Performance of the quick COVID-19 severity index and the Brescia-COVID respiratory severity scale in hospitalized patients with COVID-19 in a community hospital setting

Rodriguez‐Nava, Guillermo; Yanez‐Bello, Maria Adriana; Trelles-Garcia, Daniela Patricia; Chung, Chul Won; Friedman, Harvey; Hines, David

doi:10.1016/j.ijid.2020.11.003

Cited by 50 publications

(67 citation statements)

References 23 publications

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“…Fourth, the selection of the analyzed EWSs has necessarily been partial. We are aware of the multitude of scores that can be analyzed, but those described above have been chosen considering timeliness, bibliographic consistency and level of implementation; however, for future studies it is necessary to evaluate the behaviors of other types of scores, such as the Quick COVID-19 severity index (qCSI), a tool designed especially for patients with COVID-19 [50,51].…”

Section: Discussionmentioning

confidence: 99%

Early Warning Scores in Patients with Suspected COVID-19 Infection in Emergency Departments

Martin-Rodríguez

Conty

Sanz-García

et al. 2021

JPM

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Early warning scores (EWSs) help prevent and recognize and thereby act as the first signs of clinical and physiological deterioration. The objective of this study is to evaluate different EWSs (National Early Warning Score 2 (NEWS2), quick sequential organ failure assessment score (qSOFA), Modified Rapid Emergency Medicine Score (MREMS) and Rapid Acute Physiology Score (RAPS)) to predict mortality within the first 48 h in patients suspected to have Coronavirus disease 2019 (COVID-19). We conducted a retrospective observational study in patients over 18 years of age who were treated by the advanced life support units and transferred to the emergency departments between March and July of 2020. Each patient was followed for two days registering their final diagnosis and mortality data. A total of 663 patients were included in our study. Early mortality within the first 48 h affected 53 patients (8.3%). The scale with the best capacity to predict early mortality was the National Early Warning Score 2 (NEWS2), with an area under the curve of 0.825 (95% CI: 0.75–0.89). The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive patients presented an area under the curve (AUC) of 0.804 (95% CI: 0.71–0.89), and the negative ones with an AUC of 0.863 (95% CI: 0.76–0.95). Among the EWSs, NEWS2 presented the best predictive power, even when it was separately applied to patients who tested positive and negative for SARS-CoV-2.

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Section: Discussionmentioning

confidence: 99%

Early Warning Scores in Patients with Suspected COVID-19 Infection in Emergency Departments

Martin-Rodríguez

Conty

Sanz-García

et al. 2021

JPM

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“…Rodriguez-Nava et al [18] developed clinical scores to predict ICU admission, and reported an AUC of .76. Although the proposed score is interpretable (like our logistic regression and decision tree models), it was developed on a relatively Fig.…”

Section: Discussionmentioning

confidence: 99%

Prediction of ICU admission for COVID-19 patients: a Machine Learning approach based on Complete Blood Count data

Famiglini

Bini

Carobene

et al. 2021

2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS)

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In this article we discuss the development of prognostic Machine Learning (ML) models for COVID-19 progression: specifically, we address the task of predicting intensive care unit (ICU) admission in the next 5 days. We developed three ML models on the basis of 4995 Complete Blood Count (CBC) tests. We propose three ML models that differ in terms of interpretability: two fully interpretable models and a blackbox one. We report an AUC of .81 and .83 for the interpretable models (the decision tree and logistic regression, respectively), and an AUC of .88 for the black-box model (an ensemble). This shows that CBC data and ML methods can be used for costeffective prediction of ICU admission of COVID-19 patients: in particular, as the CBC can be acquired rapidly through routine blood exams, our models could also be applied in resource-limited settings and to get fast indications at triage and daily rounds.

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“…The demographic data (age, sex, residence), past medical history [obesity, cardiovascular disease comorbidities (CVC), chronic pulmonary diseases (CPD), digestive comorbidities (DC), diabetes mellitus (DM), neoplasm (N), chronic kidney disease (CKD)], toxic abuse (smoker), clinical manifestations (stomatitis, abdominal pain, nausea, vomiting, diarrhea, tachycardia), values for complete blood count and liver function tests (transaminase), qPCR test results of nasal or pharyngeal exudate, imaging aspects on chest-CT, and length of hospital admission (LHA) (calculated from the first positive qPCR test to discharge), period from onset to hospitalization (POH), and Brescia-COVID Respiratory Severity Scale (BCRSS) for all patients included in the study were collected and subsequently analyzed. BCRSS was applied for the first time in Italy, for patients with COVID-19 and pneumonia, and aims to assess the clinical severity of each patient admitted to the hospital (23). Dyspnea, tachypnoea, chest imaging and oxygen saturation levels (SpO 2 )/partial pressure of arterial oxygen (PaO 2 ), Horowitz Index for Lung Function [PaO 2 /fraction of inspired oxygen (FiO 2 ) ratio], non-invasive or invasive ventilation are parameters used for the scoring.…”

Section: Methodsmentioning

confidence: 99%

Efficiency of antiviral treatment in COVID‑19

et al. 2021

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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is responsible for generating a global effort to discover urgent therapeutic solutions to limit the human damage caused by COVID-19. In the period of April to June 2020, 105 patients diagnosed with COVID-19 met the conditions for inclusion in the present study. They were treated with antiviral therapy according to local guidelines: D group (53 cases), treated with darunavir/ritonavir (DRV/r); and K group (52 cases), treated with lopinavir/ritonavir (LPV/r). Patients from the K group required 7.5 days of hospitalization less compared to those from the D group (P<0.001). The blood oxygen saturation values recorded in the groups were statistically different [K group (94.02±3.12%) vs. D group (92.13±4.24%), P=0.010]. The percentage of patients with unsatisfactory clinical evolution were non-significantly higher in the D group compared with the K group [20 (37.74%) vs. 12 (23.08%), P= 0.157]. We did not note statistically significant differences between the two groups tracked considering the values for the Brescia-COVID Respiratory Severity Scale (BCRSS) of the patients with unsatisfactory clinical evolution, nor of the chest CT' evolution after 10 days of therapy. We did not register significant adverse effects after antiviral therapy in the two groups. Antiviral therapy with LPV/r had some favorable results compared to DRV/r in patients with COVID-19. Both therapies were well tolerated.

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Performance of the quick COVID-19 severity index and the Brescia-COVID respiratory severity scale in hospitalized patients with COVID-19 in a community hospital setting

Cited by 50 publications

References 23 publications

Early Warning Scores in Patients with Suspected COVID-19 Infection in Emergency Departments

Early Warning Scores in Patients with Suspected COVID-19 Infection in Emergency Departments

Prediction of ICU admission for COVID-19 patients: a Machine Learning approach based on Complete Blood Count data

Efficiency of antiviral treatment in COVID‑19

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