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Record W4416273401 · doi:10.1016/j.psycr.2025.100299

Clozapine treatment in chronic lymphocytic leukaemia and pancytopenia

2025· article· en· W4416273401 on OpenAlexaff
Daniel Morgan, Gurvir Singh, Danilo Arnone

Bibliographic record

VenuePsychiatry Research Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsClozapinePancytopeniaSchizoaffective disorderChronic lymphocytic leukemiaNeutropeniaIbrutinibHematologyPsychopathology

Abstract

fetched live from OpenAlex

There is a paucity of literature regarding clozapine initiation in patients with haematologic malignancies. We present the case of a patient with chronic lymphocytic leukaemia (CLL) and schizoaffective disorder whose clozapine was discontinued and restarted. A woman in her 60s presented to the emergency department with hypotension and symptomatic pancytopenia. Clozapine was discontinued due to the risk of neutropenia during her admission to the haematology service. Bone marrow aspiration revealed that the pancytopenia was due to CLL clonal invasion, and the decision was made to restart clozapine. The subsequent development of hospital-acquired pneumonia led to clozapine discontinuation. An evaluation of the harms and benefits of clozapine re-initiation is discussed considering the possible additive effects of clozapine and CLL on degrading immune function, the risk of opportunistic infections, and the cytotoxic effects of CLL treatment. In medicated patients with stable psychopathology the reintroduction of clozapine after completion of CCL treatment can help minimise the risk of physical complications. Earlier reintroduction of clozapine may be justified in symptomatic patients with close monitoring. Informed decisions should be guided by patients’ preferences after judicious evaluation of risks and benefits. Haematology-psychiatry collaboration is essential to best manage cases with complex, comorbid psychiatric and haematological conditions.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.121
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.406
Teacher spread0.362 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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