Risk factors for postoperative systemic inflammatory response syndrome after radical prostatectomy: development and internal validation of a prediction model

Prostate cancer is a common disease affecting the male urinary system, often developing without early warning signs before growing large enough to cause difficulty with urination. For many men, the most effective treatment is the surgical removal of the entire prostate gland, a procedure known as a radical prostatectomy. While this surgery is a standard and life-saving intervention, the body's reaction to such a major operation can sometimes become excessive. After the surgery, some patients experience a condition called systemic inflammatory response syndrome. This is not a specific infection itself, but rather a state where the body's entire defense system goes into overdrive, causing fever, a rapid heartbeat, fast breathing, and abnormal white blood cell counts. This reaction can delay recovery, extend the time a patient spends in the hospital, and cause significant physical and mental distress. Because this complication can happen to anyone, doctors need a way to predict which patients are most likely to face it, allowing them to take preventive steps before the surgery even begins.

Researchers at the Xinqiao Hospital in Chongqing, China, set out to solve this problem by looking closely at the medical histories of 309 men who underwent this specific surgery between March 2023 and March 2025. The team divided these patients into two groups: those who developed the inflammatory reaction after their operation and those who did not. By carefully comparing the details of their lives and their surgeries, the scientists searched for patterns that distinguished the two groups. They examined everything from the patient's age and body weight to the type of anesthesia used and the length of the surgery. They found that while many factors like age or the specific surgical technique did not make a difference, five specific elements stood out as clear warning signs. The study identified that patients who had diabetes, those who had a catheter inserted before the surgery, those whose catheters remained in place for a longer time after the operation, those whose surgery took longer than usual, and those with a more aggressive form of the cancer were significantly more likely to develop the inflammatory reaction.

To turn these findings into a practical tool for doctors, the researchers built a visual prediction model. Imagine a chart where a doctor can look up a patient's specific details—such as whether they have diabetes or how many days their catheter will stay in—and assign a small number of points to each factor. When these points are added together, the total score reveals the likelihood that the patient will experience the inflammatory reaction. The team tested this model rigorously using a computer method that simulated thousands of different scenarios to ensure it was reliable. The results showed that the model was highly accurate, correctly distinguishing between patients who would and would not develop the condition in about 84 out of 100 cases. The predictions made by the chart matched the actual outcomes very closely, suggesting that the tool is a trustworthy way to assess risk.

The study also clarified what does not cause this problem. The researchers found that factors often assumed to be dangerous, such as the patient's age, their body mass index, or the specific type of urinary catheter used, did not actually increase the risk of this inflammatory reaction in their data. This helps doctors focus their attention on the factors that truly matter. The findings suggest that for patients with diabetes, keeping blood sugar levels stable before surgery is crucial. It also implies that minimizing the time a catheter stays in the body and shortening the duration of the surgery whenever possible could reduce the chances of this complication. While the model was tested only on patients from a single hospital and needs further testing in other locations to confirm its universal usefulness, it offers a clear, data-driven way to anticipate risks. By using this simple scoring system, medical teams can identify vulnerable patients early and tailor their care to prevent a reaction that could otherwise turn a successful surgery into a prolonged recovery.