MétaCan
Menu
Back to cohort
Record W4409878413 · doi:10.1097/md.0000000000041959

Comparative evaluation of lung ultrasound versus chest X-ray for pneumothorax assessment post-invasive intrathoracic procedures: A case-costing evaluation

2025· article· en· W4409878413 on OpenAlexaff
Carter Winberg, Ross Prager, Chong Sung Kim, Matthew J. Meyer, Robert Arntfield

Bibliographic record

VenueMedicine · 2025
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicinePneumothoraxRadiologyRadiographyActivity-based costingChest radiographCost effectivenessEmergency medicineRisk analysis (engineering)

Abstract

fetched live from OpenAlex

BACKGROUND: Persistently increasing healthcare spending, paired with growing healthcare demand, highlights the need to identify mechanisms for cost savings. Chest radiography (CXR) is commonly performed following intrathoracic procedures to rule out pneumothorax (PTX) even if the clinical pretest probability is low. However, lung ultrasound (LUS) is known to have superior sensitivity, possibly representing a promising cost-saving tool. In response, we conducted an economic analysis comparing LUS and CXR to exclude PTX after invasive intrathoracic procedures. METHODS: A retrospective review of the radiology case-costing center was performed at an academic cardiothoracic surgical institution to identify the activity and cost of CXRs performed to rule out PTX following intrathoracic procedures. This cost was then compared to the theoretical cost of LUS. RESULTS: CXRs performed to rule out iatrogenic PTX were common with 22,274 radiographs completed and were economically burdensome, with an associated cost of $1.4 million. Portable CXR cost $75.46 per test, while CXR posteroanterior/lateral costs $41.64. Comparatively, LUS cost $38.38. Implementation would lead to cost savings of $559,537.10 or $41.58, on average, per patient. CONCLUSION: Given the superiority of LUS in terms of sensitivity and accuracy for PTX diagnosis, these findings underscore the compelling rationale for its broader integration into clinical practice.

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)0.013
metaresearch head score (Gemma)0.062
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 score0.013
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.062
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0060.003
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.141
GPT teacher head0.502
Teacher spread0.361 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueMedicineSame topicUltrasound in Clinical ApplicationsFrench-language works237,207