MétaCan
Menu
Back to cohort
Record W3031918431 · doi:10.4103/ijmy.ijmy_207_19

An evidence-based clinical pathway for the diagnosis of tuberculous lymphadenitis: A systematic review

2020· review· en· W3031918431 on OpenAlexaboutno aff
AzmawatiMohammed Nawi, Lavanyah Sivaratnam, MohdRizal Abdul Manaf

Bibliographic record

VenueInternational Journal of Mycobacteriology · 2020
Typereview
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTuberculous lymphadenitisExtrapulmonary tuberculosisTuberculosisSystematic reviewMycobacterium tuberculosisIntensive care medicineMEDLINEPediatricsPathology

Abstract

fetched live from OpenAlex

To achieve the World Health Organization end TB Strategy, early detection, and prompt treatment of not only pulmonary but also extrapulmonary tuberculosis (EPTB) should be achieved. The most common EPTB is tuberculous lymphadenitis, and the diagnosis is typically time-consuming. This review aimed to identify the best diagnostic pathway for preventing treatment delay and thus further complications. A systematic keyword search was done using four databases and other relevant publications and using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart to search for relevant articles that met the inclusion criteria. The quality of the articles was assessed using Newcastle-Ottawa Scale, and the articles were summarized based on the test for diagnosing tuberculous lymphadenitis. A total of ten articles were included for the synthesis of results, which compared the sensitivity and specificity of each diagnostic test for tuberculous lymphadenitis. The most promising test is the Xpert Mycobacterium tuberculosis/RIF, which has high sensitivity and specificity, but costs much more in comparison to the other tests. An ideal diagnostic method should include the combination of relevant patient history, clinical examination, and laboratory and radiological testing to avoid delays in treatment, misdiagnosis, and further complications.

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)0.003
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.331
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.167
GPT teacher head0.473
Teacher spread0.306 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations21
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of MycobacteriologySame topicMycobacterium research and diagnosisFrench-language works237,207