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Record W4402684931 · doi:10.14740/jmc4283

Navigating a Complex Case of Hypoplastic Right Lung With Bronchiectasis: A Ten-Year Journey

2024· article· en· W4402684931 on OpenAlexvenueno aff
Muhammad Umer Riaz Gondal, Grant Gillespie, Fawwad A Ansari, Swarup Sharma Rijal, Zainab Kiyani, Ayushi Lalwani, T.M.A. Khan, Syed Ayan Zulfiqar Bokhari, Ayushma Acharya, Ryan Zimmerman

Bibliographic record

VenueJournal of Medical Cases · 2024
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBronchiectasisLungLeft lungPediatricsInternal medicine

Abstract

fetched live from OpenAlex

Unilateral pulmonary hypoplasia (UPH) is a rare congenital disorder that presents rarely in adulthood. Most patients succumb to complications at a young age, and those who survive are rare and susceptible to frequent lifelong pulmonary infections. It has a high infant mortality rate. We present the case of a 66-year-old male with rheumatoid arthritis and severe persistent asthma who first presented to our emergency department in 2013 with worsening shortness of breath. Chest imaging with a computed tomography (CT) scan revealed right hemithorax volume loss with hypoplasia, honeycomb lung formation, and right mediastinal shift. He was treated with prednisone, inhalers, and antibiotics for asthmatic bronchitis. He continued to suffer frequent hospital admissions (56 to our hospital alone) over the next decade for pneumonia and asthma exacerbations. The hypoplastic right lung was deemed to be contributing to recurrent infections/inflammation, and he is currently being re-evaluated for a right pneumonectomy, as surgical resection is an option for localized bronchiectasis associated with recurrent respiratory infections.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0010.001

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 head0.066
GPT teacher head0.432
Teacher spread0.366 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical Cases→Same topicNeonatal Respiratory Health Research→French-language works237,207→