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Record W2519988759 · doi:10.2196/resprot.5872

EXpanding Treatment for Existing Neurological Disease (EXTEND): An Open-Label Phase II Clinical Trial of Hydroxyurea Treatment in Sickle Cell Anemia

2016· article· en· W2519988759 on OpenAlexvenueno aff
Angela Rankine‐Mullings, Courtney R Little, Marvin Reid, Deanne Soares, Carolyn Taylor‐Bryan, Jennifer Knight‐Madden, Susan E. Stuber, Asha Badaloo, Karen Aldred, Margaret Wisdom‐Phipps, Teresa Latham, Russell E. Ware

Bibliographic record

VenueJMIR Research Protocols · 2016
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
FundersInternational Fund for Agricultural DevelopmentUnited Nations High Commissioner for RefugeesUnited Nations Development ProgrammeNational Heart, Lung, and Blood InstitutePan American Health OrganizationInternational Labour OrganizationUnited Nations Population FundInternational Atomic Energy AgencyUNICEFUnited Nations Educational, Scientific and Cultural Organization
KeywordsMedicineOpen labelDiseaseClinical trialAnemiaSickle cell anemiaPediatricsIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cerebral vasculopathy in sickle cell anemia (SCA) begins in childhood and features intracranial arterial stenosis with high risk of ischemic stroke. Stroke risk can be reduced by transcranial doppler (TCD) screening and chronic transfusion therapy; however, this approach is impractical in many developing countries. Accumulating evidence supports the use of hydroxyurea for the prevention and treatment of cerebrovascular disease in children with SCA. Recently we reported that hydroxyurea significantly reduced the conversion from conditional TCD velocities to abnormal velocities; whether hydroxyurea can be used for children with newly diagnosed severe cerebrovascular disease in place of starting transfusion therapy remains unknown. OBJECTIVE: The primary objective of the EXpanding Treatment for Existing Neurological Disease (EXTEND) trial is to investigate the effect of open label hydroxyurea on the maximum time-averaged mean velocity (TAMV) after 18 months of treatment compared to the pre-treatment value. Secondary objectives include the effects of hydroxyurea on serial TCD velocities, the incidence of neurological and non-neurological events, quality of life (QOL), body composition and metabolism, toxicity and treatment response, changes to brain magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA), genetic and serologic markers of disease severity, and cognitive and pulmonary function. METHODS: This prospective Phase II trial will enroll children with SCA in Jamaica, between the ages of 2 and 17 years, with either conditional (170-199 cm/sec) or abnormal (≥ 200 cm/sec) TCD velocities. Oral hydroxyurea will be administered daily and escalated to the maximum tolerated dose (MTD). Participants will be seen in the Sickle Cell Unit (SCU) in Kingston, Jamaica monthly until achieving MTD, and then every 3 months. TCD will be performed every 6 months. RESULTS: Currently, 43 participants have been enrolled out of a projected 50. There was one withdrawal due to immigration, with no permanent screen failures. Of the 43 enrolled, 37 participants have initiated study treatment. CONCLUSIONS: This trial investigates the effects of hydroxyurea treatment at MTD in children with conditional or abnormal TCD velocities before transfusion therapy and may represent an important advance towards establishing a suitable non-transfusion protocol for stroke prevention in children with SCA. The trial outcomes will have profound significance in developing countries where the disease burden is highest. CLINICALTRIAL: ClinicalTrials.gov NCT02556099; https://clinicaltrials.gov/ct2/show/NCT02556099 (Archived by WebCite at http://www.webcitation.org/6k1yMAa9G).

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)0.002
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.477
GPT teacher head0.614
Teacher spread0.138 · 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 designNon-randomized trial
Domainnot available
GenreProtocol

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

Citations11
Published2016
Admission routes1
Has abstractyes

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