ArticlePloS one2023
Development of a urinometer for automatic measurement of urine flow in catheterized patients.
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.
What it found
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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
3 citing papers in PubMed, 8 citations in OpenAlex.
- Development and Validation of an Optical Sensor-Based Automated Urine Flow Meter for Real-Time Patient Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Recent Advances in Urinometers: Enhancing Monitoring of Urine Output, pH, and Color: A Narrative Review.Journal of pharmacy & bioallied sciences · 2025Review
- Definition of Oliguria in the Intensive Care Unit: How Do You Do It?Clinical journal of the American Society of Nephrology : CJASN · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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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.