Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 14 de 14
Filter
1.
Experimental Dermatology ; 31:95-95, 2022.
Article in English | Web of Science | ID: covidwho-2011053
2.
Journal of Urology ; 207(SUPPL 5):e724-e725, 2022.
Article in English | EMBASE | ID: covidwho-1886527

ABSTRACT

INTRODUCTION AND OBJECTIVE: In particular after the onset of the COVID-19 pandemic, there was a precipitous rush to implement virtual and online learning strategies in surgery and medicine. It is essential to understand whether this approach is sufficient and adequate to allow the development of robotic basic surgical skills. The main aim of the authors was to verify if the quality assured eLearning is sufficient to prepare individuals to perform a basic surgical robotic task. METHODS: A prospective, randomized and multi-center study conducted in September 2020 in the ORSI Academy, International surgical robotic training center. 47 participants with no experience but a special interest in robotic surgery, were matched and randomized into 4 groups who underwent a didactic preparation with different formats before carrying out a robotic suturing and anastomosis task. Didactic preparation methods, ranged from a complete eLearning path to peer-reviewed published manuscripts describing the suturing, knot tying and task assessment metrics. RESULTS: The primary outcome was the percentage of trainees who demonstrated the quantitatively defined proficiency benchmark after learning to complete an assisted but unaided robotic vesico-urethral anastomosis task. The quantitatively defined benchmark was based on the objectively assessed performance (i.e., procedure steps completed, errors and critical errors) of experienced robotic surgeons for a proficiency based progression (PBP) training course. None of the trainees in this study demonstrated the proficiency benchmarks in completing the robotic surgery task (Figure 1a-c). CONCLUSIONS: Quality assured online learning is insufficient preparation for robotic suturing and knot tying anastomosis skills.

3.
J Eur Acad Dermatol Venereol ; 36(8): 1292-1299, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1807159

ABSTRACT

BACKGROUND: Moderate-to-severe atopic dermatitis (AD) in the adolescence is a high burden disease, and its treatment can be very challenging due to paucity of approved systemic drugs for this age and their side-effects. Dupilumab was recently approved for treatment of adolescent AD. OBJECTIVES: A multicentre, prospective, real-world study on the effectiveness and safety of dupilumab in adolescents (aged from ≥12 to <18 years) with moderate-to-severe AD was conducted. The main AD clinical phenotypes were also examined. METHODS: Data of adolescents with moderate-to-severe AD treated with dupilumab at label dosage for 16 weeks were collected. Treatment outcome was assessed by EASI, NRS itch, NRS sleep loss and CDLQI scores at baseline and after 16 weeks of treatment. The clinical scores were also evaluated according to clinical phenotypes. RESULTS: One hundred and thirty-nine adolescents were enrolled in the study. Flexural eczema and head and neck eczema were the most frequent clinical phenotypes, followed by hand eczema and portrait-like dermatitis. Coexistence of more than 1 phenotype was documented in 126/139 (88.5%) adolescents. Three patients (2.1%) contracted asymptomatic SARS-CoV-2 infection and 1 of the discontinued dupilumab treatment before the target treatment period. A significant improvement in EASI, NRS itch, NRS sleep loss and CDLQI was observed after 16 weeks of treatment with dupilumab. This outcome was better than that observed in clinical trials. Dupilumab resulted effective in all AD phenotypes, especially in diffuse eczema. Twenty-eight (20.1%) patients reported adverse events, conjunctivitis and flushing being the most frequent. None of patients discontinued dupilumab due to adverse event. CONCLUSIONS: Dupilumab in adolescent AD showed excellent effectiveness at week 16 with consistent improvement of all clinical scores. Moreover, dupilumab showed a good safety profile also in this COVID-19 pandemic era.


Subject(s)
COVID-19 , Dermatitis, Atopic , Eczema , Antibodies, Monoclonal, Humanized , COVID-19/drug therapy , Dermatitis, Atopic/drug therapy , Double-Blind Method , Humans , Pandemics , Prospective Studies , Pruritus , SARS-CoV-2 , Severity of Illness Index , Treatment Outcome
4.
European Urology ; 79:S1382-S1383, 2021.
Article in English | EMBASE | ID: covidwho-1747411

ABSTRACT

Introduction & Objectives: After the onset of the COVID-19 pandemic there was a precipitous rush to implement virtual and online learning strategies in surgery and medicine. In response there appears to be a precipitous rush to implement virtual and online learning strategies in surgery and medicine which many educators (particularly in industry) appear to believe can mitigate or supplant the necessity of skills laboratory training. It is therefore essential to have a robust and evidence-based understanding of this premise and to evaluate whether this approach is sufficient and adequate for learning basic robotic surgical skills and to prepare individuals to perform a basic surgical robotic task. Materials & Methods: A prospective, randomized and multi-center study 47 participants were matched and randomized into 4 groups who underwent proficiency based progression (PBP) eLearning, eLearning without benchmarks, traditional lectures and learning from peer-reviewed published manuscripts describing the suturing, knot tying and task assessment metrics. Afterwards the PBP group had skills training under COVID secure conditions. Results: The primary outcome was the percentage of trainees who demonstrated the quantitatively defined proficiency benchmark after didactic learning. (i.e., 5-Procedure Steps completed, <10 Errors and 0 = Critical Errors). Figure 1a-c shows that none of the trainees in this study demonstrated all three proficiency benchmarks (Procedure Steps p<0.001 – 0.000;Errors, p=0.403 – 0.001;Critical Errors, 0.016 – 0.001) (Figure 1a-c). After six hands-on training trials and ~ 3 hours training all PBP trained participants met all three proficiency benchmarks. Figure 1a-c. The mean and 95% CI of procedure Steps, Errors and Critical Errors made by the four groups of trainees on the robotic surgery vesico-urethral anastomosis model relative to the proficiency benchmark for each performance metric. Also shown are how far off the proficiency benchmark performance was. (Figure Presented) Conclusions: Although better than traditional learning strategies, quality assured online learning is insufficient preparation for basic robotic surgical skills. Medicine in general but surgery and procedure-based medicine specifically would be imprudent to be overly optimistic about how effective quality assured online learning is without skills lab. training.

6.
Multiple Sclerosis Journal ; 27(2 SUPPL):546-547, 2021.
Article in English | EMBASE | ID: covidwho-1495933

ABSTRACT

Introduction: Oral cladribine is a licensed disease-modifying treatment (DMT) for highly active relapsing multiple sclerosis (RMS). We report clinical and paraclinical data collected as part of ongoing follow-up of our cohort of people with MS (pwMS) treated with subcutaneous (s.c.) cladribine personalised dosing (CPD). Objectives and Aims: To report follow-up data in pwMS treated using CPD (adjusted for weight and total lymphocyte count, TLC). Methods: CPD was offered to pwMS with signs of disease activity irrespective of their disease course. Cladribine 10 mg s.c. was given on three consecutive days (four in pwMS & gt;90kg) during week 1. Based on TLC at week 4, patients were given another 0-3 doses at week 5. A second cycle of CPD was administered 11 months later. Follow-up included recording of adverse events, relapses, annual EDSS, 9-hole peg, timed 25-foot walking, and symbol digit modalities tests. MRI (gadolinium enhancing T1 and T2 lesions), cerebrospinal fluid (CSF) neurofilament light chain (NfL) measurements and full blood counts were obtained. Results: 250 pwMS (113 RMS, 137 PMS) received CPD. 211/250 completed a second cycle. Baseline age 45 (17-72) years and baseline EDSS 0-8.5. The safety and tolerability profile of CPD was generally very good. Six severely disabled pwMS died (one each from influenza, encephalitis, hypoxic brain injury due to choking, COVID19 pneumonia, haemopericardium and dissecting aortic aneurysm and unknown [prior EDSS 9.5]). One myocardial infarction, two breast cancers, one pulmonary embolism occurred, and three severe allergic skin reactions without long term sequelae. Severe lymphopenia (WHO grade 3-4) occurred in 7% despite personalised dosing. In 74/155 pwMS (47.7% of those with EDSS data available), EDSS remained stable or improved at follow up (median 2.9 years). In n=37, mean pre- and post-treatment CSF-NfL measurements at -4.4 and 11.3 months, respectively, were 1079pg/ml (CI 557, 1601) and 508pg/ml (CI 330, 686). Conclusions: Our ongoing observations of this uncontrolled real world cohort suggests CPD is a safe, well tolerated treatment for pwMS with disease activity. Efficacy of cladribine in preserving upper limb function in advanced MS (EDSS 6.5-8.5) will be tested in the ChariotMS trial.

8.
Phys Med ; 87: 115-122, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1260715

ABSTRACT

PURPOSE: To assess the impact of lung segmentation accuracy in an automatic pipeline for quantitative analysis of CT images. METHODS: Four different platforms for automatic lung segmentation based on convolutional neural network (CNN), region-growing technique and atlas-based algorithm were considered. The platforms were tested using CT images of 55 COVID-19 patients with severe lung impairment. Four radiologists assessed the segmentations using a 5-point qualitative score (QS). For each CT series, a manually revised reference segmentation (RS) was obtained. Histogram-based quantitative metrics (QM) were calculated from CT histogram using lung segmentationsfrom all platforms and RS. Dice index (DI) and differences of QMs (ΔQMs) were calculated between RS and other segmentations. RESULTS: Highest QS and lower ΔQMs values were associated to the CNN algorithm. However, only 45% CNN segmentations were judged to need no or only minimal corrections, and in only 17 cases (31%), automatic segmentations provided RS without manual corrections. Median values of the DI for the four algorithms ranged from 0.993 to 0.904. Significant differences for all QMs calculated between automatic segmentations and RS were found both when data were pooled together and stratified according to QS, indicating a relationship between qualitative and quantitative measurements. The most unstable QM was the histogram 90th percentile, with median ΔQMs values ranging from 10HU and 158HU between different algorithms. CONCLUSIONS: None of tested algorithms provided fully reliable segmentation. Segmentation accuracy impacts differently on different quantitative metrics, and each of them should be individually evaluated according to the purpose of subsequent analyses.


Subject(s)
COVID-19 , Algorithms , Humans , Image Processing, Computer-Assisted , Lung , Neural Networks, Computer , SARS-CoV-2 , Tomography, X-Ray Computed
9.
Accounting, Auditing and Accountability Journal ; 2021.
Article in English | Scopus | ID: covidwho-1246856

ABSTRACT

Purpose: The study analyses how management control supports the organisation's response to the COVID-19 pandemic lockdown. Design/methodology/approach: Video interviews with top and middle-level managers who were directly involved in handling the response to the COVID-19 crisis in late winter and spring 2020 form the empirical base. The object-of-control framework and the distinction between organic and mechanistic management controls inform the exploratory case analysis of a large food retail cooperative in Italy. Findings: Both organic and mechanistic management control mechanisms enabled an immediate response and management of the crisis. The use of cultural, action and results controls supported employees' health and safety coordination, a tight monitoring of financial performance and social interventions in support of the local community. Originality/value: The study provides original exploratory insights on the use and role of management control in the context of an unprecedented emergency and an unplanned setting (i.e. a pandemic crisis), which is an under-investigated topic in the accounting literature. The study shows how management control operated, linking moral and technical aspects as well as facilitating organisational adaptation and pandemic effects mitigation. © 2021, Emilio Passetti, Massimo Battaglia, Lara Bianchi and Nora Annesi.

10.
Lect. Notes Comput. Sci. ; 12661 LNCS:503-514, 2021.
Article in English | Scopus | ID: covidwho-1198421

ABSTRACT

Heart diseases are still among the main causes of death in the world population. The use of tools able to discriminate early this type of problem, even by non-specialized medical personnel on an outpatient basis, would put a decrease in health pressure on hospital centers and a better patient prognosis. This paper focuses on the problem of cardiac akinesis, a condition attributable to a very large number of pathologies, and a possible serious complication for SARS-Covid19 patients. In particular, we considered echocardiographic images of both akinetic and healthy patients. The dataset, containing echocardiograms of around 700 patients, has been supplied by Sacco hospital of Milan (Italy). We implemented a modified ResNet34 architecture and we tested the model under various combinations of parameters. The final best performing model was able to achieve a F1-score of 0.91 in the binary classification Akinetic vs. Normokinetic. © 2021, Springer Nature Switzerland AG.

11.
Sci Rep ; 11(1): 4943, 2021 03 02.
Article in English | MEDLINE | ID: covidwho-1114729

ABSTRACT

The pandemic of COVID-19 is continuously spreading, becoming a worldwide emergency. Early and fast identification of subjects with a current or past infection must be achieved to slow down the epidemiological widening. Here we report a Raman-based approach for the analysis of saliva, able to significantly discriminate the signal of patients with a current infection by COVID-19 from healthy subjects and/or subjects with a past infection. Our results demonstrated the differences in saliva biochemical composition of the three experimental groups, with modifications grouped in specific attributable spectral regions. The Raman-based classification model was able to discriminate the signal collected from COVID-19 patients with accuracy, precision, sensitivity and specificity of more than 95%. In order to translate this discrimination from the signal-level to the patient-level, we developed a Deep Learning model obtaining accuracy in the range 89-92%. These findings have implications for the creation of a potential Raman-based diagnostic tool, using saliva as minimal invasive and highly informative biofluid, demonstrating the efficacy of the classification model.


Subject(s)
COVID-19/diagnosis , Saliva/chemistry , Spectrum Analysis, Raman/methods , Aged , Aged, 80 and over , Antibodies, Viral/analysis , Comorbidity , Computational Biology , Deep Learning , Female , Humans , Male , Middle Aged , Normal Distribution , Reproducibility of Results , Sensitivity and Specificity
SELECTION OF CITATIONS
SEARCH DETAIL