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Record W4394621556 · doi:10.14740/jh1251

Anorectal Infections in Neutropenic Leukemia Patients: A Common Clinical Challenge

2024· article· en· W4394621556 on OpenAlexvenueno aff
Rodrick Babakhanlou, Farhad Ravandi‐Kashani, Angel Guido Hita, Dimitrios P. Kontoyiannis

Bibliographic record

VenueJournal of Hematology · 2024
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNeutropeniaLeukemiaIntensive care medicinePathophysiologyComplicationImmunologyPathologyInternal medicineChemotherapy

Abstract

fetched live from OpenAlex

Anorectal infections in neutropenic leukemia patients are a significant and potentially life-threatening complication. The pathogenesis of this condition is not entirely understood and believed to be multifactorial, including mucosal injury as a result of cytotoxic drugs, profound neutropenia and impaired host defense. Establishing an early diagnosis is key and often made clinically on the basis of signs and symptoms, but also from imaging studies demonstrating perianal inflammation or fluid collection. The management of anorectal infections in neutropenic leukemia patients is not straightforward, as there are no well-conducted studies on this entity. This review seeks to provide a framework into the pathophysiology and clinical presentation of anorectal infections in neutropenic leukemia patients, propose a diagnostic approach and to discuss controversies in the management of this condition.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
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 head0.027
GPT teacher head0.365
Teacher spread0.338 · 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 designObservational
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

Citations5
Published2024
Admission routes1
Has abstractyes

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