Evidence map›Paper›PMID 35415364›Full record

ArticleACS omega2022

Toward a Quantitative Colorimeter for Point-of-Care Nitrite Detection.

Vince S Siu, Minhua Lu, Kuan Yu Hsieh, Kierstyn Raines, Youssef A Asaad, Krishna Patel, Ali Afzali-Ardakani, Bo Wen, Russell Budd

Open access · goldAbstract read
In one paragraph

Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

11 citing papers in PubMed, 23 citations in OpenAlex.

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  6. Energy metabolism in health and diseases.Signal transduction and targeted therapy · 2025
    Review
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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

9 authors at 2 institutions in 2 countries.

Vince S SiuIBM T.J. Watson Research Center, Yorktown Heights, New York 10598, United States.ORCID https://orcid.org/0000-0003-4652-1189
Minhua LuIBM T.J. Watson Research Center, Yorktown Heights, New York 10598, United States.
Kuan Yu HsiehIBM T.J. Watson Research Center, Yorktown Heights, New York 10598, United States.
Kierstyn RainesIBM T.J. Watson Research Center, Yorktown Heights, New York 10598, United States.
Youssef A AsaadIBM T.J. Watson Research Center, Yorktown Heights, New York 10598, United States.
Krishna PatelIBM T.J. Watson Research Center, Yorktown Heights, New York 10598, United States.
Ali Afzali-ArdakaniIBM T.J. Watson Research Center, Yorktown Heights, New York 10598, United States.
Bo WenIBM T.J. Watson Research Center, Yorktown Heights, New York 10598, United States.
Russell BuddIBM T.J. Watson Research Center, Yorktown Heights, New York 10598, United States.
IBM Research - Thomas J. Watson Research Center · USNational Yang Ming Chiao Tung University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper reports on a low-cost, quantitative, point-of-care solution for the early detection of nitrite, a common biomarker for urinary tract infections (UTIs). In a healthy individual, nitrite is not found in the urine. However, a subject with a suspected UTI will produce nitrite in their urine since the bacteria present will convert nitrate into nitrite. Traditionally, nitrite is monitored by urinary dipsticks that are either read by eye or using a reflectance spectrophotometer. Both methods provide a semiquantitative positive or negative result at best. In this paper, we described a novel, affordable, portable transmission-based colorimeter for the quantitative measurement of nitrite. A unique permutation of the Griess reaction was optimized for the clinical detection of nitrite in urine and is reported. By using nitrite spiked in a salt buffer, artificial, and human urine samples, the performance of the colorimeter was evaluated against dipsticks read using two commercial dipstick analyzers, Urisys 1100 (Roche Diagnostics) and Clinitek Status+ (Siemens Medical Solutions). The colorimeter was able to detect the clinically relevant range of nitrite from 0.78 to 200 μM in a salt buffer. The detection limit in artificial urine was determined as 1.6 μM, which is ∼16× more sensitive than commercial dipstick reflectance analyzers, enabling the possibility for earlier detection of urinary infections. The colorimeter is assembled using off-the-shelf components (<$80) and controlled by a smartphone application

Identifiers

PMID35415364
PMCPMC8991914
OpenAlexW4223509798

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.