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Record W2605520643 · doi:10.1111/hdi.12561

Iron deficiency anemia in chronic kidney disease: Uncertainties and cautions

2017· review· en· W2605520643 on OpenAlexvenueno aff
Rajiv Agarwal

Bibliographic record

VenueHemodialysis International · 2017
Typereview
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsMedicineAnemiaIron deficiencyAdverse effectKidney diseaseConstipationIntravenous ironHemodialysisIron-deficiency anemiaClinical trialHemoglobinInternal medicineSurgeryIntensive care medicine

Abstract

fetched live from OpenAlex

Anemia in chronic kidney disease is common and iron deficiency is an important cause. To repair iron-deficiency anemia, replacement of iron is needed. Iron can be replaced either by the oral route or by the intravenous route. In a meta-analysis, 5 of the 6 trials were short-term, 1 to 3 months, and compared to oral iron, the mean increase in hemoglobin with intravenous iron was only 0.31 g/dL. However, one of the studies included in this meta-analysis was 6 months long and had a mean decline in hemoglobin of 0.52 g/dL associated with intravenous iron administration. Given the short duration of most of the clinical trials comparing oral with intravenous administration of iron the long-term safety of these modes of administration of supplemental iron could not be assessed. Replacement of iron by the oral route is associated with mostly minor complications such as black stools, constipation, and abdominal discomfort. In contrast, intravenous administration of iron may lead to severe adverse events such as anaphylaxis and, as a more recent randomized trial has suggested, delayed complications such as infections and cardiovascular disease. Delayed complications of repeated intravenous iron use are difficult to recognize at an individual level therefore inpatients who have had recent cardiovascular events or are infected, intravenous iron should probably be avoided. Balancing safety and efficacy would require clinical judgment because 1 size may not fit all till we have better data to support the liberal use of parenteral iron.

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)0.037
metaresearch head score (Gemma)0.085
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.037
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.085
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0040.005
Science and technology studies0.0010.005
Scholarly communication0.0050.010
Open science0.0040.003
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0040.001

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 head0.042
GPT teacher head0.354
Teacher spread0.313 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations22
Published2017
Admission routes1
Has abstractyes

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