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Record W1971902953 · doi:10.1093/ndt/17.suppl_5.8

The relationship of haemoglobin level and survival: direct or indirect effects?

2002· review· en· W1971902953 on OpenAlexaff
Adeera Levin

Bibliographic record

VenueNephrology Dialysis Transplantation · 2002
Typereview
Languageen
FieldMedicine
TopicErythropoietin and Anemia Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineKidney diseaseDiseaseInternal medicineErythropoietinClinical trialRenal functionSurvival analysisIntensive care medicine

Abstract

fetched live from OpenAlex

The relationship between haemoglobin (Hb) level and survival in patients with chronic kidney disease (CKD) is complex. This paper explores the physiological basis for the hypothesis that Hb level and survival are causally related in this patient group, and assesses the current state of knowledge from clinical studies. Issues related to the methodology and analysis of clinical studies limit the certainty with which conclusions regarding the direct relationship between Hb level and survival can be drawn. The data support the concepts that Hb level is associated with survival in patients both with and without CKD, that changes in Hb level are associated with cardiovascular disease (CVD), and that CVD is prevalent in patients with CKD. Hb level is affected by nutritional status, inflammation, and the availability and effectiveness of human recombinant erythropoietin (rHuEPO) therapy, as well as by the degree of kidney function. Thus, the complexity of the relationships between Hb level, CVD and survival in patients with CKD requires further study from both the mechanistic and the clinical perspective. Properly designed clinical trials with survival as an endpoint, as well as data from prospectively measured modifiers of Hb levels and other markers of CVD, are needed to determine the physiological and statistical interaction of these factors in clinical practice.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

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

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 head0.078
GPT teacher head0.332
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations40
Published2002
Admission routes1
Has abstractyes

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