This project not only showed a significant improvement in the inter-shift patient handover, but also shortened the duration of handover by 21.67 min per registered nurse. This project also showed that commitment, acceptance, enthusiasm and support from all the registered nurses and stakeholders are essential contributing factors towards the success of improving clinical practice. Utilising the JBI PACES approach of audit and feedback has helped in reducing the time spent on handover. It has demonstrated that the use of evidence to improve clinical practice is possible in a challenging acute care environment.
The chatbot is one of the increasing number applications in the era of conversational series. It is a virtual application that can efficiently interact with any human being using the deep natural language processing skills. In NLP, for chatbot application, the various techniques needed for chatbot using NLTK tool are explained and implemented. The process of converting the text to numerical value is called text embedding. In NLTK tool, various text embedding tools are available such as TF-IDF vectorization and bag of words. Deep NLP is an efficient way to implement the chatbot. Thus the chatbot is implemented with sequence-to-sequence networks.
Biometrics is the automatic identification of individuals based on physiological and behavioral characteristics. In today's technologically advanced digital world, it is regarded as the new digital key. There are two operating modes for biometric systems: identification and verification. The most popular biometric modalities are fingerprints, which are employed in many different industries and professions. Three distinct thinning methods are examined in this study. The proposed work looks into how thinning affects fingerprints, as well as minutiae extraction and texture feature analysis. To improve the quality of the fingerprints, thinning techniques such as Zhang- Suen's, Halls, and Guo Halls have been used. In terms of minutiae extraction, the thinning methods were compared. The minutiae points obtained were used to elaborate on the precision rate of fingerprints after processing. The simulations were run, and the experimental data was examined.
Background: Infusion of peripheral blood stem cell (PBSC) in patients undergoing autologous transplantation (ASCT) has been conventionally performed using central venous catheters (CVC) inserted through the subclavian or internal jugular vein. Peripheral inserted central catheters (PICC) are routinely used for infusion of blood products and medication, but its use for PBSC infusion has not been well established. Our study aimed to evaluate the feasibility and safety of using PICC to deliver PBSC for ASCT through an in-vitro lab-based validation process, followed by a clinical review. Methods: Lab based validation In vitro infusion of 6 cryopreserved PBSCs was performed, 3 infused PICC whist 3 via CVC. Each product was thawed for the same amount of time and drained by gravity. Pre-infusion and post-infusion total nucleated cell counts (TNC), CD34 counts and CD34 viability of the PBSCs were analysed by flow-cytometry and compared using paired T test. In vitro infusion rates were also compared between PICC and CVC groups. Clinical Outcome Analysis The clinical study included 31 patients (Lymphoma N=21, myeloma N=5, Others, N=4) who underwent ASCT at National University Cancer Institute, Singapore (NCIS) from September 2019 to July 2021. All patients had a 19G BARDS dual lumen PICC inserted in either the brachial or basilic veins and used for PBSC infusion. The PBSC infusion rate, infusion associated complications, time to absolute neutrophil count (ANC) >1, and platelet count engraftment >100K were analysed. Clinical outcomes in the lymphoma cohort, who received BEAM conditioning (N=17) were also compared with a control group, matched for conditioning, cell dose and age, who had PBSC infused via CVC. Results: In vitro findings: Overall flow rates for infusion through PICC was slower (mean 0.1mls/s vs 0.3mls/s, p < 0.05). However, there were no significant % differences in TNC counts (5% vs 9%, p=0.4), CD34 counts (17% vs 15%, p=0.9) and viability (4% vs 7%, p=0.2) between pre and post infusion samples for PICC and CVC.. Clinical findings: 30 patients (Lymphoma N=21, myeloma N=5, N=4) were included. 15 (50% of patients) had a for ASCT while 15 (50%) had an existing PICC. For patients with an existing PICC, the median duration of catheter in situ was 86 days. New lines were inserted 2-7 days prior to the PBSC infusion. The median age of the patients was 54 (20-71) with 19 males (63%). . There were 5 infusion related complications, 2 in an existing PICC and 3 in new PICCs. 4 were related to slow flow rate and 1 was related to sediments seen in the line. None led to a need for alternative line for infusion. The median time to ANC recovery was 10 (range 9-14), 10 (range 9-11) and 11 days (range 10-12), while the median time to platelet engraftment was 18 (range 10-195), 20 (range 15-55) and 22 (16-85 days) for the lymphoma BEAM conditioning (N=17), lymphoma Carmustine/ Thiotepa conditioning (N=4), and the myeloma (N=5) cohorts respectively. Clinical outcomes in the lymphoma cohort, who also compared with a control group matched for conditioning, cell dose and conditioning. The in-vivo infusion rate was slower in the PICC group, compared to the CVC group (3.1 mls/min vs 4.5mls/min, p<0.05).There was however no differences in engraftment with median time to ANC recovery 10 days (range 9-14) vs 11 days (range 9-13) (p>0.05) and median time to platelet engraftment 18 (range 14-195) vs 19 days (range 14 -57) (p>0.05) in the PICC vs CVC groups respectively. Conclusion: Our in-vitro and clinical findings confirmed that the use of PICC for PBSC infusion is safe and efficacious and reduces the need for CVC insertion. Our findings have led to change in clinical practice with utilization of PICCs for PBSC infusions for ASCT. Disclosures No relevant conflicts of interest to declare.
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