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Record W3134987613 · doi:10.1093/jcag/gwab002.021

A22 PREVALENCE OF IRON DEFICIENCY AND SUPPLEMENTATION PRACTICES FOR PATIENTS ON HOME PARENTERAL NUTRITION

2021· article· en· W3134987613 on OpenAlexaff
Lindsey Russell, Ramandeep Mangat, Jane Plant, Stine Kjærsgaard Hansen, D Armstrong, María Inés Pinto-Sánchez

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsHamilton Health SciencesMcMaster University
Fundersnot available
KeywordsMedicineHemoglobinAnemiaContext (archaeology)Iron deficiencyFerritinPediatricsDemographicsInternal medicineIron-deficiency anemiaParenteral nutritionSerum ironRetrospective cohort studyGastroenterologyDemography

Abstract

fetched live from OpenAlex

Abstract Background Iron deficiency (ID) is common in patients receiving parenteral nutrition (PN), likely due to a lack of iron in the PN formula. There is no clear consensus on how often serum iron should be tested or iron supplementation should be given, at which dose or route, in patients on long-term PN. Within the Hamilton Health Sciences (HHS) home PN (HPN) program, the prevalence of ID or iron deficiency anemia (IDA) is unknown. This knowledge will contribute to better iron prescribing practices with ultimate benefit on patient’s health. Aims To assess the prevalence of ID and IDA in patients enrolled in the HHS HPN Program. The secondary aim was to assess supplementation practices for patients enrolled in the HPN program according to gastrointestinal(GI) diagnosis and duration on PN. Methods We conducted a retrospective study including consecutive adult patients enrolled in the HHS-HPN program from January 2015 to November 2020. We collected data on demographics (age, sex, and GI diagnosis), iron supplementation (dose, duration, and route), and information related to iron-deficiency (hemoglobin, serum iron, ferritin, TIBC, and folate) at pre-set intervals (enrollment, 3, 6, 12, 18, 24, 30, 36, 48, 60 months) and last measured. ID was defined as ferritin ≤45μg/L or serum iron ≤9μmol/L. IDA was defined as hemoglobin <130g/L in men or <120g/L in women in the context of ID. Data were expressed as median (IQR) for continuous variables and n/N(%) for categorical variables. Chi2 was performed to assess differences between groups and logistic regression to assess predictors of ID and IDA. The analysis was conducted using SPSS software(v26). Results The analysis included 125 HPN patients (50 males, median age of 55 (40–65) years). Patients received PN for a median of 195 (83–521) days. The most common diagnoses were malignancy (36.8%) and inflammatory bowel disease (23.2%); the most common indications for HPN was short bowel (29.6%) and bowel obstruction (27.2%). Iron profiles were measured in 77% of patients. At enrollment, 42.2% of patients had ID and 38.9% had IDA. Only 13% of patients with ID and 22.8% with IDA had iron supplementation (Figure 1). A total of 38 patients received iron either oral or IV (oral=44.7% vs IV=55.3%; p=0.66). There was no correlation between low levels of serum iron or ferritin with iron supplementation (p=0.23, 0.45 respectively). Age, sex, diagnosis, or reason for PN did not correlate with ID or IDA at any time point. Conclusions Iron-deficiency and IDA are common in patients enrolled in the HHS HPN program independently of age, sex, diagnosis and reason for PN. Prospective studies are needed to implement the most effective way to ensure proper monitoring and treatment of iron deficiency in this population. Funding Agencies None

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)0.000
metaresearch head score (Gemma)0.001
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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.297
Teacher spread0.280 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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