medical surveillance
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Author(s):  
Liepollo Ntlhakana ◽  
Gill Nelson ◽  
Katijah Khoza-Shangase ◽  
Elton Dorkin

Background: The relevant legislation ensures confidentiality and has paved the way for data handling and sharing. However, the industry remains uncertain regarding big data handling and sharing practices for improved healthcare delivery and medical research. Methods: A semi-qualitative cross-sectional study was used which entailed analysing miners’ personal health records from 2014 to 2018. Data were accessed from the audiometry medical surveillance database (n = 480), the hearing screening database (n = 24,321), and the occupational hygiene database (n = 15,769). Ethical principles were applied to demonstrate big data protection and sharing. Results: Some audiometry screening and occupational hygiene records were incomplete and/or inaccurate (N = 4675). The database containing medical disease and treatment records could not be accessed. Ethical challenges included a lack of clarity regarding permission rights when sharing big data, and no policy governing the divulgence of miners’ personal and medical records for research. Conclusion: This case study illustrates how research can be effectively, although not maliciously, obstructed by the strict protection of employee medical data. Clearly communicated company policies should be developed for the sharing of workers’ records in the mining industry to improve HCPs.


2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Wei Wang ◽  
Weihui Li ◽  
Dianfeng Chu ◽  
Jinlian Hua ◽  
Xinke Zhang ◽  
...  

AbstractTumors are one of the leading causes to death in pet dogs among diseases. The tumor incidence of pet dogs has been increasing, raising widespread concern.The tumor incidence of pet dogs has been increasing, raising widespread concern. In this study, retrospective analysis was performed with 246 tumor cases registered in Xi’an Animal Hospital, Northwest A&F University from 2009 to 2018. Correlations of sex, age and breed with tumor incidences were evaluated. The results showed that reproductive system tumors occupied the highest proportion (39.84%), followed by cutaneous tumors (28.05%), digestive tumors (18.70%) and ocular tumor (4.47%). Among the reproductive system tumors, breast tumors are the most common tumor in female pet dogs, especially for Pekingese (11.43%). Female dogs with high susceptibility to breast tumors were at the ages of 6–18 years old. As far as cutaneous tumors were concerned, the male pet dogs at all ages, particularly Golden Retrievers (17.39%), showed a high incidence. By contrast, male Samoyed aged from 4 to 13 years had the highest incidence (15.22%) of digestive tumors. In addition, pet dogs with ocular tumors mainly happened at the ages of 0–1 years and 6–13 years. Collectively, our findings are significant to develop effective measures of medical surveillance for pet dogs’ health and will provide insights for comparative oncology.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Manish Kumar Ahirwar ◽  
Piyush Kumar Shukla ◽  
Rakesh Singhai

Data mining is mostly utilized for a huge variety of applications in several fields like education, medical, surveillance, and industries. The clustering is an important method of data mining, in which data elements are divided into groups (clusters) to provide better quality data analysis. The Biogeography-Based Optimization (BO) is the latest metaheuristic approach, which is applied to resolve several complex optimization problems. Here, a Chaotic Biogeography-Based Optimization approach using Information Entropy (CBO-IE) is implemented to perform clustering over healthcare IoT datasets. The main objective of CBO-IE is to provide proficient and precise data point distribution in datasets by using Information Entropy concepts and to initialize the population by using chaos theory. Both Information Entropy and chaos theory are facilitated to improve the convergence speed of BO in global search area for selecting the cluster heads and cluster members more accurately. The CBO-IE is implemented to a MATLAB 2021a tool over eight healthcare IoT datasets, and the results illustrate the superior performance of CBO-IE based on F-Measure, intracluster distance, running time complexity, purity index, statistical analysis, root mean square error, accuracy, and standard deviation as compared to previous techniques of clustering like K-Means, GA, PSO, ALO, and BO approaches.


2021 ◽  
pp. 003335492110415
Author(s):  
Nicholas K. Reul ◽  
Zachary Gray ◽  
Barbara Burchell Braid ◽  
Margaret A. Leland

Both the Occupational Safety and Health Administration and Washington State require safety and health protections for workers exposed to respirable crystalline silica, including tuberculosis (TB) screening as part of occupational medical surveillance. We describe the creation of a TB screening tool for silica-exposed workers receiving regulated medical surveillance examinations in Washington State. The tool provides relevant clinical recommendations to assist health care providers and public health practitioners who choose to use the tool when performing such examinations. A cross-disciplinary team at the Washington State Department of Labor and Industries created the TB screening tool to help health care providers identify silica-exposed workers who should receive a comprehensive evaluation for active TB disease and workers who should or must receive testing for latent TB infection. The Washington State Adult Tuberculosis Screening Tool for Workers Exposed to Respirable Crystalline Silica benefits occupational and respiratory clinicians and public health practitioners by aiding both the individual- and population-level delivery of occupational health and TB screening services to silica-exposed workers receiving required medical surveillance examinations.


2021 ◽  
Vol 5 ◽  
pp. 143
Author(s):  
Ignacio Esteban ◽  
Georgina Bergero ◽  
Camila Alves ◽  
Micaela Bronstein ◽  
Valeria Ziegler ◽  
...  

Background: SARS-CoV-2 infected individuals ≥60 years old have the highest hospitalization rates and represent >80% fatalities. Within this population, those in long-term facilities represent >50% of the total COVID-19 related deaths per country. Among those without symptoms, the rate of pre-symptomatic illness is unclear, and potential predictors of progression for symptom development are unknown. Our objective was to delineate the natural evolution of asymptomatic SARS-CoV-2 infection in elders and identify determinants of progression. Methods: We established a medical surveillance team monitoring 63 geriatric institutions. When an index COVID-19 case emerged, we tested all other eligible asymptomatic elders ≥75 or >60 years old with at least 1 comorbidity. SARS-CoV-2 infected elders were followed for 28 days. Disease was diagnosed when any COVID-19 manifestation occurred. SARS-CoV-2 load at enrollment, shedding on day 15, and antibody responses were also studied. Results: After 28 days of follow-up, 74/113(65%) SARS-CoV-2-infected elders remained asymptomatic. 21/39(54%) pre-symptomatic patients developed hypoxemia and ten pre-symptomatic patients died(median day 13.5,IQR 12). Dementia was the only clinical risk factor associated with disease(OR 2.41(95%CI=1.08, 5.39). In a multivariable logistic regression model, dementia remained as a risk factor for COVID-19 severe disease. Furthermore, dementia status showed a statistically significant different trend when assessing the cumulative probability of developing COVID-19 symptoms(log-rank p=0.027). On day 15, SARS-CoV-2 was detectable in 30% of the asymptomatic group while in 61% of the pre-symptomatic(p=0.012). No differences were observed among groups in RT-PCR mean cycle threshold at enrollment(p=0.391) and in the rates of antibody seropositivity(IgM and IgG against SARS-CoV-2 nucleocapsid protein). Conclusions: In summary, 2/3 of our cohort of SARS-CoV-2 infected elders from vulnerable communities in Argentina remained asymptomatic after 28 days of follow-up with high mortality among those developing symptoms. Dementia and persistent SARS-CoV-2 shedding were associated with progression from asymptomatic to symptomatic infection.


Author(s):  
Daniela Esposito ◽  
Oskar Ragnarsson ◽  
Gudmundur Johannsson ◽  
Daniel S Olsson

Abstract Context Whether cancer risk in acromegaly is increased remains controversial. Also, the risk of benign tumors has been little studied. Objective To investigate the incidence of benign and malignant tumors in acromegaly in a nationwide population-based study. Design Adult patients diagnosed with acromegaly between 1987 and 2017 were identified in the Swedish National Patient Registry. The diagnoses of benign and malignant tumors were recorded. Standardized incidence ratios (SIRs) and standardized mortality ratios (SMRs) for neoplasms with 95% confidence intervals (CIs) were calculated using the Swedish general population as reference. Results The study included 1296 patients (52% women). Mean (SD) age at diagnosis was 51.6 (14.7) years. Median (range) follow-up time was 11.7 (0-31) years. Overall, 186 malignancies were identified in acromegalic patients compared to 144 expected in the general population (SIR 1.3; 95% CI, 1.1-1.5). The incidence of colorectal and anal cancer (SIR 1.5; 95% CI, 1.0-2.2), and renal and ureteral cancer (SIR 4.0; 95% CI, 2.3-6.5) was increased, whereas the incidence of malignancies of the respiratory system, brain, prostate, and breast was not. Only three cases of thyroid cancer were recorded. Mortality due to malignancies was not increased (SMR 1.1; 95% CI, 0.9-1.4). Incidence of benign tumors was increased more than 2-fold (SIR 2.4; 95% CI, 2.1-2.7). Conclusions Patients with acromegaly had an increased risk of both benign and malignant tumors including colorectal and anal cancer, and renal and ureteral cancer. Whether this is associated with acromegaly itself or due to more intensive medical surveillance remains to be shown.


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