Blood test predicts recovery after hip-replacement surgery, study finds

A simple blood test that analyzes immune function can forecast how quickly a person undergoing hip replacement surgery will recover.

- By Hanae Armitage

Activity data from smartwatches was used to determine how quickly patients recovered from hip-replacement surgery.
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Clues from a blood sample can predict how quickly patients who have had hip-replacement surgery will make a full recovery, according to a new study led by Stanford Medicine researchers.

The hope is that the blood test will provide insights into things patients can do before and after surgery, such as adhering to a special diet or exercise routine, that may help them regain full mobility.

The findings may also help clinicians more accurately evaluate patient recovery after surgery. Currently, physicians gauge patients’ recovery by asking them questions about pain and physical activity, among other things. But these surveys are subjective, said Nima Aghaeepour, PhD, an assistant professor of anesthesiology, perioperative and pain medicine, and it requires a lot of guesswork to interpret the responses.

“We needed to find a more reliable, data-driven method to anticipate the precise needs of patients as they get back on their feet after surgery,” Aghaeepour said. 

The paper was published Oct. 14 in Annals of Surgery. Aghaeepour; Martin Angst, MD, PhD, professor of anesthesiology, perioperative and pain medicine; and Brice Gaudilliere, MD, PhD, associate professor of anesthesiology, perioperative and pain medicine, share senior authorship. Postdoctoral scholars Ramin Fallahzadeh, PhD, and Franck Verdonk, MD, PhD, are the lead authors.

Immune cell crystal ball

In their search for a molecular harbinger of surgical recovery, the team enrolled 49 hip-replacement patients, ages 57-68, and asked each to don an activity-tracking smartwatch before and after their procedures. Before the surgery, each patient also underwent a blood draw, which the researchers analyzed using techniques that parsed cell subtypes, as well as the cells’ activity.

Nima Aghaeepour

The idea was to compare blood-test analyses, which capture information about protein levels and immune function, with how long it took for patients to fully recover after their procedure. (The researchers measured full recovery by recording activity patterns, such as sleep data, step count and other movements, before surgery, then tracking how long it took for patients to return to those levels post-surgery.)

Using the smartwatch data and information from the pre-surgery blood draw, the team devised an algorithm that could accurately predict how swiftly patients would get back on their feet. Overall, those whose blood tests showed the strongest immune function prior to surgery recovered 34% faster than those with weaker immune function.

The algorithm’s predictive power relied largely on the activity of myeloid-derived suppressor cells, a type of immune cell. But the researchers weren’t simply looking for this cell’s presence; they also were measuring its activity when exposed to a molecule that mimics an infection. Higher activity levels correlated closely with quicker recovery times.

Refining predictions

While the study’s data is preliminary and applies only to hip surgeries in people around age 60, the researchers suspect that the findings will generally apply to patients of various ages undergoing different procedures. “My expectation is that there will still be a strong connection between the immune system and recovery, but exactly what that connection will be is still to be determined,” Aghaeepour said. The researchers plan to investigate other patient populations with the same blood test and smartwatch approach.

They are not yet using the predictive data to inform patient care, but the ultimate hope is that anyone awaiting a surgical procedure will receive the blood test to guide the smoothest, fastest recovery.

Other Stanford co-authors of the study are research scientists Ivana Maric, PhD, Amy Tsai and Ed Ganio, PhD; former research data analyst Anthony Culos, PhD; postdoctoral scholars Martin Becker, PhD, Alan Chang, PhD, Thanaphong Phongpreecha, PhD, Maria Xenochristou, PhD, Neda Bidoki, PhD, and Davide De Francesco, PhD; graduate students Camilo Espinosa and Eileen Tsai, study coordinator Xiaoxiao Gao; clinical research coordinator Leslie McNeil; associate professor of obstetric anesthesiology Pervez Sultan, MD; clinical nurse Martha Tingle; associate professor of orthopaedic surgery Derek Amanatullah, MD, PhD; professor of orthopaedic surgery James Huddleston, MD; and Stuart Goodman, MD, PhD, professor of surgery.

Researchers from the University of North Carolina at Chapel Hill also contributed to the work.

Funding for this study was provided by the National Institutes of Health (grants R35GM138353, R35GM137936, AG058417, HL13984401, NS114926, DA050960 and AG065744), la Fondation des Gueules Cassées and the Philippe Foundation.

About Stanford Medicine

Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit

2023 ISSUE 3

Exploring ways AI is applied to health care