RESUMO
Objective: Prior clinical trials have shown consistent clinical benefit for Capnometry Guided Respiratory Intervention (CGRI), a prescription digital therapeutic for the treatment of panic disorder (PD) and post-traumatic stress disorder (PTSD). The purpose of this study is to report real-world outcomes in a series of patients treated with the intervention in clinical practice. Design: This paper reports pre- and post-treatment self-reported symptom reduction, measures of respiratory rate and end-tidal carbon dioxide levels, drop-out and adherence rates drawn from an automatic data repository in a large real-world series of patients receiving CGRI for panic disorder and PTSD. Setting: Patients used the intervention in their homes, supported by telehealth coaching. Participants: Patients meeting symptom criteria for panic disorder (n = 1,395) or posttraumatic stress disorder (n = 174) were treated following assessment by a healthcare professional. Intervention: Capnometry Guided Respiratory Intervention is a 28-day home-based treatment that provides breath-to-breath feedback of respiratory rate and exhaled carbon dioxide levels, aimed at normalizing respiratory style and increasing patients' mastery for coping with symptoms of stress, anxiety, and panic. Health coaches provide initial training with weekly follow up during the treatment episode. Remote data upload and monitoring facilitates individualized coaching and aggregate outcomes analysis. Main outcome measures: Self-reported Panic Disorder Severity Scale (PDSS) and the Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5) scores were obtained at pre-treatment and post-treatment. Results: Panic disorder (PD) patients showed a mean pre-to-post-treatment reduction in total PDSS scores of 50.2% (P < 0.001, d = 1.31). Treatment response rates for PD (defined as a 40% or greater reduction in PDSS total scores) were observed in 65.3% of the PD patients. PTSD patients showed a pre-to-post-treatment reduction in total PCL-5 scores of 41.1% (P < 0.001, d = 1.16). The treatment response rate for PTSD (defined as a ≥10-point reduction in PCL-5 scores) was 72.4%. In an additional analysis of response at the individual level, 55.7% of panic disorder patients and 53.5% of PTSD patients were classified as treatment responders using the Reliable Change Index. Patients with both normal and below-normal baseline exhaled CO2 levels experienced comparable benefit. Across the 28-day treatment period, mean adherence rates of 74.8% (PD) and 74.9% (PTSD) were recorded during the 28-day treatment. Dropout rates were 10% (PD) and 11% (PTSD) respectively. Conclusions: The results from this cohort of 1,569 patients treated with the CGRI intervention demonstrate significant rates of symptom reduction and adherence consistent with prior published clinical trials. The brief duration of treatment, high adherence rates, and clinical benefit suggests that CGRI provides an important addition to treatment options for panic disorder and PTSD.
RESUMO
The war against cancer has yielded important advances in the early diagnosis and treatment of certain cancer types, but the poor detection rate and 5-year survival rate for lung cancer has changed little over the past 40 years. Early detection through emerging lung cancer screening programs promise the most reliable means of improving mortality. Sputum cytology has been tried without success because sputum contains few malignant cells that are difficult for cytologists to detect. However, research has shown that sputum contains diagnostic malignant cells and could serve as a means of lung cancer detection if those cells could be detected and correctly characterized. Recently, the National Lung Screening Trial reported that screening using 3 consecutive low-dose x-ray computed tomography scans provides a 20% reduction in lung cancer mortality compared with chest x-ray. However, this reduction in mortality comes with an unacceptable false-positive rate that increases patient risks and the overall cost of lung cancer screening. The LuCED test for detection of early lung cancer is reviewed in the current article. LuCED is based on patient sputum that is enriched for bronchial epithelial cells. The enriched sample is then processed on the Cell-CT, which images cells in 3 dimensions with submicron resolution. Algorithms are applied to the 3-dimensional cell images to extract morphometric features that drive a classifier to identify cells that have abnormal characteristics. The final status of these candidate abnormal cells is established by the pathologist's manual review. LuCED promotes accurate cell classification that could enable the cost-effective detection of lung cancer.