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Record W1969863048 · doi:10.1001/jama.299.10.1166

Does This Patient Have Bacterial Peritonitis or Portal Hypertension? How Do I Perform a Paracentesis and Analyze the Results?

2008· review· en· W1969863048 on OpenAlexaff
Camilla L. Wong

Bibliographic record

VenueJAMA · 2008
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineParacentesisAscitesSpontaneous bacterial peritonitisPortal hypertensionPeritonitisAdverse effectInternal medicineGastroenterologyCirrhosisSurgery

Abstract

fetched live from OpenAlex

CONTEXT: Abdominal paracenteses are performed in patients with ascites, most commonly to assess for infection or portal hypertension and to manage refractory ascites. OBJECTIVES: To systematically review evidence for paracentesis methods that may decrease risk of adverse events or improve diagnostic yield and to determine the accuracy of ascitic fluid analysis for spontaneous bacterial peritonitis or portal hypertension. DATA SOURCES: Relevant English-language studies from Medline (1966-April 2007) and EMBASE (1980-April 2007). STUDY SELECTION: Paracentesis studies evaluating interventions (use of preprocedure coagulation parameters, needle type, insertion location, ultrasound guidance, bedside inoculation into blood culture bottles, and use of plasma expanders in therapeutic taps) for reducing adverse events or improving the diagnostic yield, and studies assessing the accuracy of ascitic fluid biochemical analyses for spontaneous bacterial peritonitis or portal hypertension. DATA EXTRACTION: For technique studies, data on intervention and outcome; and for diagnostic studies, data on parameters for diagnosing spontaneous bacterial peritonitis and portal hypertension (ie, ascitic fluid white blood cell and polymorphonuclear leukocyte [PMN] count, ascitic fluid pH, blood-ascitic fluid pH gradient, and serum-ascites albumin gradient). DATA SYNTHESIS: Thirty-seven studies met inclusion criteria: 2 showed that obtaining preprocedure coagulation was likely unnecessary prior to paracentesis; 1 showed the 15-gauge, 3.25-inch needle-cannula results in less multiple peritoneal punctures [P = .05] and termination due to poor fluid return [P = .02] vs a 14-gauge needle in therapeutic paracentesis; 1 showed immediate inoculation of culture bottles improves diagnostic yield vs delayed (from 77% to 100% [95% CI for the difference, 5.3%-40.0%]); 9 evaluated therapeutic paracentesis, performed with or without albumin or nonalbumin plasma expanders, and found no consistent effect on morbidity or mortality; 16 showed the accuracy of biochemical analysis of ascitic fluid in patients suspected of having spontaneous bacterial peritonitis to increase the likelihood of spontaneous bacterial peritonitis (PMN count >250 cells/microL [summary likelihood ratio {LR}, 6.4] 95% CI, 4.6-8.8; ascitic fluid leukocyte count >1000 cells/microL [summary LR, 9.1] 95% CI, 5.5-15.1; pH < 7.35 [summary LR, 9.0] 95% CI, 2.0-40.6; or a blood-ascitic fluid pH gradient > or = 0.10 [LR, 11.3] 95% CI, 4.3-29.9) and other levels lowered the likelihood (PMN count < or = 250 cells/microL [summary LR, 0.2] 95% CI, 0.11-0.37; or a blood-ascitic fluid pH gradient < 0.10 [summary LR, 0.12] 95% CI, 0.02-0.77); and 4 showed the diagnostic accuracy of the serum-ascites albumin gradient lowers the likelihood of portal hypertension (< 1.1 g/dL [summary LR, 0.06] 95% CI, 0.02-0.20). CONCLUSIONS: Ascitic fluid should be inoculated into blood culture bottles at the bedside. Spontaneous bacterial peritonitis is more likely at predescribed parameters of ascitic PMN count or blood-ascitic fluid pH, and portal hypertension is less likely below a predescribed serum-ascites albumin gradient.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score0.574

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.029
GPT teacher head0.272
Teacher spread0.243 · 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 designOther design
Domainnot available
GenreReview

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

Citations123
Published2008
Admission routes1
Has abstractyes

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