Predictors of Epidural Depth in Percutaneous Nephrolithotomy and Model Development

Percutaneous nephrolithotomy (PCNL) is the standard minimally invasive surgical procedure for removal of kidney stones larger than 2 cm and is established as the gold standard for the management of complex renal calculi. This procedure may be performed under either general anesthesia or regional anesthesia, including epidural or spinal anesthesia. Accumulating meta-analyses have demonstrated that, compared with general anesthesia, regional anesthesia is associated with reduced postoperative pain scores and lower total hospital costs, without compromising the stone-free rate. Furthermore, in awake patients undergoing regional anesthesia, respiratory movements may generate a so-called "respiratory-synchronous stone fragmentation effect," which facilitates the expulsion of stone debris.

Successful epidural anesthesia relies critically on accurate identification of the epidural space and precise control of puncture depth. Insufficient puncture depth may result in improper catheter placement and subsequent block failure, whereas excessive puncture depth increases the risk of dural puncture, leading to cerebrospinal fluid leakage and post-dural puncture headache. In severe cases, inadvertent injection of a large dose of local anesthetics into the subarachnoid space can cause life-threatening cardiovascular and respiratory depression. Therefore, preprocedural estimation of the skin-to-epidural space distance is of considerable clinical importance.

Although racial differences in epidural depth have been reported, systematic investigations specifically targeting the Chinese population remain scarce. Various imaging modalities, including computed tomography, magnetic resonance imaging, and ultrasound, can be used to predict epidural depth. However, these examinations increase healthcare burden and are not always feasible in emergency or bedside settings. Consequently, identifying simple, easily obtainable clinical parameters-such as sex, age, and body mass index (BMI)-for predicting epidural depth has become a research priority.

In this context, the present study aimed to identify factors influencing epidural depth through a retrospective analysis of clinical data from PCNL patients and to develop simple, level-specific predictive models for different puncture sites, thereby providing a practical reference for clinical epidural anesthesia.