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Record W4392865304 · doi:10.1093/rheumatology/keae175

Patient and health professional views on risk-stratified monitoring of immune-suppressing treatment in adults with inflammatory diseases

2024· article· en· W4392865304 on OpenAlexfundno aff
Amy Fuller, Jennie E. Hancox, Hywel C Williams, Tim Card, Maarten W. Taal, Guruprasad P. Aithal, Christopher P. Fox, Christian Mallen, James R. Maxwell, Sarah Bingham, Kavita Vedhara, Abhishek Abhishek

Bibliographic record

VenueLara D. Veeken · 2024
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
FundersDepartment of Health and Social CareNational Institute for Health and Care ResearchHealth Technology Assessment ProgrammeArthritis SocietyAstraZeneca
KeywordsMedicineThematic analysisAutonomyHealth careHealth professionalsImmune systemFlexibility (engineering)Stratified samplingQualitative researchIntensive care medicineFamily medicineImmunologyPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore the acceptability of an individualized risk-stratified approach to monitoring for target-organ toxicity in adult patients with immune-mediated inflammatory diseases established on immune-suppressing treatment(s). METHODS: Adults (≥18 years) taking immune-suppressing treatment(s) for at least six months, and healthcare professionals (HCPs) with experience of either prescribing and/or monitoring immune-suppressing drugs were invited to participate in a single, remote, one-to-one, semi-structured interview. Interviews were conducted by a trained qualitative researcher and explored their views and experiences of current monitoring and acceptability of a proposed risk-stratified monitoring plan. Interviews were transcribed verbatim and inductively analysed using thematic analysis in NVivo. RESULTS: Eighteen patients and 13 HCPs were interviewed. While participants found monitoring of immune-suppressing drugs with frequent blood-tests reassuring, the current frequency of these was considered burdensome by patients and HCPs alike, and to be a superfluous use of healthcare resources. Given abnormalities rarely arose during long-term treatment, most felt that monitoring blood-tests were not needed as often. Patients and HCPs found it acceptable to increase the interval between monitoring blood-tests from three-monthly to six-monthly or annually depending on the patients' risk profiles. Conditions of accepting such a change included: allowing for clinician and patient autonomy in determining individuals' frequency of monitoring blood-tests, the flexibility to change monitoring frequency if someone's risk profile changed, and endorsement from specialist societies and healthcare providers such as the National Health Service. CONCLUSION: A risk-stratified approach to monitoring was acceptable to patients and health care professionals. Guideline groups should consider these findings when recommending blood-test monitoring intervals.

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)0.020
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0020.003
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 head0.020
GPT teacher head0.313
Teacher spread0.293 · 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 designQualitative
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

Citations4
Published2024
Admission routes1
Has abstractyes

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