Determinants of increased nursing workload in the COVID-era: A retrospective analysis of prospectively collected data.

BACKGROUND: COVID-19 is associated with increased nursing workload, therefore a high nurse-to-patient ratio would be required. AIM: To analyse difference in nursing workload, as expressed with the Nursing Activities Score (NAS), between COVID-19 patients versus control patients without COVID-19 disease (NCOVID-19 group) in an Italian Extracorporeal Membrane Oxygenation (ECMO) centre. STUDY DESIGN: Retrospective analysis of prospectively collected data, enrolling consecutive patients admitted to a general Intensive Care Unit, between 1st May 2019 and 28th February 2021. A multivariate analysis was then performed to assess if COVID-19 disease was an independent predictor of higher NAS and to assess which other factors and procedures are independently associated with increased workload. RESULTS: We enrolled 574 patients, of which 135 (24%) were in the COVID-19 group and 439 (76%) in the NCOVID-19 group. The average NAS was higher in the COVID-19 group (79 ± 11 vs. 65 ± 15, T = -10.026; p < 0.001). Prone positioning, continuous renal replacement therapy (CRRT) and ECMO were used more frequently in the COVID-19 group. A higher fraction of patients in the COVID group showed colonization from multidrug resistant bacteria. COVID-19 group had a higher duration of mechanical ventilation and longer ICU stay. The COVID-19 diagnosis was independently associated with a higher NAS. Other independent predictors of higher NAS were the use of prone positioning and continuous renal replacement therapy (CRRT). Colonization from multidrug resistant bacteria and ECMO support were not independently associated with higher NAS. CONCLUSIONS: The higher nursing workload in COVID-19 patients is mainly due to specific procedures required to treat the most hypoxemic patients, such as prone positioning. Colonization with multidrug resistant bacteria and ECMO support were not independently associated with a higher NAS. RELEVANCE TO CLINICAL PRACTICE: Higher workload in COVID-19 patients was due to specific interventions, such as prone positioning and CRRT, with the related nursing activities, as continuous presence at patient's bed, mobilization, positioning and complex hygienic procedures.

Adaptive Quality of Service Control for MQTT-SN.

Internet of Things and wireless sensor network applications are becoming more and more popular these days, supported by new communication technologies and protocols tailored to their specific requirements. This paper focuses on improving the performance of a Wireless Sensor Network operated by the MQTT-SN protocol, one of the most popular publish/subscribe protocols for IoT applications. In particular, we propose a dynamic Quality of Service (QoS) controller for the MQTT-SN protocol, capable of evaluating the status of the underlying network in terms of end-to-end delay and packet error rate, reacting consequently by assigning the best QoS value to a node. We design and implement the QoS controller in a simulated environment based on the ns-3 network emulator, and we perform extensive experiments to prove its effectiveness compared to a non-controlled scenario. The reported results show that, by controlling the quality of service, it is possible to effectively manage the number of packets successfully received by each device and their average latency, to improve the quality of the communication of each end node.

[Over-Under Triage in Trauma Team Activation: A retrospective analysis in Asst Monza]. / Over-Under Triage nell'attivazione del Trauma Team: un'analisi retrospettiva nella ASST Monza.

INTRODUCTION: Meeting the literature standards during the triage process of trauma victims, allows to make optimal use of the resources available in Trauma Centers and defines their level of quality and efficiency. Otherwise, it may occur over or under-triage. Up to now, in the reality under study and in the national literature, there wasn't any available data about efficiency and effectiveness in the triage of traumatic patients, therefore the primary objective of this study is to evaluate the over and under-triage rate in activating Trauma Team (TT) in the ASST of Monza San Gerardo Hospital. METHOD: The study design is retrospective monocentric observational. RESULTS: During the analysis, the TT-activation in ASST of Monza-San Gerardo Hospital produced an over-triage of 62,9% and an under-triage of 1,7% for the same year. DISCUSSION: The use of TT-activation algorithm is the first step of the entire care process ofthe trauma victim. This tool should guarantee the right balance between high sensitivity and high specificity (minimum over-triage rate with the possibility of higher under-triage). However, there is no sharing of these algorithms as they are inhomogeneous in the different realities; for example, the definition of major trauma, of TT and of its composition is still uneven. CONCLUSION: This study measured the over and under-triage rate related to the TT activation in the ASST of Monza. It is therefore advisable to monitor those rates periodically, as possible indicators of quality of assistance and to pursue the mission of increasing efficiency as well as effectiveness.

Coding Local and Global Binary Visual Features Extracted From Video Sequences.

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the bag-of-visual word model. Several applications, including, for example, visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget while attaining a target level of efficiency. In this paper, we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can conveniently be adopted to support the analyze-then-compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs the visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the compress-then-analyze (CTA) paradigm. In this paper, we experimentally compare the ATC and the CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: 1) homography estimation and 2) content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with the CTA, especially in bandwidth limited scenarios.

Coding visual features extracted from video sequences.

Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.