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Record W3128752411 · doi:10.1093/tropej/fmaa131

Diagnostic Yield of Bronchoalveolar Lavage in Immunocompromised Children

2020· article· en· W3128752411 on OpenAlexaff
Jeff Wong, Kam‐Lun Ellis Hon, Karen Ka Yan Leung, Suyun Qian, Alexander K. C. Leung

Bibliographic record

VenueJournal of Tropical Pediatrics · 2020
Typearticle
Languageen
FieldMedicine
TopicPneumocystis jirovecii pneumonia detection and treatment
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineBronchoalveolar lavagePathogenAntimicrobialExact testPneumothoraxPneumoniaInternal medicineImmunologySurgeryPediatricsLungMicrobiology

Abstract

fetched live from OpenAlex

Results from early studies in the diagnostic yield of bronchoalveolar lavage (BAL) in immunocompromised adults and children were variable. This prospective study aimed to determine the diagnostic yield of BALs in immunocompromised children over the first 18 months of service at a newly established children's hospital. Relationship between BAL results and changes in antimicrobial management was also studied. Twenty-one bronchoscopic BALs were performed on 18 children; 14 BALs (66.7%) yielded at least 1 pathogen and 7 (33.3%) yielded no pathogen. Two pathogens were found in 2 samples, and 1 pathogen was identified in 12 samples. Bacteria (n = 7 patients), viruses (n = 8 patients) and fungus (Pneumocycstis jirovecii in one patient) were yielded. Of the 21 BALs, 8 (38.1%) were associated with changes in antimicrobial management (Fisher's exact test, p = 0.018). No significant side effects such as pneumothorax or pulmonary hemorrhages were observed in this series. In conclusion, BAL in immunocompromised children is rewarding and has potential to impact on antimicrobial management.

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)0.002
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.241
Teacher spread0.226 · 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 designObservational
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

Citations6
Published2020
Admission routes1
Has abstractyes

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