Beyond childhood: exploring the state of transitional care in pediatric pilocytic astrocytoma.

OBJECTIVE: Pediatric pilocytic astrocytoma (PPA) requires prolonged follow-up after initial resection. The landscape of transitional care for PPA patients is not well characterized. The authors sought to examine the clinical course and transition to adult care for these patients to better characterize opportunities for improvement in long-term care. METHODS: Pediatric patients (younger than 18 years at diagnosis) who underwent biopsy or resection for PPA between May 2000 and November 2022 at the authors' large academic center were retrospectively reviewed. Patient demographics, tumor characteristics, recurrence, adjuvant therapies, and follow-up data were extracted from the electronic medical record via chart review. Charts of patients who were 18 years or older as of January 1, 2024, were reviewed for adult follow-up notes. RESULTS: The authors identified 315 patients who underwent biopsy or resection for PPA between May 2000 and November 2022. The most common tumor location was posterior fossa (59.7%), and gross-total resection (GTR) was achieved in 187 patients (59.4%). In patients with GTR, progression/recurrence occurred less frequently (8.6% vs 41.4%, p < 0.01) compared to patients with non-GTR. Among 177 patients found to be age-eligible for transition to adult care, the authors found that 31 (17.5%) successfully transitioned. The average age at transition from pediatric to adult care was 21.7 years, and the average age at last known adult follow-up was 25.0 years. The authors found that patients who transitioned to adult care were followed longer (12.5 vs 7.0 years, p < 0.01) and were diagnosed at an older age (12.1 vs 9.6 years, p < 0.01) than their untransitioned counterparts. CONCLUSIONS: The authors found that there was a low rate of successful transition from pediatric to adult care for PPA; 17.5% of age-eligible patients are now cared for by adult providers, whereas an additional 18.6% completed appropriate follow-up during childhood and did not require transition to adult care. These findings underscore opportunities for improvement in the pediatric-to-adult transition process for patients with PPA, particularly for those with non-GTR who were not followed for at least 10 years, during which the risk of disease progression is thought to be highest.

Vein diameter, obesity, and rates of recanalization after mechanochemical ablation.

OBJECTIVE: A large vein diameter is associated with higher recanalization rates after endovenous thermal ablation procedures of the great saphenous vein (GSV) and small saphenous vein (SSV). However, relatively few studies have explored the relationship between vein diameter and recanalization rates after mechanochemical ablation (MOCA). METHODS: We conducted a retrospective review of patients with chronic venous insufficiency who underwent MOCA of the GSV or SSV from 2017 to 2021 at a single hospital. Patients with no follow-up ultrasound examination were excluded. Patients were classified as having a large (≥1 cm) or small (<1 cm) treated vein. The primary outcomes were 2-year recanalization and reintervention of the treated segment. RESULTS: A total of 186 MOCA procedures during the study period were analyzed. There was no differences in age, gender, history of venous thromboembolic events, use of anticoagulation, obesity, or length of treated segment between the cohorts. Patients with large veins were less likely to have stasis ulcers compared with those with small veins (3.2% vs 21.5%; P < .05 on Fisher exact test). Patients with large veins had a higher incidence of postoperative local complications (24.2% vs 7.2%, P < .05 on χ2 test). A survival analysis with Cox proportional hazards showed no significant difference in recanalization rates with larger vein diameters. However, obesity was found to correlate significantly with recanalization. CONCLUSIONS: A large vein diameter was not associated with higher recanalization rates after MOCA of the GSVs and SSVs. However, obesity was found to correlate with recanalization rates.

Reducing Wait Times for Radiology Exams Around Holiday Periods: A Monte Carlo Simulation.

Reducing patient wait times is a key operational goal and impacts patient outcomes. The purpose of this study is to explore the effects of different radiology scheduling strategies on exam wait times before and after holiday periods at an outpatient imaging facility using computer simulation. An idealized Monte Carlo simulation of exam scheduling at an outpatient imaging facility was developed based on the actual distribution of scheduled exams at outpatient radiology sites at a tertiary care medical center. Using this simulation, we examined three scheduling strategies: (1) no scheduling modifications, (2) increase imaging capacity before or after the holiday (i.e. increase facility hours), and (3) use a novel rolling release scheduling paradigm. In the third scenario, a fraction of exam slots are blocked to long-term follow-up exams and made available only closer to the exam date, thereby preventing long-term follow-up exams from filling the schedule and ensuring slots are available for non-follow-up exams. We examined the effect of these three scenarios on utilization and wait times, which we defined as the time from order placement to exam completion, during and after the holiday period. The baseline mean wait time for non-follow-up exams was 5.4 days in our simulation. When no scheduling modifications were made, there was a significant increase in wait times in the week preceding the holiday when compared to baseline (10.0 days vs 5.4 days, p < 0.01). Wait times remained elevated for 4 weeks following the holiday. Increasing imaging capacity during the holiday and post-holiday period by 20% reduced wait times by only 6.2% (9.38 days vs 10.0 days, p < 0.01). Increasing capacity by 50% resulted in a 7.1% reduction in wait times (9.28 days, p < 0.01), and increasing capacity by 100% resulted in a 13% reduction in wait times (8.75 days, p < 0.01). In comparison, using a rolling release model produced a reduction in peak wait times equivalent to doubling capacity (8.76 days, p < 0.01) when 45% of slots were reserved. Improvements in wait times persisted even when rolling release was limited to the 3 weeks preceding or 1 week following the holiday period. Releasing slots on a rolling basis did not significantly decrease utilization or increase wait times for long-term follow-up exams except in extreme scenarios where 80% or more of slots were reserved for non-follow-up exams. A rolling release scheduling paradigm can significantly reduce wait time fluctuations around holiday periods without requiring additional capacity or impacting utilization.