ArticleAcademic pathology
Pathology Informatics and Robotics Strategies for Improving Efficiency of COVID-19 Pooled Testing.
Article in Academic pathology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Evaluation of miniaturized Illumina DNA preparation protocols for SARS-CoV-2 whole genome sequencing.PloS one · 2023Article
- Automated HL7v2 LRI informatics framework for streamlining genomics-EHR data integration.Journal of pathology informatics · 2023Article
- Review
- Communication during a global pandemic: The utility of a professional society listserv and journal.Academic pathology · 2022Article
- The Hologic Aptima SARS-CoV-2 assay enables high ratio pooling saving reagents and improving turnaround time.Journal of clinical laboratory analysis · 2021Article
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
The global rise of the coronavirus disease 2019 pandemic resulted in an exponentially increasing demand for severe acute respiratory syndrome coronavirus 2 testing, which resulted in shortage of reagents worldwide. This shortage has been further worsened by screening of asymptomatic populations such as returning employees, students, and so on, as part of plans to reopen the economy. To optimize the utilization of testing reagents and human resources, pool testing of populations with low prevalence has emerged as a promising strategy. Although pooling is an effective solution to reduce the number of reagents used for testing, the process of pooling samples together and tracking them throughout the entire workflow is challenging. To be effective, samples must be tracked into each pool, pool-tested and reported individually. In this article, we address these challenges using robotics and informatics.
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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.