‘Big data’ is a term for data sets that are so
large or complex that traditional data processing applications are
inadequate. Billions of dollars have been spent on attempts to build predictive
tools from large sets of poorly controlled healthcare metadata.
Companies often sell reports at a physician or facility level based
on various flawed data sources, and comparative websites of ‘publicly
reported data’ purport to educate the public. Physicians should
be aware of concerns and pitfalls seen in such data definitions,
data clarity, data relevance, data sources and data cleaning when
evaluating analytic reports from metadata in health care. Cite this article:
Given the growing prevalence of obesity around
the world and its association with osteoarthritis of the knee, orthopaedic
surgeons need to be familiar with the management of the obese patient
with degenerative knee pain. The precise mechanism by which obesity
leads to osteoarthritis remains unknown, but is likely to be due
to a combination of mechanical, humoral and genetic factors. Weight loss has clear medical benefits for the obese patient
and seems to be a logical way of relieving joint pain associated
with degenerative arthritis. There are a variety of ways in which
this may be done including diet and exercise, and treatment with
drugs and bariatric surgery. Whether substantial weight loss can
delay or even reverse the symptoms associated with osteoarthritis
remains to be seen. Surgery for osteoarthritis in the obese patient can be technically
more challenging and carries a risk of additional complications.
Substantial weight loss before undertaking total knee replacement
is advisable. More prospective studies that evaluate the effect
of significant weight loss on the evolution of symptomatic osteoarthritis
of the knee are needed so that orthopaedic surgeons can treat this
patient group appropriately.
