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Record W4404769018 · doi:10.14440/bladder.2024.0036

Recurrent bladder malakoplakia: A rare bladder lesion mimicking malignancy

2024· article· en· W4404769018 on OpenAlexaff
Mukund Tinguria

Bibliographic record

VenueBladder · 2024
Typearticle
Languageen
FieldMedicine
TopicInfectious Disease Case Reports and Treatments
Canadian institutionsBrantford Energy (Canada)
Fundersnot available
KeywordsMalakoplakiaDysuriaMalacoplakiaPathologyMedicineMalignancyGenitourinary systemLesionUrotheliumUrinary systemUrinary bladderHistiocyteDifferential diagnosisCystoscopyUrologyInternal medicine

Abstract

fetched live from OpenAlex

Background: Malakoplakia is a rare granulomatous disease that commonly involves the genitourinary tract with the urinary bladder being the most frequently affected site. It is characterized by histiocytes containing distinct basophilic calcified inclusions called Michaelis–Gutmann bodies. It is believed to result from abnormally functioning macrophages, with inclusions representing calcifications around incompletely digested bacteria. Although its pathogenesis remains unknown, it is well-documented that the condition is associated with chronic urinary tract infections and immunosuppression. Grossly, it can present as soft, yellow plaques, nodules, bladder mass, or even without any visible lesion. It poses a huge diagnostic challenge as it tends to mimic malignancy. Case presentation: Described here is an 86-year-old female with recurrent bladder malakoplakia who presented with foul-smelling urine, hematuria, and dysuria. The clinicopathological features of this rare bladder lesion are described along with a review of the literature. Conclusion: Early identification of malakoplakia’s features by pathologists is essential for effective patient management. This condition should be considered in the differential diagnosis of bladder lesions, especially when Escherichia coli is present.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.309
Teacher spread0.283 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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