Dataset Information

Validation and repurposing of the MSL-COVID-19 score for prediction of severe COVID-19 using simple clinical predictors in a triage setting: The Nutri-CoV score.

ABSTRACT:

Background

During the COVID-19 pandemic, risk stratification has been used to decide patient eligibility for inpatient, critical and domiciliary care. Here, we sought to validate the MSL-COVID-19 score, originally developed to predict COVID-19 mortality in Mexicans. Also, an adaptation of the formula is proposed for the prediction of COVID-19 severity in a triage setting (Nutri-CoV).

Methods

We included patients evaluated from March 16th to August 17th, 2020 at the Instituto Nacional de Ciencias Médicas y Nutrición, defining severe COVID-19 as a composite of death, ICU admission or requirement for intubation (n = 3,007). We validated MSL-COVID-19 for prediction of mortality and severe disease. Using Elastic Net Cox regression, we trained (n = 1,831) and validated (n = 1,176) a model for prediction of severe COVID-19 using MSL-COVID-19 along with clinical assessments obtained at a triage setting.

Results

The variables included in MSL-COVID-19 are: pneumonia, early onset type 2 diabetes, age > 65 years, chronic kidney disease, any form of immunosuppression, COPD, obesity, diabetes, and age <40 years. MSL-COVID-19 had good performance to predict COVID-19 mortality (c-statistic = 0.722, 95%CI 0.690-0.753) and severity (c-statistic = 0.777, 95%CI 0.753-0.801). The Nutri-CoV score includes the MSL-COVID-19 plus respiratory rate, and pulse oximetry. This tool had better performance in both training (c-statistic = 0.797, 95%CI 0.765-0.826) and validation cohorts (c-statistic = 0.772, 95%CI 0.0.745-0.800) compared to other severity scores.

Conclusions

MSL-COVID-19 predicts inpatient COVID-19 lethality. The Nutri-CoV score is an adaptation of MSL-COVID-19 to be used in a triage environment. Both scores have been deployed as web-based tools for clinical use in a triage setting.

SUBMITTER: Bello-Chavolla OY

PROVIDER: S-EPMC7743927 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Validation and repurposing of the MSL-COVID-19 score for prediction of severe COVID-19 using simple clinical predictors in a triage setting: The Nutri-CoV score.

Bello-Chavolla Omar Yaxmehen OY Antonio-Villa Neftali E NE Ortiz-Brizuela Edgar E Vargas-Vázquez Arsenio A González-Lara María Fernanda MF de Leon Alfredo Ponce AP Sifuentes-Osornio José J Aguilar-Salinas Carlos A CA

PloS one 20201216 12

<h4>Background</h4>During the COVID-19 pandemic, risk stratification has been used to decide patient eligibility for inpatient, critical and domiciliary care. Here, we sought to validate the MSL-COVID-19 score, originally developed to predict COVID-19 mortality in Mexicans. Also, an adaptation of the formula is proposed for the prediction of COVID-19 severity in a triage setting (Nutri-CoV).<h4>Methods</h4>We included patients evaluated from March 16th to August 17th, 2020 at the Instituto Nacio ...[more]

PMID: 33326502

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Project description:AimsThe clinical manifestation and outcomes of thrombosis with thrombocytopenia syndrome (TTS) after adenoviral COVID-19 vaccine administration are largely unknown due to the rare nature of the disease. We aimed to analyse the clinical presentation, treatment modalities, outcomes, and prognostic factors of adenoviral TTS, as well as identify predictors for mortality.Methods and resultsPubMed, Scopus, Embase, and Web of Science databases were searched and the resulting articles were reviewed. A total of 6 case series and 13 case reports (64 patients) of TTS after ChAdOx1 nCoV-19 vaccination were included. We performed a pooled analysis and developed a novel scoring system to predict mortality. The overall mortality of TTS after ChAdOx1 nCoV-19 vaccination was 35.9% (23/64). In our analysis, age ≤60 years, platelet count <25 × 103/µL, fibrinogen <150 mg/dL, the presence of intracerebral haemorrhage (ICH), and the presence of cerebral venous thrombosis (CVT) were significantly associated with death and were selected as predictors for mortality (1 point each). We named this novel scoring system FAPIC (fibrinogen, age, platelet count, ICH, and CVT), and the C-statistic for the FAPIC score was 0.837 (95% CI 0.732-0.942). Expected mortality increased with each point increase in the FAPIC score, at 2.08, 6.66, 19.31, 44.54, 72.94, and 90.05% with FAPIC scores 0, 1, 2, 3, 4, and 5, respectively. The FAPIC scoring model was internally validated through cross-validation and bootstrapping, then externally validated on a panel of TTS patients after Ad26.COV2.S administration.ConclusionsFibrinogen levels, age, platelet count, and the presence of ICH and CVT were significantly associated with mortality in patients with TTS, and the FAPIC score comprising these risk factors could predict mortality. The FAPIC score could be used in the clinical setting to recognize TTS patients at high risk of adverse outcomes and provide early intensive interventions including intravenous immunoglobulins and non-heparin anticoagulants.

Dataset Information

Validation and repurposing of the MSL-COVID-19 score for prediction of severe COVID-19 using simple clinical predictors in a triage setting: The Nutri-CoV score.

Background

Methods

Results

Conclusions

Publications

Validation and repurposing of the MSL-COVID-19 score for prediction of severe COVID-19 using simple clinical predictors in a triage setting: The Nutri-CoV score.

Similar Datasets

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