1. Epidemiology and Global Health
  2. Medicine

Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study

  1. Riku Klén
  2. Ivan A Huespe  Is a corresponding author
  3. Felipe Aníbal Gregalio
  4. Antonio Lalueza Lalueza Blanco
  5. Miguel Pedrera Jimenez
  6. Noelia Garcia Barrio
  7. Pascual Ruben Valdez
  8. Matias A Mirofsky
  9. Bruno Boietti
  10. Ricardo Gómez-Huelgas
  11. José Manuel Casas-Rojo
  12. Juan Miguel Antón-Santos
  13. Javier Alberto Pollan
  14. David Gómez-Varela  Is a corresponding author
  1. Turku PET Centre, University of Turku and Turku University Hospital, Finland
  2. Italian Hospital of Buenos Aires, Argentina
  3. 12 de Octubre University Hospital, Research Institute of Hospital 12 de Octubre (imas+12), Complutense University, Spain
  4. Vélez Sarsfield Hospital, Argentina
  5. Hospital Municipal de Agudos Dr Leónidas Lucero, Argentina
  6. Regional University Hospital of Málaga, Biomedical Research Institute of Málaga (IBIMA), University of Malaga, Spain
  7. Infanta Cristina University Hospital, Spain
  8. Division of Pharmacology & Toxicology, Department of Pharmaceutical Sciences, University of Vienna, Austria
https://doi.org/10.7554/eLife.85618
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  1. Riku Klén
  2. Ivan A Huespe
  3. Felipe Aníbal Gregalio
  4. Antonio Lalueza Lalueza Blanco
  5. Miguel Pedrera Jimenez
  6. Noelia Garcia Barrio
  7. Pascual Ruben Valdez
  8. Matias A Mirofsky
  9. Bruno Boietti
  10. Ricardo Gómez-Huelgas
  11. José Manuel Casas-Rojo
  12. Juan Miguel Antón-Santos
  13. Javier Alberto Pollan
  14. David Gómez-Varela
(2023)
Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study
eLife 12:e85618.
https://doi.org/10.7554/eLife.85618
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1 figure, 3 tables and 3 additional files

Figures

Figure 1
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Area under the receiver operating characteristic curve (AUROC), (A) and calibration slopes for training and testing database (B).

Tables

Table 1
Demographic characteristics, with missing data for each variable for the training database.

We also include the coefficients of each variable included in the model.

Values in training cohortMissing, n (%)Coefficient
Sex (female) – n (%)3539 (47.1%)00.067
Age in years – median (IQR)62.5 (47.8–78.7)0
Comorbidities
Cardiac insufficiency – n (%)65 (0.8%)0
Peripheral vascular disease – n (%)365 (5.0%)0
Brain vascular disease – n (%)332 (4.5%)0
Dementia – n (%)415 (5.5%)0
COPD – n (%)592 (8.0%)0
Asthma – n (%)543 (7.0%)0
Diabetes – n (%)1525 (20.0%)0
Kidney disease – n (%)81 (1.0%)0
Liver disease – n (%)864 (11.5%)0
Solid tumor – n (%)1312 (17.5%)0
HIV – n (%)59 (0.7%)0
Active smoker – n (%)521 (7.0%)0
Obesity – n (%)1590 (21.0%)0
Clinical parameters at admission
Temperature – Md (IQR)37.1 (36.5–37.9)53 (0.71)
SBP– Md (IQR)127 (113–142)104 (1.39)
Heart rate – Md (IQR)93 (80–106)76 (1.01)
Respiration rate – Md (IQR)22 (18–28)5103 (67.98)
O2_saturation (%) – Md (IQR)96 (93–98)102 (1.36)0.058
Laboratory parameters
Sodium (mmol/l) – Md (IQR)137 (134–139)264 (3.52)
Potassium (mmol/l) – Md (IQR)4.12 (3.79–4.5)272 (3.62)
Glucose (mg/dl) – Md (IQR)116 (101–142)306 (4.08)0.002
Leukocytes (×10³/mm³) – Md (IQR)6.8 (5.1–9.3)245 (3.26)
Neutrophils (×10³/mm³) – Md (IQR)4.9 (3.5–7.2)245 (3.26)0.068
Percentage of lymphocytes – Md (IQR)15.6 (9.9–22.6)245 (3.26)0.008
Hemoglobin (g/dl) – Md (IQR)13.8 (12.4–15.1)244 (3.26)0.044
Platelets (×10³/mm³) – Md (IQR)210 (161–272)245 (3.26)0.0006
Lactate (mmol/l) – Md (IQR)1.5 (1.2–2.2)7367 (98.14)
Creatinine (mg/dl) – Md (IQR)0.9 (0.72–1.16)342 (4.56)
LDH (U/l) – Md (IQR)330 (266–419)995 (13.2)
GOT (U/l) – Md (IQR)34 (25–51)737 (9.82)
GPT (U/l) – Md (IQR)27 (17–46)453 (6.03)
Bilirubine (mg/dl) – Md (IQR)0.5 (0.3–0.7)648 (8.63)
aPTT – Md (IQR)30 (28–33)549 (7.31)
Prothrombin activity (%) – Md (IQR)83 (74–93)545 (7.26)
Intercept4.235

  1. Model calculation C = A0 + A1* × 1 + A2* × 2 +A3* × 3 + A4* × 4 + A5* × 5 + A6* × 6 + A7* × 7. Example 4.23588…+−0.05808…*7.5 +…−0.06734*1 = −0.280637. aPTT: Activated Partial Thromboplastin Time, COPD: Chronic Obstructive Pulmonary Disease, GOT: glutamic-oxaloacetic transaminase, GPT: Glutamic-Pyruvic Transaminase, HIV : Human Immunodeficiency Virus, IQR: Intercuartile range, LDH: Lactate Dehydrogenase, SBP: Systolic Blood Pressure.

Table 2
Scores of the COVID-19 Early Warning Score (COEWS) predictive model. Green color means 0 points, yellow 1 point, ornge 2 points, and red 3 or more points.
Parameters6543210123456
SpO2 (%)<8585–8687–8889–9091–9293–95>95
Neutrophils (×10³/mm³)<1.51.5–8.08.1–9.09.1–
10.0		10.1–
11.0		11.1–12.012.1–
13.0		>13
Hemoglobin (g/dl)<910–1112–1718–19>19
Platelets (×10³/mm³)<150150–400>400
Lymphocytes (%)<88–20>20
Glucose (mg/dl)<9090–140141–187188–
234		235–
280		>280
SexMaleFemale
Global score
Low risk 0–3
Moderate risk 4–5
High risk 6–7
Critical risk >7
Table 3
Area under the receiver operating characteristic curve (AUROC) of the COVID-19 Early Warning Score (COEWS) predictive model calculated with the coefficients and with the score in vaccinated and unvaccinated patinetes.
AUROC (95% CI)VaccinatedNon-vaccinated
EWS LASSOEWS scoreEWS LASSOEWS score
Training (Spanish data 75%)0.753 (0.656–0.851)0.748 (0.659–0.838)0.721 (0.706–0.736)0.723 (0.709–0.738)
Internal validation (Spanish data 25%)0.712 (0.565–0.859)0.684 (0.513–0.855)0.704 (0.677–0.732)0.711 (0.685–0.738)
External validation (Argentinian data)0.743 (0.703–0.784)0.700 (0.654–0.745)0.767 (0.749–0.785)0.741 (0.723–0.759)
NEWS2 in all databases0.677 (0.601–0.752)0.648 (0.608–0.689)
Patients hospitalized after July 20210.718 (0.569–0.867)0.682 (0.508–0.856)0.677 (0.612–0.742)0.705 (0.646–0.764)

Additional files

Supplementary file 1

Original values plotted in the area under the receiver operating characteristic curve (AUROC) shown in Figure 1.

https://cdn.elifesciences.org/articles/85618/elife-85618-supp1-v2.xlsx
Supplementary file 2

Original values plotted in the calibration curve shown in Figure 1.

https://cdn.elifesciences.org/articles/85618/elife-85618-supp2-v2.xlsx
MDAR checklist
https://cdn.elifesciences.org/articles/85618/elife-85618-mdarchecklist1-v2.docx

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  1. Riku Klén
  2. Ivan A Huespe
  3. Felipe Aníbal Gregalio
  4. Antonio Lalueza Lalueza Blanco
  5. Miguel Pedrera Jimenez
  6. Noelia Garcia Barrio
  7. Pascual Ruben Valdez
  8. Matias A Mirofsky
  9. Bruno Boietti
  10. Ricardo Gómez-Huelgas
  11. José Manuel Casas-Rojo
  12. Juan Miguel Antón-Santos
  13. Javier Alberto Pollan
  14. David Gómez-Varela
(2023)
Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study
eLife 12:e85618.
https://doi.org/10.7554/eLife.85618