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Record W4395034556 · doi:10.1055/s-0044-1783059

Acute upper gastrointestinal bleeding in the UK: patient characteristics, diagnoses, and outcomes in the 2022 prospective audit of 5000 patients

2024· article· en· W4395034556 on OpenAlexaff
Gaurav Nigam, P.H. O'Connor Davies, Paula Dhiman, Lise J Estcourt, John Grant‐Casey, Elyanne M. Ratcliffe, Bhaskar Kumar, Raman Uberoi, Kathryn Oakland, Joanna Leithead, Sarah Hearnshaw, Vipul Jairath, Michael Murphy, Simon Travis, Adrian J. Stanley, Andrew Douds

Bibliographic record

VenueEndoscopy · 2024
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Bleeding Diagnosis and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineAuditMedical diagnosisProspective cohort studyIntensive care medicineGeneral surgerySurgeryRadiologyAccounting

Abstract

fetched live from OpenAlex

<strong>Aims:</strong> With the evolving landscape of acute upper GI bleeding (AUGIB) management, a comprehensive understanding of changing clinical outcomes becomes imperative. This report presents findings from the 2022 UK-wide multi-centre AUGIB audit, drawing comparisons to the previous 2007 study. <br> <strong>Methods:</strong> A prospective multi-centre audit, conducted between May 3 and July 2, 2022, included adults (≥16 years) presenting with AUGIB in UK hospitals. <br> <strong>Results:</strong> Data on 5101 patients (median age 69yr) from 152 participating hospitals are reported. New admissions with AUGIB (n=3905) were younger than inpatients developing AUGIB (median age 67.5 vs 74 yrs, respectively) with fewer comorbidities (63% vs 80%, respectively). At presentation, 17% (877/5101) had chronic liver disease (CLD), 30% (n=1528) a history of regular alcohol use, 7% (n=371) were taking non-steroidal anti-inflammatory drugs and 46%(n=2339) antiplatelets and/or anticoagulants (18% direct oral anticoagulants, 10% heparin and 3% warfarin). 83%(n=4228) patients had an inpatient endoscopy; 30%(1277/4228) had peptic ulcer disease (PUD), 9%(417/4228) had varices, and 27%(1135/4228) received endoscopic therapy. Reasons for no endoscopy (n=873) were: 56%(n=491) not clinically indicated/27%(n=234) outpatient procedure /18%(n=156) not for active treatment /7%(n=64) self-discharged /1%(n=7) transferred to other hospital /6%(n=51) death. 10% (416/4228) had evidence of further in-patient bleeding after index endoscopy. 9%(440) underwent&gt;1 endoscopy during inpatient stay; 0.8%(n=42) underwent surgery, 2.6%(n=134) had interventional radiology (IR) and 49%(n=2511) were transfused≥1 packed red blood cells; 4%(n=212) platelets; and 5%(n=282) fresh frozen plasma for AUGIB. Median length of stay was 5 days (IQR 3-9). In-hospital mortality was 9%(n=461); 5.7% in new admissions and 18.4% in inpatients. Comparisons with the 2007 audit revealed significant differences in patient profiles in 2022, including an increase in comorbid patients (67% vs 50%), higher prevalence of anticoagulant use (31% vs 13%), and a greater proportion with underlying CLD (17% vs 9%). A higher percentage of patients underwent inpatient endoscopy (83% vs 74%) in 2022, with reductions in PUD (30% vs 36%) and varices (9% vs 11%). There was a significant increase in those receiving endotherapies (27% vs 24%) and undergoing IR procedures (2.6% vs 1.2%), along with a lower likelihood of further in-patient bleeding after an index endoscopy (10% vs 13%), surgery (0.8% vs 1.9%), and in-hospital mortality (9% vs 10%). All differences were found to be statistically significant (p&lt;0.05). <br> <strong>Conclusions:</strong> Despite a more co-morbid population, there was reduced recurrent bleeding, need for surgery and in-hospital mortality for AUGIB since 2007. These improvements may be associated with improved management and better endoscopic therapy.

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 score0.002
Threshold uncertainty score0.452

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 head0.009
GPT teacher head0.267
Teacher spread0.258 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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