Eleven routine clinical features predict COVID-19 severity uncovered by machine learning of longitudinal measurements.
Comput Struct Biotechnol J
; 19: 3640-3649, 2021.
Article
in English
| MEDLINE | ID: covidwho-1272373
ABSTRACT
Severity prediction of COVID-19 remains one of the major clinical challenges for the ongoing pandemic. Here, we have recruited a 144 COVID-19 patient cohort, resulting in a data matrix containing 3,065 readings for 124 types of measurements over 52 days. A machine learning model was established to predict the disease progression based on the cohort consisting of training, validation, and internal test sets. A panel of eleven routine clinical factors constructed a classifier for COVID-19 severity prediction, achieving accuracy of over 98% in the discovery set. Validation of the model in an independent cohort containing 25 patients achieved accuracy of 80%. The overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.70, 0.99, 0.93, and 0.93, respectively. Our model captured predictive dynamics of lactate dehydrogenase (LDH) and creatine kinase (CK) while their levels were in the normal range. This model is accessible at https//www.guomics.com/covidAI/ for research purpose.
ABG, arterial blood gas; APTT, activated partial thromboplastin time; AST, aspartate aminotransferase; AUC, area under the curve; BASO#, basophil counts; CFDA, China Food and Drug Administration; CK, creatine kinase; COVID-19; CRP, C-reactive protein; CT, computed tomography; ESR, erythrocyte sedimentation rate; GA, genetic algorithm; GGT, gamma glutamyl transpeptidase; HIS, hospital information system; LAC, lactate; LDH, lactate dehydrogenase; LOESS, locally estimated scatterplot smoothing; LOS, length of stay; Longitudinal dynamics; Machine learning; Mg, magnesium; NETs, neutrophil extracellular traps; NPV, negative predictive value; PCT, procalcitonin; PPV, positive predictive value; ROC, receiver operating characteristics; RT-PCR, reverse transcriptase -polymerase chain reaction; Routine clinical test; SARS-CoV-2; SHAP, SHapley Additive exPlanations; SVM, support vector machine; SaO2, oxygen saturation; Severity prediction; TT, thrombin time; eGFR, estimated glomerular filtration rate
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Cohort study
/
Observational study
/
Prognostic study
Language:
English
Journal:
Comput Struct Biotechnol J
Year:
2021
Document Type:
Article
Affiliation country:
J.csbj.2021.06.022
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