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We developed the Navigate intervention to improve survival among vulnerable lung cancer patients. In this intervention-only study, we examined feasibility in terms of recruitment, retention, attendance, adherence, and acceptability to specify adjustments to study procedures and intervention components prior to a randomized trial. The Navigate intervention includes nurse navigation, patient-reported outcomes, and physical exercise. Patients ≥ 18 years old, diagnosed with non-small cell lung cancer at any stage, with performance status ≤ 2, eligible for cancer treatment and vulnerable according to a screening instrument were included. The recruitment goal of eligible patients was 40% while the retention goal was 85%. The predefined cut-offs for sufficient attendance and adherence were ≥ 75%. Acceptability was evaluated by semi-structured interviews with participants, nurse navigators, and physiotherapists. Seventeen (56%) out of 30 screened patients were considered vulnerable and eligible for the study, 14 (82%) accepted participation, and 3 (21%) were subsequently excluded due to ineligibility, leaving 11 patients. Four patients dropped out (36%) and four patients died (36%) during follow-up and 3 (27%) were retained. All 11 patients participated in nurse sessions (mean 16, range 1-36) with 88% attendance and dialogue tools being applied in 68% of sessions. Ninety-one percent of patients responded to PROs (mean of 9 PROs, range 1-24) with 76% of the PRO questionnaires used (attendance) and 100% adherence (completion of all questions in PRO questionnaires), and 55% participated in exercise sessions with 58% attendance and 85% adherence. We identified important barriers primarily related to transportation, but overall acceptability was high. The Navigate intervention was feasible with high participation, acceptability and satisfactory adherence. Retention and exercise attendance were low, which resulted in adjustments.Trial registration: The feasibility study was initiated prior to the multicenter randomized controlled trial registered by ClinicalTrials.gov (number: NCT05053997; date 23/09/2021).
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http://dx.doi.org/10.1038/s41598-023-50161-w | DOI Listing |
JMIR Hum Factors
September 2025
KK Women's and Children's Hospital, Singapore, Singapore.
Background: Breast cancer treatment, particularly during the perioperative period, is often accompanied by significant psychological distress, including anxiety and uncertainty. Mobile health (mHealth) interventions have emerged as promising tools to provide timely psychosocial support through convenient, flexible, and personalized platforms. While research has explored the use of mHealth in breast cancer prevention, care management, and survivorship, few studies have examined patients' experiences with mobile interventions during the perioperative phase of breast cancer treatment.
View Article and Find Full Text PDFInt J Surg
September 2025
Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Background: Percutaneous transthoracic lung biopsy (PTNB) guided by Computed Tomography (CT) greatly depends on the operators' skill for accuracy. This study aimed to evaluate whether three-dimensionally(3D) printed navigational templates for percutaneous transthoracic lung biopsy achieve diagnostic yield comparable to conventional computed tomography guidance.
Materials And Methods: Conducted from 1 November 2020, to 27 July 2023, this noninferiority randomized clinical trial included 159 patients with peripheral lung masses (≥30 mm).
J Chem Inf Model
September 2025
Songshan Lake Materials Laboratory, Dongguan 523808, PR China.
Large language models (LLMs) have demonstrated transformative potential for materials discovery in condensed matter systems, but their full utility requires both broader application scenarios and integration with ab initio crystal structure prediction (CSP), density functional theory (DFT) methods and domain knowledge to benefit future inverse material design. Here, we develop an integrated computational framework combining language model-guided materials screening with genetic algorithm (GA) and graph neural network (GNN)-based CSP methods to predict new photovoltaic material. This LLM + CSP + DFT approach successfully identifies a previously overlooked oxide material with unexpected photovoltaic potential.
View Article and Find Full Text PDFBlood Coagul Fibrinolysis
August 2025
School of Disaster and Emergency Medicine, Tianjin University; Key Laboratory of Medical Rescue Key Technology and Equipment, Ministry of Emergency Management, Tianjin, China.
Traumatic hemorrhage poses a significant medical challenge to humanity, which is one of the primary causes of patient mortality. Rapid and effective hemostasis is crucial for saving lives, however, traditional hemostatic methods exhibiting numerous limitations, such as unstable hemostatic effects, complex operations, and potential complications. In recent years, with the rapid development of nanotechnology, significant progress has been made in the nanotechnological optimization of synthetic polymer hemostats, providing new avenues for navigating precision hemostasis.
View Article and Find Full Text PDFFront Public Health
September 2025
Department of Health Care Sciences, Marie Cederschiöld University, Stockholm, Sweden.
Purpose: This study investigates how older foreign-born adults in Sweden experience and navigate social connectedness as a determinant of wellbeing.
Methods: Employing Glaser's grounded theory methodology, we collected qualitative data through individual ( = 1) and focus group ( = 5) interviews with 23 participants aged 60 + representing four distinct cultural-linguistic groups: Arabic, Finnish, Spanish, and Chinese speakers.
Results: The analysis identified "" as the core category, encompassing three dimensions: (1) , (2) , and (3) .