Researchers have developed a disposable array of gas sensors integrated into standard FFP2 facemasks that can identify patients with chronic kidney disease by analyzing breath composition with significant accuracy. The innovative device, which leverages porphyrin-based sensors to detect ammonia and other volatile compounds associated with kidney dysfunction, achieved identification of patients with chronic kidney disease with 93.3% true positives and 86.7% true negatives.
The findings represent an advancement in noninvasive diagnostic technology for a condition affecting approximately 10% of the global population, with a particular focus on developing accessible screening methods for resource-limited settings.
"Chronic kidney disease (CKD) corresponds to the alteration of renal structure and/or function that persists for at least 3 months and [that] has implications for the individual's health," the study authors noted. "Thus, there is a strong demand for low-cost and simple-to-use diagnostic procedures."
The researchers tested the device on a cohort of 101 patients (53 patients with CKD and 48 healthy controls). During testing, the patients wore the sensor-equipped masks and performed two breathing cycles at different rates—first at physiologic speed and intensity, then at a slightly accelerated frequency—while the device recorded oscillatory patterns in sensor resistance. A continuous wavelet transform algorithm processed these patterns to extract stable, reproducible features from each sensor.
Linear Discriminant Analysis of the sensor features achieved overall classification accuracy of 90%, with true positive rates of 93.3% and true negative rates of 86.7%. Additional analysis using Principal Component Analysis suggested that the sensor array could stratify patients with CKD according to disease severity, potentially enabling monitoring of disease progression.
Previous studies have identified elevated ammonia levels in those with CKD (approximately 34 ppm compared with 2.9 ppm in healthy individuals). However, researchers acknowledged that "the reliability of ammonia as a specific biomarker is questioned because high levels are not univocally related to CKD."
The sensors demonstrated cross-selectivity, with each exhibiting distinct sensitivity patterns. Free-base porphyrins showed greater sensitivity to ammonia, while manganese porphyrins were more responsive to alcohols. This diversity enabled the array to detect multiple compounds associated with CKD, including nitrogen-containing volatiles, aldehydes, ketones, and sulfides.
"Instead of directly printing the sensitive materials onto the internal surface of the mask," the study authors wrote, "we followed an alternative approach by preparing the sensor on a flexible substrate that is then placed inside the tissue of the facemasks." This approach could address challenges related to standardization of materials across different mask manufacturers.
The sensor array consisted of four resistive gas sensors printed on a flexible polymethyl methacrylate substrate using a commercial dispense printer with silver paste electrodes. The sensitive materials were created by doping poly(3,4-ethylenedioxythiophene) polystyrenesulfonate, a conductive polymer, with various porphyrins—macrocyclic compounds with diverse binding mechanisms such as van der Waals forces, hydrogen bonds, and coordination.
Four different porphyrin compounds were utilized: tetrakis-(4-sulfonatophenyl)porphyrin (TPPS), N-methyl-4-pyridylporphyrin (TPPy), and their manganese complexes (MnTPPS and MnTPPy). This design exploits the combinatorial selectivity of the sensor array to identify volatile compounds regardless of their concentration.
The research builds on the growing interest in using facemasks as platforms for breath analysis that emerged during the COVID-19 pandemic. The complete measurement process takes approximately 2 minutes, including the time needed to wear the mask and perform the breathing protocols. The researchers suggested that with proper expansion of the sensor array, "sensitized facemasks might be applied to the diagnosis of a larger spectrum of diseases and conditions."
The authors declared having no competing interests.
Source: ACS Sensors
