MétaCan
Menu
Back to cohort
Record W3088803586 · doi:10.14740/jmc3570

Severe Aplastic Anemia Presenting as Neutropenic Sepsis

2020· article· en· W3088803586 on OpenAlexvenueno aff
Natasha Faye Daniels, Charlotte Burrin, Raiiq Ridwan

Bibliographic record

VenueJournal of Medical Cases · 2020
Typearticle
Languageen
FieldDentistry
TopicOral Health Pathology and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAplastic anemiaPancytopeniaSepsisSurgeryNeutropeniaAnemiaPhysical examinationBone marrowInternal medicineChemotherapy

Abstract

fetched live from OpenAlex

A 40-year-old female with aplastic anemia presented with a gum abscess deteriorating into neutropenic sepsis. Infection is an incredibly rare initial manifestation of aplastic anemia even on a background of significant neutropenia, hence the uniqueness of this case. The patient's initial complaints were of a subacute history of heavy vaginal bleeding and unexplained bruising, however on examination in the emergency department the patient was also noted to be pyrexial with gingival hyperplasia and a left sided submandibular lymphadenopathy. Initial blood results were phoned through from the lab reporting pancytopenia, confirming clinical suspicion of neutropenic sepsis. Antibiotic therapy was commenced and maxillofacial review for her unrelenting jaw pain revealed a gum abscess ultimately requiring tooth extraction. The patient underwent bone marrow biopsy showing hypocellular marrow with erythroid-dominant, dysplastic hematopoiesis. A thorough panel of investigations to rule out secondary causes led to the diagnosis of aplastic anemia, for which the patient is currently being managed with oral ciclosporin plus eltrombopag-bridging therapy, plus counselling for the potential requirement for stem cell transplant.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.055
GPT teacher head0.367
Teacher spread0.312 · 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 designCase report
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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical CasesSame topicOral Health Pathology and TreatmentFrench-language works237,207