ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019

Abstract

Background: Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19.Methods: 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients.Results: Age, neutrophil-to-lymphocyte ratio, D-dimer and C-reactive protein obtained on admission were identified by LASSO regression as predictors of mortality for COVID-19 patients. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC > 101) was more than 50%, respectively.Conclusion: The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management.

ABC2-SPH risk score for in-hospital mortality in COVID-19 patients: development, external validation and comparison with other available scores

“…C-reactive protein in an acute phase reactor with established prognostic prediction role in intensive care septic and non-septic patients 49,50 , and it has been included in different scores an independent predictor for mortality. 51,52…”

“…C-reactive protein in an acute phase reactor with established prognostic prediction role in intensive care septic and non-septic patients 49,50 , and it has been included in different scores an independent predictor for mortality. 51,52 The prognostic value of thrombocytopenia in patients with COVID-19 has shown in a recent meta-analysis 53 , and it was also included in other scores 10,51 . The exact explanation is still unknown, and it is probably multifactorial, related to direct infection of bone marrow cells by the virus, resulting in abnormal hematopoiesis; platelet destruction by the immune system; endothelial damage triggering platelet activation, aggregation and microthrombi in the lung; and abnormal platelet defragmentation in the lungs 53 .…”

“…A recent meta-analysis of 16 studies, which included 2783 surviving and 697 non-surviving cases, has shown significantly higher levels of D-dimer on admission in patients who died compared to the ones who were discharged 47 . This exam was included as a predictor in different scores 13,16,52,54,55 . Although D-dimer was collected in our study, D-dimer assays varied widely among different hospitals.…”

An Early Warning Tool for Predicting Mortality Risk of COVID-19 Patients Using Machine Learning

“…Weng et al [20] reported an early prediction score called ANDC to predict mortality risk for COVID-19 patients using 301 adult patients' data. Least absolute shrinkage and selection operator (LASSO) regression has identified age, neutrophil-to-lymphocyte ratio (NLR), D-dimer, and C-reactive protein (CRP) recorded during admission as mortality predictors for COVID-19 patients [20]. They have developed a nomogram demonstrating good performance and also derived an integrated score, ANDC, with its corresponding death probability.…”

The Age Again in The Eye of The Covid-19 Storm: Evidence-Based Decision Making.

“…Since the early days of the pandemic, enormous efforts have been made to identify epidemiological and clinical factors that can predict the severity of the disease [7][8][9][10][11][12][13][14][15]. These efforts have firmly established age as one of the crucial elements along with comorbidities closely associated with age, most notably hypertension, diabetes, and obesity [16][17][18][19][20][21][22][23]. Independently, the male sex has also been described to be related to a severe evolution [16, 18-20, 22, 23].…”