Evidence map›Paper›PMID 37651353›Full record

ArticlePloS one2023

Development of a urinometer for automatic measurement of urine flow in catheterized patients.

José-Luis Lafuente, Samuel González, Enrique Puertas, Vicente Gómez-Tello, Eva Avilés, Niza Albo, Claudia Mateo, Juan-Jose Beunza

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Definition of Oliguria in the Intensive Care Unit: How Do You Do It?Clinical journal of the American Society of Nephrology : CJASN · 2024
    Article
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

8 authors at 2 institutions in 1 country.

José-Luis LafuenteIASalud, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid, Spain.
Samuel GonzálezIASalud, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid, Spain.
Enrique PuertasIASalud, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid, Spain.ORCID 0000-0002-5115-1226
Vicente Gómez-TelloIASalud, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid, Spain.
Eva AvilésIASalud, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid, Spain.ORCID 0000-0001-5435-9367
Niza AlboIASalud, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid, Spain.
Claudia MateoIASalud, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid, Spain.
Juan-Jose BeunzaIASalud, Universidad Europea de Madrid, Villaviciosa de Odón, Madrid, Spain.ORCID 0000-0001-8192-2952
Universidad Europea de Madrid · ESHospital Universitario HM Madrid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urinary flow measurement and colorimetry are vital medical indicators for critically ill patients in intensive care units. However, there is a clinical need for low-cost, continuous urinary flow monitoring devices that can automatically and in real-time measure urine flow. This need led to the development of a non-invasive device that is easy to use and does not require proprietary disposables. The device operates by detecting urine flow using an infrared barrier that returns an unequivocal pattern, and it is capable of measuring the volume of liquid in real-time, storing the history with a precise date, and returning alarms to detect critical trends. The device also has the ability to detect the color of urine, allowing for extended data and detecting problems in catheterized patients such as hematuria. The device is proposed as an automated clinical decision support system that utilizes the concept of the Internet of Medical Things. It works by using a LoRa communication method with the LoRaWAN protocol to maximize the distance to access points, reducing infrastructure costs in massive deployments. The device can send data wirelessly for remote monitoring and allows for the collection of data on a dashboard in a pseudonymous way. Tests conducted on the device using a gold standard medical grade infusion pump and fluid densities within the 1.005 g/ml to 1.030 g/ml urine density range showed that droplets were satisfactorily captured in the range of flows from less than 1 ml/h to 500 ml/h, which are acceptable ranges for urinary flow. Errors ranged below 15%, when compared to the values obtained by the hospital infusion pump used as gold standard. Such values are clinically adequate to detect changes in diuresis patterns, specially at low urine output ranges, related to renal disfunction. Additionally, tests carried out with different color patterns indicate that it detects different colors of urine with a precision in detecting RGB values <5%. In conclusion, the results suggest that the device can be useful in automatically monitoring diuresis and colorimetry in real-time, which can facilitate the work of nursing and provide automatic decision-making support to intensive care physicians.

Indexed as

Body FluidsFlowmetersAnonyms and PseudonymsColorimetryDiuresisHumans

Identifiers

PMID37651353
PMCPMC10470914
OpenAlexW4386323707

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.