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The explosive outbreak of COVID-19 led to a shortage of medical resources, including isolation rooms in hospitals, healthcare workers (HCWs) and personal protective equipment. Here, we constructed a new model, non-contact community treatment centres to monitor and quarantine asymptomatic and mildly symptomatic COVID-19 patients who recorded their own vital signs using a smartphone application. This new model in Korea is useful to overcome shortages of medical resources and to minimise the risk of infection transmission to HCWs.
To verify the validity of a semiautomated surgical site infection (SSI) surveillance system using electronic screening algorithms in 38 categories of surgery.
A cohort study for validation of semiautomated SSI surveillance system using screening algorithms.
A 1,989-bed tertiary-care referral center in Seoul, Republic of Korea.
A dataset of 40,516 surgical procedures in 38 categories stored in the conventional SSI surveillance registry at the Samsung Medical Center between January 2013 and December 2014 was used as the reference standard. In the semiautomated surveillance system, electronic screening algorithms flagged cases meeting at least 1 of 3 criteria: antibiotic prescription, microbial culture, and infectious disease consultation. Flagged cases were audited by infection preventionists. Analyses of sensitivity, specificity, and positive predictive value (PPV) were conducted for the semiautomated surveillance system, and its effect on reducing the workload for chart review was evaluated.
A total of 575 SSI events (1·42%) were identified by conventional SSI surveillance. The sensitivity of the semiautomated SSI surveillance was 96·7%, and the PPV of the screening algorithms alone was 4·1%. Semiautomated SSI surveillance reduced the chart review workload of the infection preventionists from 1,283 to 482 person hours per year (a 62·4% decrease).
Compared to conventional surveillance, semiautomated surveillance using electronic screening algorithms followed by chart review of selected cases can provide high-validity surveillance results and can significantly reduce the workload of infection preventionists.
Two kinds of Sr2FeReO6 (SFRO) samples, pristine SFRO and Re-excess SFRO, were prepared and we visualized the local atomic structure in terms of cationic ordering in the prepared SFRO samples via high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM). HAADF-STEM results demonstrated the high degree of cationic ordering maintains in both the pristine SFRO and Re-excess SFRO samples. On the other hand, defective structures such as antiphase boundary and Re-deficient phase were observed dominantly in the pristine SFRO, and thus the poor magnetic property in the pristine SFRO is attributed to those defective structures related with the frustrated Fe/Re ordering.
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