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Diagnosis and Management of Group 2 Pulmonary Hypertension Due to Left Heart Disease in the UAE

2025· article· en· W4407786026 on OpenAlexaff
Hani Sabbour, Mohammed B Al Saiari, Ashraf Alzaabi, Hazem El Badaoui, Rizwan Ahmed, Hadi Skouri, Mohammad Daud Khan, Marco Harari, Magdi Tofeig, Amrish Agrawal, Hosam Zaky, Noha Yaseen, Wael Al Mahmeed, Ahmed Reda Taha, Vivek Kakar, Yasser El Hennawi, Yogeeswari Vellore Satyanarayanan, Aref Al Hakami, Anwar Al Zaabi, Hussein Heshmat, Abdullah Shehab

Bibliographic record

VenueNew Emirates Medical Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsPulmonary hypertensionCardiologyMedicineEjection fractionInternal medicineHeart failureSildenafilHeart failure with preserved ejection fractionDiabetes mellitusIntensive care medicine

Abstract

fetched live from OpenAlex

: Pulmonary hypertension (PH) due to left heart disease (PH-LHD) is the most common type of PH and is observed in patients with underlying left heart disease conditions, including valvular heart disease, heart failure (HF) with preserved ejection fraction (HFpEF), HF with reduced ejection fraction (HFrEF), cardiomyopathies, and arrhythmic diseases. Group 2 PH is postcapillary PH categorised into 2 components as isolated postcapillary PH (IpcPH) and combined precapillary and postcapillary PH (CpcPH), based on the value of pulmonary vascular resistance (PVR). : PH-LHD diagnosis is a three-step process and includes identification of clinical phenotype, determination of pre-test probability for invasive evaluation, and haemodynamic assessments. Management of PH-LHD primarily encompasses optimisation of treatment of underlying conditions, such as hypertension, obesity and diabetes mellitus, and treatment of PH-LHD with targeted PAH-specific drugs, like phosphodiesterase type 5 inhibitors (PDE5i) and sildenafil. In patients with PH-LHD, the use of PAH-specific drugs can lead to pulmonary oedema and clinical deterioration. : The article aimed to provide updated information on diagnosis and emerging treatment options for PH-LHD. Although the emerging alternative treatment options are not approved, the randomised studies discussed provide insight into the management and thus demand future clinical trials to establish the safety and efficacy of novel molecules and combination therapies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.024
GPT teacher head0.312
Teacher spread0.288 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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