Modifiable factors associated with loss of donors in a human milk bank
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective To identify factors associated with the increased risk of loss of human milk donors (HM) to the milk bank (MB) of the Hospital General de Medellín (HGM) between 2014 and 2019. Methodology A total of 559 women who contacted the MB to be HM donors between 2014 and 2019 were evaluated according to their classification as contact eligible or ineligible to donate. A logistic regression model was used to identify the variables associated with the classification of a contact as ineligible. Results A total of 8.8% (n=49) of contacts were classified as ineligible. Ineligible contacts were 1.8 years older, with twice as many being exclusive donation method users. A higher percentage of ineligible contacts produced milk from preterm babies or colostrum. A higher percentage were classified as ineligible during the first years of the MB's operation, and a higher percentage had not undergone diagnostic tests for sexuallytransmitted infections in the last year. Additionally, 22.9% had been diagnosed with anemia during gestation (P<0.05). Contacting the MB between 2014-2016 (OR=3.08; P=0.004) and being from the exclusive donation method (OR=3.11; P=0.004) increased the risk of being classified as an ineligible contact. The absence of an HIV diagnostic test and a diagnosis of anemia during gestation were considered exclusion factors. Conclusion Modifiable factors increased the risk of a contact being classified as ineligible to donate human milk, identifying and treating them would allow increasing the number of HM donors to a MB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it