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Record W3134052966 · doi:10.1016/j.ekir.2021.02.024

Systematic Review and Meta-analysis of Herpes Zoster Vaccine in Patients With CKD

2021· article· en· W3134052966 on OpenAlexaboutno aff
Mohamad A. Hamad, Hilda Allam, Ashna Sulaiman, Karumathil Murali, Hicham I. Cheikh Hassan

Bibliographic record

VenueKidney International Reports · 2021
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsnot available
FundersU.S. Food and Drug Administration
KeywordsMedicineMeta-analysisHazard ratioConfidence intervalRandomized controlled trialAdverse effectInternal medicineRelative riskKidney diseaseCohort studyCochrane LibraryPlaceboAlternative medicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Chronic kidney disease (CKD) is a risk factor for herpes zoster (HZ) infection. Few studies have examined HZ vaccine (HZV) in this population. We conducted a systematic review and meta-analysis investigating the efficacy and safety of HZV in patients with renal disease (CKD, dialysis, and transplant). METHODS: MEDLINE, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) databases (up to May 2020) were searched for randomized controlled trials and nonrandomized controlled studies evaluating HZV in patients with CKD for effectiveness and adverse event risks. Studies without a control group (placebo or no vaccine) were excluded. Extraction of prespecified data and risk of bias assessments using the Newcastle-Ottawa scale for cohort studies and the Cochrane Risk of Bias Tool for randomized controlled trials were done by 3 authors. Random-effects meta-analysis was used to generate pooled treatment effects and 95% confidence intervals. RESULTS: = 0.8). CONCLUSIONS: HZV compared with control significantly lowers the risk of HZ without an increase in adverse events in CKD patients. However, significant heterogeneity was present. HZV should be actively considered in CKD patients because the prevalence of HZ is higher in this 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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.014
GPT teacher head0.285
Teacher spread0.271 · 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.

Study designMeta-analysis
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

Citations19
Published2021
Admission routes1
Has abstractyes

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