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Record W2410819335 · doi:10.1177/082585971503100406

Indwelling Peritoneal Catheters for Managing Malignancy-Associated Ascites

2015· article· en· W2410819335 on OpenAlexaff
Benson Chun To Wong, Lorraine Cake, Lynn Kachuik, Kayvan Amjadi

Bibliographic record

VenueJournal of Palliative Care · 2015
Typearticle
Languageen
FieldMedicine
TopicPleural and Pulmonary Diseases
Canadian institutionsUniversity of OttawaOttawa Hospital
Fundersnot available
KeywordsAscitesMalignancyMedicineIntensive care medicineAscitic fluidGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

We investigated use of the tunnelled catheter in a large palliative population with malignancy-associated ascites employing retrospective analysis of a prospectively maintained patient database of tunnelled peritoneal catheter insertions for refractory malignancy-associated ascites or new rapidly accumulating ascites. We found that a 100 percent procedural success rate was achieved with 395 tunnelled catheters inserted in 386 patients. Catheters remained in situ for 66 days, on average. In a total of 22 cases (5.57 percent), complications developed. Nonfatal infections occurred most commonly--in 15 cases (3.80 percent). Ascites stopped reaccumulating in 16 cases (4.05 percent), leading to catheter removal. The mean Baseline Dyspnea Index was 3.79 (95 percent confidence interval [CI], 3.64-3.94); the mean Transitional Dyspnea Index postinsertion was 5.14 (95 percent CL, 4.94-5.34). In all, 13 patients completed serial European Organisation for Research and Treatment of Cancer Quality of Life Questionnaires. Postinsertion, overall quality of life improved significantly (p < 0.05), as did all functional domains and fatigue, pain, dyspnea, and appetite symptoms. The tunnelled peritoneal catheter is feasible and safe and causes minimal complications. Its use results in significant improvement in dyspnea and improvement in overall quality of life for a small number of patients.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.069
GPT teacher head0.334
Teacher spread0.265 · 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

Citations28
Published2015
Admission routes1
Has abstractyes

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