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Record W2767736302 · doi:10.2215/cjn.00630117

Residual Kidney Function and Peritoneal Dialysis–Associated Peritonitis Treatment Outcomes

2017· article· en· W2767736302 on OpenAlexaff
Rachel C. W. Whitty, Joanne M. Bargman, Alex Kiss, Linda Dresser, Philip C.W. Lui

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2017
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity Health NetworkSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineOdds ratioPeritoneal dialysisPeritonitisRenal functionCreatinineConfidence intervalInternal medicineDialysisUrologySurgery

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Residual kidney function contributes to the clearance of antibiotics excreted by the kidneys, lowering the antibiotic concentration, which may adversely affect the treatment of peritoneal dialysis-associated peritonitis. The objective of our study was to examine the relationship between residual kidneyfunction and peritonitis treatment outcomes. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Our study included 181 participants who experienced 339 episodes of Gram-positive, Gram-negative, and culture-negative peritoneal dialysis-associated peritonitis at a single centerfrom 2003 to 2010. Episodes were categorized according to participants' urinary creatinine clearance (0, >0-5, and >5 ml/min). The data were analyzed using generalized estimating equation models to determine the covariate-adjusted association between urinary creatinine clearance and treatment failure (defined as relapse or recurrent peritonitis episodes, peritoneal catheter removal, or death from any cause during peritonitis treatment). RESULTS: Among episodes of peritonitis due to Gram-positive organisms or culture-negative infections, those experienced by participants with urinary creatinine clearance >5 ml/min had significantly higher odds of treatment failure than episodes experienced by anuric participants (27 of 80 versus 20 of 119 episodes resulting in treatment failure for creatinine clearance >5 versus 0 ml/min; odds ratio, 6.80; 95% confidence interval, 2.37 to 19.6). Episodes experienced by participants with creatinine clearance >0-5 ml/min also had significantly higher odds of treatment failure than episodes experienced by anuric participants (14 of 64 episodes resulting in treatment failure for creatinine clearance >0-5 ml/min; odds ratio, 2.87; 95% confidence interval, 1.12 to 7.35). The odds of relapse and recurrent peritonitis among participants with creatinine clearance >5 ml/min was also significantly higher compared with in anuric participants (17 of 80 versus 12 of 119 episodes resulting in relapse and recurrence for creatinine clearance >5 versus 0 ml/min; odds ratio, 6.76; 95% confidence interval, 1.90 to 23.8). Among participants with Gram-negative peritonitis, creatinine clearance was significantly associated with neither treatment failure nor relapse and recurrent peritonitis. CONCLUSIONS: Residual kidney function as measured by greater urinary creatinine clearance was associated with treatment failure among participants with Gram-positive and culture-negative peritonitis.

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)0.002
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.045
GPT teacher head0.367
Teacher spread0.321 · 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

Citations68
Published2017
Admission routes1
Has abstractyes

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