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S0623 Time Trends and Outcomes of Inter-Hospital Transfer in Patients With Upper Gastrointestinal Bleeding: A Nationwide Analysis

2020· article· en· W3093669489 on OpenAlexaff
Mary Sedarous, Quazim A. Alayo, Obioma Nwaiwu, Philip Dinh, Kavitha Subramanian, Philip N. Okafor

Bibliographic record

VenueThe American Journal of Gastroenterology · 2020
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Bleeding Diagnosis and Treatment
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineUpper gastrointestinal bleedingBleedEmergency medicineConfoundingInternal medicineSurgeryEndoscopy

Abstract

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INTRODUCTION: Inter-hospital transfers occur commonly in clinical practice. However, outcomes in acute upper gastrointestinal bleed (UGIB) transfer patients have not been well described. Using a national database, we aimed to describe time-trends and outcomes in patients transferred to new hospitals with UGIB within the United States. METHODS: Adults with UGIB (defined using ICD-9 codes for acute variceal hemorrhage -AVH and acute nonvariceal hemorrhage-ANVH) were identified in the 2007-2014 National Inpatient Sample. Trends in inter-hospital UGIB transfers, along with patient and hospital-level descriptors were examined. Outcomes including all-cause in-hospital mortality, upper endoscopy (EGD) utilization, length of stay (LOS), and total hospital costs (THC) were also assessed after controlling for confounding variables. RESULTS: We identified 1,523,519 ANVH discharges of which 66,974 (4.3%) were transferred to a recipient hospital; 218,748 AVH discharges were identified of which 7,857 (9%) were transfers. Between 2007- 2014, there was a rise in AVH and ANVH transfers in the US (P = 0.02, Figure 1). The mean age at transfer was lower in AVH compared to ANVH (55 vs. 64 years) with the majority of transfer patients being White, on Medicare, and living below the median level of income [Table 1]. Twenty-seven percent of UGIB transfers occurred during the weekends, predominantly to teaching hospitals 71.9% (ANVH) and 79.9% (AVH). While 52% of ANVH transfers went to hospitals with a low/medium- volume of UGIB discharges, majority of AVH transfers went to high-volume hospitals (54.2%). In addition to poor UGIB outcomes, the adjusted odds of all-cause in-hospital mortality was significantly higher in transferred ANVH patients (adjusted Odds Ratio [aOR] 1.81, 95% Confidence Interval [C.I.] (1.52-2.14) and in transferred AVH patients (aOR = 1.44, 95% CI 1.52-2.1). EGD utilization was also significantly lower in transferred patients at their new hospitals where they had longer LOS and incurred higher hospital costs [Table 2]. CONCLUSION: Inter-hospital transfers for UGIB are on the rise in the US and these patients appear to be a vulnerable group with significantly lower odds of getting an EGD when they arrive recipient hospitals but with significantly higher adjusted odds of death, LOS, THC at the new hospitals. More research is needed to identify high-performing recipient hospitals to improve UGIB outcomes in this high-risk group.Figure 1.: Trends in inter-hospital transfer of acute non-variceal hemorrhage (ANVH) and acute variceal hemorrhage (AVH).Table 1.: Baseline demographics and comorbidity of inter-hospital transfer patients with acute non-variceal hemorrhage (ANVH) and acute variceal hemorrhage (AVH)Table 2.: Crude and adjusted odds ratio and mean ratios of outcomes of inter-hospital transfer patients with acute non-variceal hemorrhage (ANVH) and acute variceal hemorrhage (AVH)

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)0.003
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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.006
GPT teacher head0.227
Teacher spread0.221 · 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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Citations2
Published2020
Admission routes1
Has abstractyes

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