Assessing variability in predictors of adequate follow-up after esophageal food bolus impaction: a retrospective study and literature review

Background: Despite guidelines recommending comprehensive post-esophageal food bolus impaction (EFBI) evaluation, follow-up adherence varies. It’s unclear whether predictors of follow-up are consistent or unique to individual populations. We assess post EFBI follow-up rates and predictors at our center and compare them to existing literature.

Methods: We retrospectively studied adults (≥18 years) presenting with EFBI between June 2021 and October 2024. Patients without follow-up data or with non-food bolus impactions were excluded. Patients were categorized by follow-up adequacy (endoscopy or office visit within six months). We compared demographic, clinical, and endoscopic variables. Predictors of follow-up were identified using univariable and multivariable logistic regression. We also reviewed comparable studies to evaluate differences in patient populations, study designs, and factors influencing follow-up rates.

Results: Among 137 patients, 60 (44%) lacked adequate follow-up. On multivariable analysis, predictors of follow-up included Caucasian race [odds ratio (OR) 24.4, P<0.001], county of residence (OR 0.31, P=0.02), history of anti-reflux surgery (OR 6.57, P=0.03), suspecting esophageal disease at index encounter (OR 3.09, P=0.02), ordering follow-up endoscopy (OR 5.26, P=0.01), and scheduling gastroenterology/gastrointestinal (GI) appointments (OR 10.7, P<0.001). A review of seven comparable studies involving 1,663 patients revealed variability in follow-up rates (16% to 55%), predictors of follow-up, and inconsistencies in inclusion criteria and follow-up definitions.

Conclusions: Ambulatory follow-up after EFBI remains suboptimal, with 44% of our cohort lacking follow-up within six months. Race was the strongest predictor; however, given the wide confidence interval, this finding should be interpreted as exploratory rather than definitive. Other modifiable and demographic predictors include county of residence and discharge-planning practices. Our literature review revealed variability in follow-up rates and predictors across studies, highlighting the need for institution-specific strategies that address healthcare inequities and barriers.