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Record W2584597757 · doi:10.1182/blood.v116.21.392.392

Understanding Treatment Preferences In Patients with Primary Immune Thrombocytopenia Contemplating Splenectomy: A Qualitative Study

2010· article· en· W2584597757 on OpenAlexaff
Karen Wang, Donald M. Arnold, Emmy Arnold, Nancy M. Heddle, John G. Kelton, Cathy Charles

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSplenectomyMedicineInterquartile rangeImmune thrombocytopeniaInter-rater reliabilityInternal medicinePediatricsSurgeryPlateletPsychologySpleenRating scale

Abstract

fetched live from OpenAlex

Abstract Abstract 392 Introduction Primary immune thrombocytopenia (ITP) is a common autoimmune bleeding disorder characterized by low platelet counts and an increased risk of bleeding. Recent consensus recommendations on ITP management (Provan, Blood 2010) emphasize the need for individualized treatment strategies based on patient preference; however little is known about which treatments patients prefer and why. Although splenectomy is most likely to induce a durable remission, uptake of splenectomy by patients and physicians is variable and a general tendency towards splenectomy avoidance has recently been observed. The objective of this study was to better understand patient preference and the factors affecting patients' decision for or against splenectomy. Methods We designed an exploratory qualitative interview study. Criterion sampling was used to identify eligible patients 18 years of age or older who were diagnosed with relapsed (lasting 3 – 12 months) or chronic (lasting longer than 12 months) primary ITP and who had been offered splenectomy as a treatment option by their physician, until data saturation was achieved. One to one, semi-structured interviews were conducted using an open-ended interview guide designed to investigate factors impacting splenectomy decision-making. Interview transcripts were coded independently in triplicate and interrater agreement was high. Major themes were identified from the data using a team analytic approach and audit trail. Results. Data saturation was achieved after 15 patients were interviewed; 6 were for splenectomy, 7 were against, and 2 were undecided. Patients were between the ages of 19 and 82 [median 43 years; interquartile range (IQR), 31 – 61] and 9 (60%) were female. Median duration of ITP was 49 months (IQR 13 – 113); patients had received a median of 2 prior treatments (IQR 2 – 3) and median platelet count at the time of the interview was 72 × 109/L (IQR 29 – 106). Four major themes were identified from the data about influences on treatment preferences: 1) patients' understanding of the ITP disease process; 2) patients' perception of the impact of ITP on their quality of life; 3) patients' understanding of the risks and benefits of treatments offered by their physician; and 4) patients' perception of splenectomy as a last resort. Patients were likely to accept splenectomy if their disease was perceived as having a negative impact on their quality of life. In general, patients had limited understanding of the cause of ITP and often misinterpreted the meaning of quoted probabilities of success with splenectomy. Conclusion Increased awareness of influences on patient treatment preferences will help physicians guide ITP patients through the complex decision-making process regarding splenectomy and can inform the design of decision-aids. Disclosures: Arnold: Hoffmann-LaRoche: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Talecris: Honoraria. Kelton:Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees.

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)0.018
metaresearch head score (Gemma)0.029
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 score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0070.006
Scholarly communication0.0040.004
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.072
GPT teacher head0.317
Teacher spread0.245 · 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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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