Robotic One Anesthetic Diagnosis and Treatment: A Novel Program for Lung Cancer Care

机器人辅助麻醉诊断和治疗:一种新型肺癌治疗方案

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Abstract

BACKGROUND: Early diagnosis and treatment of lung cancer can improve patient outcomes. To reduce the delay between diagnosis and treatment, we initiated a Robotic One Anesthetic Diagnosis and Treatment (ROADAT) program for lung nodules that combined robotic navigational bronchoscopy, liquid rapid on-site evaluation (ROSE), and surgical resection in the same setting. METHODS: A retrospective review was conducted of patients who underwent the ROADAT procedure from December 1, 2021, through January 31, 2024. These patients were compared with sequential controls from the same time window, who would have been ROADAT candidates but underwent diagnosis and treatment using a standard lung nodule workup. RESULTS: There were 36 patients in the ROADAT group and 35 controls. Of the 36 ROADAT patients, 31 (86%) underwent lung resections. When final pathology was available, ROSE was concordant in 91% (29 of 32) of cases. Compared with robotic lobectomies alone, ROADAT procedures that resulted in lobectomies added 73 minutes (P = .003). However, total operating room time for when lobectomy and biopsy were done in separate settings was 54 minutes shorter in the ROADAT group (P = .028). Direct (ROADAT, $19,244; controls, $21,737; P = .004) procedure costs and total (ROADAT, $26,668; controls, $29,882; P = .005) procedure costs were lower in the ROADAT group for patients who underwent lobectomy. Time from detection to resection was 35 days shorter in the ROADAT group (ROADAT, 82 days; controls, 117 days; P = .001). CONCLUSIONS: The ROADAT procedure reduced time from nodule detection to surgical resection compared with the standard approach. Liquid-based ROSE had high concordance with final pathology. Total operative time, direct costs, and total costs were lower for the ROADAT procedure.

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