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Automated surveillance of healthcare-associated infections reduces workload and improves standardization, but it has not yet been adopted widely. In this study, we assessed the performance and feasibility of an easy implementable framework to develop algorithms for semiautomated surveillance of deep incisional and organ-space surgical site infections (SSIs) after orthopedic, cardiac, and colon surgeries.
Design:
Retrospective cohort study in multiple countries.
Methods:
European hospitals were recruited and selected based on the availability of manual SSI surveillance data from 2012 onward (reference standard) and on the ability to extract relevant data from electronic health records. A questionnaire on local manual surveillance and clinical practices was administered to participating hospitals, and the information collected was used to pre-emptively design semiautomated surveillance algorithms standardized for multiple hospitals and for center-specific application. Algorithm sensitivity, positive predictive value, and reduction of manual charts requiring review were calculated. Reasons for misclassification were explored using discrepancy analyses.
Results:
The study included 3 hospitals, in the Netherlands, France, and Spain. Classification algorithms were developed to indicate procedures with a high probability of SSI. Components concerned microbiology, prolonged length of stay or readmission, and reinterventions. Antibiotics and radiology ordering were optional. In total, 4,770 orthopedic procedures, 5,047 cardiac procedures, and 3,906 colon procedures were analyzed. Across hospitals, standardized algorithm sensitivity ranged between 82% and 100% for orthopedic surgery, between 67% and 100% for cardiac surgery, and between 84% and 100% for colon surgery, with 72%–98% workload reduction. Center-specific algorithms had lower sensitivity.
Conclusions:
Using this framework, algorithms for semiautomated surveillance of SSI can be successfully developed. The high performance of standardized algorithms holds promise for large-scale standardization.
Preliminary evidence suggests that hoarding disorder (HD) and obsessive-compulsive disorder (OCD) may show distinct patterns of brain activation during executive performance, although results have been inconclusive regarding the specific neural correlates of their differential executive dysfunction. In the current study, we aim to evaluate differences in brain activation between patients with HD, OCD and healthy controls (HCs) during response inhibition, response switching and error processing.
Methods
We assessed 17 patients with HD, 18 patients with OCD and 19 HCs. Executive processing was assessed inside a magnetic resonance scanner by means of two variants of a cognitive control protocol (i.e. stop- and switch-signal tasks), which allowed for the assessment of the aforementioned executive domains.
Results
OCD patients performed similar to the HCs, differing only in the number of successful go trials in the switch-signal task. However, they showed an anomalous hyperactivation of the right rostral anterior cingulate cortex during error processing in the switch-signal task. Conversely, HD patients performed worse than OCD and HC participants in both tasks, showing an impulsive-like pattern of response (i.e. shorter reaction time and more commission errors). They also exhibited hyperactivation of the right lateral orbitofrontal cortex during successful response switching and abnormal deactivation of frontal regions during error processing in both tasks.
Conclusions
Our results support that patients with HD and OCD present dissimilar cognitive profiles, supported by distinct neural mechanisms. Specifically, while alterations in HD resemble an impulsive pattern of response, patients with OCD present increased error processing during response conflict protocols.