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Record W3120152842 · doi:10.1002/rth2.12484

The psychological impact of pulmonary embolism: A mixed‐methods study

2021· article· en· W3120152842 on OpenAlexaff
Anna Tran, Marcus Redley, Kerstin de Wit

Bibliographic record

VenueResearch and Practice in Thrombosis and Haemostasis · 2021
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsQueen's UniversityMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsAnxietyMedicineDistressPsychiatryClinical psychologyMental healthDepression (economics)

Abstract

fetched live from OpenAlex

BACKGROUND: Patients diagnosed with pulmonary embolism (PE) are reported to experience symptoms of posttraumatic stress disorder (PTSD) and existential anxiety following their diagnosis. They may also experience negative changes in perspective and hypervigilance of PE symptoms. OBJECTIVE: The aim of this study was to document the mental and emotional experience associated with PE diagnosis through the lens of PTSD, to better understand the factors involved in psychological distress following receipt of a PE diagnosis. PATIENTS/METHODS: This was a mixed-methods study in two parts: (i) measurement of self-reported PTSD symptoms among patients attending thrombosis clinic and (ii) semistructured interviews with patients about their experience of receiving a diagnosis of PE and its psychological aftermath. RESULTS: Of 72 patients who participated in the survey, two met the criteria for a tentative diagnosis of PTSD. The semistructured interviews with 37 patients suggested that around half of respondents experienced some degree of ongoing psychological distress. Those with psychological distress often recalled painful symptoms, recalled diagnosis delivery as stressful, worried about PE recurrence, and had anxieties about stopping their anticoagulant medication. Few patients reported inclination to seek support from professional mental health services. CONCLUSIONS: We found ongoing and untreated psychological distress among people who were previously diagnosed with PE.

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)0.007
metaresearch head score (Gemma)0.004
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 score0.932
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.229
GPT teacher head0.577
Teacher spread0.348 · 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

Citations53
Published2021
Admission routes1
Has abstractyes

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