Decision tree–based machine learning analysis of intraoperative vasopressor use to optimize neurological improvement in acute spinal cord injury

Nitin Agarwal, Alexander A. Aabedi, Abel Torres-Espin, Austin Chou, Thomas A. Wozny, Praveen V. Mummaneni, John F. Burke, Adam R. Ferguson, Nikos Kyritsis, Sanjay S. Dhall, Philip R. Weinstein, Xuan Duong-Fernandez, Jonathan Pan, Vineeta Singh, Debra D. Hemmerle, Jason F. Talbott, William D. Whetstone, Jacqueline C. Bresnahan, Geoffrey T. Manley, Michael S. BeattieAnthony M. DiGiorgio

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


OBJECTIVE Previous work has shown that maintaining mean arterial pressures (MAPs) between 76 and 104 mm Hg intraoperatively is associated with improved neurological function at discharge in patients with acute spinal cord injury (SCI). However, whether temporary fluctuations in MAPs outside of this range can be tolerated without impairment of recovery is unknown. This retrospective study builds on previous work by implementing machine learning to derive clinically actionable thresholds for intraoperative MAP management guided by neurological outcomes. METHODS Seventy-four surgically treated patients were retrospectively analyzed as part of a longitudinal study assessing outcomes following SCI. Each patient underwent intraoperative hemodynamic monitoring with recordings at 5-minute intervals for a cumulative 28,594 minutes, resulting in 5718 unique data points for each parameter. The type of vasopressor used, dose, drug-related complications, average intraoperative MAP, and time spent in an extreme MAP range (< 76 mm Hg or > 104 mm Hg) were collected. Outcomes were evaluated by measuring the change in American Spinal Injury Association Impairment Scale (AIS) grade over the course of acute hospitalization. Features most predictive of an improvement in AIS grade were determined statistically by generating random forests with 10,000 iterations. Recursive partitioning was used to establish clinically intuitive thresholds for the top features. RESULTS At discharge, a significant improvement in AIS grade was noted by an average of 0.71 levels (p = 0.002). The hemodynamic parameters most important in predicting improvement were the amount of time intraoperative MAPs were in extreme ranges and the average intraoperative MAP. Patients with average intraoperative MAPs between 80 and 96 mm Hg throughout surgery had improved AIS grades at discharge. All patients with average intraoperative MAP > 96.3 mm Hg had no improvement. A threshold of 93 minutes spent in an extreme MAP range was identified after which the chance of neurological improvement significantly declined. Finally, the use of dopamine as compared to norepinephrine was associated with higher rates of significant cardiovascular complications (50% vs 25%, p < 0.001). CONCLUSIONS An average intraoperative MAP value between 80 and 96 mm Hg was associated with improved outcome, corroborating previous results and supporting the clinical verifiability of the model.

Original languageEnglish
Article numberE9
JournalNeurosurgical focus
Issue number4
StatePublished - 2022


  • Acute spinal cord injury
  • Decompression
  • Mean arterial pressure
  • Neurological outcome
  • Vasopressor


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