AI Model Accurately Predicts Blood Loss During Liposuction, Enhancing Patient Safety

New Delhi — Researchers have developed a new artificial intelligence (AI) model capable of accurately predicting blood loss in patients undergoing high-volume cosmetic procedures such as liposuction, a breakthrough that could significantly improve surgical safety and outcomes.

Liposuction, performed on more than 2.3 million patients annually to remove excess fat from areas such as the face, abdomen, thighs, arms, and neck, is generally considered safe. However, excessive blood loss remains a serious potential complication, particularly during procedures involving large volumes of fat removal.

According to a study published in the journal Plastic and Reconstructive Surgery, the AI-based prediction model represents a “groundbreaking advancement” in cosmetic surgery, offering surgeons a powerful tool to better anticipate and manage intraoperative risks.

“By harnessing AI-driven predictive models, surgeons can customise their approach to each patient’s specific profile, optimising outcomes while minimising complications like excessive blood loss,” said the international research team, which included experts from Ecuador’s Ministry of Public Health and the Mayo Clinic in the United States.

The researchers applied machine learning techniques to analyse data from 721 patients who underwent large-volume liposuction procedures, each involving the removal of more than 4,000 millilitres (four litres) of fat and fluid. All surgeries were conducted at two clinics—one in Colombia and the other in Ecuador—using identical surgical protocols.

Data from 621 patients were used to train the predictive model, incorporating a broad range of demographic, clinical, and surgical variables. The model’s accuracy was then tested on the remaining 100 patients to assess its ability to estimate blood loss.

The results showed an accuracy rate of 94 per cent, indicating the model’s strong potential to enhance patient safety during liposuction procedures.

“This level of accuracy highlights the model’s value as a clinical decision-support tool in body contouring surgeries, where anticipating blood loss is essential for effective operative planning,” the researchers noted.

They added that surgeons can use these predictions to make informed decisions on perioperative care, including fluid management, the possible need for blood transfusions, and other critical interventions.

With inputs from IANS