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Record W3209787956 · doi:10.12968/gasn.2021.19.8.36

Nurse-led early evaluation following corticosteroid prescription in patients with inflammatory bowel disease

2021· article· en· W3209787956 on OpenAlexaboutno aff
Philip Harvey, J Slater, Akram Algieder, Judith Jones, Beth Bates, Shanika De Silva

Bibliographic record

VenueGastrointestinal Nursing · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseMedical prescriptionUlcerative colitisRetrospective cohort studyAuditCorticosteroidHelplinePrednisoloneInternal medicineDiseaseEmergency medicineNursing

Abstract

fetched live from OpenAlex

Background The Toronto consensus for management of ulcerative colitis (UC) recommends early evaluation of UC patients 2 weeks after initiation on corticosteroids. A system for early evaluation of inflammatory bowel disease patients was established by specialist nurses in a secondary care centre. Aim To compare outcomes following early evaluation to the previous service. Methods All patients undergoing early evaluation over a 1-year period were prospectively audited and compared to a retrospective cohort of patients receiving prednisolone in the preceding year. Findings Of 140 patients included, 76 (54.3%) underwent early evaluation. All patients in the early evaluation group received drug education and details of the nurse helpline (17.1% of patients did not already have this). Of patients, 81.6% were prescribed Adcal, and 83.9% were on 5-aminosalicylates. Fewer admissions were observed within 6 months following early evaluation (8.6% vs. 23.4%, p=0.013). Conclusion Multiple benefits of early evaluation were observed, including a potential reduction in hospital admissions.

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 score0.018
Threshold uncertainty score0.948

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 head0.006
GPT teacher head0.233
Teacher spread0.228 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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