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Wearable devices (WDs) are increasingly integrated into clinical workflows to enable continuous, non-invasive vital signs monitoring. Combined with Artificial Intelligence (AI), these systems can shift clinical monitoring from being reactive to predictive, allowing for earlier detection of deterioration and more personalized interventions. The value of these technologies lies not in absolute measurements, but in detecting physiological parameters trends relative to each patient’s baseline. Such a trend-based approach enables real-time prediction of deterioration, enhancing patient safety and continuity of care. However, despite their shared multiparametric capabilities, WDs are not interchangeable. This narrative review analyzes nine clinically validated devices, Radius VSM® (Masimo Corporation, Irvine, CA, USA), BioButton® (BioIntelliSense Inc., Redwood City, CA, USA. Distributed by Medtronic), Portrait Mobile® (GE HealthCare, Chicago, IL, USA), VitalPatch® (VitalConnect Inc., San Jose, CA, USA), CardioWatch 287-2® (Corsano Health B.V., The Hague, The Netherlands. Distributed by Medtronic), Cosinuss C-Med Alpha® (Cosinuss Gmb, Munich, Germany), SensiumVitals® (Sensium Healthcare Limited, Abingdon, Oxfordshire, UK), Isansys Lifetouch® (Isansys Lifecare Ltd., Abingdon, Oxfordshire, UK), and CheckPoint Cardio® (CheckPoint R&D LTD., Kazanlak, Bulgaria), highlighting how differences in sensor configurations, battery life, connectivity, and validation contexts influence their suitability across various clinical environments. Rather than establishing a hierarchy of technical superiority, this review emphasizes the importance of context-driven selection, considering care setting, patient profile, infrastructure requirements, and interoperability. Each device demonstrates strengths and limitations depending on patient population and operational demands, ranging from perioperative, post-operative, emergency, or post-Intensive Care Unit (ICU) settings. The findings support a tailored approach to WD implementation, where matching device capabilities to clinical needs is key to maximizing utility, safety, and efficiency.

Data regarding safety of bedside surgical tracheostomy in novel coronavirus 2019 (COVID-19) mechanically ventilated patients admitted to the intensive care unit (ICU) are lacking. We performed this study to assess the safety of bedside surgical tracheostomy in COVID-19 patients admitted to ICU. This retrospective, single-center, cohort observational study (conducted between February, 23 and April, 30, 2020) was performed in our 45-bed dedicated COVID-19 ICU. Inclusion criteria were: a) age over 18 years; b) confirmed diagnosis of COVID-19 infection (with nasopharyngeal/oropharyngeal swab); c) invasive mechanical ventilation and d) clinical indication for tracheostomy. The objectives of this study were to describe: 1) perioperative complications, 2) perioperative alterations in respiratory gas exchange and 3) occurrence of COVID-19 infection among health-care providers involved into the procedure. A total of 125 COVID-19 patients were admitted to the ICU during the study period. Of those, 66 (53%) underwent tracheostomy. Tracheostomy was performed after a mean of 6.1 (± 2.1) days since ICU admission. Most of tracheostomies (47/66, 71%) were performed by intensivists and the mean time of the procedure was 22 (± 4.4) minutes. No intraprocedural complications was reported. Stoma infection and bleeding were reported in 2 patients and 7 patients, respectively, in the post-procedure period, without significant clinical consequences. The mean PaO2 / FiO2 was significantly lower at the end of tracheostomy (117.6 ± 35.4) then at the beginning (133.4 ± 39.2) or 24 hours before (135.8 ± 51.3) the procedure. However, PaO2/FiO2 progressively increased at 24 hours after tracheostomy (142 ± 50.7). None of the members involved in the tracheotomy procedures developed COVID-19 infection. Bedside surgical tracheostomy appears to be feasible and safe, both for patients and for health care workers, during COVID-19 pandemic in an experienced center.

Data regarding safety of bedside surgical tracheostomy in novel coronavirus 2019 (COVID-19) mechanically ventilated patients admitted to the intensive care unit (ICU) are lacking. We performed this study to assess the safety of bedside surgical tracheostomy in COVID-19 patients admitted to ICU. This retrospective, single-center, cohort observational study (conducted between February, 23 and April, 30, 2020) was performed in our 45-bed dedicated COVID-19 ICU. Inclusion criteria were: a) age over 18 years; b) confirmed diagnosis of COVID-19 infection (with nasopharyngeal/oropharyngeal swab); c) invasive mechanical ventilation and d) clinical indication for tracheostomy. The objectives of this study were to describe: 1) perioperative complications, 2) perioperative alterations in respiratory gas exchange and 3) occurrence of COVID-19 infection among health-care providers involved into the procedure. A total of 125 COVID-19 patients were admitted to the ICU during the study period. Of those, 66 (53%) underwent tracheostomy. Tracheostomy was performed after a mean of 6.1 (± 2.1) days since ICU admission. Most of tracheostomies (47/66, 71%) were performed by intensivists and the mean time of the procedure was 22 (± 4.4) minutes. No intraprocedural complications was reported. Stoma infection and bleeding were reported in 2 patients and 7 patients, respectively, in the post-procedure period, without significant clinical consequences. The mean PaO2 / FiO2 was significantly lower at the end of tracheostomy (117.6 ± 35.4) then at the beginning (133.4 ± 39.2) or 24 hours before (135.8 ± 51.3) the procedure. However, PaO2/FiO2 progressively increased at 24 hours after tracheostomy (142 ± 50.7). None of the members involved in the tracheotomy procedures developed COVID-19 infection. Bedside surgical tracheostomy appears to be feasible and safe, both for patients and for health care workers, during COVID-19 pandemic in an experienced center.

Managing the acute phase after a severe traumatic brain injury (TBI) with polytrauma represents a challenging situation for every trauma team member. A worldwide variability in the management of these complex patients has been reported in recent studies. Moreover, limited evidence regarding this topic is available, mainly due to the lack of well-designed studies. Anesthesiologists, as trauma team members, should be familiar with all the issues related to the management of these patients. In this narrative review, we summarize the available evidence in this setting, focusing on perioperative brain protection, cardiorespiratory optimization, and preservation of the coagulative function. An overview on simultaneous multisystem surgery (SMS) is also presented.

The human selection of food plants cannot always have been aimed exclusively at isolating the traits typical of domesticated species today. Each phase of global change must have obliged plants and humans to cope with and develop innovative adaptive strategies. Hundreds of thousands of wild cereal seeds from the Holocene ‘green Sahara’ tell a story of cultural trajectories and environmental instability revealing that a complex suite of weediness traits were preferred by both hunter-gatherers and pastoralists. The archaeobotanical record of the Takarkori rockshelter in southwest Libya covering four millennia of human occupation in the central Sahara gives us a unique insight into long-term plant manipulation and cultivation without domestication. The success of a number of millets was rooted in their invasive-opportunistic behaviour, rewarded during their coexistence with people in Africa. These wild plants were selected for features that were precious in the past but pernicious for agriculture today. Reconnecting past practices with modern farming strategies can help us to seek out the best resources for the future. Examination of wild cereal seed concentration at sites in Saharan Africa, and whether their traits of ‘weediness’ led to use and cultivation by humans from the eighth millennium bc .

Randomized controlled clinical trials require management effort, involving huge organizational, economic and informatics investments. Information technology offers opportunities to approach clinical trial methodology in new ways. However, there are only a few reports of computerized data and drug management systems. This paper describes a novel software created specifically for the management of a randomized trial of diet and metformin in people with metabolic syndrome (the Me.Me.Me. trial). Me.Me.Me. is an ongoing phase III randomized controlled trial in healthy people with metabolic syndrome to test the hypothesis that comprehensive lifestyle changes and/or metformin can prevent age-related chronic non-communicable diseases. To manage all the phases of the trial, we created a software which is a state pattern machine, user friendly, web-based, able to maintain the correct balance between randomization groups, and structured in various levels of security in order to guarantee the participant's privacy and compliance with the study protocol. The software achieves budget savings: drug management is not based on patients' packs, but on the actual need for drugs according to each participant's \"state\", with strict guidelines for the handling and supply of medication. The trial is ongoing and recruitment will close on August 31, 2018. To date, 11737 bottles of metformin/placebo have been dispensed to 1054 randomized participants, with drug savings of 29.5%. A software which takes into account the \"state\" of participant might be a powerful resource for developing and managing clinical trials, helping avoid poor treatment allocation, and wastage of drugs and money. EUDRACT no. 2012-005427-32. ClinicalTrials.gov Identifier: NCT02960711.

Aerobiological data have especially demonstrated that there is correlation between climate warming and the pollination season of plants. This paper focuses on airborne pollen monitoring of Betulaceae and Poaceae, two of the main plant groups with anemophilous pollen and allergenic proprieties in Northern Italy. The aim is to investigate plant responses to temperature variations by considering long-term pollen series. The 15-year aerobiological analysis is reported from the monitoring station of Vignola (located near Modena, in the Emilia-Romagna region) that had operated in the years 1990–2004 with a Hirst spore trap. The Yearly Pollen Index calculated for these two botanical families has shown contrasting trends in pollen production and release. These trends were well identifiable but fairly variable, depending on both meteorological variables and anthropogenic causes. Based on recent reference literature, we considered that some oscillations in pollen concentration could have been a main effect of temperature variability reflecting global warming. The duration of pollen seasons of Betulaceae and Poaceae, depending on the different species included in each family, has not unequivocally been determined. Phenological responses were particularly evident in Alnus and especially in Corylus as a general moving up of the end of pollination. The study shows that these trees can be affected by global warming more than other, more tolerant, plants. The research can be a contribution to the understanding of phenological plant responses to climate change and suggests that alder and hazelnut trees have to be taken into high consideration as sensible markers of plant responses to climate change.

Randomized controlled clinical trials require management effort, involving huge organizational, economic and informatics investments. Information technology offers opportunities to approach clinical trial methodology in new ways. However, there are only a few reports of computerized data and drug management systems. This paper describes a novel software created specifically for the management of a randomized trial of diet and metformin in people with metabolic syndrome (the Me.Me.Me. trial). Me.Me.Me. is an ongoing phase III randomized controlled trial in healthy people with metabolic syndrome to test the hypothesis that comprehensive lifestyle changes and/or metformin can prevent age-related chronic non-communicable diseases. To manage all the phases of the trial, we created a software which is a state pattern machine, user friendly, web-based, able to maintain the correct balance between randomization groups, and structured in various levels of security in order to guarantee the participant's privacy and compliance with the study protocol. The software achieves budget savings: drug management is not based on patients' packs, but on the actual need for drugs according to each participant's \"state\", with strict guidelines for the handling and supply of medication. The trial is ongoing and recruitment will close on August 31, 2018. To date, 11737 bottles of metformin/placebo have been dispensed to 1054 randomized participants, with drug savings of 29.5%. A software which takes into account the \"state\" of participant might be a powerful resource for developing and managing clinical trials, helping avoid poor treatment allocation, and wastage of drugs and money.

Randomized controlled clinical trials require management effort, involving huge organizational, economic and informatics investments. Information technology offers opportunities to approach clinical trial methodology in new ways. However, there are only a few reports of computerized data and drug management systems. This paper describes a novel software created specifically for the management of a randomized trial of diet and metformin in people with metabolic syndrome (the Me.Me.Me. trial). Me.Me.Me. is an ongoing phase III randomized controlled trial in healthy people with metabolic syndrome to test the hypothesis that comprehensive lifestyle changes and/or metformin can prevent age-related chronic non-communicable diseases. To manage all the phases of the trial, we created a software which is a state pattern machine, user friendly, web-based, able to maintain the correct balance between randomization groups, and structured in various levels of security in order to guarantee the participant's privacy and compliance with the study protocol. The software achieves budget savings: drug management is not based on patients' packs, but on the actual need for drugs according to each participant's \"state\", with strict guidelines for the handling and supply of medication. The trial is ongoing and recruitment will close on August 31, 2018. To date, 11737 bottles of metformin/placebo have been dispensed to 1054 randomized participants, with drug savings of 29.5%. A software which takes into account the \"state\" of participant might be a powerful resource for developing and managing clinical trials, helping avoid poor treatment allocation, and wastage of drugs and money.