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Record W2784006623 · doi:10.7326/acpjc-2018-168-2-010

Review: In adults, contrast-enhanced CT is not linked to acute kidney injury or mortality vs noncontrast CT

2018· letter· en· W2784006623 on OpenAlexaboutno aff
Tejas Patel, Vihas Patel

Bibliographic record

VenueAnnals of Internal Medicine · 2018
Typeletter
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAcute kidney injuryKidney diseaseInternal medicineNephrologyGuidelinePathology

Abstract

fetched live from OpenAlex

ACP Journal Club16 January 2018Review: In adults, contrast-enhanced CT is not linked to acute kidney injury or mortality vs noncontrast CTTejas Patel, MD, FASN, Vihas Patel, MDTejas Patel, MD, FASNIcahn School of Medicine at Mount Sinai, New York City, New York, USA (T.P.)Search for more papers by this author, Vihas Patel, MDZucker School of Medicine at Hofstra/Northwell, New Hyde Park, New York, USA (V.P.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/ACPJC-2018-168-2-010 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Source CitationAycock RD, Westafer LM, Boxen JL, et al. Acute kidney injury after computed tomography: a meta-analysis. Ann Emerg Med. 2017 Aug 12. [Epub ahead of print]. https://pubmed.ncbi.nlm.nih.gov/28811122Clinical Impact RatingsEmergency Med: Hospitalists: Nephrology: References1 McCullough PA, Choi JP, Feghali GA, et al. Contrast-induced acute kidney injury. J Am Coll Cardiol. 2016;68:1465-73. [PMID: 27659469] Google Scholar2 Canadian Association of Radiologists. Consensus guidelines for the prevention of contrast induced nephropathy. www.car.ca/uploads/standards%20guidelines/20110617_en_prevention_cin.pdf (accessed 7 Nov 2017). Google Scholar3 Mehran risk score calculator. www.zunis.org/Contrast-Induced%20Nephropathy%20Calculator.htm (accessed 7 Nov 2017). Google Scholar4 Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int Suppl. 2012:2:1-138. Google Scholar Author, Article, and Disclosure InformationAffiliations: Icahn School of Medicine at Mount Sinai, New York City, New York, USA (T.P.)Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, New York, USA (V.P.)This article was published at Annals.org on 2 January 2018. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics 16 January 2018Volume 168, Issue 2Page: JC10KeywordsAcute kidney injuryAcute renal failureCervical intraepithelial neoplasiaComputed axial tomographyMortalityObservational studiesOdds ratioRandomized trialsRetrospective studiesStatins ePublished: 16 January 2018 Issue Published: 16 January 2018 Copyright & PermissionsCopyright © 2018 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.029
GPT teacher head0.345
Teacher spread0.316 · 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 designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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