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Record W4391873573 · doi:10.1093/jcag/gwad061.114

A114 IMPROVING THE QUALITY OF PARACENTESIS PRACTICES IN PEOPLE WITH ADVANCED CIRRHOSIS IN AN AMBULATORY CARE SETTING

2024· article· en· W4391873573 on OpenAlexaffabout
Mary Sedarous, E Lee, Amol A. Verma, Kieran L. Quinn, Gideon M. Hirschfield

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAmbulatoryParacentesisMedicineCirrhosisIntensive care medicineInternal medicineAscites

Abstract

fetched live from OpenAlex

Abstract Background Spontaneous bacterial peritonitis (SBP) is a lethal complication of decompensated cirrhosis carrying a 90% mortality rate when left untreated. Despite AASLD recommendations, there is a practice gap regarding fluid cell count (FCC) collection during paracentesis. Aims We initiated prospective quality improvement (QI) project to improve FCC collection in an ambulatory care setting from a baseline of 78% to a goal of 100% compliance between September 11, 2022 and April 17, 2023. Methods We examined the effects of a quality improvement initiative in 233 adult patient encounters with cirrhosis undergoing paracentesis in an ambulatory setting located within a quaternary care centre in Toronto, Canada within the study timeframe. Using a multidisciplinary approach, the quality improvement initiatives included focused groups, education regarding AASLD guidelines, development of a paracentesis bundle, and streamlining workflow process. Descriptive statistics were collected. Statistical analysis using run charts and p-charts were conducted using QI Macros. Approval was obtained from the QI Review Committee at the institution where this QI initiative took place. Results Baseline adherence for collecting ascitic FCC per paracentesis procedure was 78%. Inconsistencies during process mapping such as variations in documentation, printing FCC labels and consistency in FCC collection were identified as root causes. Thus, bedside paracentesis bundles were introduced to standardize process and improve workflow. Post-intervention, the FCC rate increased marginally to 79.6% with no special cause variation identified (Figure 1). Subgroup analysis demonstrated FCC collection rates of 100% amongst registered nurse (RN) and nurse practitioners (NP), 97% amongst resident physicians, and 92% amongst attending physicians. Subsequently, another subgroup analysis was completed demonstrating 97% FCC collection rate amongst general hepatology group, while 40% FCC rate amongst specialty hepatology group. Overall rate of SBP was 1.62% (N=3). Conclusions This prospective QI study revealed a gap in guidance pertaining to the role of ascitic fluid cell count collection in patients with cirrhosis undergoing paracentesis in ambulatory settings. Further studies ascertaining rationale for not sending FCC may be helpful in elucidating why there is a gap in clinical practice. Additionally conducting studies in ambulatory settings to assess FCC collection's impact on morbidity and mortality will provide vital evidence and clarity for the role of FCC in this vulnerable patient group. Figure 1: P-chart demonstrating percentage FCC Collection per week from September 11, 2022 to April 17, 2023. UCL indicates upper control limit; CL, center line; LCL, lower Control Limit. Funding Agencies Toronto Centre for Liver Disease funded the MSc QI program for Mary Sedarous (writer) who completed this study as her MSc QI project.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.187
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.284
Teacher spread0.273 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

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