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A COVID-19 specific multiparametric and ECG-based score for the prediction of in-hospital mortality: ELCOVID score

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Abstract

We aimed to develop and validate a COVID-19 specific scoring system, also including some ECG features, to predict all-cause in-hospital mortality at admission. Patients were retrieved from the ELCOVID study (ClinicalTrials.gov identifier: NCT04367129), a prospective, multicenter Italian study enrolling COVID-19 patients between May to September 2020. For the model validation, we randomly selected two-thirds of participants to create a derivation dataset and we used the remaining one-third of participants as the validation set. Over the study period, 1014 hospitalized COVID-19 patients (mean age 74 years, 61% males) met the inclusion criteria and were included in this analysis. During a median follow-up of 12 (IQR 7–22) days, 359 (35%) patients died. Age (HR 2.25 [95%CI 1.72–2.94], p < 0.001), delirium (HR 2.03 [2.14–3.61], p = 0.012), platelets (HR 0.91 [0.83–0.98], p = 0.018), D-dimer level (HR 1.18 [1.01–1.31], p = 0.002), signs of right ventricular strain (RVS) (HR 1.47 [1.02–2.13], p = 0.039) and ECG signs of previous myocardial necrosis (HR 2.28 [1.23–4.21], p = 0.009) were independently associated to in-hospital all-cause mortality. The derived risk-scoring system, namely EL COVID score, showed a moderate discriminatory capacity and good calibration. A cut-off score of ≥ 4 had a sensitivity of 78.4% and 65.2% specificity in predicting all-cause in-hospital mortality. ELCOVID score represents a valid, reliable, sensitive, and inexpensive scoring system that can be used for the prognostication of COVID-19 patients at admission and may allow the earlier identification of patients having a higher mortality risk who may be benefit from more aggressive treatments and closer monitoring.

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Data availability

The data underlying this article are available, upon reasonable request, by contacting the Corresponding Author.

Abbreviations

COVID-19:

Coronavirus disease 2019

CI:

Confidence interval

ECG:

Electrocardiogram

ED:

Emergency department

HR:

Hazard ratio

NTWs:

Negative T waves in anterior leads

RBBB:

Right bundle branch block

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Acknowledgements

This article is dedicated to the memory of Prof. Claudio Rapezzi.

Author information

Authors and Affiliations

  1. Unit of Cardiology, Department of Translational Medicine, Centro Cardiologico, Universita’ degli studi di Ferrara, Via Aldo Moro, 8, 44124, Cona, Ferrara, Italy

    Marco Zuin, Gabriele Guardigli, Michele Malagù, Francesco Vitali, Ottavio Zucchetti, Emanuele D’Aniello, Luca Di Ienno, Federico Gibiino & Matteo Bertini

  2. Unit of Cardiology, Maria Cecilia Hospital, Cotignola, Ravenna, Italy

    Roberto Ferrari, Paolo Cimaglia & Marco Manfrini

  3. Unit of Cardiology, Ospedale degli Infermi, Rimini, Italy

    Daniele Grosseto

  4. Unit of Cardiology, Ospedale Bufalini, Cesena, Italy

    Alessandro Corzani

  5. Unit of Cardiology, Ospedale Morgagni-Pierantoni, Forlì, Italy

    Marcello Galvani

  6. Unit of Cardiology, Ospedale S. Maria della Scaletta, Imola, Italy

    Paolo Ortolani

  7. Unit of Cardiology, Ospedale S. Maria delle Croci, Ravenna, Italy

    Andrea Rubboli

  8. Unit of Cardiology, Ospedale di Bentivoglio, Bentivoglio, Bologna, Italy

    Gianfranco Tortorici

  9. Unit of Cardiology, Ospedale Maggiore C.A. Pizzardi, Bologna, Italy

    Gianni Casella

  10. Unit of Cardiology, Ospedale del Delta, Lagosanto, Ferrara, Italy

    Biagio Sassone

  11. Unit of Cardiology, Arcispedale S. Maria Nuova, Reggio Emilia, Italy

    Alessandro Navazio

  12. Unit of Cardiology, Ospedale Guglielmo da Saliceto, Piacenza, Italy

    Luca Rossi

  13. Unit of Cardiology, Ospedale Civile di Castel San Giovanni, Piacenza, Italy

    Daniela Aschieri

  14. Istituto Clinico Covid3 Casalpalocco, GVM Care&Research, Rome, Italy

    Roberto Mezzanotte

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  1. Marco Zuin
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  2. Roberto Ferrari
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  3. Gabriele Guardigli
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  4. Michele Malagù
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Contributions

MB: Conceptualization, formal analysis, writing—original draft, validation and supervision. MZ: Conceptualization, writing—original draft. MM: Methodology, investigation, writing—review and editing. RF: Methodology; GG: Methodology; FV: Investigation; GF: Investigation; GP: Validation; AC: Validation; MG: Investigation; PO: Investigation; AR: Validation and investigation; GT: Investigation; BS: Investigation; AN: Validation; LR: Investigation; DA: Investigation; RM; Investigation; MMan: Investigation; PR: Validation; PC: Validation; GF: Validation; LDI: Validation; EDA: Validation; OZ: Validation; CR: Formal analysis & project administration; Methodology: MM, RF, GG, PR. All authors have read and approved the manuscript.

Corresponding author

Correspondence to Matteo Bertini.

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Conflict of interest

The authors declare that they have no conflict of interest to disclose statement.

Ethical approval

The study was approved by the local Ethics Committees and conducted according to the current Italian laws for the clinical research.

Informed consent

Informed consent was obtained by all patients enrolled.

Human and animal rights statement

All procedures performed in the study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Bioethics Committee of the Medical University of Ferrara (No. IRB n° 385/2020/Oss/AOUFe).

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Zuin, M., Ferrari, R., Guardigli, G. et al. A COVID-19 specific multiparametric and ECG-based score for the prediction of in-hospital mortality: ELCOVID score. Intern Emerg Med (2024). https://doi.org/10.1007/s11739-024-03599-3

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