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Record W2793553100 · doi:10.1155/2018/7056360

Pulmonary Arterial Hypertension Specific Therapy in Patients with Combined Post- and Precapillary Pulmonary Hypertension

2018· article· en· W2793553100 on OpenAlexaff
Hassan Alfraidi, Sultan Qanash, Zoheir Bshouty

Bibliographic record

VenuePulmonary Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsMcGill UniversityUniversity of Manitoba
Fundersnot available
KeywordsMedicineAlgorithmInternal medicineMathematics

Abstract

fetched live from OpenAlex

Background. Specific therapy for patients with PAH is associated with good outcomes. Little is known about the effect of this treatment in patients with Cpc-PH (PAPm ≥ 25 mmHg, PAWP > 15 mmHg, DPG ≥ 7 mmHg, and/or PVR > 3 WU). This study evaluates the outcome of treating patients with Cpc-PH using PAH specific therapy. Methods. The primary outcome was survival. Secondary outcomes were WHO functional class and 6-minute walk distance (6-MWD). Results. Twenty-six patients with Cpc-PH (half with VHD and half with HF) received PAHST. Six patients did not tolerate treatment due to pulmonary edema. No predictors for treatment intolerance were identified. In twenty patients who tolerated the treatment, the mean WHO functional class improved from 2.70±0.21 at initial assessment to 2.22±0.21 ( p<0.04 ) and 2.06±0.21 ( p<0.03 ) at 6 and 9 months, respectively. Mean 6-MWD improved from 276.0±38.50 meters at initial assessment to 343.9±22.99 meters ( p<0.04 ) and 364.6±34.85 meters ( p=0.07 ) at 6 and 9 months, respectively. Twelve patients died during the follow-up period. Mean survival for all patients was 1279.7±193.60 days. Conclusion. PAHST may be beneficial in the treatment of Cpc-PH (both short and long term). Prospective randomized controlled trials of PAHST in this population are needed to assess its potential efficacy.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.246
Teacher spread0.222 · 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
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

Citations3
Published2018
Admission routes1
Has abstractyes

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