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Pandian, Adithya Shyamala

0000-0001-9488-3075

Mayo Clinic

Mayo Clinic in Arizona

Citations 3

Development and Validation of an Optical Sensor-Based Automated Urine Flow Meter for Real-Time Patient Monitoring
Hota, Piyush , Pandian, Adithya Shyamala , Domínguez, Rodrigo E., Mo, Manni , Fu, Bo , Miranda, Sandra, Cay-Durgun, Pinar , Sirganagari, Dheeraj, Serhan, Michael , Serhan, Peter , Karam, Kevin Abi , Gades, Naomi M. , Wiktor, Peter , Thomas, Leslie F. , Lind, Mary Laura , Forzani, Erica , Domínguez, R. , Dominguez, Rodrigo E , Thomas, Leslie , Miranda, Sandra, Sirganagari, Dheeraj Reddy

Sensors | January 28, 2026 | Volume: 26 | Issue: 3 | Pages: 849

10.3390/s26030849 Get It

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 (R2 = 0.9889), minimal bias (mean error −0.1 mL), and 94.18% agreement within confidence limits (n = 86), outperforming the initial V1 prototype (R2 = 0.9971, mean error −1.69 mL, n = 207) and intermediate V2 design (R2 = 0.9941, mean error 3.63 mL, n = 390), primarily in terms of reduced bias and improved agreement. The P-meter offers accurate urine output monitoring at a lower cost than commercial systems, facilitating its use in early AKI detection and thereby improving patient outcomes.
Efficacy of Portable Fugitive Aerosol Mitigation Systems for Nebulizer Therapy During High-Flow Nasal Cannula and Non-Invasive Ventilation
Pandian, Adithya Shyamala , Patel, B. M. , Karam, Karam Abi , Lowell, Amelia , McKay, Kelly, Hota, Piyush , Pyznar, Gabriel , Batchelor, Sandra, Peworski, Charles, Rivas, David A., Sanghavi, Devang , Nguyen, Ngan Anh, Eltantawy, Aliaa, Li, Xueqi , Serhan, Michael , Forzani, Erica , Patel, Bhavesh M , Mora, Sabrina , Batchelor, Sandra, Peworski, Charles, Rivas, David, Xian, Xiaojun

Emergency Care and Medicine | July 29, 2025 | Volume: 2 | Issue: 3 | Pages: 36

10.3390/ecm2030036 Get It

Objectives: This study evaluates the efficacy of existing and new aerosol mitigation methods during nebulization (Neb) in combination with high-flow nasal cannula (HFNC) oxygen supplementation and non-invasive ventilation (NIV). Methods: We recorded fugitive aerosol particle concentrations over time and assessed the peak (P) and area (A) efficacy of active and passive mitigation methods, comparing them to a no-mitigation condition. Peak efficacy was measured by the reduction in maximum aerosol concentration, while area efficacy was quantified by the reduction of the area under the aerosol concentration–time curve. Results: For HFNC with Neb, we found that active mitigation using a mask with a biofilter and a fan (referred to as the aerosol barrier mask) significantly outperformed passive mitigation with a face mask. The peak and area efficacy for aerosol reduction were 99.0% and 96.4% for active mitigation and 35.9% and 7.6% for passive mitigation, respectively. For NIV with Neb, the active mitigation method, using a box with a biofilter and fan, also outperformed passive mitigation using only the box. The peak and area efficacy for aerosol reduction were 92.1% and 85.5% for active mitigation and 53.7.0% and 25.4% for passive mitigation, respectively. Conclusion: We concluded that active mitigation set up systems advantageous for effective reduction of airborne aerosols during aerosol generated procedures.
Self-contained system for mitigation of contaminated aerosol sources of SARS-CoV-2 
Patel, B. M. , Forzani, Erica , Lowell, Amelia , McKay, Kelly, Karam, Karam Abi , Pandian, Adithya Shyamala , Pyznar, Gabriel , Xian, Xiaojun, Serhan, Michael

No container title available | February 24, 2021 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-237873/v1 Get It

Abstract Contaminated aerosols and micro droplets are easily generated by infected hosts through sneezing, coughing, speaking and breathing1-3 and harm humans’ health and the global economy. While most of the efforts are usually targeted towards protecting individuals from getting infected,4 eliminating transmissions from infection sources is also important to prevent disease transmission. Supportive therapies for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2) pneumonia such as oxygen supplementation, nebulizers and non-invasive mechanical ventilation all carry an increased risk for viral transmission via aerosol to healthcare workers.5-9 In this work, we study the efficacy of five methods for self-containing aerosols emitted from infected subjects undergoing nebulization therapies with a diverse spectrum on oxygen delivery therapies. The work includes five study cases: Case I: Use of a Full-Face Mask with biofilter in bilevel positive airway pressure device (BPAP) therapy, Case II: Use of surgical mask in High Flow Nasal Cannula (HFNC) therapy, Case III: Use of a modified silicone disposable mask in a HFNC therapy, Case IV: Use of a modified silicone disposable mask with a regular nebulizer and normal breathing, Case V: Use of a mitigation box with biofilter in a Non-Invasive Positive Pressure Ventilator (NIPPV). We demonstrate that while cases I, III and IV showed efficacies of 98-100%; cases II and V, which are the most commonly used, resulted with significantly lower efficacies of 10-24% to mitigate the dispersion of nebulization aerosols. Therefore, implementing cases I, III and IV in health care facilities may help battle the contaminations and infections via aerosol transmission during a pandemic.