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SHR Neuro Krebs Kardio Lipid Stoffw Microb

Breitwieser, M; Moore, V; Wiesner, T; Wichlas, F; Deininger, C.
NLP-Driven Analysis of Pneumothorax Incidence Following Central Venous Catheter Procedures: A Data-Driven Re-Evaluation of Routine Imaging in Value-Based Medicine.
Diagnostics (Basel). 2024; 14(24): Doi: 10.3390/diagnostics14242792 [OPEN ACCESS]
Web of Science PubMed FullText FullText_MUG

Co-Autor*innen der Med Uni Graz: Deininger Christian
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Abstract:: Background: This study presents a systematic approach using a natural language processing (NLP) algorithm to assess the necessity of routine imaging after central venous catheter (CVC) placement and removal. With pneumothorax being a key complication of CVC procedures, this research aims to provide evidence-based recommendations for optimizing imaging protocols and minimizing unnecessary imaging risks. Methods: We analyzed electronic health records from four university hospitals in Salzburg, Austria, focusing on X-rays performed between 2012 and 2021 following CVC procedures. A custom-built NLP algorithm identified cases of pneumothorax from radiologists' reports and clinician requests, while excluding cases with contraindications such as chest injuries, prior pneumothorax, or missing data. Chi-square tests were used to compare pneumothorax rates between CVC insertion and removal, and multivariate logistic regression identified risk factors, with a focus on age and gender. Results: This study analyzed 17,175 cases of patients aged 18 and older, with 95.4% involving CVC insertion and 4.6% involving CVC removal. Pneumothorax was observed in 106 cases post-insertion (1.3%) and in 3 cases post-removal (0.02%), with no statistically significant difference between procedures (p = 0.5025). The NLP algorithm achieved an accuracy of 93%, with a sensitivity of 97.9%, a specificity of 87.9%, and an area under the ROC curve (AUC) of 0.9283. Conclusions: The findings indicate no significant difference in pneumothorax incidence between CVC insertion and removal, supporting existing recommendations against routine imaging post-removal for asymptomatic patients and suggesting that routine imaging after CVC insertion may also be unnecessary in similar cases. This study demonstrates how advanced NLP techniques can support value-based medicine by enhancing clinical decision making and optimizing resources.
Find related publications in this database (Keywords): pneumothorax; CVC; central venous catheterization; removal; NLP; natural language processing; machine learning; value-based medicine