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Record W3092070847 · doi:10.1177/2054358120964115

Utility of Abdominal Imaging in Peritoneal Dialysis Patients Presenting With Peritonitis

2020· article· en· W3092070847 on OpenAlexaffabout
Emilie Trinh, Joanne M. Bargman

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2020
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity Health NetworkMcGill University Health Centre
Fundersnot available
KeywordsMedicinePeritoneal dialysisPeritonitisUnivariate analysisIntensive care unitHemodialysisRadiologyRetrospective cohort studySurgeryInternal medicineMultivariate analysis

Abstract

fetched live from OpenAlex

Background: Peritonitis remains a major complication in peritoneal dialysis (PD). Abdominal imaging is often performed in the setting of peritonitis to evaluate for concomitant intra-abdominal processes. However, the usefulness of this procedure is unknown. Objective: The aim of this study was to assess the prevalence of abdominal imaging performed in the setting of PD peritonitis and to evaluate clinical parameters associated with abnormal imaging results to identify clinical situations in which radiographic examinations are informative. Design: This is a retrospective cohort study. Setting: The study was conducted at the Toronto General Hospital, Ontario, Canada. Patients: We studied 166 episodes of PD peritonitis in 114 patients between January 1, 2011, and June 30, 2016. Measurements: Baseline demographics, characteristics of PD peritonitis, and characteristics of abdominal imaging performed. Methods: The association between relevant clinical parameters and abnormal abdominal imaging was examined using a univariate and multivariate logistic regression model. Results: Abdominal imaging (computed tomography [CT] scan or ultrasound) was performed in 68 cases (41%). Patients were more likely to undergo imaging if they required hospitalization, were admitted to the intensive care unit (ICU), had polymicrobial or fungal organisms causing peritonitis, had relapsing/recurrent/refractory peritonitis, had an indication for hemodialysis or PD catheter removal, or presented with hypotension, tachycardia, or an elevated serum lactate. Of the imaging performed, abnormalities were found in 32 cases (47%). The most common findings were bowel obstruction, intra-abdominal collection, and biliary abnormalities. In the univariate analysis, ICU admission (43.3% vs 14.3%, P < .01) and need for temporary or permanent hemodialysis (62.5% vs 30.6%, P < .01) were associated with imaging abnormalities. Importantly, the peritonitis organism was not associated with abnormal imaging results. In a multivariate analysis, ICU admission was the only significant clinical parameter associated with imaging abnormalities with an odds ratio (OR) of 4.4 (95% confidence interval [CI]: 1.1-17.4, P = .04). Limitations: Single-center study, small sample size, and lack of detailed information on the exact indications leading to abdominal imaging. Conclusions: Abdominal imaging is commonly performed in the setting of PD peritonitis. Abnormalities are not infrequent and are present in almost half of the cases, with need for ICU admission being the most significant clinical parameter associated with abnormal findings. Therefore, abdominal imaging should be performed in carefully selected patients with PD peritonitis, especially if there is evidence of hemodynamic instability. While the finding of fungal or polymicrobial peritonitis was a driver for abdominal imaging, the presence of these organisms did not predict radiologic abnormalities.

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)0.007
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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".

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Citations6
Published2020
Admission routes2
Has abstractyes

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