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Record W2760979631 · doi:10.1093/pch/19.6.e35-26

26: Prevalence, Practice Patterns and Hematological Outcomes of Young Canadian Children Identified with Non-Anemic Iron Deficiency (NAID): Implications of Screening in Primary Care Settings

2014· article· en· W2760979631 on OpenAlexaffabout
Kawsari Abdullah, JL Maguire, CS Birken, KE Thorpe, A.J.G. Hanley, Darcy Fehlings, PC Parkin

Bibliographic record

VenuePaediatrics & Child Health · 2014
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAnemiaLogistic regressionPediatricsIron deficiencyPrimary careIntervention (counseling)CohortIron-deficiency anemiaMultivariate analysisFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

There is emerging evidence that non-anemic iron deficiency (NAID) in early childhood may be association with poor health and developmental outcomes. Some guidelines recommend screening for iron deficiency anemia; however, the role of screening for NAID is unknown. Our overall objective was to evaluate outcomes following screening for NAID. Our specific objectives were: to determine the prevalence and risk factors associated with NAID in pre-school children; describe the practice patterns associated with the management of NAID in primary care settings; and describe the hematological outcomes of NAID with or without treatment. A cohort study of healthy children, aged one to five years, seen for primary health care between July 2008 and June 2012 was conducted through the TARGet Kids! practice based research network. Descriptive statistics were used to describe the prevalence, risk factors, practice patterns and the hematological outcomes of children identified with NAID (defined as serum ferritin level ≤12 μg/L and a hemoglobin level ≥110 g/L). The association between NAID and potential risk factors were examined using a multivariate logistic regression analysis. Of 2276 children undergoing screening, 155 had NAID, for a prevalence of 7% (95% CI 5.95 to 8.05%). Risk factors significantly associated with NAID included younger age and those with higher zBMI. An assessment of practice patterns revealed that for 57 of 155 children (37%) an intervention for NAID was recommended (diet, oral iron or both); and for 14 of 155 children (9%) a follow-up blood test was completed to reevaluate their iron status. An assessment of the hematological outcomes of NAID with treatment (n=57) revealed that of the 14 children with a follow-up blood test, 11 children resolved their NAID and in three cases NAID did not resolve. An assessment of the hematological outcomes of NAID without treatment (n=98), revealed that of the 26 children with a follow-up blood test, NAID resolved in 17, did not resolve in eight, and in one child progressed to iron deficiency anemia. This study shows that NAID is a prevalent condition in young Canadian children; that there is substantial practice variation in management of NAID following screening. Further research is necessary to understand the benefits of screening for NAID and evidence-based practice guidelines are needed to manage NAID in early childhood.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.007
GPT teacher head0.260
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes2
Has abstractyes

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