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Record W3209963010 · doi:10.1097/lbr.0000000000000821

Use of a Novel, Shortened, Indwelling Pleural Catheter (PleurX) for the Ambulatory Management of Malignant Pleural Effusion

2021· article· en· W3209963010 on OpenAlexaffabout
Jason Rajchgot, Kayvan Amjadi

Bibliographic record

VenueJournal of Bronchology & Interventional Pulmonology · 2021
Typearticle
Languageen
FieldMedicine
TopicPleural and Pulmonary Diseases
Canadian institutionsOttawa HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineCatheterMalignant pleural effusionAmbulatorySurgeryPleural effusionComplicationEffusionDemographics

Abstract

fetched live from OpenAlex

BACKGROUND: Indwelling pleural catheters are frequently used for the treatment of malignant pleural effusion. The PleurX catheter (Becton, Dickinson and Company) is a commonly used indwelling pleural catheter across Canada. The traditional PleurX catheter is designed with a long segment of tubing outside of the patient's chest, making insertion, drainage, and dressing changes awkward. Our clinic developed a novel, shortened, PleurX catheter that is easier to handle. METHODS: We conducted retrospective chart review for all patients treated with a shortened PleurX catheter at our center from December 2015 to May 2019 and demographics, clinical information, and complications were recorded retrospectively. A survey was designed and distributed to nurses experienced with the use of both catheters to elicit a preference between the short and long catheter. RESULTS: We analyzed data from 503 catheters placed in 491 patients. The most frequently encountered complications were loculation requiring fibrinolytic (2.4%), catheter dislodgement (1.2%), and pleural infection (0.6%). Of nurses surveyed, 74% preferred using the shortened PleurX catheter. CONCLUSION: Complication rates of the novel, shortened PleurX catheter are low. Further research is needed to better determine the optimal catheter length for ambulatory management of malignant pleural effusion.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.083
GPT teacher head0.323
Teacher spread0.239 · 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.

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
Published2021
Admission routes2
Has abstractyes

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