Inova Fairfax Medical Campus is the largest hospital campus in Northern Virginia and the flagship hospital of Inova Health System. Located in Woodburn in Fairfax County, Virginia, Inova Fairfax Hospital is one of the largest employers in the county. Inova Fairfax Hospital is also home to a neonatal intensive care unit, and a dedicated pediatrics intensive care unit, an oncology unit, an adolescent medicine unit, and centers for cardiac surgery and pediatric surgery.The Inova Fairfax Hospital can be more accurately described as a campus encompassing three hospitals: the Inova Fairfax Hospital proper, which includes the original building, the Inova Children's Hospital, and the Inova Heart and Vascular Institute.
BACKGROUND:Allograft injury in the early post-transplant period is a known risk factor of death after lung transplantation. However, the recipient tissue injury profile and its association with outcomes remain unexplored. This study leverages cell-free DNA (cfDNA) to test this association. METHODS:The prospective cohort multicentre study included lung transplant recipients (GRAfT; ClinicalTrials.gov: NCT02423070) with serial plasma measurements of recipient-derived (rd)-cfDNA using digital droplet PCR. Non-transplant healthy controls were recruited as the comparator. Whole-genome bisulfite sequencing identified tissue sources of cfDNA. Mean rd-cfDNA levels within 30 days post-transplant were computed. Multivariable regression models were used to assess the association between rd-cfDNA tertiles and the primary outcome (death) and secondary outcomes. RESULTS:The study included 215 patients with 2530 cfDNA values, including 675 cfDNA assessments in the first 30 days. Median rd-cfDNA levels in the first 30 days post-transplant were ∼16-fold higher than cfDNA for healthy controls. Patients in the highest tertile rd-cfDNA group had lower lung function post-transplant, and increased risk of death (hazard ratio (HR) 3.15, 95% CI 1.59-6.24; p<0.001) and acute rejection (HR 2.33, 95% CI 1.33-4.08; p=0.03) compared to the low/middle tertile group. Tissue-specific cfDNA sources were distinct in the highest versus lowest rd-cfDNA tertiles, with cfDNA from innate immune cells serving as the strongest predictor of mortality. CONCLUSION:Post-transplant recipient tissue injury varies between lung transplant patients, and is associated with increased risk of acute rejection and mortality.
BACKGROUND:Preclinical data indicate that inhaled treprostinil may be useful for the treatment of idiopathic pulmonary fibrosis (IPF) through an antifibrotic mechanism, a premise that is supported by clinical observation. METHODS:In this phase 3, double-blind trial, we randomly assigned patients with IPF to receive inhaled treprostinil or placebo (12 breaths four times daily) over a period of 52 weeks. The primary end point was the change from baseline in the absolute forced vital capacity (FVC) at week 52. Secondary end points, which were analyzed in a prespecified order to control for multiplicity, were clinical worsening and acute exacerbation of IPF (each assessed in a time-to-event analysis), death by week 52, and the change from baseline in the percentage of predicted FVC, quality of life, and the diffusing capacity of the lungs for carbon monoxide by week 52. Safety was also assessed. RESULTS:A total of 593 patients underwent randomization and received at least one dose of treprostinil (298 patients) or placebo (295 patients). Of these, 463 patients (224 in the treprostinil group and 239 in the placebo group) completed the trial assessments through week 52. The mean age of the patients was 71.7 years, 80.1% were men, the mean FVC at baseline was 76.8%, and 75.4% of the patients were receiving background antifibrotic therapy. The median change in FVC at week 52 was -49.9 ml (95% confidence interval [CI], -79.2 to -19.5) in the treprostinil group and -136.4 ml (95% CI, -172.5 to -104.0) in the placebo group; the between-group difference in the change in FVC was 95.6 ml (95% CI, 52.2 to 139.0; P<0.001). Clinical worsening occurred in 81 patients (27.2%) in the treprostinil group and 115 patients (39.0%) in the placebo group (hazard ratio, 0.71; 95% CI, 0.53 to 0.95; P = 0.02). No substantial between-group difference in the time to IPF exacerbation was observed, and so no further inferences with regard to subsequent secondary end points were made. The most common adverse event was cough, reported in 48.3% of the patients in the treprostinil group and 24.1% of those in the placebo group. Discontinuation of treprostinil or placebo occurred in 33.6% and 24.7%, respectively, with approximately half these patients citing adverse events as the primary reason for discontinuation. CONCLUSIONS:In patients with IPF, inhaled treprostinil was associated with a smaller decline in FVC and fewer clinical-worsening events than placebo over a period of 52 weeks. (Funded by United Therapeutics; TETON-2 ClinicalTrials.gov number, NCT05255991.).
As artificial intelligence tools become increasingly integrated into emergency department workflows, healthcare providers face a growing risk of legal liability stemming from improper use, particularly with respect to data privacy and Health Insurance Portability and Accountability Act (HIPAA) compliance. This article explores a realistic clinical scenario in which an emergency physician inadvertently violates HIPAA using a publicly available AI tool, such as ChatGPT, Gemini, Llama, and Grok, without a valid Business Associate Agreement in place.We review the legal framework of the HIPAA Privacy, Security, and Breach Notification Rules and delineate the respective liabilities of healthcare institutions and individual clinicians. Key distinctions are made between incidental, accidental, and unauthorized disclosures of protected health information, and we provide clear guidance on post-breach mitigation steps. The article also discusses the statistical likelihood of protected health information reidentification or reproduction by AI models and outlines risks associated with state-level data protection laws.Ultimately, we offer practical recommendations for physicians seeking to leverage AI responsibly in clinical care, including verifying institutional Business Associate Agreements, understanding platform-specific privacy policies, and consulting with privacy officers before entering any patient data. As AI rapidly evolves, clinicians must remain vigilant in safeguarding patient information to avoid legal exposure and uphold ethical standards of care.
