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Record W3126781814 · doi:10.4103/ejcdt.ejcdt_123_19

Disseminated tuberculosis in a pregnant immunocompetent healthcare worker

2020· article· en· W3126781814 on OpenAlexaff
N. Belloumi, Mersni Meriem, Mechergui Najla, Mejda Bani, Nizar Ladhari, Youssef Imen

Bibliographic record

VenueEgyptian Journal of Chest Diseases and Tuberculosis · 2020
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
Fundersnot available
KeywordsMedicineTuberculosisMiliary tuberculosisPregnancyPediatricsMycobacterium tuberculosisPopulationDiseaseSurgeryObstetricsInternal medicinePathology

Abstract

fetched live from OpenAlex

Health care workers (HCWs) have an increased risk of Mycobacterium Tuberculosis (TB) infection compared to general population. Pregnancy suppresses the Lymphocyte T-helper 1 (Th1) pro-inflammatory response. Frequent and consecutive pregnancies may also promote TB infection or reactivation of latent TB. But there is still no evidence of certain risk of severe disseminated infection. A 35-year-old pregnant woman, working as a laboratory officer, presented with fever, general weakness then acute respiratory failure. Miliary lung nodules were noted on chest X-ray. Under the impression of miliary tuberculosis, anti TB medication was administered. Likelihood of This diagnosis was due to her occupation, exposition to Mycobacterium Tuberculosis, clinical and radiologic findings. CT scan revealed cerebro-meningeal, pulmonary, splenic and ganglionary TB. The patient was treated successfully with ordinary anti TB combination regimen. Delivery and post partum was without complication. Cases of severe TB in an otherwise healthy pregnant woman are rare. This is an occupational disease to prevent.

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)0.001
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.303
Teacher spread0.280 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueEgyptian Journal of Chest Diseases and Tuberculosis→Same topicTuberculosis Research and Epidemiology→French-language works237,207→