ArticleCritical care (London, England)2010
Pulse pressure analysis: to make a long story short.
Article in Critical care (London, England), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Multimorbidity and Critical Care Neurosurgery: Minimizing Major Perioperative Cardiopulmonary Complications.Neurocritical care · 2021Review
- Pavane for a pulse pressure variation defunct.Critical care (London, England) · 2013Article
- Impact of arterial load on the agreement between pulse pressure analysis and esophageal Doppler.Critical care (London, England) · 2013Observational
- Cardiac output obtained by pulse pressure analysis: to calibrate or not to calibrate may not be the only question when used properly.Intensive care medicine · 2013Article
Corrections and comments
- Comment on
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pulse pressure analysis algorithms are commonly used to measure cardiac output and to allow for the rational titration of therapy in critically ill patients. The ability of these algorithms to accurately track changes in stroke volume (and cardiac output) is thus very important. Most of the currently available algorithms can provide robust data so long as there is no fundamental change in the vasomotor tone (arterial compliance or impedance). If the tone changes significantly, for instance with vasodilatation or vasoconstriction, then the data become less robust. For this reason, unless there is a mechanism for compensating for changes in vasomotor tone, these algorithms are best used only over short time periods in order to get the most accurate and precise data on changes in cardiac output.
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.