The Journal of Bone and Joint Surgery (American). 2006;88:480-485.
doi:10.2106/JBJS.E.00629
© 2006 The Journal of Bone and Joint Surgery, Inc.
Factors Predicting Complication Rates Following Total Knee Replacement
Nelson F. SooHoo, MD1,
Jay R. Lieberman, MD1,
Clifford Y. Ko, MD, MS, MSHS2 and
David S. Zingmond, MD, PhD3
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
A commentary is available with the electronic versions of this article,
on our web site
(www.jbjs.org)
and on our quarterly CD-ROM (call our subscription department, at
781-449-9780, to order the CD-ROM).
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.
Background: The purpose of this investigation was to expand on
previous studies by more fully examining the role of a variety of patient and
hospital characteristics in determining adverse outcomes following total knee
replacement.
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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