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Hepatitis C infection in hemodialysis patients in Iran: A systematic review

2010· review· en· W1561848625 on OpenAlexvenueno aff
Seyed Moayed Alavian, Ali Kabir, Amir Ahmadi, Kamran Bagheri Lankarani, Mohammad Ali Shahbabaie, Masoud Ahmadzad-Asl

Bibliographic record

VenueHemodialysis International · 2010
Typereview
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemodialysisMeta-analysisHepatitis C virusConfidence intervalHepatitis CInternal medicinePopulationPrevalenceCross-sectional studyImmunologyEnvironmental healthVirusPathology

Abstract

fetched live from OpenAlex

Hemodialysis (HD) patients are recognized as one of the high-risk groups for hepatitis C virus (HCV) infection. The prevalence of HCV infection varies widely between 5.5% and 24% among different Iranian populations. Preventive programs for reducing HCV infection prevalence in these patients require accurate information. In the present study, we estimated HCV infection prevalence in Iranian HD patients. In this systematic review, we collected all published and unpublished documents related to HCV infection prevalence in Iranian HD patients from April 2001 to March 2008. We selected descriptive/analytic cross-sectional studies/surveys that have sufficiently declared objectives, a proper sampling method with identical and valid measurement instruments for all study subjects, and proper analysis methods regarding sampling design and demographic adjustments. We used a meta-analysis method to calculate nationwide prevalence estimation. Eighteen studies from 12 provinces (consisting 49.02% of the Iranian total population) reported the prevalence of HCV infection in Iranian HD patients. The HCV infection prevalence in Iranian HD patients is 7.61% (95% confidence interval: 6.06-9.16%) with the recombinant immunoblot assay method. Iran is among countries with low HCV infection prevalence in HD patients.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.047
GPT teacher head0.374
Teacher spread0.327 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
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

Citations66
Published2010
Admission routes1
Has abstractyes

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