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Assessment of endpoints in pulmonary arterial hypertension associated with connective tissue disease

2010· review· en· W2138545856 on OpenAlexaff
Gerry Coghlan, Janet Pope, Christopher P. Denton

Bibliographic record

VenueCurrent Opinion in Pulmonary Medicine · 2010
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsSt Joseph's Health Centre
FundersActelion PharmaceuticalsUnited Therapeutics Corporation
KeywordsMedicineConnective tissue diseasePulmonary hypertensionMixed connective tissue diseaseConnective tissueInterstitial lung diseaseClinical endpointIdiopathic pulmonary fibrosisClinical trialPopulationConnective Tissue DisorderInternal medicineDiseaseComorbidityPulmonary fibrosisFibrosisPathologyLungAutoimmune disease

Abstract

fetched live from OpenAlex

Connective tissue disease-associated pulmonary arterial hypertension (PAH) is mostly related to systemic sclerosis, overlap syndromes with features of systemic sclerosis, mixed connective tissue disease, and systemic lupus erythematosus. It is an important cause of mortality in these conditions and represents up to one third of patients seen in most specialist pulmonary hypertension centers. Patients with PAH associated with connective tissue disease may have a worse outcome than those with other forms of PAH. Most randomized clinical trials of PAH therapies have included patients with connective tissue disease as part of a mixed population. Overall, analyses suggest that treatment responses parallel those seen in idiopathic PAH, though subgroup analyses must be interpreted with caution. There may also be significant comorbidity from other pulmonary complications such as interstitial fibrosis, aspiration, or chest wall restriction. In addition, the majority of clinical trials have used 6-minute walk distance as the primary endpoint; the clinical relevance of this is questionable in connective tissue disease patients, who often have multiple comorbidities, other than PAH, which adversely affect exercise tolerance.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.114
GPT teacher head0.426
Teacher spread0.312 · 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 designOther design
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

Citations20
Published2010
Admission routes1
Has abstractyes

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