ArticleFrontiers in cardiovascular medicine2021
Sex-Specific Patterns of Mortality Predictors Among Patients Undergoing Cardiac Resynchronization Therapy: A Machine Learning Approach.
Article in Frontiers in cardiovascular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis.BMC cardiovascular disorders · 2025Pooled it
- The Epidemiological and Clinical Profiling of Heart Failure-A Retrospective and Comparative Analysis of Cases Before, During, and After the COVID-19 Pandemic in a Romanian Emergency County Clinical Hospital.Medicina (Kaunas, Lithuania) · 2025Observational
- A supervised machine learning approach with feature selection for sex-specific biomarker prediction.NPJ systems biology and applications · 2025Article
- Machine learning-based prediction of 1-year all-cause mortality in patients undergoing CRT implantation: validation of the SEMMELWEIS-CRT score in the European CRT Survey I dataset.European heart journal. Digital health · 2024Article
- Artificial Intelligence in Heart Failure: Friend or Foe?Life (Basel, Switzerland) · 2024Review
- Article
- Combination of personalized computational modeling and machine learning for optimization of left ventricular pacing site in cardiac resynchronization therapy.Frontiers in physiology · 2023Article
- Interpretable machine learning predicts cardiac resynchronization therapy responses from personalized biochemical and biomechanical features.BMC medical informatics and decision making · 2022Article
- Utilizing longitudinal data in assessing all-cause mortality in patients hospitalized with heart failure.ESC heart failure · 2022Article
- Best Practices on Big Data Analytics to Address Sex-Specific Biases in Our Understanding of the Etiology, Diagnosis, and Prognosis of Diseases.Annual review of biomedical data science · 2022Review
- Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data.Frontiers in physiology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.