BACKGROUND:This study aimed to characterize the types of intraoperative delays during robotic-assisted thoracic surgery, operating room staff awareness/perceptions of delays, and cost impact of delays on overall operative costs. METHODS:Robotic-assisted thoracic surgery cases from May to August 2019 were attended by 3 third-party observers to record intraoperative delays. The postoperative surveys were given to operating room staff to elicit perceived delays. Observed versus perceived delays were compared using the McNemar test. Direct costs and charges per delay were calculated. RESULTS:Forty-four cases were observed, of which a majority were lobectomies (n = 38 [86%]). A total of 71 delays were recorded by observers, encompassing 75% of cases (n = 33), with an average delay length of 3.6 minutes (±5.3 minutes). The following delays were observed: equipment failure (n = 40, average delay length 5.0 minutes (±6.5 minutes), equipment missing (n = 15, 2.2 minutes [±1.4 minutes]), staff unfamiliarity with equipment (n = 4, 3.4 minutes [± 1.5 minutes]), and other (n = 12, 4.5 minutes [±5.3 minutes]). The detection rates for any intraoperative delay were consistently lower for all of the operating room team members compared with observers, including surgeons (34.3% vs 77.1%; P = .0003), first assistants (41.9% vs 74.2%; P = .0075), surgical technologists (39.4% vs 72.7%; P = .0045), and circulating nurses (41.18% vs 76.47% minutes; P = .0013). The average operating room variable direct cost of delays based on the average total delay length per case was $225.52 (±$350.18) and was 1.6% (range 0-10.6%) of the total case charges. CONCLUSION:The lack of perception of intraoperative delays hinders operating teams from effectively closing the variable cost gaps. Future studies are needed to explore methods of increasing perception of delays and opportunities to improve operating room efficiency.

Immediate recurrence of AF (IRAF) is a common cause of direct current cardioversion (DCC) failure, and long-term recurrence of AF (LRAF) frequently occurs after a successful DCC. Identification of modifiable factors associated with IRAF and LRAF might improve overall success of DCC for atrial fibrillation.

Objective: To identify radiomic and clinical features associated with post-ablation recurrence of AF, given that cardiac morphologic changes are associated with persistent atrial fibrillation (AF), and initiating triggers of AF often arise from the pulmonary veins which are targeted in ablation. Methods: Subjects with pre-ablation contrast CT scans prior to first-time catheter ablation for AF between 2014–2016 were retrospectively identified. A training dataset (D1) was constructed from left atrial and pulmonary vein morphometric features extracted from equal numbers of consecutively included subjects with and without AF recurrence determined at 1 year. The top-performing combination of feature selection and classifier methods based on C-statistic was evaluated on a validation dataset (D2), composed of subjects retrospectively identified between 2005–2010. Clinical models ( $\text{M}_{\mathrm {C}}$ ) were similarly evaluated and compared to radiomic ( $\text{M}_{\mathrm {R}}$ ) and radiomic-clinical models ( $\text{M}_{\mathrm {RC}}$ ), each independently validated on D2. Results: Of 150 subjects in D1, 108 received radiofrequency ablation and 42 received cryoballoon. Radiomic features of recurrence included greater right carina angle, reduced anterior-posterior atrial diameter, greater atrial volume normalized to height, and steeper right inferior pulmonary vein angle. Clinical features predicting recurrence included older age, greater BMI, hypertension, and warfarin use; apixaban use was associated with reduced recurrence. AF recurrence was predicted with radio-frequency ablation models on D2 subjects with C-statistics of 0.68, 0.63, and 0.70 for radiomic, clinical, and combined feature models, though these were not prognostic in patients treated with cryoballoon. Conclusions: Pulmonary vein morphology associated with increased likelihood of AF recurrence within 1 year of catheter ablation was identified on cardiac CT. Significance: Radiomic and clinical features-based predictive models may assist in identifying atrial fibrillation ablation candidates with greatest likelihood of successful outcome.