A Nomogram to Predict Pneumothorax Requiring Chest Tube Placement following Percutaneous CT-guided Lung Biopsy

ABSTRACT Background Pneumothorax requiring chest tube after CT-guided transthoracic lung biopsy is one of the common complications, and the required hospital stay after chest tube placement represents an added clinical risk to patients and cost to the healthcare system. Identifying high-risk patients can prompt alternative biopsy modes and/or better preparation for more focused post-procedural care.Purpose To develop and externally validate a risk nomogram for pneumothorax requiring chest tube placement following CT-guided lung biopsy, leveraging quantitative emphysema algorithm.Materials & Methods This two-center retrospective study included patients who underwent CT-guided lung biopsy from between 1994 and 2023. Data from one hospital was set aside for validation (n=613). Emphysema severity was quantified and categorized to 3-point scale using a previously published algorithm based on 3×3×3 kernels and Hounsfield thresholding, and a risk calculator was developed using forward variable selection and logistic regression. The model was validated using bootstrapping and Harrell’s C-index.Results 2,512 patients (mean age, 64.47 years +/-13.38 [standard deviation]; 1250 men) were evaluated, of whom 157 (6.7%) experienced pneumothorax complications requiring chest tube placement. After forward variable selection to reduce the covariates to maximize clinical usability, the risk score was developed using age over 60 (OR 1.80 [1.15-2.93]), non-prone patient position (OR 2.48 [1.63-3.75]), and severe emphysema (OR 1.99 [1.35-2.94]). The nomogram showed mean absolute error of 0.5% in calibration and Harrell’s C-index of 0.664 in discrimination in the internal cohort.Conclusion The developed nomogram predicts age over 60, non-prone position during biopsy, and severe emphysema to be most predictive of pneumothorax requiring chest tube placement following CT-guided lung biopsy..

Medienart:

Preprint

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

bioRxiv.org - (2024) vom: 06. Feb. Zur Gesamtaufnahme - year:2024

Sprache:

Englisch

Beteiligte Personen:

Bondarenko, Masha [VerfasserIn]
Zhang, Jianxiang [VerfasserIn]
Baal, Ulysis Hugo [VerfasserIn]
Lam, Brian [VerfasserIn]
Chaudhari, Gunvant [VerfasserIn]
Lee, Yoo Jin [VerfasserIn]
Schroeder, Jamie [VerfasserIn]
Vella, Maya [VerfasserIn]
Haas, Brian [VerfasserIn]
Vu, Thienkhai [VerfasserIn]
Kallianos, Kimberly [VerfasserIn]
Liu, Jonathan [VerfasserIn]
Sridhar, Shravan [VerfasserIn]
Elicker, Brett [VerfasserIn]
Sohn, Jae Ho [VerfasserIn]

Links:

Volltext [kostenfrei]

Themen:

570
Biology

doi:

10.1101/2024.02.01.24302030

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI042386225