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Record W3156897604 · doi:10.1016/j.ekir.2021.03.561

POS-533 Association of end-stage renal disease with mortality in COVID-19 positive patients- A systematic review and meta-analysis

2021· review· en· W3156897604 on OpenAlexfundno aff
Abhishek Kumar, Rajkumar Chinnadurai, A. Ponnusamy

Bibliographic record

VenueKidney International Reports · 2021
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
FundersAlberta Health Services
KeywordsMedicineEnd stage renal diseaseMeta-analysisCoronavirus disease 2019 (COVID-19)Observational studyDiseasePandemicInternal medicineStage (stratigraphy)Mortality rate2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Intensive care medicinePathologyInfectious disease (medical specialty)Outbreak

Abstract

fetched live from OpenAlex

End-stage renal disease (ESRD) patients are a high-risk group in the COVID-19 pandemic due to their associated comorbidities. Several observational studies have highlighted a higher mortality rate in COVID-19 positive patients with ESRD. We conducted a systematic review and meta-analysis on studies comparing the association of ESRD on mortality in COVID-19 positive 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 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)0.006
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.022
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.101
GPT teacher head0.478
Teacher spread0.377 · 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 designMeta-analysis
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

Citations0
Published2021
Admission routes1
Has abstractyes

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