Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing 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.
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
16 authors.
Piyush HotaSchool for Engineering of Matter, Transport & Energy, Ira A. Fulton School of Engineering, Tempe, AZ 85287, USA.ORCID 0000-0002-1312-6863
Adithya Shyamala PandianDepartment of Nephrology and Hypertension, Mayo Clinic Arizona, 5777 E Mayo Boulevard, Phoenix, AZ 85054, USA.ORCID 0000-0001-9488-3075
Rodrigo E DomínguezCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave., Tempe, AZ 85287, USA.ORCID 0000-0002-2252-0715
Manni MoDepartment of Nephrology and Hypertension, Mayo Clinic Arizona, 5777 E Mayo Boulevard, Phoenix, AZ 85054, USA.ORCID 0000-0002-0253-0406
Bo FuCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave., Tempe, AZ 85287, USA.
Sandra MirandaCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave., Tempe, AZ 85287, USA.
Pinar Cay-DurgunDepartment of Nephrology and Hypertension, Mayo Clinic Arizona, 5777 E Mayo Boulevard, Phoenix, AZ 85054, USA.ORCID 0000-0001-6875-6603
Dheeraj SirganagariDepartment of Nephrology and Hypertension, Mayo Clinic Arizona, 5777 E Mayo Boulevard, Phoenix, AZ 85054, USA.
Michael SerhanCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave., Tempe, AZ 85287, USA.ORCID 0000-0001-9228-7480
Peter SerhanCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave., Tempe, AZ 85287, USA.
Kevin Abi KaramCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave., Tempe, AZ 85287, USA.ORCID 0009-0005-1923-2455
Naomi M GadesDepartment of Comparative Medicine, Mayo Clinic Arizona, 13400 East Shea Boulevard, Scottsdale, AZ 85259, USA.ORCID 0000-0003-2581-2243
Peter WiktorCenter for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave., Tempe, AZ 85287, USA.ORCID 0000-0001-8917-2607
Leslie ThomasDepartment of Nephrology and Hypertension, Mayo Clinic Arizona, 5777 E Mayo Boulevard, Phoenix, AZ 85054, USA.ORCID 0009-0002-2413-1374
Mary Laura LindSchool for Engineering of Matter, Transport & Energy, Ira A. Fulton School of Engineering, Tempe, AZ 85287, USA.ORCID 0000-0001-8585-8054
Erica ForzaniSchool for Engineering of Matter, Transport & Energy, Ira A. Fulton School of Engineering, Tempe, AZ 85287, USA.ORCID 0000-0003-2407-8251
Funding
A real-time monitoring and predictive device for cardiovascular surgeries and sepsisR61HL173926 · NHLBI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI Erica Silvia Forzani · 2025 to 2026
$802k
Mayo Clinic in Arizona Mayo Clinic Team Science GrantNHLBI NIH HHS R61 HL173926NIH HHS 1R61HL173926-25U.S. National Science Foundation 2122901
6 · The paper itself
Abstract
Acute kidney injury (AKI) affects thousands of hospitalized patients annually, yet early detection remains challenging as serum creatinine elevation lags behind clinical deterioration. Decreased urine output (UO) represents a key diagnostic criterion of AKI, sometimes manifesting hours before biochemical changes; however, current manual monitoring methods are labor-intensive and prone to error. Here, we developed and validated a simple, cost-effective automated urine flow meter using non-contact optical sensors, a peristaltic pump, and microcontroller-based automation for precise, real-time monitoring of urine output in clinical settings, named P-meter. Three successive prototypes (V1, V2, V3) were validated against gold-standard gravimetric measurements over 285 h of testing during animal experiments that required bladder catheterization. Iterative refinement addressed miniaturization challenges, fluid dynamics optimization, and sensor positioning to achieve progressively improved accuracy. The optimized V3 prototype demonstrated further enhanced volumetric precision, stability, and flow accuracy with near-unity linearity vs. reference method (R
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.
Development and Validation of an Optical Sensor-Based Automated Urine Flow Meter for Real-Time Patient Monitoring. · full record | OpenQuestion