MATERIALS AND METHODS: This was an interventional study involving 382 blood donors who were deferred for low hemoglobin. The donors were divided equally into two groups: a control group and the intervention group. The control group received standard management for low hemoglobin deferral, which includes a short counseling session and a 1-month course of oral iron therapy. The intervention group used a mobile application in addition to standard management. The primary endpoint was the number of blood donors who returned during the 7 months of follow-up. The secondary endpoints were the hemoglobin increment at the first visit after the donors' deferral.
RESULTS: The return rate was higher in the intervention group, with 81.2% of the donors returning in the 7 months of follow-up compared to 66% of the control group (p<0.001). Male and female donors had mean hemoglobin increments of 1.0 g/dL and 0.7 g/dL, respectively, in the intervention group, compared to decrements of 0.2 g/dL and 0.4 g/dL, respectively, in the control group (p<0.001). Multivariable analysis showed a significant association between intervention method, education level and donation status on donor return (p=0.015, p<0.001, and p<0.001, respectively).
DISCUSSION: Higher return rate and greater hemoglobin increase in the interventional group could be attributed to features in the mobile application. Repeat donors had the highest odds of returning to donate, followed by those with a tertiary level of education, and those given the mobile application. This study showed that a mobile application was effective in enhancing donor return and increasing hemoglobin level among deferred blood donors on their first return.
MATERIALS AND METHODS: A MATLAB platform was used to develop software of algorithms based on image segmentation techniques to automate the calculation of patient size and SSDE. The algorithm was used to automatically estimate the individual size and SSDE of four CT dose index phantoms and 80 CT images of pediatric patients comprising head, thorax, and abdomen scans. For validation, the American Association of Physicists in Medicine (AAPM) manual methods were used to determine the patient's size and SSDE for the same subjects. The accuracy of the proposed algorithm in size and SSDE calculation was evaluated for agreement with the AAPM's estimations (manual) using Bland-Altman's agreement and Pearson's correlation coefficient. The normalized error, system bias, and limits of agreement (LOA) between methods were derived.
RESULTS: The results demonstrated good agreement and accuracy between the automated and AAPM's patient size estimations with an error rate of 1.9% and 0.27% on the patient and phantoms study, respectively. A 1% percentage difference was found between the automated and manual (AAPM) SSDE estimates. A strong degree of correlation was seen with a narrow LOA between methods for clinical study (r > 0.9771) and phantom study (r > 0.9999).
CONCLUSION: The proposed automated algorithm provides an accurate estimation of patient size and SSDE with negligible error after validation.