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To identify potential participants for clinical trials, electronic health records (EHRs) are searched at potential sites. As an alternative, we investigated using medical devices used for real-time diagnostic decisions for trial enrollment.
To project cohorts for a trial in acute coronary syndromes (ACS), we used electrocardiograph-based algorithms that identify ACS or ST elevation myocardial infarction (STEMI) that prompt clinicians to offer patients trial enrollment. We searched six hospitals’ electrocardiograph systems for electrocardiograms (ECGs) meeting the planned trial’s enrollment criterion: ECGs with STEMI or > 75% probability of ACS by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI). We revised the ACI-TIPI regression to require only data directly from the electrocardiograph, the e-ACI-TIPI using the same data used for the original ACI-TIPI (development set n = 3,453; test set n = 2,315). We also tested both on data from emergency department electrocardiographs from across the US (n = 8,556). We then used ACI-TIPI and e-ACI-TIPI to identify potential cohorts for the ACS trial and compared performance to cohorts from EHR data at the hospitals.
Receiver-operating characteristic (ROC) curve areas on the test set were excellent, 0.89 for ACI-TIPI and 0.84 for the e-ACI-TIPI, as was calibration. On the national electrocardiographic database, ROC areas were 0.78 and 0.69, respectively, and with very good calibration. When tested for detection of patients with > 75% ACS probability, both electrocardiograph-based methods identified eligible patients well, and better than did EHRs.
Using data from medical devices such as electrocardiographs may provide accurate projections of available cohorts for clinical trials.
Surgical site infections (SSIs) following colorectal surgery (CRS) are among the most common healthcare-associated infections (HAIs). Reduction in colorectal SSI rates is an important goal for surgical quality improvement.
To examine rates of SSI in patients with and without cancer and to identify potential predictors of SSI risk following CRS
American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) data files for 2011–2013 from a sample of 12 National Comprehensive Cancer Network (NCCN) member institutions were combined. Pooled SSI rates for colorectal procedures were calculated and risk was evaluated. The independent importance of potential risk factors was assessed using logistic regression.
Of 22 invited NCCN centers, 11 participated (50%). Colorectal procedures were selected by principal procedure current procedural technology (CPT) code. Cancer was defined by International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) codes.
The primary outcome of interest was 30-day SSI rate.
A total of 652 SSIs (11.06%) were reported among 5,893 CRSs. Risk of SSI was similar for patients with and without cancer. Among CRS patients with underlying cancer, disseminated cancer (SSI rate, 17.5%; odds ratio [OR], 1.66; 95% confidence interval [CI], 1.23–2.26; P=.001), ASA score ≥3 (OR, 1.41; 95% CI, 1.09–1.83; P=.001), chronic obstructive pulmonary disease (COPD; OR, 1.6; 95% CI, 1.06–2.53; P=.02), and longer duration of procedure were associated with development of SSI.
Patients with disseminated cancer are at a higher risk for developing SSI. ASA score >3, COPD, and longer duration of surgery predict SSI risk. Disseminated cancer should be further evaluated by the Centers for Disease Control and Prevention (CDC) in generating risk-adjusted outcomes.
Infect Control Hosp Epidemiol 2018;39:555–562
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