External Validation and Calibration of a Novel and Practical RIRS-FUTI Predictive Scoring System for Febrile Urinary Tract Infection After Retrograde Intrarenal Surgery
This external validation study confirms that the novel RIRS-FUTI scoring system effectively discriminates and calibrates the risk of febrile urinary tract infections following retrograde intrarenal surgery, demonstrating its utility as a practical preoperative risk stratification tool.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Every year, millions of people around the world suffer from painful kidney stones. For many of these patients, doctors use a procedure called retrograde intrarenal surgery to remove the stones without making a single cut on the skin. During this operation, a thin, flexible tube is passed up through the bladder and into the kidney, where a laser breaks the stone into dust that can be washed away. While this method is highly effective and has become a standard way to treat kidney stones, it carries a hidden risk. The manipulation of the urinary tract can sometimes allow bacteria to enter the bloodstream, triggering a fever and a serious infection known as a febrile urinary tract infection. For the patient, this means a sudden spike in temperature, chills, and a need for stronger antibiotics or even hospitalization. For the medical team, predicting who might get sick before the surgery begins has been a difficult puzzle, often leaving them to guess which patients need extra protection.
A team of researchers at Başakşehir Çam ve Sakura City Hospital in Turkey set out to solve this puzzle by testing a new tool designed to predict these infections. They wanted to see if a simple scoring system, created by other scientists just a year earlier, could work reliably in their own hospital with a different group of patients. This scoring system, known as the RIRS-FUTI score, acts like a pre-surgery checklist. It does not require complex genetic testing or expensive new machines. Instead, it relies on three pieces of information that doctors already gather before every patient arrives: whether the kidney is swollen due to a blockage, whether the patient has had a similar infection after a previous scope procedure, and whether their urine shows signs of inflammation under a microscope. The idea is that by adding up points based on these three factors, doctors could get a clear picture of how likely a patient is to develop a fever after surgery.
To test if this checklist worked, the researchers looked back at the medical records of 525 adults who had undergone this stone-removal surgery between January 2024 and March 2025. They carefully reviewed the data for each person, checking their age, the size of their stones, and their medical history. They then split the group into two categories: those who developed a fever and infection after the operation, and those who did not. In this group, 44 patients, or about 8.4 percent, did develop a postoperative infection. The researchers compared the two groups to see what made the infected patients different. They found that the patients who got sick were more likely to have had a history of urinary tract infections after previous scope procedures, had higher counts of white blood cells in their urine before surgery, and were more likely to have a swollen kidney.
The team then applied the scoring system to every single patient in their study. They calculated a score for each person based on the three specific risk factors. The results showed that the score worked very well at separating the high-risk patients from the low-risk ones. Patients with a score of zero had a very low chance of getting sick, with only 1.7 percent developing an infection. As the score went up, the risk climbed steadily. For patients with the highest possible score, the risk of infection was extremely high, reaching 86.7 percent in the group with the maximum points. The system was particularly good at identifying who would stay healthy; it correctly predicted that 98.3 percent of the people it marked as low-risk would indeed remain free of infection. Conversely, when the score was high, it was very good at warning the doctors that a specific patient was in danger, with a 99.6 percent accuracy in identifying those who would get sick.
The study confirmed that the scoring system is not just a theory but a practical tool that holds up when used in a real-world hospital setting. The researchers found that the two most powerful predictors were a history of infection after a previous scope procedure and the presence of white blood cells in the urine before surgery. While the swelling of the kidney was a factor, it was not as strong a predictor as the other two once all the data was analyzed together. The team noted that because the system uses information doctors already have, it can be calculated instantly without adding cost or delay to patient care. This allows a surgeon to look at a patient's chart before the operation and know exactly who needs extra monitoring or more aggressive prevention strategies.
Despite these promising results, the researchers were careful to note that their study was a single look back at one hospital's records, and they acknowledged that the group of patients with the very highest scores was small. This means that while the tool is excellent, it still needs to be tested in larger, forward-looking studies across many different hospitals to be certain it works for everyone. Nevertheless, the findings provide strong evidence that a simple, three-part checklist can significantly improve how doctors prepare for kidney stone surgery. By identifying the patients most likely to suffer from a fever and infection, this score offers a way to tailor medical care to the individual, potentially preventing complications before they even begin.
Drowning in papers in your field?
Get daily digests of the most novel papers matching your research keywords — with technical summaries, in your language.