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Record W2752709095 · doi:10.1183/16000617.0039-2017

Exertional dyspnoea in pulmonary arterial hypertension

2017· review· en· W2752709095 on OpenAlexaff
Daniel Dumitrescu, Olivier Sitbon, Jason Weatherald, Luke Howard

Bibliographic record

VenueEuropean Respiratory Review · 2017
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineCardiologyPathophysiologyPulmonary hypertensionInternal medicineDiseaseAbnormalityNeuropsychologyReflexPulmonary function testingCognitionPsychiatry

Abstract

fetched live from OpenAlex

Dyspnoea is a principal presenting symptom in pulmonary arterial hypertension (PAH), and often the most distressing. The pathophysiology of PAH is relatively well understood, with the primary abnormality of pulmonary vascular disease resulting in a combination of impaired cardiac output on exercise and abnormal gas exchange, both contributing to increased ventilatory drive. However, increased ventilatory drive is not the sole explanation for the complex neurophysiological and neuropsychological symptom of dyspnoea, with other significant contributions from skeletal muscle reflexes, respiratory muscle function, and psychological and emotional status. In this review, we explore the physiological aspects of dyspnoea in PAH, both in terms of the central cardiopulmonary abnormalities of PAH and the wider, systemic impact of PAH, and how these interact with common comorbidities. Finally, we discuss its relationship with disease severity.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.294
GPT teacher head0.418
Teacher spread0.124 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations42
Published2017
Admission routes1
Has abstractyes

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