Evidence map›Paper›PMID 27733894›Full record

ArticleBiomicrofluidics2016

3D printed auto-mixing chip enables rapid smartphone diagnosis of anemia.

Kimberly Plevniak, Matthew Campbell, Timothy Myers, Abby Hodges, Mei He

Abstract read
In one paragraph

Article in Biomicrofluidics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
  10. 3D Printed Microfluidics.Annual review of analytical chemistry (Palo Alto, Calif.) · 2020
    Review
  11. Review
  12. Article
  13. Digital Manufacturing for Microfluidics.Annual review of biomedical engineering · 2019
    Review
  14. Article
  15. Review
  16. 3D-printed miniaturized fluidic tools in chemistry and biology.Trends in analytical chemistry : TRAC · 2018
    Article
  17. Review
  18. Review
  19. Article
  20. Review
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

5 authors.

Kimberly PlevniakDepartment of Biological and Agricultural Engineering, Kansas State University , Manhattan, Kansas 66506, USA.
Matthew CampbellAdvanced Manufacturing Institute, Kansas State University , Manhattan, Kansas 66506, USA.
Timothy MyersDepartment of Science and Mathematics, MidAmerica Nazarene University , Olathe, Kansas 66062, USA.ORCID 0000-0001-7862-0558
Abby HodgesDepartment of Science and Mathematics, MidAmerica Nazarene University , Olathe, Kansas 66062, USA.
Mei He

Funding

Mentoring CoreP20GM103418 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI SUSAN J. BROWN · 2012 to 2026
$63.0M
NIGMS NIH HHS P20 GM103418
6 · The paper itself

Abstract

Clinical diagnosis requiring central facilities and site visits can be burdensome for patients in resource-limited or rural areas. Therefore, development of a low-cost test that utilizes smartphone data collection and transmission would beneficially enable disease self-management and point-of-care (POC) diagnosis. In this paper, we introduce a low-cost

Identifiers

PMID27733894
PMCPMC5055529

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.