To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
To determine the effect of graft choice (allograft, bone-patellar tendon-bone autograft, or hamstring autograft) on deep tissue infections following anterior cruciate ligament (ACL) reconstructions.
Retrospective cohort study.
SETTING AND POPULATION
Patients from 6 US health plans who underwent ACL reconstruction from January 1, 2000, through December 31, 2008.
We identified ACL reconstructions and potential postoperative infections using claims data. A hierarchical stratified sampling strategy was used to identify patients for medical record review to confirm ACL reconstructions and to determine allograft vs autograft tissue implanted, clinical characteristics, and infection status. We estimated infection rates overall and by graft type. We used logistic regression to assess the association between infections and patients’ demographic characteristics, comorbidities, and choice of graft.
On review of 1,452 medical records, we found 55 deep wound infections. With correction for sampling weights, infection rates varied by graft type: 0.5% (95% CI, 0.3%-0.8%) with allografts, 0.6% (0.1%–1.5%) with bone-patellar tendon-bone autografts, and 2.5% (1.9%–3.1%) with hamstring autograft. After adjusting for potential confounders, we found an increased infection risk with hamstring autografts compared with allografts (odds ratio, 5.9; 95% CI, 2.8–12.8). However, there was no difference in infection risk among bone-patellar tendon-bone autografts vs allografts (odds ratio, 1.2; 95% CI, 0.3–4.8).
The overall risk for deep wound infections following ACL reconstruction is low but it does vary by graft type. Infection risk was highest in hamstring autograft recipients compared with allograft recipients and bone-patellar tendon-bone autograft recipients.
To explore the feasibility of identifying anterior cruciate ligament (ACL) allograft implantations and infections using claims.
Retrospective cohort study.
We identified ACL reconstructions using procedure codes at 6 health plans from 2000 to 2008. We then identified potential infections using claims-based indicators of infection, including diagnoses, procedures, antibiotic dispensings, specialty consultations, emergency department visits, and hospitalizations. Patients’ medical records were reviewed to determine graft type, validate infection status, and calculate sensitivity and positive predictive value (PPV) for indicators of ACL allografts and infections.
A total of 11,778 patients with codes for ACL reconstruction were identified. After chart review, PPV for ACL reconstruction was 96% (95% confidence interval [CI], 94%–97%). Of the confirmed ACL reconstructions, 39% (95% CI, 35%–42%) used allograft tissues. The deep infection rate after ACL reconstruction was 1.0% (95% CI, 0.7%–1.4%). The odds ratio of infection for allografts versus autografts was 0.41 (95% CI, 0.19–0.78). Sensitivity of individual claims-based indicators for deep infection after ACL reconstruction ranged from 0% to 75% and PPV from 0% to 100%. Claims-based infection indicators could be combined to enhance sensitivity or PPV but not both.
While claims data accurately identify ACL reconstructions, they poorly distinguish between allografts and autografts and identify infections with variable accuracy. Claims data could be useful to monitor infection trends after ACL reconstruction, with different algorithms optimized for different surveillance goals.
Infect Control Hosp Epidemiol 2014;35(6):652–659
Email your librarian or administrator to recommend adding this to your organisation's collection.