Outpatient parenteral antimicrobial therapy (OPAT) from an emergency model applied during the COVID-19 pandemic to standard of care: Preliminary lessons from our experience.

OBJECTIVES: We wish to report on our experience of OPAT during the first two years of the COVID19 outbreak. PATIENTS AND METHODS: We recorded data on all patients treated in the OPAT regimen in 2020 and 2021 and compared overall trends, use of carbapenems and saved days of hospitalization. RESULTS: The OPAT model enabled us to ensure the administration of first choice antibiotic therapy to 239 patients with an increase of 21.3% from 2020 to 2021 (108 vs 131). Applying this model, we also recorded a reduction in the use of carbapenems from 33% in 2020 to 26% in 2021 and a total of 3041 recovery days saved in 2021.The clinical cure rate reached 94%. Few adverse events occurred (35/239; 14.6%), and they did not require hospitalization. CONCLUSION: OPAT is a safe, efficacious, and cost-effective model that functioned effectively during the COVID-19 crisis and could become the standard of care for the treatment of selected patients.

HIV Patients’ Tracer for Clinical Assistance and Research during the COVID-19 Epidemic (INTERFACE): A Paradigm for Chronic Conditions

The health emergency linked to the SARS-CoV-2 pandemic has highlighted problems in the health management of chronic patients due to their risk of infection, suggesting the need of new methods to monitor patients. People living with HIV/AIDS (PLWHA) represent a paradigm of chronic patients where an e-health-based remote monitoring could have a significant impact in maintaining an adequate standard of care. The key objective of the study is to provide both an efficient operating model to “follow” the patient, capture the evolution of their disease, and establish proximity and relief through a remote collaborative model. These dimensions are collected through a dedicated mobile application that triggers questionnaires on the basis of decision-making algorithms, tagging patients and sending alerts to staff in order to tailor interventions. All outcomes and alerts are monitored and processed through an innovative e-Clinical platform. The processing of the collected data aims into learning and evaluating predictive models for the possible upcoming alerts on the basis of past data, using machine learning algorithms. The models will be clinically validated as the study collects more data, and, if successful, the resulting multidimensional vector of past attributes will act as a digital composite biomarker capable of predicting HIV-related alerts. Design: All PLWH > 18 sears old and stable disease followed at the outpatient services of a university hospital (n = 1500) will be enrolled in the interventional study. The study is ongoing, and patients are currently being recruited. Preliminary results are yielding monthly data to facilitate learning of predictive models for the alerts of interest. Such models are learnt for one or two months of history of the questionnaire data. In this manuscript, the protocol—including the rationale, detailed technical aspects underlying the study, and some preliminary results—are described. Conclusions: The management of HIV-infected patients in the pandemic era represents a challenge for future patient management beyond the pandemic period. The application of artificial intelligence and machine learning systems as described in this study could enable remote patient management that takes into account the real needs of the patient and the monitoring of the most relevant aspects of PLWH management today. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Clinical role of lung ultrasound for diagnosis and monitoring of COVID-19 pneumonia in pregnant women.

Lung ultrasound has been suggested recently by the Chinese Critical Care Ultrasound Study Group and Italian Academy of Thoracic Ultrasound as an accurate tool to detect lung involvement in COVID-19. Although chest computed tomography (CT) represents the gold standard to assess lung involvement, with a specificity superior even to that of the nasopharyngeal swab for diagnosis, lung ultrasound examination can be a valid alternative to CT scan, with certain advantages, particularly for pregnant women. Ultrasound can be performed directly at the bed-side by a single operator, reducing the risk of spreading the disease among health professionals. Furthermore, it is a radiation-free exam, making it safer and easier to monitor those patients who require a series of exams. We report on four cases of pregnant women affected by COVID-19 who were monitored with lung ultrasound examination. All patients showed sonographic features indicative of COVID-19 pneumonia at admission: irregular pleural lines and vertical artifacts (B-lines) were observed in all four cases, and patchy areas of white lung were observed in two. Lung ultrasound was more sensitive than was chest X-ray in detecting COVID-19. In three patients, we observed almost complete resolution of lung pathology on ultrasound within 96 h of admission. Two pregnancies were ongoing at the time of writing, and two had undergone Cesarean delivery with no fetal complications. Reverse transcription polymerase chain reaction analysis of cord blood and newborn swabs was negative in both of these cases. Copyright © 2020 ISUOG. Published by John Wiley & Sons Ltd.