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Record W2276454067 · doi:10.1017/s0950268815003064

The treatment of HCV in patients with haemoglobinopathy in Kurdistan Region, Iraq: a single centre experience

2015· article· en· W2276454067 on OpenAlexaff
Nawfal R Hussein, I. Tunjel, Zarrin Basharat, alsayada M Taha, William L. Irving

Bibliographic record

VenueEpidemiology and Infection · 2015
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsQueen's University
FundersMedical Research Council
KeywordsGenotypeInternal medicineAlanine transaminaseMedicineGastroenterologyViral loadPopulationImmunologyBiologyHuman immunodeficiency virus (HIV)GeneGenetics

Abstract

fetched live from OpenAlex

Various variables that might influence the rapid and sustained virological response to recombinant PEG-IFN-α-2a were explored in Iraqi HCV-infected patients with haemoglobinopathy. Forty-three patients were evaluated for the relationship between rapid virological response (RVR), IL-28B polymorphism, viral load, liver enzyme levels, blood group, ultrasound findings, or HCV genotype and the sustained virological response (SVR) achievement. The overall RVR was 55·81% while the overall SVR was 53·49%. SVR in patients that achieved RVR was 82·61% (P = 0·0004). A significant association was found between initial alanine transaminase levels and viral load with SVR achievement (P = 0·025) and (P = 0·004), respectively. Thirty-two (74%) out of 43 of our samples were host genotyped at the IL-28B locus as CC, a significant association was found between CC group and SVR achievement (P = 0·04). Of our samples, 23/43 (53%) were typed as HCV genotype 4, 10/43 (23%) as genotype 1, 9/43 (20·9%) as genotype 3 and 1/43 (2·3%) as genotype 2. A significant association was found between genotype 3 and SVR achievement (P = 0·006). Multivariate analysis showed that only RVR achievement independently associated with SVR in the Iraqi population (P = 0·00). These results can be used to classify the patients requiring the more expensive new direct-acting antiviral drugs.

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 score0.037
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.077
GPT teacher head0.343
Teacher spread0.266 · 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
Published2015
Admission routes1
Has abstractyes

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