AI predicts infection risk after brain surgery – study aims to stop it

NCT ID NCT07378683

Recruiting now Disease control Sponsor: Ming Yang Source: ClinicalTrials.gov ↗

First seen Jun 24, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study tests whether a machine learning tool can identify patients at high risk for surgical site infection after brain or spinal tumor surgery. High-risk patients will receive extra preventive care, like stronger antibiotics and nutrition support. The goal is to see if this personalized approach lowers infection rates within 90 days after surgery.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance: Machine learning-based enhanced prevention package (tailored antibiotics, nutrition, monitoring)
What this could lead to: If successful, this could provide a practical way to cut infection rates after brain or spinal tumor surgery, improving recovery and reducing complications.
What could go wrong: This is a single-center study with 500 participants, so results may not apply to all hospitals. The model's predictions might not always be accurate, and enhanced measures could increase costs or side effects.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

central nervous system cancer Surgical Wound Infection

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

CENTRAL NERVOUS SYSTEM TUMOR SURGICAL SITE INFECTION (SSI)

Contacts and locations

Locations

National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
RECRUITING

Beijing, PUMC, 10010, China

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