Evidence map›Paper›PMID 28330865›Full record

ArticleScience translational medicine2017

An automated smartphone-based diagnostic assay for point-of-care semen analysis.

Manoj Kumar Kanakasabapathy, Magesh Sadasivam, Anupriya Singh, Collin Preston, Prudhvi Thirumalaraju, Maanasa Venkataraman, Charles L Bormann, Mohamed Shehata Draz, John C Petrozza, Hadi Shafiee

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Science translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 1 pooled it
23.3field-weighted citation impact, top 1% of its field
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

65 citing papers in PubMed, 1 synthesis or guideline pooled it, 190 citations in OpenAlex.

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5 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Manoj Kumar KanakasabapathyDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.ORCID 0000-0002-0756-8585
Magesh SadasivamDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.ORCID 0000-0001-9752-5695
Anupriya SinghDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.ORCID 0000-0003-4345-2683
Collin PrestonDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.ORCID 0000-0002-0438-7156
Prudhvi ThirumalarajuDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.ORCID 0000-0002-0573-0243
Maanasa VenkataramanDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.ORCID 0000-0001-8543-8463
Charles L BormannDivision of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
Mohamed Shehata DrazDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.ORCID 0000-0001-8734-0443
John C PetrozzaDivision of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.ORCID 0000-0001-5864-2119
Hadi ShafieeDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA. hshafiee@bwh.harvard.edu.ORCID 0000-0003-2240-7648
Brigham and Women's Hospital · USMassachusetts General Hospital · US

Funding

Translational Research Support CoreP30ES000002 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI SUSAN A KORRICK · 1985 to 2026
$44.6M
Sensitive and quantitative point-of-care viral load testing on paperR01AI118502 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI SHAFIEE, HADI · 2016 to 2020
$2.2M
NIAID NIH HHS R01 AI118502NIEHS NIH HHS P30 ES000002
6 · The paper itself

Abstract

Male infertility affects up to 12% of the world's male population and is linked to various environmental and medical conditions. Manual microscope-based testing and computer-assisted semen analysis (CASA) are the current standard methods to diagnose male infertility; however, these methods are labor-intensive, expensive, and laboratory-based. Cultural and socially dominated stigma against male infertility testing hinders a large number of men from getting tested for infertility, especially in resource-limited African countries. We describe the development and clinical testing of an automated smartphone-based semen analyzer designed for quantitative measurement of sperm concentration and motility for point-of-care male infertility screening. Using a total of 350 clinical semen specimens at a fertility clinic, we have shown that our assay can analyze an unwashed, unprocessed liquefied semen sample with <5-s mean processing time and provide the user a semen quality evaluation based on the World Health Organization (WHO) guidelines with ~98% accuracy. The work suggests that the integration of microfluidics, optical sensing accessories, and advances in consumer electronics, particularly smartphone capabilities, can make remote semen quality testing accessible to people in both developed and developing countries who have access to smartphones.

Indexed as

Diagnostic Techniques and ProceduresPoint-of-Care SystemsSmartphoneCryopreservationHumansMaleSemen AnalysisSperm Count

Identifiers

PMID28330865
PMCPMC5701517
OpenAlexW2599086938

What OpenQuestion holds

Textmetadata
LicenceTDM
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.