://doi.org/10.3390/cells10123367

    Article  PubMed  PubMed Central  Google Scholar 

  3. Becerra-Munoz VM, Nunez-Gil IJ, Eid CM, Garcia Aguado M, Romero R, Huang J et al (2021) Clinical profile and predictors of in-hospital mortality among older patients hospitalised for COVID-19. Age Ageing 50(2):326–334. https://doi.org/10.1093/ageing/afaa258

    Article  PubMed  Google Scholar 

  4. Lim WS, van der Eerden MM, Laing R, Boersma WG, Karalus N, Town GI et al (2003) Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax 58(5):377–382. https://doi.org/10.1136/thorax.58.5.377

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Guo L, Wei D, Zhang X, Wu Y, Li Q, Zhou M et al (2019) Clinical features predicting mortality risk in patients with viral pneumonia: the MuLBSTA score. Front Microbiol 10:2752. https://doi.org/10.3389/fmicb.2019.02752

    Article  PubMed  PubMed Central  Google Scholar 

  6. Knight SR, Ho A, Pius R, Buchan I, Carson G, Drake TM et al (2020) Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score. BMJ 370:m3339. https://doi.org/10.1136/bmj.m3339

    Article  PubMed  Google Scholar 

  7. Dong Y, Zhou H, Li M, Zhang Z, Guo W, Yu T et al (2020) A novel simple scoring model for predicting severity of patients with SARS-CoV-2 infection. Transbound Emerg Dis 67(6):2823–2829. https://doi.org/10.1111/tbed.13651

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Innocenti F, De Paris A, Lagomarsini A, Pelagatti L, Casalini L, Gianno A et al (2022) Stratification of patients admitted for SARS-CoV2 infection: prognostic scores in the first and second wave of the pandemic. Intern Emerg Med 17(7):2093–2101. https://doi.org/10.1007/s11739-022-03016-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Fumagalli C, Rozzini R, Vannini M, Coccia F, Cesaroni G, Mazzeo F et al (2020) Clinical risk score to predict in-hospital mortality in COVID-19 patients: a retrospective cohort study. BMJ Open 10(9):e040729. https://doi.org/10.1136/bmjopen-2020-040729

    Article  PubMed  Google Scholar 

  10. Fumagalli C, Ungar A, Rozzini R, Vannini M, Coccia F, Cesaroni G et al (2021) Predicting mortality risk in older hospitalized persons with COVID-19: a comparison of the COVID-19 mortality risk score with frailty and disability. J Am Med Dir Assoc 22(8):1588–1592. https://doi.org/10.1016/j.jamda.2021.05.028

    Article  PubMed  PubMed Central  Google Scholar 

  11. Aletreby WT, Mumtaz SA, Shahzad SA, Ahmed I, Alodat MA, Gharba M et al (2022) External validation of 4C ISARIC mortality score in critically ill COVID-19 patients from Saudi Arabia. Saudi J Med Med Sci 10(1):19–24. https://doi.org/10.4103/sjmms.sjmms_480_21

    Article  PubMed  PubMed Central  Google Scholar 

  12. Vallipuram T, Schwartz BC, Yang SS, Jayaraman D, Dial S (2023) External validation of the ISARIC 4C Mortality Score to predict in-hospital mortality among patients with COVID-19 in a Canadian intensive care unit: a single-centre historical cohort study. Can J Anaesth 70(8):1362–1370. https://doi.org/10.1007/s12630-023-02512-4

    Article  PubMed  Google Scholar 

  13. Yang S, Zhang Y, He Y, Liu S (2023) Comparison of prognostic scores for patients with COVID-19 presenting with dyspnea in the emergency department. J Emerg Med 65(6):e487–e494. https://doi.org/10.1016/j.jemermed.2023.07.013

    Article  PubMed  Google Scholar 

  14. Cunha LL, Perazzio SF, Azzi J, Cravedi P, Riella LV (2020) Remodeling of the immune response with aging: immunosenescence and its potential impact on COVID-19 immune response. Front Immunol 11:1748. https://doi.org/10.3389/fimmu.2020.01748

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Meftahi GH, Jangravi Z, Sahraei H, Bahari Z (2020) The possible pathophysiology mechanism of cytokine storm in elderly adults with COVID-19 infection: the contribution of “inflame-aging.” Inflamm Res 69(9):825–839. https://doi.org/10.1007/s00011-020-01372-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Xu KQ, Wei YQ, Giunta S, Zhou M, Xia SJ (2021) Do inflammaging and coagul-aging play a role as conditions contributing to the co-occurrence of the severe hyper-inflammatory state and deadly coagulopathy during COVID-19 in older people? Exp Gerontol. https://doi.org/10.1016/j.exger.2021.111423

    Article  PubMed  PubMed Central  Google Scholar 

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FI and LP gave substantial contributions to the conception and design of the work. GF, ADP, AL, EP, FP, MV, FT, and SM gave substantial contributions in the acquisition, and analysis of data for the work. GF, FP, and FC gave their contribution for the interpretation of data. LP and GF drafted the manuscript; FP and FI revised it critically for important intellectual content. RP gave the final approval of the version to be published.

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Correspondence to Francesca Innocenti.

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The study protocol was approved by the “Toscana—Area Vasta—Centro” inter-institutional ethic committee (NO. 17104) and was conducted in accordance with the Helsinki Declaration of 1964 (revised 2008).

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Retrospective study.

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Retrospective study.

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Pelagatti, L., Fabiani, G., De Paris, A. et al. 4C mortality score and COVID-19 mortality risk score: an analysis in four different age groups of an Italian population. Intern Emerg Med (2024). https://doi.org/10.1007/s11739-024-03551-5

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