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S784 Use of Antiplatelet Therapy Without Clear Medical Indications in Patients With Upper Gastrointestinal Bleeds

2023· article· en· W4387750674 on OpenAlexaffabout
Kevin Kecskemeti, Mark Borgaonkar, Jerry McGrath

Bibliographic record

VenueThe American Journal of Gastroenterology · 2023
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Bleeding Diagnosis and Treatment
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicineMedical prescriptionMedical recordUpper gastrointestinal bleedingRetrospective cohort studyClopidogrelDemographicsCohortInternal medicineEmergency medicinePediatricsEndoscopyAspirin

Abstract

fetched live from OpenAlex

Introduction: Recent studies have shown increasing usage of antiplatelet medication to treat a variety of chronic conditions. Although these medications improve survival in certain conditions, antiplatelet agents increase the risk of upper GI bleeds (UGIBs). This study aimed to assess the prevalence of antiplatelet therapy and their medical indications in patients who had UGIBs at our institution. Methods: This retrospective cohort study recruited all patients from a single academic tertiary gastroenterology practice who received endoscopic treatment for upper GI bleeds during the years 2015-2022. Patients were identified using physician billing codes for endoscopic treatment for upper GI bleeds. Information regarding demographics, medications, and previous GI diagnoses were collected using endoscopy reports and medication records from the local hospital medical database. We documented antiplatelet medication status at time of endoscopic treatment for UGIB. We assessed medical indication for the antiplatelet therapy based on the Canadian Cardiovascular Society guidelines on antiplatelet therapy1. We analyzed the patient’s physician narrative reports for these conditions and the documented rationale for first prescribing the medication. Furthermore, we defined a recent medication prescription as any therapy that was initiated 3 months prior to the UGIB. All the information was coded using a standardized data sheet and entered into SPSS for data analysis. Results: Data were collected from 102 upper GI bleeds. The average patient age of the sample was 62.9 years old. The sample consisted of 70 males (68%) and 32 females (31%). In total, 27 patients were prescribed antiplatelet therapy at time of the UGIB. The most common medical indications for antiplatelet therapy were previous PCI with 33%, CABG with 15% and stroke with 11% (Table 1). Meanwhile, 30% of all patients prescribed antiplatelet therapy had no clear medical indication for therapy. 33% of patients began their antiplatelet therapy within 3 months of their UGIB. Conclusion: At the time of endoscopic treatment for upper GI bleed, a third of patients on antiplatelet medications had no clear medical indications. This may place patients at risk of UGIBs without gaining reciprocal benefits from therapy. Research at other centers involving compressive patient datasets can help further investigate this phenomenon. Resources: 1-https://pubmed.ncbi.nlm.nih.gov/21640290/ Table 1. - Medical Indications for Antiplatelet Therapy Medical Indications Number of Patients Percentage PCI 9 33.3 CABG 4 14.8 Stroke 3 11.1 ACS 2 7.4 No clear indication 8 29.6 Total 27 100.0 PCI (percutaneous coronary intervention), CABG (coronary artery bypass graft), ACS (acute coronary syndrome).

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)0.002
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.269
Teacher spread0.251 · 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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Citations0
Published2023
Admission routes2
Has abstractyes

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