Evidence map›Paper›PMID 28432561›Full record

ArticleJournal of clinical monitoring and computing2018

Predicting fluid responsiveness in whom? A simulated example of patient spectrum influencing the receiver operating characteristics curve.

Lars Øivind Høiseth, Jostein S Hagemo

Abstract read
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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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Lars Øivind HøisethDivision of Emergencies and Critical Care, Department of Anesthesiology, Oslo University Hospital, Kirkeveien 166, 0368, Oslo, Norway. lars.oivind.hoiseth@hotmail.com.ORCID http://orcid.org/0000-0003-0669-8297
Jostein S HagemoNorwegian Air Ambulance Foundation, Drøbak, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

ROC CurveSignal Processing, Computer-AssistedStroke VolumeComputer SimulationHumansLinear ModelsMonitoring, PhysiologicRegression AnalysisReproducibility of ResultsSensitivity and SpecificityDiagnostic techniques and proceduresPopulation characteristicsSensitivity and specificity

Identifiers

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Registered trials

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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.