10 research outputs found
Increasing patient safety with neonates via handoff communication during delivery: a call for interprofessional health care team training across GME and CME
Allison A Vanderbilt,1 Scott M Pappada,2 Howard Stein,3 David Harper,4 Thomas J Papadimos5 1Department of Family Medicine, 2Department of Anesthesiology, College of Medicine and Life Sciences, University of Toledo, 3Department of Pediatrics, ProMedica Toledo Children’s Hospital, 4Department of Obstetrics and Gynecology, ProMedica Toledo Hospital, 5Department of Anesthesiology, College of Medicine and the Life Sciences, University of Toledo, Toledo, OH, USA Abstract: Hospitals have struggled for years regarding the handoff process of communicating patient information from one health care professional to another. Ineffective handoff communication is recognized as a serious patient safety risk within the health care community. It is essential to take communication into consideration when examining the safety of neonates who require immediate medical attention after birth; effective communication is vital for positive patient outcomes, especially with neonates in a delivery room setting. Teamwork and effective communication across the health care continuum are essential for providing efficient, quality care that leads to favorable patient outcomes. Interprofessional simulation and team training can benefit health care professionals by improving interprofessional competence, defined as one’s knowledge of other professionals including an understanding of their training and skillsets, and role clarity. Interprofessional teams that include members with specialization in obstetrics, gynecology, and neonatology have the potential to considerably benefit from training effective handoff and communication practices that would ensure the safety of the neonate upon birth. We must strive to provide the most comprehensive systematic, standardized, interprofessional handoff communication training sessions for such teams, through Graduate Medical Education and Continuing Medical Education that will meet the needs across the educational continuum. Keywords: interprofessional health care teams, handoffs, neonates, patient safety, communicatio
Stenting of atherosclerotic stenoses of the extracranial carotid artery
BACKGROUND: Percutaneous transluminal angioplasty (PTA) and stenting seems to be, at present, the treatment of choice for early restenosis after endarterectomy and for atherosclerotic stenoses of supra-aortic trunks near or at the ostium. In contrast, the role of PTA and stenting for treatment of symptomatic and asymptomatic atherosclerotic stenosis of carotid bifurcation is still debated. METHODS: The present study comprises 27 consecutive cases of atherosclerotic lesions of the carotid bifurcation treated with PTA and stenting. All patients were symptomatic, except for 2 suffering from asymptomatic stenosis with contralateral carotid occlusion. There were 23 stenoses occluding 70% or more of the lumen according to the NASCET criteria and 4 mild stenoses (50-60% of the lumen) with large type C ulcers. Criteria for exclusion from surgery in these cases were aged >79 years, previous neck surgery for laryngeal cancer, carotid bifurcation at C2, association with intracranial aneurysms, occlusion of the contralateral carotid artery, and heart, lung and kidney diseases. All procedures were performed under local anaesthesia associated with mild sedation in a few cases. In all cases, self-expandable stents (Wallstent) were used. Follow-up ranged from 6 to 37 months. FINDINGS: Transient neurological deficit occurred in 3 cases (11%). One case (3.7%) experienced a minor stroke at three months. Asymptomatic tight restenosis due to intimal hyperplasia occurred in one case (3.7%). In 8 cases (40%) of complex stenosis involving common and internal carotid arteries there was some loss of contact of the stent with the wall of the common carotid artery in the late follow-up. One case (3.7%) experienced severe and prolonged hypotension and bradycardia during the release of the stent. INTERPRETATION: From literature data and our results it emerges that periprocedural catastrophic embolism is unlikely to occur. The best results are undoubtedly obtained when treating stenosis limited to the internal carotid artery. Nevertheless, the ideal stent to treat vessels of different calibre, as occurs at the carotid bifurcation, is not yet available. The problem of periprocedural cerebral protection has not been resolved. Reported series are heterogeneous and retrospective, and an adequate follow-up of cases is still lacking
Development of a Neural Network for Prediction of Glucose Concentration in Type 1 Diabetes Patients
Comparative assessment of glucose prediction models for patients with type 1 diabetes mellitus applying sensors for glucose and physical activity monitoring
Jump Neural Network for Real-Time Prediction of Glucose ConcentrationArtificial Neural Networks
Prediction of the future value of a variable is of central importance in a wide variety of fields, including
economy and finance, meteorology, informatics, and, last but not least important, medicine. For example,
in the therapy of Type 1 Diabetes (T1D), in which, for patient safety, glucose concentration in the blood
should be maintained in a defined normoglycemic range, the ability to forecast glucose concentration in
the short-term (with a prediction horizon of around 30 min) might be sufficient to reduce the incidence
of hypoglycemic and hyperglycemic events. Neural Network (NN) approaches are suitable for prediction
purposes because of their ability to model nonlinear dynamics and handle in their inputs signals coming
from different domains. In this chapter we illustrate the design of a jump NN glucose prediction algorithm
that exploits past glucose concentration data, measured in real-time by a minimally invasive continuous
glucose monitoring (CGM) sensor, and information on ingested carbohydrates, supplied by the patient
himself or herself. The methodology is assessed by tuning the NN on data of ten T1D individuals and then
testing it on a dataset of ten different subjects. Results with a prediction horizon of 30 min show that
prediction of glucose concentration in T1D via NN is feasible and sufficiently accurate. The average time
anticipation obtained is compatible with the generation of preventive hypoglycemic and hyperglycemic
alerts and the improvement of artificial pancreas performance