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Factors Predicting Complication Rates Following Total Knee Replacement

¹ Department of Orthopaedic Surgery, University of California at Los Angeles, 10945 Le Conte Avenue, PVUB #3355, Los Angeles, CA 90095. E-mail address for N.F. SooHoo: nsoohoo{at}mednet.ucla.edu
² Department of Surgery, University of California at Los Angeles, School of Medicine, 10833 Le Conte Avenue, Room 72-215, Los Angeles, CA 90095
³ Department of Internal Medicine, University of California at Los Angeles, School of Medicine, 911 Broxton Plaza, Los Angeles, CA 90095

Investigation performed at the Department of Orthopaedic Surgery, University of California at Los Angeles, Los Angeles, California

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The authors did not receive grants or outside funding in support of their research for or preparation of this manuscript. They did not receive payments or other benefits or a commitment or agreement to provide such benefits from a commercial entity. No commercial entity paid or directed, or agreed to pay or direct, any benefits to any research fund, foundation, educational institution, or other charitable or nonprofit organization with which the authors are affiliated or associated.

Methods: With use of data from all hospital admissions in California from 1991 through 2001, multiple logistic regression was performed on the information regarding patients treated with total knee replacement. Rates of mortality and readmission due to infection and pulmonary embolism during the first ninety days after discharge were regressed against a variety of independent variables, including demographic factors (age, gender, race, ethnicity, and insurance type), burden of comorbid disease (Charlson comorbidity index), and provider variables (hospital size, teaching status, and surgical volume). A separate baseline probability analysis was then performed to compare the relative importance of all predictor variables.

Results: The sample size for this analysis was 222,684. A total of 1176 deaths (rate, 0.53%), 1586 infections (0.71%), and 914 pulmonary emboli (0.41%) occurred within the first ninety days after discharge. The average age of the patients at the time of surgery was sixty-nine years. Sixty-two percent of the patients were women, and 32% had a Charlson comorbidity index of >0. The significant predictors for complications (p < 0.05) included age, gender, race/ethnicity, Charlson comorbidity index, insurance type, and hospital volume. A baseline probability analysis was performed with the base case considered to be a white woman who was over the age of sixty-five years, had a Charlson comorbidity index of 0, had Medicare insurance, and was treated at a high-volume, non-teaching hospital. For a patient with the baseline case characteristics, the probability of death was 31/10,000, the probability of infection was 59/10,000, and the probability of pulmonary embolism was 41/10,000 in the first ninety days after discharge. Altering the base case by assuming that care was received at a low-volume hospital increased the expected mortality rate by a factor of 26%. Increasing the Charlson comorbidity index to 1 increased the mortality rate by 170%, whereas decreasing the age to younger than sixty-five years lowered the mortality rate by 73%. Hospital volume, comorbidity, and age had similar effects on the expected rates of readmission due to infection and pulmonary embolism.

Conclusions: The effects of age and the Charlson comorbidity index on the baseline probability of adverse outcomes following total knee replacement were shown to be similar to or greater than the effect of hospital volume. This study elucidates and compares the relative importance of the effects of several different factors on outcome. This information is important when considering the conclusions and implications of this type of policy-relevant outcomes research.

Level of Evidence: Prognostic Level II. See Instructions to Authors for a complete description of levels of evidence.

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