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Record W3022054469 · doi:10.3899/jrheum.191249

Exercise Echocardiography as a Screening Tool in Systemic Sclerosis

2020· letter· en· W3022054469 on OpenAlexvenueno aff
Monica Mukherjee, Stephen C. Mathai

Bibliographic record

VenueThe Journal of Rheumatology · 2020
Typeletter
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteJohns Hopkins UniversityNational Institutes of HealthScleroderma Foundation
KeywordsMedicineInternal medicineCardiologyRight heart catheterizationPulmonary hypertensionObservational studyHemodynamicsBlood pressure

Abstract

fetched live from OpenAlex

In this issue of The Journal , Quinn, et al describe the utility of exercise echocardiography (EE) in the identification of patients with systemic sclerosis (SSc) deemed high risk for the development of pulmonary arterial hypertension (PAH)1. In a single-center observational study, the authors demonstrated that a significantly higher percentage of SSc patients with a persistently positive EE, as defined by an increase in right ventricular systolic pressure (RVSP) ≥ 20 mmHg with exercise, subsequently developed pulmonary hypertension (PH) compared with those who had persistently negative EE. The majority of patients with a baseline positive EE were found to have a persistently positive EE over time. However, interestingly, a proportion of those patients did not develop resting PAH. Similarly, 3 patients with baseline negative EE developed PAH shortly after initial testing, possibly representing a false-negative result. Because invasive hemodynamics with right heart catheterization (RHC) was not performed unless clinically indicated and was also performed up to 6 months following EE, it is difficult to ascertain the meaning of the present findings. Certainly, other SSc-specific features or biomarkers of increased risk in combination with positive EE need to be identified; however, lack of standardization in annual testing limits identification in this present study. In contrast, a negative EE may be helpful in identifying a group protected from developing PH in the future. This finding, if confirmed in larger studies, could lead to improved early detection strategies for patients with SSc at highest risk for development of PAH, and potentially other at-risk populations with connective tissue disease. The current study is an extension of an original 2008 manuscript, also by Steen, et al , in which SSc patients at risk for PAH underwent EE to determine whether … Address correspondence to Dr. M. Mukherjee, Johns Hopkins University Division of Cardiology, 301 Mason Lord Drive, Suite 2400, Baltimore, Maryland 21224, USA. E-mail: mmukher2{at}jhmi.edu

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)0.002
metaresearch head score (Gemma)0.005
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: Editorial · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.001
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 head0.038
GPT teacher head0.269
Teacher spread0.230 · 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
GenreEditorial

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
Published2020
Admission routes1
Has abstractyes

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