CAD effectiveness in the clinical trial
CAD, fibrosis
PULMONARY INVOLVEMENT, PNEUMOTHORAX, FIBROSIS, CAD
To study the effect of CAD on the involvement assessment problem, we used the AI-PROBE protocol with A total of 85 enrolled patients were randomised between the control arm (AI intervention off) and the experimental arm (access to AI results). An additional analysis exclusion criterion eliminated 9 studies that failed to mention the involvement quantification marker from the final radiological report. Across all randomised patients, 76 CT studies (CAD access, n = 38; No CAD access, n = 38) were successfully analysed for the study outcome. This was a representative, consecutive sample of COVID-19 patients examined at HOSP-TM between 21 February 2022 and 15 March 2022 who met the inclusion criteria. The participants (37 females and 39 males) were aged 20–89 years (median = 72 years, interquartile range (IQR) = 66–81 years) and covered a wide spectrum of clinical conditions ranging from asymptomatic or milder to critical COVID-19 cases, in both inpatient and outpatient care. The results of the patient selection process are presented in Fig. CONSORT-AI flow diagram describing the patient selection process.The patients’ true lung involvement ratios (reference standards) fit an exponential distribution (λ = 0.032). The overall mean pulmonary involvement was 32.319% (CAD access, m = 31.381%; No CAD access, m = 33.157%), and the distribution tail ended at a maximum involvement percentage of 78.030% (CAD access, M = 70.748%; No CAD access, M = 78.030%). The number of patients with other reported clinically important findings that could influence the quantitative analysis (e.g., pneumothorax, fibrosis) was also evenly distributed, with nine (23.7%) in the control group and seven (18.9%) in the intervention group. The root mean square error of the AI outputs was 4.206, with no apparent skewness between severity subgroups, as shown in Extended Data Figure Measured estimation differences between the two arms. (AI intervention reduced the mean overestimation difference from 9.471 ± 6.561 (95% CI) in the control arm, to 0.983% ± 5.181 (95% CI) (Fig. 