Researchers have devised what they hope is a more accurate system for predicting in-hospital mortality in patients undergoing major surgery (Anesthesiology 2016;124:570-579).
The number of patient deaths during or after surgery may be small, but the rate among some subgroups can be as high as 10%, making accurate predictions of in-hospital mortality crucial, according to the international team of researchers composed of physicians from Canada, France, the United Kingdom and South America.
Multimillion Data Set
“In light of this substantial mortality risk, it is important that the patient, their family and the attending physician are able to accurately and objectively predict the preoperative risk (probability) of in-hospital mortality,” they wrote.
The aim was to come up with a scoring system that is complex enough to accurately project mortality rates, yet simple enough to use in an everyday clinical setting, said Yannick Le Manach, MD, PhD, the lead study author, who is assistant professor in the Departments of Anesthesia and Clinical Epidemiology & Biostatistics at McMaster University, in Hamilton, Ontario.
“That was a target, making it usable,” Dr. Le Manach said.
They developed the Preoperative Score To Predict Postoperative Mortality (POSPOM) system, which uses a scale of 0 to 50 points, with 0 given to patients with the lowest risk. A single point represents a standard increase in risk equivalent to a five-year increase in age.
The team analyzed data from more than 5.5 million patients in France to test the efficacy of the POSPOM system for predicting in-hospital mortality, which was defined as “death after surgery or before discharge, regardless of length of stay.” All patients were 18 years of age or older, underwent surgery and required anesthesia. The patients were randomly assigned to the derivation cohort (n=2.71 million) or the prediction model (n=2.78 million).
The researchers examined 17 “potential predictors,” which were determined using International Classification of Diseases, Tenth Revision codes (Table).
The POSPOM system predicted 14,933 deaths compared with 12,786 actual deaths reported in the derivation cohort. The in-hospital mortality after surgery was 0.54% (95% CI, 0.53%-0.55%) for the POSPOM group and 0.47% (95% CI, 0.46%-0.48%) for the derivation group.
The findings show that POSPOM has “good calibration and excellent discrimination for in-hospital mortality,” the researchers wrote. They also suggested that the POSPOM system could be a significant improvement to the current standards for assessing in-hospital risks.
POSPOM, ASA and POSSUM
The American Society of Anesthesiologists (ASA) physical status score relies heavily on a physician’s “subjective” assessment of a patient’s preoperative clinical state, the researchers noted. The scoring system puts patients in five broad risk categories, but fails to take into account their age or the type of surgery they will be undergoing.
The subjectivity at the core of the ASA assessment makes it difficult to replicate results.
“If you take two physicians grading the same patient using the ASA score, they may subjectively score them differently, which is not the case when you are using a score that is not subjective,” Dr. Le Manach said.
By contrast, POSPOM relies on using preoperative clinical factors to ensure that results can be replicated across hospitals and health systems, according to the study.
The Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity is a “widely validated” measure; however, it includes data, such as the amount of blood lost during the operation and malignancy, which rule it out for preoperative risk assessment.
“There are very few risk scores that use objective, preoperative patient information to predict post-operative in-hospital mortality for patients scheduled for any type of surgery,” the researchers noted.
With its emphasis on evaluating preoperative clinical factors, POSPOM is a significant departure from prevailing risk score models in other ways as well.
The traditional approach to weighing the risk for various surgeries has been to look at predicting mortality for different types of operations. However, this approach does not calculate how much of the mortality rate is due to the surgery itself and how much can be attributed to preoperative comorbidities. When preexisting conditions are accounted for, some surgeries turn out to be far less risky than previously thought.
The unadjusted mortality rate for trauma-related orthopedic surgery was three times higher than minor vascular surgery (3.46% vs. 1.09%). But researchers found the risk for both surgeries to be fairly similar after adjusting for preexisting comorbidities.
“These findings suggest that traditional surgery-specific risk (estimation) based only on the observed postoperative outcome rate does not provide a true reflection of surgical risk,” the researchers noted.
Dr. Le Manach and his team are working to develop an app that physicians can use to run POSPOM as they make their rounds. He also is working on validating POSPOM at a major North American medical center.
Peter J. Papadakos, MD, director of critical care medicine and professor of anesthesiology and surgery at the University of Rochester School of Medicine and Dentistry, in New York, said the POSPOM system has potential. “It is going to be a robust tool,” Dr. Papadakos said. “Will it replace the ASA score? I don’t know.”