ReviewHeart failure reviews2022
Ambulatory factors influencing pulmonary artery pressure waveforms and implications for clinical practice.
Review in Heart failure reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Expanding Anatomical Feasibility of CardioMEMS Implantation: A Case Report of Successful Implantation in a Patient With Significant Morbid Obesity.Journal of the Society for Cardiovascular Angiography & Interventions · 2026Article
- Article
- CardioMEMS Device Release Failure Necessitating Percutaneous Retrieval.Journal of the Society for Cardiovascular Angiography & InterventionsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
CardioMEMS, a remote pulmonary artery pressure monitoring system, provides waveform patterns for the ambulatory heart failure patient. These waveforms provide significant insights into patient volume and clinical management. We aim to provide a foundation for understanding the determinants of waveform characteristics and provide practical examples illustrating how to interpret and integrate common scenario waveforms into clinical decision-making. A total of three groups of relevant scenarios were included namely (a) location and activity at time of waveform transmission, (b) impact of contemporary interventions, and (c) arrhythmias. We illustrate that waveform analysis can be individualized to each patient's care strategy in the appropriate clinical context to help guide clinical decision-making.
Indexed as
Identifiers
35587304What Socratic 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 Socratic graph.