This study uses the National Inpatient Sample to describe the current epidemiology of revision TKA in the US. It analyzes 337,597 revision procedures from 2009-2013 by failure etiology, procedure type, demographics, length of stay, and hospital charges.
The single fact to carry out of this paper: infection is now the leading cause of revision TKA nationally, at 20.4%, narrowly ahead of mechanical loosening.
That matters because prior single-center data from academic centers often reported aseptic loosening or polyethylene wear on top. A national all-payer database of 337,597 cases captures community hospital patients those series missed, so this is a more representative snapshot.
Build a simple mental model from the etiology-by-procedure data. When you see a knee explanted without replacement, infection is the cause 77% of the time. When you see a single component revised, think mechanical loosening.
The economics reinforce prevention. Mean charge is $75,028 and climbing, and explant for infection produces the longest stays. As bundled payment models expand, high infection-risk patients risk being selected against, which makes reducing modifiable infection risk a shared responsibility.
As a caveat, NIS is administrative claims data. It cannot capture readmissions, post-discharge complications, or reliably isolate polyethylene wear, so treat these as epidemiologic frequencies, not outcome measures.
This study uses the National Inpatient Sample to describe the current epidemiology of revision TKA in the US. It analyzes 337,597 revision procedures from 2009-2013 by failure etiology, procedure type, demographics, length of stay, and hospital charges.
The single fact to carry out of this paper: infection is now the leading cause of revision TKA nationally, at 20.4%, narrowly ahead of mechanical loosening.
That matters because prior single-center data from academic centers often reported aseptic loosening or polyethylene wear on top. A national all-payer database of 337,597 cases captures community hospital patients those series missed, so this is a more representative snapshot.
Build a simple mental model from the etiology-by-procedure data. When you see a knee explanted without replacement, infection is the cause 77% of the time. When you see a single component revised, think mechanical loosening.
The economics reinforce prevention. Mean charge is $75,028 and climbing, and explant for infection produces the longest stays. As bundled payment models expand, high infection-risk patients risk being selected against, which makes reducing modifiable infection risk a shared responsibility.
As a caveat, NIS is administrative claims data. It cannot capture readmissions, post-discharge complications, or reliably isolate polyethylene wear, so treat these as epidemiologic frequencies, not outcome measures.