Abstract
Objective
A predictive model for hospitalization due to COVID-19 or death was developed in the placebo group (N=2,084) from a large clinical trial of colchicine in COVID-19 patients (N = 4,159).
Results
The 7 variables retained in the predictive model were age, gender, body-mass index, history of respiratory disease, use of diabetes drugs, use of anticoagulants, and use of oral steroids at the time of randomization. An optimal threshold value identified from the predictive model was used to classify high-risk patients (those with a predicted probability above the optimal threshold) and low-risk patients (those with a predicted probability below the optimal threshold). The number needed to treat to prevent 1 hospitalization or death with colchicine treatment decreased from 71 in the whole study population (N = 4,159) to 29 in the high-risk subgroup (N=1,692).
Conclusion
This model could serve to identify high-risk subjects who will particularly benefit from early colchicine therapy.
【저자키워드】 COVID-19, Risk factors, Hospitalization, Sex, Colchicine, 【초록키워드】 clinical trial, randomization, drugs, Gender, Probability, Respiratory disease, Patient, death, age, threshold, Anticoagulants, COVID-19 patient, Predictive, study population, subject, treat, threshold value, variable, high-risk patient, objective, Prevent, benefit, colchicine treatment, Result, predicted, identify, was used, retained, diabete, body-mass, colchicine therapy, oral steroid, the placebo group, 【제목키워드】 risk factor, patients with COVID-19, response to colchicine,