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Repeated blood donations can cause or exacerbate iron deficiency, and the incidence is higher among young blood donors and premenopausal women
.
Although fingertip hemoglobin is required and the minimum blood donation interval is 56 days, repeated donations can still cause and exacerbate iron deficiency
.
Past studies have identified several factors that increase the risk of iron deficiency in blood donors
.
However, no predictive model has yet been established to consider the hemoglobin delay and the competitive risk of collecting blood from donors with sufficient hemoglobin but low or lacking potential iron reserves
.
.
Although fingertip hemoglobin is required and the minimum blood donation interval is 56 days, repeated donations can still cause and exacerbate iron deficiency
.
Past studies have identified several factors that increase the risk of iron deficiency in blood donors
.
However, no predictive model has yet been established to consider the hemoglobin delay and the competitive risk of collecting blood from donors with sufficient hemoglobin but low or lacking potential iron reserves
.
Repeated blood donations can cause or exacerbate iron deficiency, and the incidence is higher among young blood donors and premenopausal women
.
Although fingertip hemoglobin is required and the minimum blood donation interval is 56 days, repeated donations can still cause and exacerbate iron deficiency
A foreign team used data from the REDS-II donor iron status evaluation study to develop a multi-class prediction model to estimate hemoglobin delay and the competitive risk of collecting blood from donors with sufficient hemoglobin but low or lack of potential iron reserves
.
The average multi-class AUC of each model configuration being evaluated was evaluated using 5-fold cross-validation, and the average evaluation was performed on 15 tuning sets (not including the integrated model)
.
Each configuration (model type and hyperparameter set) is drawn as a point
.
The distribution of each model type is shown
.
.
Each configuration (model type and hyperparameter set) is drawn as a point
.
The distribution of each model type is shown
.
The distribution of multi-category AUCs of 15 tuning sets for top-level integrated model configurations and their basic model configurations
.
For the ``standard'' and ``additional biomarker'' versions, the top set is the average of the base model
The distribution of multi-category AUCs of 15 tuning sets for top-level integrated model configurations and their basic model configurations
The relative variable importance of the top "standard biomarker" model
.
.
The relative variable importance of the top "extra biomarker" model
.
.
In the first return data set stratified by gender, the average risk trajectory of donors is 95% confidence interval
.
Compared with men, women have a higher risk of iron deficiency and delayed hemoglobin, but the average risk trajectory of low iron is similar
.
Compared with men, women have a higher risk of iron deficiency and delayed hemoglobin, but the average risk trajectory of low iron is similar
In the first returned data set, the average risk trajectory of blood donors stratified by heme dietary iron intake score was 95% confidence interval, which was calculated based on self-reported diet data at the time of index donation
.
On average, donors with the lowest one-third of hemoglobin iron intake have a higher risk of iron deficiency, but the risk trajectory for delayed hemoglobin or iron deficiency is similar
.
On average, donors with the lowest one-third of hemoglobin iron intake have a higher risk of iron deficiency, but the risk trajectory for delayed hemoglobin or iron deficiency is similar
The results showed that using standard biomarkers, the multi-class area under the receiver operating characteristic curve (AUC) of the top model was 77.
6% (95% CI [77.
3%-77.
8%])
.
With additional biomarkers, the multi-class AUC increased to 82.
8% (95% CI [82.
5%-83.
1%])
.
In the additional biomarker model, ferritin is the most important single variable, followed by the donation interval
.
We have identified three risk archetypes: "rapid recovery" (risk of any adverse result <10% on the 56th day after donation), "slow recovery" (risk of adverse result on the 56th day> 60%, to the 250th day Decrease to <35%) and "chronic high risk" (risk of adverse results on day 250>85%)
.
In summary , for most donors, a longer donation interval reduces the estimated risk of iron-related adverse consequences, but for some donors, the risk is still high
.
Tailoring safeguards based on personal risk assessments can reduce blood collection from donors with low iron reserves or iron deficiency
The results showed that using standard biomarkers, the multi-class area under the receiver operating characteristic curve (AUC) of the top model was 77.
Original source:
Original source:Russell, WA , Scheinker, D , Custer, B .
Russell, WA , Scheinker, D , Custer, B .
Individualized Risk Related adverse Trajectories for Iron-REPEAT Outcomes in Blood Donors .
Transfusion .
2021 ; .
1 - .
9 .
.
Https://doi.
org/10.
1111/trf.
16740 Russell, WA , Scheinker, D , Custer, B .
Individualized Risk Related adverse Trajectories for Iron-REPEAT Outcomes in Blood Donors .
Transfusion .
2021 ; .
1 - .
9 .
https://doi.
org/10.
1111/trf.
16740.
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