Tag: pubmed

PLoS One. 2022 Apr 19;17(4):e0262008. doi: 10.1371/journal.pone.0262008. eCollection 2022.

ABSTRACT

BACKGROUND: Climate change is expected to exacerbate diarrhoea outbreaks across the developing world, most notably in Sub-Saharan countries such as South Africa. In South Africa, diseases related to diarrhoea outbreak is a leading cause of morbidity and mortality. In this study, we modelled the impacts of climate change on diarrhoea with various machine learning (ML) methods to predict daily outbreak of diarrhoea cases in nine South African provinces.

METHODS: We applied two deep Learning DL techniques, Convolutional Neural Networks (CNNs) and Long-Short term Memory Networks (LSTMs); and a Support Vector Machine (SVM) to predict daily diarrhoea cases over the different South African provinces by incorporating climate information. Generative Adversarial Networks (GANs) was used to generate synthetic data which was used to augment the available data-set. Furthermore, Relevance Estimation and Value Calibration (REVAC) was used to tune the parameters of the ML methods to optimize the accuracy of their predictions. Sensitivity analysis was also performed to investigate the contribution of the different climate factors to the diarrhoea prediction method.

RESULTS: Our results showed that all three ML methods were appropriate for predicting daily diarrhoea cases with respect to the selected climate variables in each South African province. However, the level of accuracy for each method varied across different experiments, with the deep learning methods outperforming the SVM method. Among the deep learning techniques, the CNN method performed best when only real-world data-set was used, while the LSTM method outperformed the other methods when the real-world data-set was augmented with synthetic data. Across the provinces, the accuracy of all three ML methods improved by at least 30 percent when data augmentation was implemented. In addition, REVAC improved the accuracy of the CNN method by about 2.5% in each province. Our parameter sensitivity analysis revealed that the most influential climate variables to be considered when predicting outbreak of diarrhoea in South Africa were precipitation, humidity, evaporation and temperature conditions.

CONCLUSIONS: Overall, experiments indicated that the prediction capacity of our DL methods (Convolutional Neural Networks) was found to be superior (with statistical significance) in terms of prediction accuracy across most provinces. This study’s results have important implications for the development of automated early warning systems for diarrhoea (and related disease) outbreaks across the globe.

PMID:35439258 | DOI:10.1371/journal.pone.0262008

PLoS One. 2022 Apr 19;17(4):e0267292. doi: 10.1371/journal.pone.0267292. eCollection 2022.

ABSTRACT

BACKGROUND: Digital health technologies have been used to enhance adherence to TB medication, but the cost-effectiveness remains unclear.

METHODS: We used the real data from the study conducted from April 2014 to December 2020 in Morocco using a smart pillbox with a web-based medication monitoring system, called Medication Event Monitoring Systems (MEMS). Cost-effectiveness was evaluated using a decision analysis model including Markov model for Multi-drug resistant (MDR) TB from the health system perspective. The primary outcome was the incremental cost-effectiveness ratio (ICER) per disability adjusted life-year (DALY) averted. Two-way sensitive analysis was done for the treatment success rate between MEMS and standard of care.

RESULTS: The average total per-patient health system costs for treating a new TB patient under MEMS versus standard of care were $398.70 and $155.70, respectively. The MEMS strategy would reduce the number of drug-susceptible TB cases by 0.17 and MDR-TB cases by 0.01 per patient over five years. The ICER of MEMS was $434/DALY averted relative to standard of care, and was most susceptible to the TB treatment success rate of both strategies followed by the managing cost of MEMS.

CONCLUSION: MEMS is considered cost-effective for managing infectious active TB in Morocco.

PMID:35439273 | DOI:10.1371/journal.pone.0267292

J Thorac Imaging. 2022 May 1;37(3):194-200. doi: 10.1097/RTI.0000000000000638. Epub 2022 Jan 28.

ABSTRACT

PURPOSE: We investigated the impact of modality-specific volumes and other potential stressors on burnout and career-choice satisfaction.

MATERIALS AND METHODS: An anonymous survey of 36 questions was sent by email to all 875 faculty members of the STR. These included 11 multiple-choice questions, 23 Likert questions, and 2 free-text questions. The Maslach Burnout Index was used to assess the prevalence of the 3 components of burnout (emotional exhaustion, depersonalization, and low professional accomplishment), and we assessed variations among the potential sources of stress with respect to the respondent sex, career stage, and practice setting. Respondents were asked to estimate daily work volume as if interpreting only chest radiographs (CXRs) or only chest/cardiac computed tomography (CT). Statistical analysis was performed using Excel (Microsoft), open-source statistical computing package pandas and SciPy for Python, and Jupyter Notebook, an open-source interactive computing platform.

RESULTS: Although financial concerns (49.3%), lack of input into decisions (48.6%), and inadequate staffing (45.2%) were additional stressors, the major sources were work-life balance (67.4%) and workload (66.8%), which were more frequently cited by women than men (78.9% vs. 60.8%, P=0.001). Emotional exhaustion and depersonalization were related to higher CXR volumes. Although 83.2% were satisfied being a diagnostic radiologist, 18.8% had thought of leaving medicine. More than half of all radiologists interpreted ≥150 CXRs daily (51.1% vs. 53.6%); more in private practice read ≥200 CXRs (23.2% vs. 14.7%). Of the academic radiologists, 80.2% interpreted 21 to 49 CTs; twice as many in private practice read ≥50 CTs (25.5% vs. 12.7%).

CONCLUSIONS: The contributing factors to cardiothoracic radiologist burnout vary by sex, career stage, and practice setting. Several stressors, especially work-life balance, were associated with higher burnout prevalence. Most respondents expressed career-choice satisfaction. Defining threshold work volumes associated with higher rates of burnout is an important first step in defining burnout prevention guardrails.

PMID:35439240 | DOI:10.1097/RTI.0000000000000638

Cancer Nurs. 2022 Apr 12. doi: 10.1097/NCC.0000000000001098. Online ahead of print.

ABSTRACT

BACKGROUND: Cancer survivors face an increased risk of non-cancer-related deaths, particularly associated with metabolic syndrome. With increased cancer survivors having metabolic syndrome, health-related quality of life beyond cancer diagnosis and treatment has assumed greater importance.

OBJECTIVE: This study evaluated the prevalence rate of metabolic syndrome in cancer survivors. It examined the correlation between health-related quality of life and influencing factors according to the prevalence of metabolic syndrome.

METHODS: This is a cross-sectional national study using secondary data from the 2010-2018 Korean National Health and Nutrition Examination Survey by the Korea Disease Control and Prevention Agency. We analyzed a final sample of 1293 cancer survivors using multiple regression.

RESULTS: The prevalence rate of metabolic syndrome in cancer survivors was measured at 32.1%. Cancer survivors with metabolic syndrome had a lower health-related quality of life than those without it. The difference was statistically significant. Compared with cancer survivors without metabolic syndrome, those with it experienced substantial negative effects from stress, reducing health-related quality of life. Walking and muscle-building workouts had a positive effect on stress and improved quality of life.

CONCLUSIONS: Cancer survivors’ metabolic syndrome should be monitored closely. Development of a customized intervention program including stress management and physical activities improves their health-related quality of life.

IMPLICATIONS FOR PRACTICE: Stress management and physical activities increase health-related quality of life among cancer survivors with metabolic syndrome; thus, healthcare providers should implement intervention programs that promote exercise engagement and stress management for this population.

PMID:35439201 | DOI:10.1097/NCC.0000000000001098

IEEE Trans Neural Netw Learn Syst. 2022 Apr 19;PP. doi: 10.1109/TNNLS.2022.3165530. Online ahead of print.

ABSTRACT

Structured pruning has received ever-increasing attention as a method for compressing convolutional neural networks. However, most existing methods directly prune the network structure according to the statistical information of the parameters. Besides, these methods differentiate the pruning rates only in each pruning stage or even use the same pruning rate across all layers, rather than using learnable parameters. In this article, we propose a network redundancy elimination approach guided by the pruned model. Our proposed method can easily tackle multiple architectures and is scalable to the deeper neural networks because of the use of joint optimization during the pruning procedure. More specifically, we first construct a sparse self-representation for the filters or neurons of the well-trained model, which is useful for analyzing the relationship among filters. Then, we employ particle swarm optimization to learn pruning rates in a layerwise manner according to the performance of the pruned model, which can determine optimal pruning rates with the best performance of the pruned model. Under this criterion, the proposed pruning approach can remove more parameters without undermining the performance of the model. Experimental results demonstrate the effectiveness of our proposed method on different datasets and different architectures. For example, it can reduce 58.1% FLOPs for ResNet50 on ImageNet with only a 1.6% top-five error increase and 44.1% FLOPs for FCN_ResNet50 on COCO2017 with a 3% error increase, outperforming most state-of-the-art methods.

PMID:35439146 | DOI:10.1109/TNNLS.2022.3165530

J Math Biol. 2022 Apr 19;84(5):39. doi: 10.1007/s00285-022-01741-3.

ABSTRACT

We derive an alternative expression for a delayed logistic equation in which the rate of change in the population involves a growth rate that depends on the population density during an earlier time period. In our formulation, the delay in the growth term is consistent with the rate of instantaneous decline in the population given by the model. Our formulation is a modification of Arino et al. (J Theor Biol 241(1):109-119, 2006) by taking the intraspecific competition between the adults and juveniles into account. We provide a complete global analysis showing that no sustained oscillations are possible. A threshold giving the interface between extinction and survival is determined in terms of the parameters in the model. The theory of chain transitive sets and the comparison theorem for cooperative delay differential equations are used to determine the global dynamics of the model. We extend our delayed logistic equation to a system modeling the competition between two species. For the competition model, we provide results on local stability, bifurcation diagrams, and adaptive dynamics. Assuming that the species with shorter delay produces fewer offspring at a time than the species with longer delay, we show that there is a critical value, [Formula: see text], such that the evolutionary trend is for the delay to approach [Formula: see text].

PMID:35438310 | DOI:10.1007/s00285-022-01741-3

Osteoporos Int. 2022 Apr 19. doi: 10.1007/s00198-022-06398-8. Online ahead of print.

ABSTRACT

Both weight gain and weight loss in type 2 diabetic population were associated with increased risk of hip fracture, while maintaining weight lowered the risk of hip fracture. Regarding the risk of hip fracture, we can propose active monitoring to maintain the weight of type 2 diabetes patients.

INTRODUCTION: In type 2 diabetes, patients are often asked to control their weight in order to reduce their diabetic morbidity. The American Diabetes Association recommends that diabetic patients conduct high-intensity interventions for regulating diet, physical activity, and behavior to reduce weight, followed by long-term comprehensive weight maintenance programs. Although such weight control attempts are required in diabetic patients, there are few studies on the effect of weight change on hip fracture in this population. We aim to investigate the association between body weight change and the incidence of hip fracture in subjects with type 2 diabetes using large-scale, nationwide cohort data on the Korean population.

MATERIALS AND METHODS: A total of 1,447,579 subjects (894,204 men and 553,375 women) > 40 years of age, who were diagnosed with type 2 diabetes, were enrolled in this study. Weight change within 2 years was divided into five categories: from weight loss ≥ 10% to weight gain ≥ 10%. The hazard ratios (HRs) and 95% confidence intervals for the incidence of hip fracture were analyzed, compared with the reference of the stable weight group (weight change < 5%).

RESULTS: Among 5 weight change groups, more than 10% weight loss showed the highest HR (HR, 1.605; 95% CI, 1.493 to 1.725), followed by more than 10% weight gain (HR, 1.457; 95% CI, 1.318 to 1.612). The effect of weight change on hip fracture risk was greater in males than in females, and those under 65 years of age were greater than those over 65 years of age. Baseline BMI did not play a role of weight change affecting the risk of hip fracture. The HR for hip fracture of subjects with regular exercise was lower than those without regular exercise.

CONCLUSIONS: In the type 2 diabetes population, both weight gain and weight loss were significantly associated with a higher risk of hip fracture, whereas maintaining body weight reduced the risk of hip fracture the most.

PMID:35438308 | DOI:10.1007/s00198-022-06398-8

J Assoc Physicians India. 2022 Mar;70(3):11-12.

ABSTRACT

INTRODUCTION: Idiopathic Membranous nephropathy (IMN) is one of the most common causes of adult onset nephrotic syndrome worldwide. About 50% will slowly progress to renal failure if untreated.

METHODS: We did a retrospective study in patients with Idiopathic membranous nephropathy who were on follow-up between 2016-2018 at Madras medical college, Chennai. Clinical records, investigations, treatment and treatment response were analyzed. Risk stratification was done according to urine protein estimation, Modified Ponticelli regimen was administered in patients with high risk of renal failure and those with complications. They were followed up 6-12 months.

RESULTS: Among 61 patients with IMN, 37 were treated with Modified Ponticelli regimen after 6months of supportive treatment. Spontaneous remission was 14%, after mean follow up of 3.14 yrs total remission was 64.86 %( CR 43.24%; PR-21.62%) and 35.14% had no remission. Three patients progressed to CKD. Tacrolimus was initiated in non responders to IST. Analysis between IST responders and non responders shows those who presented with lesser proteinuria had statistically better outcome.

CONCLUSION: This retrospective study of IMN showed a reasonably better outcome. Seventeen per cent of patients had spontaneous remission and 64.86% achieved remission with Modified Ponticelli regimen.

PMID:35438279

Eur J Prosthodont Restor Dent. 2022 Apr 11. doi: 10.1922/EJPRD_2367Althubaitiy09. Online ahead of print.

ABSTRACT

The effects of using and varying the material and diameter of implant scan bodies (ISBs) on the level of accuracy of digital implant impressions is unclear. The purpose of this study was to investigate these effects on the level of accuracy of scans made by an extraoral scanner (EOS) and intraoral scanner (IOS). A stone cast with two sets of ISBs was used. ISBs were made of titanium (TI) or polyether ether ketone (PEEK). Each set consisted of two narrow diameter (ND) and two regular diameter (RD) ISBs. Sixtysix scans were performed and imported into an inspection and metrology software to conduct the three-dimensional (3D) comparisons (N=140) and obtain root mean square (RMS) values. RMS values were analyzed with descriptive and inferential non-parametric statistics (α=.05). The use of ISBs did not improve the overall EOS and IOS scans accuracies. Also, varying the ISBs’ diameter and material influenced the EOS and IOS accuracies. For the EOS, the precision in descending order was as follows RD TI, ND TI, RD PEEK, ND PEEK. In contrast, for the IOS an inverse relationship was noted. Finally, precision assessment should always be performed for any reference scanner under the proposed test conditions.

PMID:35438267 | DOI:10.1922/EJPRD_2367Althubaitiy09

J Assoc Physicians India. 2022 Mar;70(3):11-12.

ABSTRACT

COVID-19 is the disease caused by SARS-CoV-2. The present hospital based study was performed to find out prevalence of Urinary Tract Infection among COVID 19 patients. The cross sectional study was performed with seven hundred fifty three laboratory confirmed COVID 19 cases over six months (from 1st July to 31st December, 2020). Urine samples collected from laboratory confirmed COVID-19 cases in appropriate sterile manner and were screened for pus cells and bacteria. This was followed by plating on Mac-conkey’s agar media and 5% Sheep Blood agar media. Inoculated plates were incubated overnight in aerobic condition at 37°C. Discrete colonies were further studied by Gram staining, tests for motility, battery of biochemical tests. Antibiogram was performed by disk diffusion method as per CLSI guidelines. Species confirmation and MIC (Minimum Inhibitory Concentration) values of the tested antibiotics were detected by automation. Results were analyzed according to standard statistical methods. Ninety urine samples were culture positive (11.95%). Escherichia coli was found to be the commonest pathogen, isolated in forty three cases (47.78%) followed by Enterococcus faecalis in twenty nine (32.22%) and Klebsiella pneumoniae subspp. pneumonia in eighteen occasions (20%). Enterococcus faecalis isolates were sensitive to Vancomycin, Linezolid and Nitrofurantoin and nineteen isolates were resistant to fluroquinolones (65.51%). Majority of the Gram Negative isolates were susceptible to nitrofurantoin (80.32%) where as fifteen carbapenemase producers, thirteen AmpC Betalactamase producers and twenty one Extended Spectrum Beta Lactamase (ESBL) producers have been recorded. Constant awareness regarding the antibiotic guidelines for COVID-19 cases is the need of the hour.

PMID:35438276