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Record W4402311585 · doi:10.1186/s12959-024-00648-x

Values and preferences towards the use of prophylactic low-molecular-weight heparin during pregnancy: a convergent mixed-methods secondary analysis of data from the decision analysis in shared decision making for thromboprophylaxis during pregnancy (DASH-TOP) study

2024· article· en· W4402311585 on OpenAlexaff
Montserrat León‐García, Brittany Humphries, Feng Xie, Derek L. Gravholt, Elizabeth H. Golembiewski, Mark H. Eckman, Shannon M. Bates, Ian Hargraves, Irene Pelayo, Sandra Redondo López, Juan Antonio Millón Caño, Milagros A Suito Alcántara, Rohan D’Souza, Nadine Shehata, Susan M. Jack, Gordon Guyatt, Lilisbeth Perestelo‐Pérez, Pablo Alonso‐Coello

Bibliographic record

VenueThrombosis Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsMount Sinai HospitalMcMaster UniversityImpact
FundersUniversitat Autònoma de Barcelona
KeywordsMedicineAngiologyLow molecular weight heparinPregnancyHeparinDecision analysisObstetricsIntensive care medicineInternal medicineStatisticsGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Venous thromboembolism (VTE) in pregnancy is a major cause of maternal morbidity and mortality, and the use of preventive low-molecular-weight heparin (LMWH) can be challenging. Clinical guidelines recommend eliciting pregnant individuals' preferences towards the use of daily injections of LMWH and discussing the best option through a shared decision-making (SDM) approach. Our aim was to identify individuals' preferences concerning each of the main clinical outcomes, and categorize attributes influencing the use of LMWH during pregnancy. METHODS: Design: Convergent mixed-methods. PARTICIPANTS: Pregnant women or those planning a pregnancy with VTE recurrence risk. INTERVENTION: A SDM intervention about thromboprophylaxis with LMWH in pregnancy. ANALYSIS: Quantitatively, we report preference scores assigned to each of the health states. Qualitatively, we categorized preference attributes using Burke's pentad of motives framework: act (what needs to be done), scene (patient's context), agent (perspectives and influence of people involved in the decision), agency (aspects of the medication), and purpose (patient's goals). We use mixed-method convergent analysis to report findings using side-by-side comparison of concordance/discordance. RESULTS: We comprehensively determined preferences for using LMWH by pregnant individuals at risk of VTE: through value elicitation exercises we found that the least valued health state was to experience a pulmonary embolism (PE), followed by major obstetrical bleeding (MOB), deep vein thrombosis (DVT), and using daily injections of LMWH (valued as closest to a 'healthy pregnancy'); through interviews we found that: previous experiences, access to care (scene) and shared decision-making (agent) affected preferences. LMWH's benefits were noted, but substantial drawbacks were described (agency). For participants, the main goal of using LMWH was avoiding any risks in pregnancy (purpose). Side-by-side comparisons revealed concordance and discordance between health states and motives. CONCLUSIONS: Mixed-methods provide a nuanced understanding of LMWH preferences, by quantifying health states preferences and exploring attributes qualitatively. Incorporating both methods may improve patient-centered care around preference-sensitive decisions in thromboprophylaxis during pregnancy.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.102
GPT teacher head0.389
Teacher spread0.287 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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