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2021 ◽  
pp. 126-132
Author(s):  
Nina Lee Barnett ◽  
Barry Jubraj ◽  
Daniel Grant ◽  
Bhavana Reddy ◽  
Jennifer M Stevenson

Background: As part of tackling polypharmacy, effective medication review and safe deprescribing are key to World Health Organisation’s (WHO) 3rd Global Patient Safety Challenge. There is little information about whether this occurs consistently in pharmacy and medicine courses in England. Objective: To create a snapshot of medication review, polypharmacy and deprescribing educational activity in a small number of university courses for medicines, pharmacy and non-medical prescribing. Method: The authors undertook a pilot scoping exercise by emailing colleagues in schools of pharmacy and medicine across England about course inclusion of medication review and deprescribing. 11 universities, describing 17 programmes, responded (eight undergraduate pharmacy, four undergraduate medicine, four postgraduate medicine, one non-medical prescribing course). Data were categorised as: programme content, tools to support deprescribing, learning outcomes, and future intentions for deprescribing teaching. Results: The results suggested variation in what was being taught. Conclusion: In order to address both national and international agenda, the authors suggest that inclusion of training in this area and consistency of curricula are crucial to adequately equipping our future workforce to be fit for purpose.


2021 ◽  
Author(s):  
Tianxiao Liu ◽  
Lina Chen ◽  
Min Shi ◽  
Weixin Dai ◽  
Jing Chen ◽  
...  

Abstract Background Modified radical mastectomy (MRM) has a large incision range and can cause strong intraoperative stress, a high incidence of postoperative acute pain, and chronic pain. There are few studies on the objective evaluation of the perioperative stress response by some stress-related serological indicators and on the long-term follow-up evaluation of postoperative quality of life and the incidence of chronic pain. This study aimed to evaluate the efficacy of ultrasound guided type Ⅰ Pecs block (Pecs Ⅰ), type Ⅱ Pecs block (Pecs Ⅱ) and transverse thoracic muscle plane block (TTP) on reducing CRP, IL-6, and WBC values during surgery and on enhancing World Health Organization on Quality of Life Brief Scale (QOL) scores 6 months after MRM.Methods The randomized, placebo-controlled and double-blind study was conducted in 76 patients assigned to two groups that received either ultrasound guided Pec Ⅰ + Pec Ⅱ +TTP block with 40 ml of 0.25% ropivacaine (group PT) or saline (group C). The primary outcomes were the changes in CRP, IL-6 and WBC values on the first day before surgery and the first and third days after surgery, the changes in blood glucose levels before and after surgery, and the QOL scores evaluated 6 months after surgery.Results The median (IQR) CRP, IL-6, and WBC values were significantly reduced in group PT on the first day compared with those in group C (12 (10-13.25) mg/l, 10.45 (9.575-11.65) pg/ml, 9 (7.75-9.25)×109/ l, vs 24 (20.75-26.25) mg/l, 25.35 (19.3-29.675) pg/ml, 12 (11-13) ×109/l, respectively, p< 0.001). The median (IQR) QOL was significantly higher in group PT 6 months after surgery than in group C (53(51.75-55) vs 43 (41-51.5), p< 0.001). The incidence of chronic pain was significantly lower, n/all was 4/33 vs 0/34, p< 0.001. Conclusions Ultrasound guided Pecs I, II and TTP block, significantly reduced the CRP, IL-6 and WBC values on the first day; increased the QOL scores and the incidence of chronic pain 6 months after surgery; and promoted the rapid recovery of patients.Trial registration: chictr.org.cn ChiCTR2000033275. Registered on 26 May 2020


2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Hasmina Tari Mokui ◽  
Luther Pagiling ◽  
Tachrir Tachrir ◽  
Ranno Marlany Rachman

The number of positive cases of COVID-19 has continued to increase since it was announced by the Government in early March 2020. According to the World Health Organization (WHO), the provision of hygiene and sanitation facilities is one of the most important means of mitigating the outbreak of COVID-19 and other infectious diseases. This study aims to evaluate the socialization of assistance in making automatic handwashing devices online to communities in Southeast Sulawesi as an effort to mitigate COVID-19. The socialization was carried out by collaborating with the Southeast Sulawesi COVID-19 SATGAS Secretariat as a display location for a prototype automatic hand washing device. Meanwhile, assistance is carried out through the implementation of webinars via Zoom and the publication of video tutorials on social media in the form of YouTube and other media. The performance evaluation of the mentoring program is carried out in two forms, namely searches on online media and through online feedback presented after the webinar. Based on the response from online media and the feedback, the public responded positively to this and some of them were interested in making similar hand washing devices.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lin Du ◽  
Yan Pang

AbstractInfluenza is an infectious disease that leads to an estimated 5 million cases of severe illness and 650,000 respiratory deaths worldwide each year. The early detection and prediction of influenza outbreaks are crucial for efficient resource planning to save patient’s lives and healthcare costs. We propose a new data-driven methodology for influenza outbreak detection and prediction at very local levels. A doctor’s diagnostic dataset of influenza-like illness from more than 3000 clinics in Malaysia is used in this study because these diagnostic data are reliable and can be captured promptly. A new region index (RI) of the influenza outbreak is proposed based on the diagnostic dataset. By analysing the anomalies in the weekly RI value, potential outbreaks are identified using statistical methods. An ensemble learning method is developed to predict potential influenza outbreaks. Cross-validation is conducted to optimize the hyperparameters of the ensemble model. A testing data set is used to provide an unbiased evaluation of the model. The proposed methodology is shown to be sensitive and accurate at influenza outbreak prediction, with average of 75% recall, 74% precision, and 83% accuracy scores across five regions in Malaysia. The results are also validated by Google Flu Trends data, news reports, and surveillance data released by World Health Organization.


Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1155
Author(s):  
Nora El-Rashidy ◽  
Samir Abdelrazik ◽  
Tamer Abuhmed ◽  
Eslam Amer ◽  
Farman Ali ◽  
...  

Since December 2019, the global health population has faced the rapid spreading of coronavirus disease (COVID-19). With the incremental acceleration of the number of infected cases, the World Health Organization (WHO) has reported COVID-19 as an epidemic that puts a heavy burden on healthcare sectors in almost every country. The potential of artificial intelligence (AI) in this context is difficult to ignore. AI companies have been racing to develop innovative tools that contribute to arm the world against this pandemic and minimize the disruption that it may cause. The main objective of this study is to survey the decisive role of AI as a technology used to fight against the COVID-19 pandemic. Five significant applications of AI for COVID-19 were found, including (1) COVID-19 diagnosis using various data types (e.g., images, sound, and text); (2) estimation of the possible future spread of the disease based on the current confirmed cases; (3) association between COVID-19 infection and patient characteristics; (4) vaccine development and drug interaction; and (5) development of supporting applications. This study also introduces a comparison between current COVID-19 datasets. Based on the limitations of the current literature, this review highlights the open research challenges that could inspire the future application of AI in COVID-19.


2021 ◽  
Author(s):  
H.M.K.K.M.B. Herath ◽  
G.M.K.B. Karunasena ◽  
S.V.A.S.H. Ariyathunge ◽  
H.D.N.S. Priyankara ◽  
B.G.D.A. Madhusanka ◽  
...  

Abstract COVID-19 was announced as a global pandemic by the World Health Organization (WHO) in March 2020. With more than 31.3 million confirmed cases and over 965 thousand deaths recorded as of September 2020, it has inflicted catastrophic damage worldwide. The aim of this study is to develop an algorithm based on artificial intelligence (AI) and image processing techniques to identify COVID-19 patients with the aid of CT chest scan images. This study used a CT scan image dataset that is publically available for the researchers at Kaggle. We randomly extracted 27% of positive CT (pCT) images and 11% of negative CT (nCT) images from the original dataset. In the testing process, 120 of the test subjects in both nCT and pCT were used to validate the algorithm. Based on the experimental findings, the proposed COVID-19 detection algorithm shows promising results for the identification of COVID-19 patients with 90.83% accuracy at an average precision of 0.905.


Biomolecules ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 940
Author(s):  
Andy Kuo ◽  
Laura Corradini ◽  
Janet R. Nicholson ◽  
Maree T. Smith

Cisplatin, which is a chemotherapy drug listed on the World Health Organisation’s List of Essential Medicines, commonly induces dose-limiting side effects including chemotherapy-induced peripheral neuropathy (CIPN) that has a major negative impact on quality of life in cancer survivors. Although adjuvant drugs including anticonvulsants and antidepressants are used for the relief of CIPN, analgesia is often unsatisfactory. Herein, we used a rat model of CIPN (cisplatin) to assess the effect of a glycine transporter 2 (GlyT2) inhibitor, relative to pregabalin, duloxetine, indomethacin and vehicle. Male Sprague-Dawley rats with cisplatin-induced mechanical allodynia and mechanical hyperalgesia in the bilateral hindpaws received oral bolus doses of the GlyT2 inhibitor (3–30 mg/kg), pregabalin (3–100 mg/kg), duloxetine (3–100 mg/kg), indomethacin (1–10 mg/kg) or vehicle. The GlyT2 inhibitor alleviated both mechanical allodynia and hyperalgesia in the bilateral hindpaws at a dose of 10 mg/kg, but not at higher or lower doses. Pregabalin and indomethacin induced dose-dependent relief of mechanical allodynia but duloxetine lacked efficacy. Pregabalin and duloxetine alleviated mechanical hyperalgesia in the bilateral hindpaws while indomethacin lacked efficacy. The mechanism underpinning pain relief induced by the GlyT2 inhibitor at 10 mg/kg is likely due to increased glycinergic inhibition in the lumbar spinal cord, although the bell-shaped dose–response curve warrants further translational considerations.


Children ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 536
Author(s):  
Darine Dogui ◽  
Radhouene Doggui ◽  
Jalila El Ati ◽  
Myriam El Ati-Hellal

Aim: This study explored the association between the diet diversity score (DDS) and overweight among Tunisian children. Methods: A representative sample of children living in Greater Tunis was selected based on a two-stage clustered sampling design. A total of 1200 children (3–9 years) were recruited. Dietary assessment was realized using a 24 h dietary recall. Anthropometric measurements were realized, and overweight was defined according to the World Health Organization standards. Logistic regression was used for the association between DDS with overweight. Results: A quarter of children were found to be overweight. Overweight prevalence was found to decrease with the increase of mother education level (p = 0.010) among children <6 years. Crude DDS score was higher among non-overweight children irrespective of the age class (p = 0.002). Tunisian children appeared to consume much more than six food groups, corresponding to a more than recommended intake of most nutrients. Intriguingly, DDS was positively associated with the occurrence of overweight children <6 years, adjusted odd ratio = 1.37, 95% CI (1.03–1.82). Conclusion: Overweight is a public health problem among Tunisian children. A high DDS signifies adequate nutrient intake. An increase of DDS was found to be a positive predictor of overweight only in pre-school children.


2021 ◽  
Vol 10 (13) ◽  
pp. 2774
Author(s):  
Ysaline Seynaeve ◽  
Justine Heylen ◽  
Corentin Fontaine ◽  
François Maclot ◽  
Cécile Meex ◽  
...  

(1) Background: In the current context of the COVID-19 crisis, there is a need for fast, easy-to-use, and sensitive diagnostic tools in addition to molecular methods. We have therefore decided to evaluate the performance of newly available antigen detection kits in “real-life” laboratory conditions. (2) Methods: The sensitivity and specificity of two rapid diagnostic tests (RDT)—the COVID-19 Ag Respi-Strip from Coris Bioconcept, Belgium (CoRDT), and the coronavirus antigen rapid test cassette from Healgen Scientific, LLC, USA (HeRDT)—were evaluated on 193 nasopharyngeal samples using RT-PCR as the gold standard. (3) Results: The sensitivity obtained for HeRDT was 88% for all collected samples and 91.1% for samples with Ct ≤ 31. For the CoRDT test, the sensitivity obtained was 62% for all collected samples and 68.9% for samples with Ct ≤ 31. (4) Conclusions: Despite the excellent specificity obtained for both kits, the poor sensitivity of the CoRDT did not allow for its use in the rapid diagnosis of COVID-19. HeRDT satisfied the World Health Organization’s performance criteria for rapid antigen detection tests. Its high sensitivity, quick response, and ease of use allowed for the implementation of HeRDT at the laboratory of the University Hospital of Liège.


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