Caustic Ingestion: A Risk-Based Algorithm

INTRODUCTION:Caustic ingestion management could be improved with a diagnostic approach based on risk factors. This study aimed to develop an algorithm derived from predictive factors of a poor clinical course, to evaluate its diagnostic accuracy and resource consumption, and to compare it with 2 other approaches, a radiological one based on computed tomography and a classical one based on symptoms and endoscopy. METHODS:All patients older than 15 years presenting with caustic ingestion in our tertiary care hospital between 1995 and 2021 were prospectively included. Adverse outcome was defined as intensive care unit admission, emergency surgery, or death. Ingestion characteristics, symptoms, and laboratory and endoscopic findings were analyzed to determine the most relevant risk factors. Diagnostic accuracy and the number of examinations required were estimated and compared with the other 2 algorithms applied to our series. RESULTS:The sample included 532 cases of caustic ingestion, 13.2% (95% confidence interval [CI]: 10.3-16.0) of which had adverse outcomes. Volume and type of caustic substance; presence of symptoms and pharyngolaryngeal involvement; and neutrophilia, acidosis, and endoscopic injury were combined to develop an algorithm that would provide the highest diagnostic odds ratio (167.2; 95% CI: 71.9-388.7). Following this approach, half of the patients (50.6%; 95% CI: 46.2-55.1) would not require any examination and, overall, the need for endoscopy (20.0%; 95% CI: 16.4-23.5) and computed tomography (16.3%; 95% CI: 13.0-19.5) would be lower than that for the other 2 algorithms. DISCUSSION:A risk-based algorithm could improve caustic ingestion management by maintaining high diagnostic accuracy while reducing diagnostic test requirements.