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Record W3092487946 · doi:10.1097/tp.0000000000003486

Influenza Virus Infection and Transplantation

2020· review· en· W3092487946 on OpenAlexaff
Tina Marinelli, Deepali Kumar

Bibliographic record

VenueTransplantation · 2020
Typereview
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineImmunologyTransplantationIntensive care medicinePopulationInfluenza vaccineChemoprophylaxisImmunogenicityImmunosuppressionOrgan transplantationOrthomyxoviridaeEpidemiologyInfluenza A virusVaccinationVirusInternal medicineImmune systemEnvironmental health

Abstract

fetched live from OpenAlex

Influenza infection poses significant risk for solid organ transplant recipients who often experience more severe infection with increased rates of complications, including those relating to the allograft. Although symptoms of influenza experienced by transplant recipients are similar to that of the general population, fever is not a ubiquitous symptom and lymphopenia is common. Annual inactivated influenza vaccine is recommended for all transplant recipients. Newer strategies such as using a higher dose vaccine or multiple doses in the same season appear to provide greater immunogenicity. Neuraminidase inhibitors are the mainstay of treatment and chemoprophylaxis although resistance may occur in the transplant setting. Influenza therapeutics are advancing, including the recent licensure of baloxavir; however, many remain to be evaluated in transplant recipients and are not yet in routine clinical use. Further population-based studies spanning multiple influenza seasons are needed to enhance our understanding of influenza epidemiology in solid organ transplant recipients. Specific assessment of newer influenza therapeutics in transplant recipients and refinement of prevention strategies are vital to reducing morbidity and mortality.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.163
GPT teacher head0.443
Teacher spread0.280 · 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
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

Citations13
Published2020
Admission routes1
Has abstractyes

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