The Age-AST-D Dimer (AAD) Regression Model Predicts Severe COVID-19 Disease

Abstract

Aim. Coronavirus disease (COVID-19) ranges from mild clinical phenotypes to life-threatening conditions like severe acute respiratory syndrome (SARS). It has been suggested that early liver injury in these patients could be a risk factor for poor outcome. We aimed to identify early biochemical predictive factors related to severe disease development with intensive care requirements in patients with COVID-19. Methods. Data from COVID-19 patients were collected at admission time to our hospital. Differential biochemical factors were identified between seriously ill patients requiring intensive care unit (ICU) admission (ICU patients) versus stable patients without the need for ICU admission (non-ICU patients). Multiple linear regression was applied, then a predictive model of severity called Age-AST-D dimer (AAD) was constructed ( n = 166 ) and validated ( n = 170 ). Results. Derivation cohort: from 166 patients included, there were 27 (16.3%) ICU patients that showed higher levels of liver injury markers ( P < 0.01 ) compared with non-ICU patients: alanine aminotrasnferase (ALT) 225.4 ± 341.2 vs. 41.3 ± 41.1 , aspartate aminotransferase (AST) 325.3 ± 382.4 vs. 52.8 ± 47.1 , lactic dehydrogenase (LDH) 764.6 ± 401.9 vs. 461.0 ± 185.6 , D-dimer (DD) 7765 ± 9109 vs. 1871 ± 4146 , and age 58.6 ± 12.7 vs. 49.1 ± 12.8 . With these finding, a model called Age-AST-DD (AAD), with a cut-point of <2.75 ( sensitivity = 0.797 and specificity = 0.391 , c − statistic = 0.74 ; 95%IC: 0.62-0.86, P < 0.001 ), to predict the risk of need admission to ICU ( OR = 5.8 ; 95% CI: 2.2-15.4, P = 0.001 ), was constructed. Validation cohort: in 170 different patients, the AAD model < 2.75 ( c − statistic = 0.80 (95% CI: 0.70-0.91, P < 0.001 ) adequately predicted the risk ( OR = 8.8 , 95% CI: 3.4-22.6, P < 0.001 ) to be admitted in the ICU (27 patients, 15.95%). Conclusions. The elevation of AST (a possible marker of early liver injury) along with DD and age efficiently predict early (at admission time) probability of ICU admission during the clinical course of COVID-19. The AAD model can improve the comprehensive management of COVID-19 patients, and it could be useful as a triage tool to early classify patients with a high risk of developing a severe clinical course of the disease.

Association of Prognostic Nutritional Index with Severity and Mortality of Hospitalized Patients with COVID-19: A Systematic Review and Meta-Analysis

“…As the symptoms of COVID-19 vary widely, ranging from no symptoms to critical illness requiring urgent medical attention [ 45 , 46 ], an accurate prediction of disease progression is essential to guiding medical resource allocation to reduce mortality [ 47 ]. For instance, assigning patients with a relatively minor condition (e.g., mild pneumonia) to ambulatory care and those with a severe disease to the intensive care unit (ICU) [ 48 ]. In countries where medical resources are limited, a simple feasible indicator of disease severity may be critical for the effective allocation of medical supplies and manpower.…”

Statistical Analysis and Machine Learning Prediction of Disease Outcomes for COVID-19 and Pneumonia Patients

“…In addition to the clinical indicators discussed above, other features highlighted in Figure 6 were also found to have associations with COVID-19. Higuera-De-La-Tijera et al. (2021) showed the aspartate aminotransferase (AST) levels of severe COVID-19 patients were significantly higher than non-severe COVID-19 patients since AST is related to liver function.…”

“…One of the major symptoms caused by COVID-19 is pneumonia, which is also a common infectious diseases threatening both human health and medical resources ( Zimlichman et al., 2013 ). Patients with mild pneumonia only need outpatient treatment, while severe patients have to be hospitalized or even admitted to the intensive care unit (ICU) for rescue ( Wei, 2020 ). Timely treatment for severe patients is significantly associated with reduced mortality ( Attaway et al., 2021 ).…”

Are platelet volume indices of clinical use in COVID-19? A systematic review

“…Two studies provided a comparison of patient groups combining severity and mortality (21,24). Many studies classified disease severity as patients who were admitted to an ICU or presented with at least one of the clinical manifestations listed in national guidelines for severe or critical diagnosis of COVID-19 (19,(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36). Only three studies reported subjects with similar ages between groups (p > 0.05) (30,37,38), and seven studies reported significantly different male:female ratios (p < 0.05) (18,22,37,(39)(40)(41)(42).…”