ArticleJournal of clinical monitoring and computing2018
Predicting fluid responsiveness in whom? A simulated example of patient spectrum influencing the receiver operating characteristics curve.
Article in Journal of clinical monitoring and computing, 2018. 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
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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.
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Who cites it
3 citing papers in PubMed.
- Peripheral intravenous waveform analysis for evaluating volume status in healthy volunteers and mechanically ventilated patients.Journal of clinical monitoring and computing · 2026Article
- Journal of clinical monitoring and computing end of year summary 2018: hemodynamic monitoring and management.Journal of clinical monitoring and computing · 2019Review
- Volumetric and End-Tidal Capnography for the Detection of Cardiac Output Changes in Mechanically Ventilated Patients Early after Open Heart Surgery.Critical care research and practice · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The influence of patient spectrum on the sensitivities and specificities of diagnostic methods has been termed spectrum bias or spectrum effect. Receiver operating characteristics curves are often used to assess the ability of diagnostic methods to predict fluid responsiveness. As a receiver operating characteristics curve is a presentation of sensitivity and specificity, the purpose of the present manuscript was to explore if patient spectrum could affect areas under receiver operating characteristics curves and their gray zones. Relationships between stroke volume variation and change in stroke volume in two different patient populations using simulated data. Simulated patient populations with stroke volume variation values between 5 and 15 or 3 and 25% had median (2.5th-97.5th percentiles) areas under receiver operating characteristics curves of 0.79 (0.65-0.90) and 0.93 (0.85-0.99), respectively. The gray zones indicating range of diagnostic uncertainty were also affected. The patient spectrum can affect common statistics from receiver operating characteristics curves, indicating the need for considering patient spectrum when evaluating the abilities of different methods to predict fluid responsiveness.
Indexed as
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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.