Validation of natural language processing to determine the presence and size of abdominal aortic aneurysms in a large integrated health system.

OBJECTIVE: Previous studies of the natural history of abdominal aortic aneurysms (AAAs) have been limited by small cohort sizes or heterogeneous analyses of pooled data. By quickly and efficiently extracting imaging data from the health records, natural language processing (NLP) has the potential to substantially improve how we study and care for patients with AAAs. The aim of the present study was to test the ability of an NLP tool to accurately identify the presence or absence of AAAs and detect the maximal abdominal aortic diameter in a large dataset of imaging study reports. METHODS: Relevant imaging study reports (n = 230,660) from 2003 to 2017 were obtained for 32,778 patients followed up in a prospective aneurysm surveillance registry within a large, diverse, integrated healthcare system. A commercially available NLP algorithm was used to assess the presence of AAAs, confirm the absence of AAAs, and extract the maximal diameter of the abdominal aorta, if stated. A blinded expert manual review of 18,000 randomly selected imaging reports was used as the reference standard. The positive predictive value (PPV or precision), sensitivity (recall), and the kappa statistics were calculated. RESULTS: Of the randomly selected 18,000 studies that underwent expert manual review, 48.7% were positive for AAAs. In confirming the presence of an AAA, the interrater reliability of the NLP compared with the expert review showed a kappa value of 0.84 (95% confidence interval [CI], 0.83-0.85), with a PPV of 95% and sensitivity of 88.5%. The NLP algorithm showed similar results for confirming the absence of an AAA, with a kappa of 0.79 (95% CI, 0.799-0.80), PPV of 77.7%, and sensitivity of 91.9%. The kappa, PPV, and sensitivity of the NLP for correctly identifying the maximal aortic diameter was 0.88 (95% CI, 0.87-0.89), 88.8%, and 88.2% respectively. CONCLUSIONS: The use of NLP software can accurately analyze large volumes of radiology report data to detect AAA disease and assemble a contemporary aortic diameter-based cohort of patients for longitudinal analysis to guide surveillance, medical management, and operative decision making. It can also potentially be used to identify from the electronic medical records pre- and postoperative AAA patients "lost to follow-up," leverage human resources engaged in the ongoing surveillance of patients with AAAs, and facilitate the construction and implementation of AAA screening programs.

Exosomal TAR DNA binding protein 43 profile in canine model of amyotrophic lateral sclerosis: a preliminary study in developing blood-based biomarker for neurodegenerative diseases.

OBJECTIVE: Blood-based biomarkers provide a crucial information in the progress of neurodegenerative diseases with a minimally invasive sampling method. Validated blood-based biomarker application in people with amyotrophic lateral sclerosis would derive numerous benefits. Canine degenerative myelopathy is a naturally occurring animal disease model to study the biology of human amyotrophic lateral sclerosis. Serum derived exosomes are potential carriers for cell-specific cargoes making them ideal venue to study biomarkers for a variety of diseases and biological processes. This study assessed the exosomal proteins that may be assigned as surrogate biomarker that may reflect biochemical changes in the central nervous system. METHODS: Exosomes were isolated from canine serum using commercial exosome isolation reagents. Exosomes target proteins contents were analyzed by the Western blotting method. RESULTS: The profiles of potential biomarker candidates in spinal cord homogenate and that of serum-derived exosomes were found elevated in dogs with degenerative myelopathy as compared to control subjects. CONCLUSIONS: Serum-derived exosomal biomolecules can serve as surrogate biomarkers in neurodegenerative diseases.KEY MESSAGESA canine with degenerative myelopathy can serve as a model animal to study human amyotrophic lateral sclerosis.Serum-derived exosomes contain Transactive Response DNA Binding Protein 43 (TDP-43), a potential biomarker candidate.The levels of spinal cord TDP-43 proteins and that of serum-derived exosomes exhibited similar profiling. Therefore, serum derived exosomes may be used as a venue for establishing blood-based biomarkers for neurodegenerative diseases.