Lung ultrasound for early diagnosis and severity assessment of pneumonia in patients with coronavirus disease 2019.

BACKGROUND/AIMS: Current evidence supports lung ultrasound as a point-ofcare alternative diagnostic tool for various respiratory diseases. We sought to determine the utility of lung ultrasound for early detection of pneumonia and for assessment of respiratory failure among patients with coronavirus disease 2019 (COVID-19). METHODS: Six patients with confirmed COVID-19 by reverse transcription-polymerase chain reaction were enrolled. All had undergone chest X-ray and chest computed tomography (CT) on the day of admission and underwent multiple point-of-care lung ultrasound scans over the course of their hospitalization. RESULTS: Lung ultrasound detected early abnormal findings of representative B-lines in a patient with a normal chest X-ray, corresponding to ground-glass opacities on the chest CT scan. The ultrasound findings improved as her clinical condition improved and her viral load decreased. In another minimally symptomatic patient without significant chest X-ray findings, the ultrasound showed B-lines, an early sign of pneumonia before abnormalities were detected on the chest CT scan. In two critically ill patients, ultrasound was performed to assess for evaluation of disease severity. In both patients, the clinicians conducted emergency rapid sequence intubation based on the ultrasound findings without awaiting the laboratory results and radiological reports. In two children, ultrasound was used to assess the improvement in their pneumonia, thus avoiding further imaging tests such as chest CT. CONCLUSION: Lung ultrasound is feasible and useful as a rapid, sensitive, and affordable point-of-care screening tool to detect pneumonia and assess the severity of respiratory failure in patients hospitalized with COVID-19.

Electronically implemented clinical indicators based on a data warehouse in a tertiary hospital: its clinical benefit and effectiveness.

OBJECTIVE: Assessing and monitoring care and service using clinical indicators (CIs) can allow the measurement of and lead to improvements in the quality of care. However, the management and maintenance of CI data has been shown to be difficult because the data are usually collected and provided manually. In this study, for the purpose of efficient managing quality indicators, a data warehouse (DW)-based CI monitoring system was developed. The clinical effectiveness and efficiency of a DW-based CI monitoring was investigated through several case studies of the system's operation at a tertiary hospital. METHODS: This study analyzed the CIs that have been developed over the past 8 years at a 1340-bed tertiary general university hospital in South Korea to improve and monitor the quality of care and patient safety. The hospital was opened as a fully digital hospital in 2003, and the CIs were computerized in 2005 by implementing a DW-based CI monitoring system. We classified the computerized CIs and evaluated the monitoring results for several representative CIs, such as the optimal prescribing of preventive antibiotics, the average length of stay, the mortality rate, and the rehospitalization rate. RESULTS: During the development of the system in 2005, 12 of 19 CIs were computerized, and this number gradually increased until 299 of 335 CIs were computerized by 2012. In addition, among the CIs built computationally through the CI task force team, focal CIs subject to monitoring were selected annually, and the results of this monitoring were shared with all of the staff or the related department and its staff. By providing some examples of our CI monitoring results, we showed the feasibility of improving the quality of care, and maintaining the optimum level of patient care with less labor. CONCLUSIONS: The results of this study provide evidence regarding the clinical effectiveness and efficiency as well as the systems operation experience of a DW-based CI monitoring system. These findings may aid medical institutions that plan on computerizing CIs with respect to decision and policy making regarding their systems development and operations.

Multiplex enzyme assay for galactosemia using ultraperformance liquid chromatography-tandem mass spectrometry.

BACKGROUND: Galactosemia is one of the most important inherited disorders detected by newborn screening tests. Abnormal results in screening tests should be confirmed by enzyme activity assays, but existing methods are time and labor intensive. We developed a novel multiplex enzyme assay for galactosemia using ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). METHODS: [(13)C6]-galactose, [(13)C2]-galactose-1-phosphate, and UDP-glucose were used as substrates for 3 galactose-metabolizing enzymes. The end products from the combined reaction mixtures, [(13)C6]-galactose-1-phosphate, UDP-[(13)C2]-galactose, and UDP-galactose, were simultaneously measured using UPLC-MS/MS. Linearity, imprecision, ion suppression, and the effects of substrate were evaluated to determine assay performance. Enzyme activities from 35 healthy individuals, 8 patients with enzyme deficiency, and 18 mutant cells were analyzed. RESULTS: Substrates, products, and internal standards from the mixture of 3 enzyme reactions were clearly separated by using UPLC-MS/MS, with an injection cycle time of 10 min. Ion suppression was 0.1%-2.5%, the interassay imprecision of UPLC-MS/MS was 3.3%-10.6% CV, and the linearity of each system was good (R(2) = 0.994-0.999). Patient samples and mutated cells showed consistently low enzyme activities compared with those of normal individuals and wild-type cells. CONCLUSIONS: This method allows for a high-throughput and reproducible multiplex enzyme assay for galactosemia in erythrocytes.