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Record W3096283968 · doi:10.1093/infdis/jiaa697

Risk Factors for Cytomegalovirus Reactivation and Association With Outcomes in Critically Ill Adults With Sepsis: A Pooled Analysis of Prospective Studies

2020· article· en· W3096283968 on OpenAlexaff
Hannah Imlay, Sayan Dasgupta, Michael Boeckh, Renee D. Stapleton, Gordon D. Rubenfeld, Ying Chen, Ajit P. Limaye

Bibliographic record

VenueThe Journal of Infectious Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsSunnybrook Health Science Centre
FundersNational Institute of Allergy and Infectious DiseasesNational Heart, Lung, and Blood InstituteNational Institutes of HealthMerck
KeywordsCritically illMedicineSepsisCytomegalovirusProspective cohort studyIntensive care medicineMeta-analysisCritical illnessImmunologyInternal medicineViral diseaseHerpesviridaeHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

We performed multivariable analysis of potential risk factors (including cytomegalovirus [CMV] reactivation) for clinical outcomes by day 28 (death or continued hospitalization, ventilator-free days, intensive care unit (ICU)-free days, hospital-free days) from pooled cohorts of 2 previous prospective studies of CMV-seropositive adults with sepsis. CMV reactivation at any level, >100 IU/mL, >1000 IU/mL, peak viral load, and area under the curve were independently associated with the clinical outcomes. We identified the potential effect size of CMV on outcomes that could be used as end points for future interventional trials of CMV prevention using antiviral prophylaxis in ICU patients with sepsis.

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)0.018
metaresearch head score (Gemma)0.025
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.025
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.013
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.017
GPT teacher head0.311
Teacher spread0.294 · 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
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

Citations28
Published2020
Admission routes1
Has abstractyes

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