key: cord-0914487-w36vg4vo
authors: Rubio-Rivas, Manuel; Mora-Luján, José María; Formiga, Francesc; Arévalo-Cañas, Coral; Lebrón Ramos, Juan Manuel; Villalba García, María Victoria; Fonseca Aizpuru, Eva Mª; Díez-Manglano, Jesús; Arnalich Fernández, Francisco; Romero Cabrera, Juan Luis; García García, Gema María; Pesqueira Fontan, Paula M.; Vargas Núñez, Juan Antonio; Freire Castro, Santiago Jesús; Loureiro Amigo, José; Pascual Pérez, Maria de los Reyes; Alcalá Pedrajas, José N.; Encinas-Sánchez, Daniel; Mella Pérez, Carmen; Ena, Javier; Gracia Gutiérrez, Anyuli; Esteban Giner, María José; Varona, José F.; Millán Núñez-Cortés, Jesús; Casas-Rojo, José-Manuel
title: WHO Ordinal Scale and Inflammation Risk Categories in COVID-19. Comparative Study of the Severity Scales
date: 2022-04-08
journal: J Gen Intern Med
DOI: 10.1007/s11606-022-07511-7
sha: af32cc9062413ca6719282857ec3c9e29c46aa29
doc_id: 914487
cord_uid: w36vg4vo

BACKGROUND: The WHO ordinal severity scale has been used to predict mortality and guide trials in COVID-19. However, it has its limitations. OBJECTIVE: The present study aims to compare three classificatory and predictive models: the WHO ordinal severity scale, the model based on inflammation grades, and the hybrid model. DESIGN: Retrospective cohort study with patient data collected and followed up from March 1, 2020, to May 1, 2021, from the nationwide SEMI-COVID-19 Registry. The primary study outcome was in-hospital mortality. As this was a hospital-based study, the patients included corresponded to categories 3 to 7 of the WHO ordinal scale. Categories 6 and 7 were grouped in the same category. KEY RESULTS: A total of 17,225 patients were included in the study. Patients classified as high risk in each of the WHO categories according to the degree of inflammation were as follows: 63.8% vs. 79.9% vs. 90.2% vs. 95.1% (p<0.001). In-hospital mortality for WHO ordinal scale categories 3 to 6/7 was as follows: 0.8% vs. 24.3% vs. 45.3% vs. 34% (p<0.001). In-hospital mortality for the combined categories of ordinal scale 3a to 5b was as follows: 0.4% vs. 1.1% vs. 11.2% vs. 27.5% vs. 35.5% vs. 41.1% (p<0.001). The predictive regression model for in-hospital mortality with our proposed combined ordinal scale reached an AUC=0.871, superior to the two models separately. CONCLUSIONS: The present study proposes a new severity grading scale for COVID-19 hospitalized patients. In our opinion, it is the most informative, representative, and predictive scale in COVID-19 patients to date. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-022-07511-7.

COVID-19 is a disease with a viral trigger that causes an inflammatory escalation leading to acute respiratory distress syndrome (ARDS) in some patients. 1 From the beginning of the pandemic, WHO proposed a severity classification based on the respiratory status of patients. 2 This strategy facilitated the therapeutic approach and the prediction of clinical worsening during admission in patients with COVID-19. On the other hand, it also served as a guide for the clinical trials (RCT) of the different therapies that have been proposed during this time. 3 However, COVID-19 is a particularly clinic-functionalradiological dissociated disease and characteristically produces a well-tolerated hypoxemia that does not reflect the underlying severity. A severity classification strategy has recently been proposed by our group based on the degrees of analytical inflammation. 4 The present study aimed to compare both strategies and a model based on a combination of both.

This is a retrospective cohort study with data on patients collected and followed up from March 1, 2020, to May 1, 2021, from the nationwide Spanish SEMI-COVID-19 Registry. The characteristics of the patients included in this registry have been extensively described previously. 5 This is a multicenter, nationwide registry with over 150 hospitals registered so far. All included patients were diagnosed by polymerase chain reaction (PCR) test taken from a nasopharyngeal sample, sputum, or bronchoalveolar lavage. The analytical data collected in the present study correspond to the analysis upon admission as well. The collection of data from each patient in terms of laboratory data, treatments, and outcomes was verified by the principal investigator of each center through the review of clinical records.

All participating centers in the register received confirmation from the relevant Ethics Committees, including Bellvitge University Hospital (PR 128/20).

The WHO ordinal clinical severity scale was collected at the time of hospital admission. The 9 points of the scale are as follows: 0: no clinical or virological evidence of infection; 1: ambulatory, no activity limitation; 2: ambulatory, activity limitation; 3: hospitalized, no oxygen therapy; 4: hospitalized, oxygen mask or nasal prongs; 5: hospitalized, noninvasive mechanical ventilation (NIMV) or high-flow nasal cannula (HFNC); 6: hospitalized, intubation and invasive mechanical ventilation (IMV); 7: hospitalized, IMV + additional support such as pressors or extracardiac membranous oxygenation (ECMO); 8: death.

As this was a hospital-based study, the patients included corresponded to categories 3 to 7 of the WHO ordinal scale. Categories 6 and 7 were grouped in the same category because there were few patients in each category and also because of difficulties in differentiating between the two in our database.

We previously reported the 3 categories of risk (low, intermediate, and high risk) based on the total lymphocyte count, and the C-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin, and D-dimer values taken at the time of admission. 4

The scale we propose in the present study combines the WHO ordinal scale and the degrees of inflammation. It thus results in 6 categories in hospitalized population by COVID-19 ( Fig. 1) : 3a: hospitalized, no oxygen therapy and not high risk of inflammation; 3b: hospitalized, no oxygen therapy and high risk of inflammation; 4a: hospitalized, oxygen mask or nasal cannula and not high risk of inflammation; 4b: hospitalized, oxygen mask or nasal prongs and high risk of inflammation; 5a: hospitalized, NIMV, HFNC, IMV, ICU, ECMO, or pressors and not high risk of inflammation; 5b: hospitalized, NIMV, HFNC, IMV, ICU, ECMO, or pressors and high risk of inflammation.

Regarding antiviral treatment, the use of antivirals (lopinavir/ ritonavir, 6 remdesivir 3 ), hydroxychloroquine, 7 azithromycin, 7 corticosteroids (CS), 8 and tocilizumab (TCZ) 9-11 was allowed according to the recommendations of the Spanish Ministry of Health.

The primary outcome of the study was in-hospital mortality. Secondary outcomes were the requirement of HFNC, NIMV, IMV, ECMO, and intensive care unit (ICU) admission.

Categorical variables were expressed as absolute numbers and percentages. Continuous variables are expressed as mean plus standard deviation (SD) in the case of parametric distribution or median [IQR] in the case of non-parametric distribution. Differences among groups were assessed using the chi-square test for categorical variables and ANOVA or Kruskal-Wallis test as appropriate for continuous variables. p values< 0.05 indicated statistical significance.

For the study of risk factors associated with in-hospital mortality, univariate and multivariate binary logistic regression was performed. For the latter, variables with p<0.10 in the univariate study plus age and gender were included. The differences in mortality were shown graphically using Kaplan-Meier curves with their log-rank test (event: death; 

A total of 21,962 patients were included in the Registry by May 2021. Of these, 17,225 patients had community (nonnosocomial) COVID-19 infection and their baseline oxygenation data were collected in the database for inclusion in the present study ( Figure S1 ). Table 1 shows the differences in overall baseline data between the different WHO severity categories. Table 1 shows the differences in overall baseline data between the different WHO severity categories.

Symptoms at the time of hospital admission are shown in Table 2 shows the analytical parameters between the different WHO categories. As expected, the higher the severity, the lower the PaO 2 /FiO 2 and lymphocyte count and the higher the CRP, LDH, and ferritin. It is noteworthy that between WHO categories 5 and 6/7 this progression in the analytical figures was not observed. As for D-dimer, differences were observed between the 4 groups but the differences were not progressive in parallel to the severity on the scale.

The patients classified as high risk in each of the WHO categories according to the degree of inflammation were as follows: 63.8% vs. 79.9% vs. 90.2% vs. 95.1% (p<0.001) ( Table 2 ; Fig. 2 ). The high-risk parameters elevated in each of the WHO categories are detailed in Table S2 . Likewise, the correlation between the WHO clinical severity categories and the inflammatory parameters is detailed in Table S3 .

As expected, those treatments with greater evidence of effectiveness (CS, TCZ, remdesivir, and heparin) were more frequently used in higher severity categories (Table S4 ).

The outcomes are shown in Table 3 and Figure S2 Figure 3 . Table S5 shows the regression model with our proposal combined with categories 3a to 5b. The AUC of this model was also 0.871 ( Figure S5 ).

In the present study, we demonstrate and propose a new and better method of classifying the clinical severity of patients admitted for COVID-19 according to respiratory status and degrees of analytical inflammation. We believe that it is more in line with reality and better defines subgroups of patients who were previously grouped in the same category. It also allows progress to be made in therapeutic strategies since it identifies patients at risk without waiting for subsequent respiratory deterioration.

Several severity scores have been proposed in the last 2 decades to assess community-acquired pneumonia severity: Pneumonia Severity Index (PSI), 12 CURB-65, 13 A-DROP, 14 SMART-COP, 15 NEWS2, 16 and qSOFA. 17 They focus on the respiratory state and organ failure. They were not developed for COVID-19 and, therefore, the inflammatory response is not represented in them. Thus, and although the AUC is high for some of them as predictive tool in COVID-19, 18 it is not a good tool in some inflamed patients with not yet impaired respiratory condition. Besides, these scores cannot lead trials focused on immunosuppressants in COVID-19. The WHO severity scale has been a good classifying and predictive tool for patients with COVID-19. 2 However, it has some shortcomings that should be recalled. On the one hand, category 4 defines patients hospitalized in a conventional ward with oxygen therapy. Obviously, a patient with nasal cannula at 2 L per minute is not the same as a patient with a 50% mask or with a reservoir, but in this classification they are included in the same group. On the other hand, and as we showed in our article, categories 5-6-7 do not differ so much in their basal and analytical characteristics and in their outcomes, and neither are these progressive. 4 Besides, we cannot forget it is not a validated scale. For this reason, we believe that these subcategories are informative of the resources used but do not provide added informative value of their clinical, analytical, or predictive characteristics and, therefore, should be grouped in the same category. Finally, the predictive leap in in-hospital mortality between categories 3 and 4, and subsequently 4 and 5, is very large. This means that, for simplicity's sake, there are groups of patients that have been grouped with others and are not completely well represented. The alternative model based on degrees of inflammation is a different approach to the disease and its severity. 4 It has the advantage of being able to identify patients at high risk who have not yet presented respiratory deterioration. In this sense, Figure S1 shows how in categories with mild and moderate disease there are about 60% and 80%, respectively, of patients characterized as high risk according to analytical degrees of inflammation.

The model we propose is a combination of both models. It is more informative and representative of the real severity of each patient. In addition, the multivariate study performed shows a slightly higher AUC than the other 2 models. Not only should it be a practical tool for clinical use, but we believe it should be the basis for RCTs, many of which have failed for these reasons. Especially those RCTs assessing immunosuppressants such as CS and TCZ without including and defining patient inflammation well could have benefited greatly from this clinical-analytical approach. [8] [9] [10] [11] The advantage of a model based on degrees of inflammation is the fact that the escalation of inflammation precedes respiratory deterioration. Thus, clinicians can detect earlier those patients susceptible to clinical worsening in the following days. On the other hand, COVID-19 is a clinicofunctional-radiological dissociated disease. Thus, a patient with significant hypoxemia can tolerate it acceptably without requiring additional ventilatory resources as in other diseases. It can also guide the anti-inflammatory/immunosuppressive therapies accepted in the treatment of COVID-19. Certainly, not all patients die from the accompanying inflammation of the disease; there are other accompanying predictive variables and, therefore, the WHO classification based on respiratory status and oxygen/ventilation support also provides predictive power. Surely this combination is what makes the hybrid model the most complete and predictive.

Our study has some obvious strengths. The patient sample is very large and comes from a wide range of hospitals of all types nationwide. The database is very large and includes numerous clinical and analytical variables at the time of hospital admission.

Our study also has some limitations that deserve comment. First, it is a retrospective study. Second, being a multicenter study, it gives a good idea of what COVID-19 has been in our country but introduces a certain degree of heterogeneity when it comes to including the data.

In conclusion, the present study proposes a new severity classification scale for patients hospitalized by COVID-19. In our opinion, it is the most informative, representative, and predictive scale in COVID-19 patients to date.

The online version contains supplementary material available at https://doi.org/10.1007/s11606-022-07511-7.

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Acknowledgements: We gratefully acknowledge all the investigators who participated in the SEMI-COVID-19 Registry. We also thank the SEMI-COVID-19 Registry Coordinating Center for their quality control data, logistic, and administrative support.