Iron Status, Development, and Behavior in Young Children in the Pennsylvania Foster Care System, an Exploratory Retrospective Medicaid Chart Review
Bibliographic record
Abstract
To 1) quantify the prevalence of iron deficiency (ID), iron deficiency anemia (IDA), and/or anemia in children in the Pennsylvania (PA) Foster Care System and 2) examine if a child's iron status is associated with the frequency of certain developmental and behavioral diagnoses. Retrospective cohort Medicaid chart review of children, from 6 mos to 10 yrs of age, in the PA Foster Care System using the most recently available data (2010–2015), extracted from the Medicaid Analytic eXtract database. Data from ICD-9 and ICD-10 codes which capture iron status and anemia, along with 16 relevant behavioral and 10 relevant developmental diagnoses were extracted. ICD codes for ID, IDA, and anemia cannot be differentiated; therefore, we used ID/anemia as a group label. The prevalence of ID/anemia was calculated and the prevalence of developmental delays and behavioral impairments among those diagnosed with ID/anemia was compared to those who were not diagnosed with ID/anemia. Group differences were determined using Pearson's chi-squared tests. From 2010–2015, there were 50,311 children, ages 6 mos to 10 yrs, in the PA Foster Care System. Of these, 1,365 (2.7%) were diagnosed with ID/anemia. Specific delays in development (a category with several sub-diagnoses) were reported in 48% of children with ID/anemia and 19% of children without diagnosed ID/anemia (χ2 = 679.42, p < 0.001). Moderate, severe, and profound intellectual disability (IQ < 49) were each reported in 0.5% of children with ID/anemia, and in children without diagnosed ID/anemia, in 0.16% (χ2 = 9.84, p = 0.002), 0.1% (χ2 = 19.79, p < 0.001), and 0.08% (χ2 = 26.44, p < 0.001), respectively. Adjustment disorder with depressive mood was reported in 1% of children with diagnosed ID/anemia and 0.6% of children without (χ2 = 4.10, p < 0.05). Irritability was different between groups (χ2 = 59.91, p < 0.001; 0.9% of children with ID/anemia and 0.1% of children without). In 2010–2015, 2.7% of children in PA Foster Care (6 mos-10 yrs old) were diagnosed as ID, IDA, and/or anemic. Frequency of developmental and behavioral diagnoses were generally greater in children with ID, IDA, or anemia, emphasizing the need for follow up of these children. The John L. Beard Endowment and the CHHD Limited Endowment Funds, The Pennsylvania State University.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".