MétaCan
Menu
← Back to cohort
Record W4317914435 · doi:10.1093/eurheartj/ehac779.071

Natural history of functional mitral regurgitation: a systematic review and individual patient data meta-analysis

2023· review· en· W4317914435 on OpenAlexaboutno aff
Yao Neng Teo, Gayathri Basker, Seth En Teoh, E W X Tan, Yao Hao Teo, Ping Chai, R C C Wong, James WL Yip, Ivandito Kuntjoro, Yong Lim, Kian Keong Poh, Tiong Cheng Yeo, William Kong, Ching‐Hui Sia

Bibliographic record

VenueEuropean Heart Journal · 2023
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisInternal medicineEjection fractionNatural historyMitral regurgitationCohortCardiologyPhysical therapyHeart failure

Abstract

fetched live from OpenAlex

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Ching-Hui Sia was supported by the National University of Singapore Yong Loo Lin School of Medicine's Junior Academic Fellowship Scheme. Background Functional mitral regurgitation (FMR) precipitates a vicious cycle of left ventricular volume overload and remodelling, leading to perpetual worsening of FMR and left ventricular dysfunction, with a resultant poor prognosis. However, there is a lack of conclusive data on the natural progression of FMR in patients who do not undergo valvular intervention. Purpose We performed a one-stage meta-analysis on reconstructed individual patient data (IPD) to elucidate the natural history of FMR. Methods Four databases (PubMed, Embase, Scopus, Cochrane) were searched for randomised controlled trials or cohorts, published from inception to March 13, 2022, reporting clinical outcomes in patients with FMR not receiving valvular intervention. IPD meta-analysis, as the gold standard approach for evidence synthesis, was performed with reconstructed IPD obtained from the survival curves reported in the included studies. Pooled survival estimates were derived. Quality assessment of included studies was conducted using the Cochrane risk-of-bias tool and Newcastle Ottawa Scale. This study was registered on the International Prospective Register of Systematic Reviews. Results A total of five studies were included, comprising a total cohort of 691 patients with FMR who did not undergo valvular intervention. The mean age of the cohort was 72.4 years (95% CI 67.6 to 77.1) and the proportion of males was 61.1% (95% CI 43.8 to 76.0). All-cause mortality was analysed over a follow-up duration of five years, while hospitalisation for heart failure, cardiovascular death, and the composite of all-cause mortality and hospitalisation for heart failure were analysed over a follow-up duration of three years. The probability of survival of patients with FMR without intervention was 79.4% (95% CI 76.2 to 82.3), 50.9% (95% CI 46.6 to 55.1), and 39.6% (95% CI 33.1 to 46.0) at one, three, and five years respectively. The probability of survival free from the composite of all-cause mortality and hospitalisation for heart failure was 51.3% (95% CI 46.8 to 55.6) and 12.0% (95% CI 8.9 to 15.7) at one year and three years respectively. The probability of survival free from hospitalisation for heart failure was 58.3% (95% CI 54.0 to 62.3) and 19.7% (95% CI 16.0 to 23.7) at one and three years respectively. The probability of survival free from cardiovascular death was 75.4% (95% CI 68.9 to 80.8) and 45.6% (95% CI 29.1 to 60.7) at one and three years respectively. All included studies were of low to moderate risk of bias. Conclusion FMR in the absence of valvular intervention is associated with poor survival and cardiovascular outcomes. Further research should focus on the role of interventions to mitigate its poor prognosis.

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)0.025
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.055
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0200.047
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.399
GPT teacher head0.431
Teacher spread0.032 · 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 designMeta-analysis
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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Heart Journal→Same topicCardiac Valve Diseases and Treatments→French-language works237,207→