MétaCan
Menu
Back to cohort
Record W2522601182 · doi:10.14740/cii.v1i1.8

A Case Report of Disseminated Tuberculosis With an Atypical Presentation

2016· article· en· W2522601182 on OpenAlexvenueno aff
Ratul Sarkar, Pratyay Hasan, Ahmedul Kabir

Bibliographic record

VenueClinical Infection and Immunity · 2016
Typearticle
Languageen
FieldMedicine
TopicDiagnosis and treatment of tuberculosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTuberculosisLungDifferential diagnosisSputumPresentation (obstetrics)LesionDermatologyFine-needle aspirationChronic coughSurgeryPathologyRadiologyInternal medicineBiopsyAsthma

Abstract

fetched live from OpenAlex

Here we report a 45-year-old male who presented to us with fever, loss of appetite, and painless bilateral testicular swellings. His routine chest X-ray revealed reticulo-nodular opacities in both lung fields. Ultra-sonogram of both testes revealed multiple fairly large space occupying lesions in both testes and epididymides. Initially thought to be a case of testicular tumor with lung metastases, the case later proved to be a case of chronic disseminated tuberculosis (TB), following fine needle aspiration and cytology of both testicular swellings and lung lesion. His sputum smear also revealed acid fast bacilli (2+). Interestingly, this patient had fever, loss of appetite, and cough 2 years ago, but remained well without specific anti-tubercular therapy in the intervening period. This case illustrates that common diseases can present in confusing and atypical ways. This cloaked appearance can misguide us to make a wrong diagnosis. Especially in a TB endemic zone such as ours, TB should not be excluded from the list of differential diagnoses, and should be actively searched. Clin Infect Immun. 2016;1(1):23-26 doi: http://dx.doi.org/10.14740/cii40e

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)0.004
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 score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.063
GPT teacher head0.403
Teacher spread0.340 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueClinical Infection and ImmunitySame topicDiagnosis and treatment of tuberculosisFrench-language works237,207