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Record W4408378844 · doi:10.1111/hdi.13224

The Use of Nocturnal Home Hemodialysis in Sickle Cell Disease

2025· article· en· W4408378844 on OpenAlexaffvenue
Ryan Chan, Daniela Arustei, Christopher T. Chan

Bibliographic record

VenueHemodialysis International · 2025
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineHemodialysisHome hemodialysisNocturnalDiseaseIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Despite being a rare cause of end-stage kidney disease (ESKD), sickle cell disease has broad kidney implications. Patients with both sickle cell disease and ESKD are at a greater risk of adverse events including mortality; while these patients can be managed with hemodialysis (HD), the use of nocturnal HD in sickle cell disease has not been previously described. METHODS: Here, we report a patient with sickle cell disease and ESKD who transitioned from conventional HD to nocturnal home HD. FINDINGS: Following the initiation of extended HD, we observed a significant improvement in her blood pressure (BP) parameters, serum potassium levels, and volume status. We describe the importance of nitric oxide (NO) in maintaining normal endothelial function, and how NO bioavailability is disrupted in both the sickle cell disease and ESKD populations. We speculated that our patient had significant vasoconstriction secondary to NO depletion causing uncontrolled hypertension and intravascular hemolysis (leading to recurrent hyperkalemia), and theorized that extended HD could have enhanced the bioavailability of NO, restoring the vasodilatory capability of her endothelium. DISCUSSION: Having a dialysis modality that counters the negative pathophysiologic endothelial changes in sickle cell disease and ESKD could result in fewer complications in this vulnerable population.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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