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Perihospitalization hemoglobin‐epoetin associations in U.S. hemodialysis patients, 1998 to 2003

2007· article· en· W2018378406 on OpenAlexvenueno aff
Craig A. Solid, Robert N. Foley, David T. Gilbertson, Allan J. Collins

Bibliographic record

VenueHemodialysis International · 2007
Typearticle
Languageen
FieldMedicine
TopicErythropoietin and Anemia Treatment
Canadian institutionsnot available
FundersAmgen
KeywordsMedicineHemoglobinHemodialysisAnemiaEpoetin alfaErythropoietinInternal medicineGastroenterologySurgery

Abstract

fetched live from OpenAlex

While hospitalization is common for hemodialysis patients, perihospitalization associations between hemoglobin levels and epoetin doses are not well characterized. U.S. Medicare claims were used to identify 71,360 hemodialysis patients hospitalized from 1998 to 2003. Hemoglobin levels, epoetin doses, and epoetin responsiveness index (ERI) were compared by calendar year. In the prehospitalization month, the mean hemoglobin levels increased from 10.96 g/dL in 1998 to 11.76 in 2003 and the mean epoetin doses from 63,715 to 75,012 U; corresponding values in the hospitalization month were 10.53 and 11.19 g/dL, and 66,623 and 80,569 U. In each year, prehospitalization hemoglobin levels were achieved within 2 months, but ERI declined to prehospitalization levels within 12 months only in 2000. With mixed models, hemoglobin declines in the 3 prehospitalization months grew between 1998 (-0.1362 g/dL/month) and 2003 (-0.2003 g/dL/month). Epoetin responsiveness index slopes were J-shaped, with values of 287.9, 221.1, and 356.5U/month per g/dL in 1998, 2000, and 2003. In the 3 postadmission months, a modest increase in the rapidity of hemoglobin recovery was seen (+0.2538 g/dL/month in 1998, +0.2743 in 2003), with increasing rates of ERI change (+8.7 U/month/g/dL in 1998, +146.8 in 2003). While time to recovery of prehospitalization hemoglobin levels remained constant year to year, epoetin doses and ERI did not, suggesting that optimum perihospitalization anemia management practices have yet to be determined.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.030
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

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)0.0010.000

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 head0.009
GPT teacher head0.276
Teacher spread0.267 · 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 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

Citations16
Published2007
Admission routes1
Has abstractyes

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