P1.067: A Comparison of Pediatric Quality-of-Life Assessment Tools and Disease Complexity in Patients with Esophageal Atresia

Background: Esophageal atresia (EA) is a complex condition that requires longitudinal and multi-disciplinary care. Quality of life (QoL) research in EA patients is sparse, and often utilizes generic QoL assessment tools, which may not accurately capture the impact of disease. We aim to study three QoL tools in EA patients, as well as elucidate the potential impact of disease complexity.

Methods: We offered QoL assessments to our EA patients at least 2 years of age (IRB #23-106). Three QoL tools were utilized for comparison of patient results, including a generic (PedsQL), a symptom-specific (GIPedsQL) and a disease-specific survey (EAQL). Disease complexity was compared to QoL and determined by comorbidities, as well as the medical burden within the past two years measured by clinic visits, emergency/urgent care visits, procedures/surgeries, and clinic communications. Statistical analysis included repeated measures one-way ANOVA, Fisher’s exact test, and t-test.

Results: Overall response rate was 64% (n=21/33), with higher participation rate during in-person clinic visits (n=16) compared to electronic-mail (n=5). Age, Gross Type EA and presence of VACTERL syndrome did not impact QoL.

Overall, 52% (n=11) of patients report a poor QoL on at least one assessment tool. There was no statistically significant difference among survey tools (p=0.145), but only a portion of these patients (45%) had consistently poor QoL totals across all three tools.

Subcategory analysis reveals variability among QoL tools. The disease-specific tool highlights eating as the most problematic area (45%), while the generic tool identifies larger concerns with school (64%) and psychosocial (50%) factors, rather than physical factors. When assessing gastrointestinal symptoms (GIPedsQL), the largest complaint for patients was “stomach hurting” (57%).

When assessing impact of medical care needs, we found that patients with poorer QoL scores had significantly more emergent visits, communications (telephone/electronic), and multi-disciplinary clinic visits (Table 1).

Conclusion: Disease-specific QoL assessment tools are an ideal means to capture QoL in patients with complex diseases, especially in EA patients where multiple systems may impact QoL, i.e., gastrointestinal, respiratory and cardiac. However, generic tools may still capture accurate QoL since these disease-specific factors also impact overall wellbeing. The preciseness of a disease-specific tool can better guide resources offered to address factors affecting QoL. Validation of a disease-specific QoL tool for EA patients in the US is still needed.

We identified lower QoL in EA patients with higher disease complexity as evidenced by more frequent medical encounters. Although multi-disciplinary encounters were more frequent in poor QoL patients, this may be a marker of disease complexity, rather than an influence on poor QoL. The collaborative and patient-centered care offered by multi-disciplinary encounters is a studied positive for families. Further study is needed to demonstrate this outcome for EA patients.