Is lung ultrasound score a useful tool to monitoring and handling moderate and severe COVID-19 patients in the general ward? An observational pilot study.

Lung ultrasound is a well-established diagnostic tool in acute respiratory failure, and it has been shown to be particularly suited for the management of COVID-19-associated respiratory failure. We present exploratory analyses on the diagnostic and prognostic performance of lung ultrasound score (LUS) in general ward patients with moderate-to-severe COVID-19 pneumonia receiving O2 supplementation and/or noninvasive ventilation. From March 10 through May 1, 2020, 103 lung ultrasound exams were performed by our Forward Intensive Care Team (FICT) on 26 patients (18 males and 8 females), aged 62 (54 - 76) and with a Body Mass Index (BMI) of 30.9 (28.7 - 31.5), a median 6 (5 - 9) days after admission to the COVID-19 medical unit of the University Hospital of Parma, Italy. All patients underwent chest computed tomography (CT) the day of admission. The initial LUS was 16 (11 - 21), which did not significantly correlate with initial CT scans, probably due to rapid progression of the disease and time between CT scan on admission and first FICT evaluation; conversely, LUS was significantly correlated with PaO2/FiO2 ratio throughout patient follow-up [R = - 4.82 (- 6.84 to - 2.80; p < 0.001)]. The area under the receiving operating characteristics curve of LUS for the diagnosis of moderate-severe disease (PaO2/FiO2 ratio ≤ 200 mmHg) was 0.73, with an optimal cutoff value of 11 (positive predictive value: 0.98; negative predictive value: 0.29). Patients who eventually needed invasive ventilation and/or died during admission had significantly higher LUS throughout their stay.

Wireless Peripheral Nerve Stimulation for The Upper Limb: A Case Report.

Peripheral neuro-stimulation (PNS) has been proved to be effective for the treatment of neuropathic pain as well as other painful conditions. We discuss two approaches to PNS placement in the upper extremity. The first case describes a neuropathic syndrome after the traumatic amputation of the distal phalanx of the fifth digit secondary to a work accident with lack of responsiveness to a triple conservative therapy. An upper arm region approach for the PNS was chosen. The procedure had a favorable outcome; in fact, after one month the pain symptoms were absent (VAS 0) and the pharmacological therapy was suspended. The second case presented a patient affected by progressive CRPS type II in the sensory regions of the ulnar and median nerve in the hand, unresponsive to drug therapy. For this procedure, the PNS device was implanted in the forearm. Unfortunately, in this second case the migration of the catheter affected the effectiveness of the treatment. After examining the two cases in this paper, we changed our practice and suggest the implantation of PNS for radial, median and/or ulnar nerve stimulation in the upper arm region, which has significant advantages over the forearm region.

Current Applications of Artificial Intelligence in Bariatric Surgery.

The application of artificial intelligence technologies is growing in several fields of healthcare settings. The aim of this article is to review the current applications of artificial intelligence in bariatric surgery. We performed a review of the literature on Scopus, PubMed and Cochrane databases, screening all relevant studies published until September 2021, and finally including 36 articles. The use of machine learning algorithms in bariatric surgery is explored in all steps of the clinical pathway, from presurgical risk-assessment and intraoperative management to complications and outcomes prediction. The models showed remarkable results helping physicians in the decision-making process, thus improving the quality of care, and contributing to precision medicine. Several legal and ethical hurdles should be overcome before these methods can be used in common practice.

COVID-19 What are drugs and strategies now?

From February 2019 the World faces the Covid19 pandemic. The data in our possession are still insufficient to effectively combat this pathology. The gold standard for diagnosis remains molecular testing, while clinical and instrumental and serological diagnostics are highly nonspecific leading to a slowdown in the battle against covid19.[3] Can Artificial Intelligence (AI) and Machine Learning (ML) help us? The use of large databases to cross-reference data to stratify the diagnostic scores, to quickly differentiate a critical Covid-19 patient from a non-critical one is the challenge of the future. All to achieve better management of resources in the field and a more effective therapeutic approach.[2].

The "pandemic" increase in lung ultrasound use in response to Covid-19: can we complement computed tomography findings? A narrative review.

Coronavirus disease of 2019 (COVID-19) is a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has rapidly spread to a global pandemic in March 2020. This emergency condition has been putting a severe strain on healthcare systems worldwide, and a prompt, dynamic response is instrumental in its management. While a definite diagnosis is based on microbiological evidence, the relationship between lung ultrasound (LU) and high-resolution computed tomography (HRCT) in the diagnosis and management of COVID-19 is less clear. Lung ultrasound is a point-of-care imaging tool that proved to be useful in the identification and severity assessment of different pulmonary conditions, particularly in the setting of emergency and critical care patients in intensive care units; HRCT of the thorax is regarded as the mainstay of imaging evaluation of lung disorders, enabling characterization and quantification of pulmonary involvement. Aims of this review are to describe LU and chest HRCT main imaging features of COVID-19 pneumonia, and to provide state-of-the-art insights regarding the integrated role of these techniques in the clinical decision-making process of patients affected by this infectious disease.