Back

Sterilizable, Time-Integrating Hydrogel Sensors Enable Continuous Gastrointestinal Leak Surveillance in Low- and High-Resource Settings

Jessernig, A.; von Forcade de Biaix, I.; Himmel, C.; Gomez-Ochoa, S. A.; Wolf, A.; Spengler, F.; Hernandez-Vargas, J. C.; Quintero-Gamboa, D. C.; Pacheco-Maldonado, J. M.; Serrano-Pastrana, J. P.; Schlegel, A.; Quiroga-Centeneo, A. C.; Tarantino, I.; Herrmann, I. K.

2026-07-27 gastroenterology
10.64898/2026.07.21.26358572 medRxiv
Show abstract

Gastrointestinal anastomotic leakage (AL) remains a life-threatening complication following gastrointestinal surgery, where outcomes critically depend on timely diagnosis. Current diagnostic strategies rely on periodic sampling and resource-intensive analysis in centralized laboratories. Here, we present a sterilizable, time-integrating hydrogel sensor platform for continuous, infrastructure-free monitoring of the patient's postoperative drain fluid. We introduce enzyme-responsive macromolecular networks for semi-quantitative bedside assessment of leak-associated digestive enzymes. The sensors retain functionality following lyophilization and ethylene oxide sterilization, enabling long-term storage and scalable deployment around the world. In a Swiss clinical cohort of 56 patients, including 19 with gastrointestinal anastomotic leakage, the sensor detected amylase-associated leaks two days (median) prior to clinical diagnosis with a sensitivity of 78% (95% CI 55-91) and a specificity of 95% (95% CI 82-99). The prospective validation in an independent cohort of 37 patients in Colombia, including seven patients with leaks, demonstrated 100% sensitivity (95% CI 64.6-100) and a 100% negative predictive value (95% CI 87.9-100.0), with sensor activation preceding standard clinical diagnosis by a median of five days. By converting episodic biochemical measurements into continuous, cumulative visual records, this infrastructure-free material platform enables close-meshed postoperative monitoring and may facilitate earlier recognition of anastomotic leakage across diverse healthcare settings.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.