ArticleJournal of clinical monitoring and computing2020
Optimizing the use of point of care testing devices for screening patients.
Article in Journal of clinical monitoring and computing, 2020. 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.
- Electronic health record data is unable to effectively characterize measurement error from pulse oximetry: a simulation study.Journal of clinical monitoring and computing · 2024Article
- Application of microfluidic technology based on surface-enhanced Raman scattering in cancer biomarker detection: A review.Journal of pharmaceutical analysis · 2023Review
- Expanding the boundaries of point of care testing.Journal of clinical monitoring and computing · 2020Article
Corrections and comments
- Commented on by
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Point of Care Testing (POCT) devices are regularly used to improve clinical workflows in the hospital setting despite generally having inferior performance when compared to standardized laboratory analyzers. We describe a method to improve the efficacy of using a POCT device as a screening test when the laboratory values occur over a continuum and applied this methodology to the process of International Normalized Ratios (INR) screening on day of surgery. Following IRB approval, laboratory INR values on the day of surgery were extracted from the University of Vermont Medical Center operating room's electronic health record. Two separate theoretical POCT device values were simulated from the performance characterized by two prior publications (Jacobson and Hur). The sensitivities and specificities of the two theoretical devices were calculated over a range of values, in order detect an INR value greater or equal than 1.5 and 1.8. Subsequently, the percentage of the population with an INR value over each threshold was also calculated. Laboratory data from March 2008 to December 2016 were collected, and 9320 discrete INR values were compiled ranging from 0.8 to > 20. Two POCT devices were simulated using that dataset. The sensitivities and specificities over a range of values were determined, and the optimal cutoff values were identified for each device separately. Calculating the sensitivities and specificities over a range of values can optimize the clinical efficacy of a POCT device. By optimizing the use of POCT devices, hospitals may be able to improve clinical processes and reduce costs.
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Identifiers
31183771What 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.