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Record W4408138391 · doi:10.3389/jpps.2025.14067

Ensuring guideline adherence and cost savings in stress ulcer prophylaxis practices in the intensive care unit: a pre-post education study

2025· article· en· W4408138391 on OpenAlexvenueno aff
Yunus Emre Ayhan, Namigar Turgut

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2025
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsnot available
Fundersnot available
KeywordsGuidelineMedicineStress ulcerIntensive care unitEmergency medicineIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Objective: This study aims to enhance adherence to the guideline through an educational program focused on reducing inappropriate use of stress ulcer prophylaxis (SUP) and cost savings in the intensive care unit (ICU). Method: This study was designed as a nonrandomized, controlled, prospective study created according to the pre-education (PreEd) and post-education (PostEd) evaluation model and conducted between January and July 2024. The appropriateness of SUP uses for the indication was evaluated according to the Sociedade Portuguesa de Cuidados (SPC) SUP guideline. Adherence rates to the SPC SUP guideline and the costs associated with nonadherence were evaluated. Results: 495 patients were included in the study, 244 in PreEd and 251 in PostEd. 58.2% of the patients were male, and the hospitalization was mainly for medical reasons (59.6%). The mean ± SD rate of patients with appropriate SUP indication was 38.3 ± 41.6% in PreEd and 47.8 ± 42.8% in PostEd (p = 0.005). The total costs of inappropriate indication and proton pump inhibitor use in PreEd and PostEd were 272 dollars and 246 dollars, respectively (p = 0.007). Accordingly, when inappropriate SUP agent use was calculated per patient in both periods, the total cost saving was 34 dollars. Conclusion: Inappropriate SUP use is common in the ICU. Adequate adherence to guidelines and proactive involvement of clinical pharmacists may reduce inappropriate SUP use and associated costs.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.186
GPT teacher head0.581
Teacher spread0.396 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

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