Actus Santé

A classification model to predict specialty drug use

ABSTRACT Objective Predicting who is likely to become utilizers of specialty drugs allows care managers to have an early intervention and payers to have financial preparation for the upcoming spending. Our administrative claims-based predictive model is to predict the members who might use specialty drugs. Materials and Methods A national database* and a commercial health plan claim data were used to select a total 6.5 million people who were not taking any specialty drugs before the Target Prediction Window. There were about 136,700 members who were older than 65 in the study. We extracted 81 features from past history of medical, pharmacy claims, and demographic data to predict the specialty drug use in the following year. Members having at least three-month continuous enrollment either under medical or pharmacy plan in the previous year immediately before the start of the target prediction window and with no specialty drug taking history were eligible for this study. We trained and tuned on 75% of the data using an extreme gradient boosting binary classifier. We used the remaining 25% of the data to predict the outcomes and evaluate the performance. We also recorded the performance for the age group older than 65 years old. Results There were 3% of members who used specialty drugs in the cohort under the current study. The important features for prediction included age, monthly pharmacy payment, monthly medical payment, diseases, procedure, or drug-related codes. On the test data with members of all ages, model performance for the area under the receiving operator characteristics curve (AUROC) was 78.6%. For the test set on members older than 65 (prevalence rate 3.6%), we had an AUROC of 79.3%. Discussion There is no similar machine learning model in the field to predict specialty drug use. Our model provides an unparalleled opportunity to allow early intervention for people who might develop diseases that require specialty drug use. It is also important for health plans and providers to know their covered population who might use specialty drugs and predict the increased cost in the next year. Conclusion A predictive model of specialty drug use can be helpful for both payers and providers to prepare for a spending spike or have an early intervention. In return, this helps to improve patients' overall satisfaction.
Catégories: Actus Santé

Adherence to the EAT-Lancet Healthy Reference Diet in relation to Coronary Heart Disease, All-Cause Mortality Risk and Environmental Impact: results from the EPIC-NL Cohort

Objectives: To construct a diet-score measuring the level of adherence to the Healthy Reference Diet (HRD), to explore whether adherence to the HRD is associated with coronary heart disease (CHD), all-cause mortality risk, and to calculate its environmental impact. Design: Prospective cohort study. Setting: The Dutch contribution to the European Prospective Investigation into Cancer and Nutrition (EPIC-NL). Participants: 37,349 adults (20-70y) without CHD at baseline. Main outcome measures: Primary outcomes were incident CHD and all-cause mortality. Secondary outcomes were greenhouse gas emission (GHGE), land use, blue water use, freshwater eutrophication, marine eutrophication, and terrestrial acidification. Results: During a median 15.3-year follow-up, 2,543 cases of CHD occurred, and 5,648 individuals died from all causes. The average HRD-score was 73 (SD=10). High adherence to the HRD was associated with a 15% lower risk of CHD (hazard ratio 0.85, 95% confidence interval 0.75 to 0.96), as well as a 17% lower risk of all-cause mortality (hazard ratio 0.83, 95% confidence interval 0.77 to 0.90) in multivariable-adjusted models. Better adherence to the HRD was associated with lower environmental impact from GHGE ({beta}= -0.10 kg CO2-eq, 95% confidence interval -0.13 to -0.07), land use ({beta}= -0.11 m2 per year, 95% confidence interval -0.12 to -0.09), freshwater eutrophication ({beta}= -0.000002 kg P-eq, 95% confidence interval -0.000004 to -0.000001), marine eutrophication ({beta}= -0.00035 kg N-eq, 95% confidence interval -0.00042 to -0.00029), and terrestrial acidification ({beta} = -0.004 kg SO2-eq, 95% confidence interval -0.004 to -0.003), but with higher environmental impact from blue water use ({beta}=0.044 m3, 95% confidence interval 0.043 to 0.045). Conclusion: High adherence to the HRD was associated with lower risk of CHD and all-cause mortality. Additionally, increasing adherence to the HRD could lower some aspects of the environmental impact of diets, but attention is needed for the associated increase in blue water use.
Catégories: Actus Santé

Urinary cell mRNA Profiling of Kidney Allograft Recipients: A Systematic Investigation of a Filtration Based Protocol for the Simplification of Urine Processing

Background. Kidney transplantation is a life-restorative therapy, but immune rejection undermines allograft survival. Urinary cell mRNA profiles offer a noninvasive means of diagnosing kidney allograft rejection, but urine processing protocols have logistical constraints. We aimed to determine whether the centrifugation-based method for urinary cell mRNA profiling could be replaced with a simpler filtration-based method without undermining quality. Methods. We isolated RNA from urine collected from kidney allograft recipients using the Cornell centrifugation-based protocol (CCBP) or the Zymo filter-based protocol (ZFBP) and compared RNA purity and yield using a spectrophotometer or a fluorometer and measured absolute copy number of transcripts using customized real-time quantitative PCR assays. We investigated the performance characteristics of RNA isolated using ZFBP and stored either at -80oC or at ambient temperature for 2 to 4 days and also when shipped to our Gene Expression Monitoring (GEM) Core at ambient temperature. We examined the feasibility of initial processing of urine samples by kidney allograft recipients trained by the GEM Core staff and the diagnostic utility for acute rejection, of urine processed using the ZFBP. Results. RNA purity (P=0.0007, Wilcoxon matched paired signed-ranks test ) and yield (P<0.0001) were higher with ZFBP vs. CCBP, and absolute copy number of 18S rRNA was similar (P=0.79) following normalization of RNA yield by reverse transcribing a constant amount of RNA isolated using either protocol. RNA purity, yield, and absolute copy numbers of 18S rRNA, TGF-{beta}1 mRNA and microRNA-26a were not different (P>0.05) in the filtrates containing RNA stored either at -800C or at ambient temperature for 2 to 4 days or shipped overnight at ambient temperature. RNA purity, yield, and absolute copy numbers of 18S rRNA and TGF-{beta}1 mRNA were also not different (P>0.05) between home processed and laboratory processed urine filtrates. Urinary cell levels of mRNA for granzyme B (P=0.01) and perforin (P=0.0002) in the filtrates were diagnostic of acute rejection in human kidney allografts. Conclusions. Urinary cell mRNA profiling was simplified using the ZFBP without undermining RNA quality or diagnostic utility. Home processing by the kidney allograft recipients, the stability of RNA containing filtrates at ambient temperature, and the elimination of the need for centrifuges and freezers represent some of the advantages of ZFBP over the CCBP for urinary cell mRNA profiling.
Catégories: Actus Santé

Will Vaccine-derived Protective Immunity Curtail COVID-19 Variants in the US?

Multiple effective vaccines are currently being deployed to combat the COVID-19 pandemic (caused by SARS-COV-2), and are viewed as the major factor in marked reductions in disease burden in regions around the world with moderate to high coverage of these vaccines. The effectiveness of COVID-19 vaccination programs is, however, significantly threatened by the emergence of new SARS-COV-2 variants that, in addition to being more transmissible and potentially more virulent than the wild (resident) strain, may at least partially evade existing vaccines. A new two-strain (one resident, the other wild) and two-group (vaccinated or otherwise) mechanistic mathematical model is designed and used to assess the impact of the vaccine-induced cross-protective efficacy on the spread the COVID-19 pandemic in the United States. Analysis of the model, which is fitted using COVID-19 mortality data for the US, shows that vaccine-induced herd immunity can be achieved if 61% of the American population is fully vaccinated with the Pfizer or Moderna vaccines. Parameter sensitivity analysis suggests three main factors that significantly affect the COVID-19 burden in the US, namely (a) daily vaccination rate, (b) the level of cross-protection the vaccines offer against the variant, and (c) the relative infectiousness of the dominant variant relative to the wild strain. This study further suggests that a new variant can cause a significant disease surge in the US if (i) the vaccine coverage against the wild strain is low (roughly < 50%), (ii) the variant is much more transmissible (e.g., twice more transmissible) than the wild-type strain, or (iii) the level of cross-protection offered by the vaccine is relatively low (e.g., less than 70%). A new variant will not cause such surge in the US if it is only moderately more transmissible (e.g., 1:56 more transmissible) than the wild strain, at least 66% of the population of the US is fully vaccinated, and the three vaccines being deployed in the US (Pfizer, Moderna, and Johnson & Johnson) offer a moderate level of cross-protection against the variant.
Catégories: Actus Santé

Volumetric quantification of wound healing by machine learning and optical coherence tomography in adults with type 2 diabetes: the GC-SHEALD RCT

Type 2 diabetes mellitus is associated with impaired wound healing, which contributes substantially to patient morbidity and mortality. Glucocorticoid (stress hormone) excess is also known to delay wound repair. Optical coherence tomography (OCT) is an emerging tool for monitoring healing by 'virtual biopsy', but largely requires manual analysis, which is labour-intensive and restricts data volume processing. This limits the capability of OCT in clinical research. Using OCT data from the GC-SHEALD trial, we developed a novel machine learning algorithm for automated volumetric quantification of discrete morphological elements of wound healing (by 3mm punch biopsy) in patients with type 2 diabetes. This was able to differentiate between early / late granulation tissue, neo-epidermis and clot structural features and quantify their volumetric transition between day 2 and day 7 wounds. Using OCT, we were able to visualize differences in wound re-epithelialisation and re-modelling otherwise indistinguishable by gross wound morphology between these time points. Automated quantification of maximal early granulation tissue showed a strong correlation with corresponding (manual) GC-SHEALD data. Further, % re-epithelialisation was improved in patients treated with oral AZD4017, an inhibitor of systemic glucocorticoid-activating 11{beta}-hydroxysteroid dehydrogenase type 1 enzyme action, with a similar trend in neo-epidermis volume. Through the combination of machine learning and OCT, we have developed a highly sensitive and reproducible method of automated volumetric quantification of wound healing. This novel approach could be further developed as a future clinical tool for the assessment of wound healing e.g. diabetic foot ulcers and pressure ulcers.
Catégories: Actus Santé

Analysis of Feature Influence on Covid-19 Death Rate Per Country Using a Novel Orthogonalization Technique

We have developed a new technique of Feature Importance, a topic of machine learning, to analyze the possible causes of the Covid-19 pandemic based on country data. This new approach works well even when there are many more features than countries and is not affected by high correlation of features. It is inspired by the Gram-Schmidt orthogonalization procedure from linear algebra. We study the number of deaths, which is more reliable than the number of cases at the onset of the pandemic, during Apr/May 2020. This is while countries started taking measures, so more light will be shed on the root causes of the pandemic rather than on its handling. The analysis is done against a comprehensive list of roughly 3,200 features. We find that globalization is the main contributing cause, followed by calcium intake, economic factors, environmental factors, preventative measures, and others. This analysis was done for 20 different dates and shows that some factors, like calcium, phase in or out over time. We also compute row explainability, i.e. for every country, how much each feature explains the death rate. Finally we also study a series of conditions, e.g. comorbidities, immunization, etc. which have been proposed to explain the pandemic and place them in their proper context. While there are many caveats to this analysis, we believe it sheds light on the possible causes of the Covid-19 pandemic.
Catégories: Actus Santé

Dynamic, stage-course protein interaction network using high power CpG sites in Head and Neck Squamous Cell Carcinoma

Head and neck cancer is the sixth leading cause of cancer across the globe and is significantly more prevalent in South Asian countries, including Pakistan. Prediction of pathological stages of cancer can play a pivotal role in early diagnosis and personalized medicine. This project ventures into the prediction of different stages of head and neck squamous cell carcinoma (HNSCC) using prioritized DNA methylation patterns. DNA methylation profiles for each HNSCC stage (stage-I- IV) were used to extensively analyze 485,577 methylation CpG sites and prioritize them on the basis of the highest predictive power using a wrapper-based feature selection method, along with different classification models. We identified 68 high-power methylation sites which predicted the pathological stage of HNSCC samples with 90.62 % accuracy using a Random Forest classifier. We set out to construct a protein-protein interaction network for the proteins encoded by the 67 genes associated with these sites to study its network topology and also undertook enrichment analysis of nodes in their immediate neighborhood for GO and KEGG Pathway annotations which revealed their role in cancer-related pathways, cell differentiation, signal transduction, metabolic and biosynthetic processes. With information on the predictive power of each of the 67 genes in each HNSCC stage, we unveil a dynamic stage-course network for HNSCC. We also intend to further study these genes in light of functional datasets from CRISPR, RNAi, drug screens for their putative role in HNSCC initiation and progression.
Catégories: Actus Santé

An Approach for Open Multivariate Analysis of Integrated Clinical and Environmental Exposures Data

The Integrated Clinical and Environmental Exposures Service (ICEES) provides regulatory compliant open access to sensitive patient data that have been integrated with public exposures data. ICEES was designed initially to support dynamic cohort creation and bivariate contingency tests. The objective of the present study was to develop an open approach to support multivariate analyses using existing ICEES functionalities and abiding by all regulatory constraints. We first developed an open approach for generating a multivariate table that maintains contingencies between clinical and environmental variables using programmatic calls to the open ICEES application programming interface. We then applied the approach to data on a large cohort (N = 22,365) of patients with asthma or related conditions and generated an eight feature table. Due to regulatory constraints, data loss was incurred with the incorporation of each successive feature variable, from a starting sample size of N = 22,365 to a final sample size of N = 4,556 (20.5%), but data loss was < 10% until the addition of the final two feature variables. We then applied a generalized linear model to the subsequent dataset and focused on the impact of seven select feature variables on asthma exacerbations, defined as annual emergency department or inpatient visits for respiratory issues. We identified five feature variables sex, race, obesity, prednisone, and airborne particulate exposure as significant predictors of asthma exacerbations. We discuss the advantages and disadvantages of ICEES open multivariate analysis and conclude that, despite limitations, ICEES can provide a valuable resource for open multivariate analysis and can serve as an exemplar for regulatory compliant informatics solutions to open patient data, with capabilities to explore the impact of environmental exposures on health outcomes.
Catégories: Actus Santé

Survey of SARS-CoV-2 genetic diversity in two major Brazilian cities using a fast and affordable Sanger sequencing strategy.

Genetic variants of SARS-CoV-2 have been emerging and circulating in many places across the world. Rapid detection of these variants is essential since their dissemination can impact transmission rates, diagnostic procedures, disease severity, response to vaccines or patient management. Sanger sequencing has been used as the preferred approach for variant detection among circulating human immunodeficiency and measles virus genotypes. Using primers to amplify a fragment of the SARS-CoV-2 genome encoding part of the Spike protein, we showed that Sanger sequencing allowed us to rapidly detect the introduction and spread of three distinct SARS-CoV-2 variants in two major Brazilian cities. In both cities, after the predominance of variants closely related to the virus first identified in China, the emergence of the P.2 variant was quickly followed by the identification of the P1 variant, which became dominant in less than one month after it was first detected.
Catégories: Actus Santé

Prevalence and Correlates of Parosmia and Phantosmia among Smell Disorders

Among those many individuals who suffer from a reduced odor sensitivity (hyposmia/anosmia) some individuals also experience disorders that lead to odor distortion, such as parosmia (i.e., distorted odor with a known source), or odor phantoms (i.e., odor sensation without an odor source). We surveyed a large population with at least one olfactory disorder (N = 2031) and found that odor distortions were common (46%), with respondents reporting either parosmia (19%), phantosmia (11%), or both (16%). In comparison to respondents with hyposmia or anosmia, respondents with parosmia were more likely to be female, young, and suffered from post-viral olfactory loss (p < 0.001), while phantosmia occurred most frequently in middle-aged respondents (p < 0.01) and was more likely to be caused by head trauma than parosmia (p < 0.01). A higher prevalence of odor distortion was observed 3 months to a year after their olfactory symptom onset (p < 0.001), which coincides with the timeline of physiological recovery. Additionally, we observed that the frequency and duration of distortions negatively affects quality of life, with parosmia showing a higher range of severity than phantosmia (p < 0.001). Previous research often grouped these distortions together, but our results show that they have distinct patterns of demographics, medical history, and loss in quality of life.
Catégories: Actus Santé

ERAP1, ERAP2, and two copies of HLA-Aw19 alleles increase the risk for Birdshot Chorioretinopathy in HLA-A29 carriers

Purpose: Birdshot Chorioretinopathy (BSCR) is strongly associated with HLA-A29. This study was designed to elucidate the genetic modifiers of BSCR in HLA-A29 carriers. Methods: We sequenced the largest BSCR cohort to date, including 286 cases and 108 HLA-A29 positive controls to perform genome wide common and rare variant associations. We further typed the HLA alleles of cases and 45,386 HLA-A29 controls of European ancestry to identify HLA alleles that associate with BSCR risk. Results: Carrying a second allele that belongs to the HLA-Aw19 broad antigen family (including HLA-A29, A30, A31, and A33) increases the risk for BSCR (OR=4.44, p=2.2e-03). This result was validated by comparing allele frequencies to large HLA-A29-controlled cohorts (n=45,386, OR>2.5, p<1.3e-06). We also confirm that ERAP1 and ERAP2 haplotypes modulate the risk for disease within our HLA-A29 controlled cohort. A meta-analysis with an independent dataset confirmed that ERAP1 and ERAP2 haplotypes modulate the risk for disease at a genome-wide significant level: ERAP1-rs27432 (OR 2.46; 95% CI 1.85-3.26; p=4.07e-10), an eQTL decreasing ERAP1 expression, and ERAP2-rs10044354 (OR 1.95; 95% CI 1.55-2.44; p=6.2e-09), an eQTL increasing ERAP2 expression. Furthermore, ERAP2-rs2248374 that disrupts ERAP2 expression is protective (OR 0.56; 95% CI [0.45-0.70]; p=2.39e-07). BSCR risk is additively increased when combining ERAP1/ERAP2 risk genotypes with two copies of HLA-Aw19 alleles (OR 13.53; 95% CI 3.79-54.77, p=1.17e-05). Conclusions: The genetic factors increasing BSCR risk demonstrate a pattern of increased processing, as well as increased presentation of ERAP2 specific peptides. This suggests a mechanism in which exceeding a peptide presentation threshold activates the immune response in choroids of A29 carriers.
Catégories: Actus Santé

Awareness regarding Anemia in Antenatal women attending tertiary care hospitals in South India

Lack of adequate nutrition during pregnancy is one of the major risk factors for the development of anemia which further leads to a high-risk pregnancy. Anemia in pregnancy accounts for one-fifth of maternal deaths and is a major factor responsible for low birth weight. The aim of the study was to evaluate the awareness about anemia among the antenatal women attending tertiary care hospitals in South India and also to find out the methods adopted by the women to prevent and correct their anemia. It was a cross-sectional type of study conducted on pregnant women who gave consent. . A majority of the pregnant women were aware of the term anemia and the most common source of their knowledge was their treating physician, followed by ASHA/Anganwadi worker and friends/family. Half of the participants in the study were well aware that anemia was a problem related to blood and a majority knew that it is most common in pregnant women. Around half of the study population knew the correct value of minimum Hb level in a pregnant woman and even a lesser percentage of women knew about the consequence of severe anemia during delivery. Most of the pregnant women were including iron-rich foods normally in their diet. A majority of the respondents noticed a health benefit after taking the iron and folic acid tablets. Thus, there is a need to endorse the IFA tablets and educate the women about the anemia in pregnancy so that the health benefits of the free supplementation program of the government percolates down to even the lower strata of the society.
Catégories: Actus Santé

Cerebral hypoperfusion is a late pathological event in the course of Alzheimer's disease

Although several studies have shown decreased cerebral blood flow (CBF) in Alzheimer's disease (AD), the role of hypoperfusion in the disease pathogenesis remains unclear. Combining arterial spin labeling MRI, positron emission tomography, and biomarkers of cerebrospinal fluid, we investigated the associations between CBF and the key mechanisms in AD including amyloid-{beta} (A{beta}) and tau pathology, synaptic dysfunction and axonal degeneration. Further, we applied a disease progression modeling to characterize the temporal sequence of different AD biomarkers. Lower perfusion was observed in the temporo-occipito-parietal regions in the A{beta}-positive cognitively impaired compared to both the A{beta}-positive and A{beta}-negative cognitively unimpaired individuals. In participants along the AD spectrum (those with A{beta} pathology regardless of their cognitive status), CBF was inversely associated with tau and synaptic dysfunction, but not A{beta} in similar cortical regions. Moreover, the disease progression modeling revealed that CBF disruption followed the abnormality of biomarkers of A{beta}, tau and brain atrophy. These findings indicate that tau tangles and synaptic degeneration are more closely connected with CBF changes rather than A{beta} pathology. This supports the notion that hypoperfusion is not an early event associated with the build-up of A{beta} during the preclinical phase of AD.
Catégories: Actus Santé

Investigation on the current situation of stroke patients in northernern Henan Province of China

Objectives: To analyze the basic situations and clinical characteristics of stroke patients in our hospital from May 2018 to April 2021, lay a foundation for the prevention and reasonable treatment of stroke patients in northern Henan Province. Methods: The basic information of 835 stroke patients in our hospital was collected and classified according to age, gender, bad habits, accompanied diseases and drug use before admission to hospital, and severity of the stroke patients were also evaluated according to mRS scoring standard. Results: A total of 835 stroke patients were collected from May 2018 to April 2021 in our hospital. The age range of stroke patients was 28-95 years old, 96.29% stroke patients was above 40 years old; there were 202 stroke patients with smoking history and 225 stroke patients with drinking history; Among the 835 stroke patients, hypertension, cerebral infarction and diabetes mellitus were the main accompanied diseases. Antihypertensive drugs (506 cases), antiplatelet drugs (208 cases), statins (173 cases) and antidiabetic drugs (143 cases) were the main therapeutic drugs in stroke patients before admission in the northern Henan Province; the results of mRS scoring standard showed that among 835 stroke patients, there were 609 cases with milder symptoms, accounting for 82.84% (there were 330 stroke patients with 1 points, 279 stroke patients with 2 points, and 83 stroke patients with 3 points), and 120 cases with severe symptoms, accounting for 14.37% (55 cases with 4 points, 65 cases with 5 points). Conclusion: The age of stroke patients in northern Henan Province was mainly over 40 years old, most of stroke patients were in the early stage of stroke; smoking, drinking, hypertension and diabetes mellitus were main risk factors of stroke. And there was a sex difference between male stroke patients and female stroke patients in stroke risk factors smoking and hypertension. those data may help us for active prevention and rational drug use for stroke in clinic.
Catégories: Actus Santé

EFFECTIVE CONNECTIVITY IN SUBCORTICAL VISUAL STRUCTURES IN DE NOVO PATIENTS WITH PARKINSON DISEASE

Background: PD is associated with non-motor symptoms appearing before the motor symptoms onset. Recent studies report dysfunctions of visual structures at early stages of PD. Objective: This study addresses effective connectivity in the visual network of PD patients. Methods: Using brain functional MRI and Dynamic Causal Modeling analysis, we investigated the connectivity between the superior colliculus, the lateral geniculate nucleus and the primary visual area V1 in 22 de novo untreated PD patients and six months after starting dopaminergic treatment compared to age-matched healthy controls. Results: Our findings indicate that the superior colliculus drives cerebral activity for luminance contrast processing both in healthy controls and untreated PD patients. The same effective connectivity was observed with neuromodulatory differences in terms of neuronal dynamic interactions. The modulation induced by luminance contrast changes of the superior colliculus connectivity (self-connectivity and connectivity to the lateral geniculate nucleus) was inhibited in PD patients (effect of contrast: p = 0.79 and p = 0.77 respectively). The introduction of dopaminergic medication failed to restore the effective connectivity modulation observed in the healthy controls. Interpretation: The deficits in luminance contrast processing in PD seem due to a deficiency in connectivity adjustment from the superior colliculus to the lateral geniculate nucleus and to V1. Administration of a dopaminergic treatment over six months was not able to normalize the observed alterations in inter-regional coupling. These findings highlight the presence of early dysfunctions in primary visual areas, which might be used as early markers of the disease.
Catégories: Actus Santé

Online tests for sexually transmitted infections - Friend or Foe? An analysis of providers in the United Kingdom.

Objectives: Online testing for sexually transmitted infections (STIs) may contribute to overcoming barriers to traditional testing such as stigma and inconvenience. However, regulation of these tests is lacking, and the quality of services is variable, with potential short- and long-term personal, clinical and public health implications. This study aimed to evaluate online tests available in the UK against national standards. Methods: Providers of online STI tests (self-sampling and self-testing) in the UK were identified by an internet search of Google and Amazon (June 2020). Website information on tests and care was collected, and further information requested from providers via an online survey, sent twice (July 2020, April 2021). The information obtained was compared to British Association for Sexual Health and HIV (BASHH) guidelines for diagnostics and standards of STI management. Results: 31 providers were identified: 13 self-test, 18-self-sample, and two laboratories that serviced multiple providers. Seven responded to the online survey. Many conflicts with national guidelines were identified, including: lack of health promotion information, lack of sexual history taking, use of tests licensed for professional use only marketed for self-testing, inappropriate infections tested for, incorrect specimen type used, and lack of advice for post-diagnosis management. Conclusions: Very few online providers met the BASHH national STI management guidelines standards that were assessed, and there is concern that this will also be the case in areas that were not covered by this study. For-profit providers were the least compliant, with concerning implications for patient care and public health. Regulatory change is urgently needed to ensure that online providers are compliant with national guidelines to ensure high-quality patient care, and providers are held to account if non-compliant.
Catégories: Actus Santé

Assessing our capability to predict the presence of respiratory diseases at the age of four using data available at one month of age

Chronic respiratory diseases are often difficult to cure and are likely to originate early in life. Therefore, early identification of such diseases is of interest for early prevention. We explored the potential to predict these almost from birth; using data at 1 month of age, we attempted to predict disease occurrence 4 years later in life. Our data came from the Barwon Infant Study; after cleaning and processing, we had measurements on 41 variables from 401 participants. We considered three respiratory diseases: asthma, wheeze and hay fever. As predictors, we used a variety of information that would be available in a clinical setting. Of particular interest to our investigation was whether lung function measurements (newly available at such an early age) would helpfully improve predictive accuracy. We also investigated whether maternal smoking (previously associated with respiratory illnesses) is a helpful predictor. Our methods included logistic regression as the main model, multiple imputation to deal with missing values, stepwise selection and LASSO to select variables, and cross-validation to assess performance. We measured predictive performance using AUC (area under the receiver operating characteristic curve), sensitivity and specificity. Broadly, we found that the best models had only modest predictive power for each disease. For example, for asthma we achieved an AUC of 0.67, a sensitivity of 68% and a corresponding specificity of 63%. Performance for the other two diseases was similar. We also found that our lung function measurements did not improve predictive performance; somewhat surprisingly, this was also true for maternal smoking. The most useful predictors included, among others, family history of these diseases and variables relating to the size of the infants. Given the modest performance of these models, our findings suggest that very early prediction of respiratory illnesses is still a challenging task.
Catégories: Actus Santé

Simulated Diagnostic Performance of Ultra-Low-Field MRI: Harnessing Open-Access Datasets to Evaluate Novel Devices

The purpose of this study is to demonstrate a method for virtually evaluating novel imaging devices using machine learning and open-access datasets, here applied to a new, ultra-low-field strength (ULF), 64mT, portable MRI device. Paired 3T and 64mT brain images were used to develop and validate a transformation converting standard clinical images to ULF-quality images. Separately, 3T images were aggregated from open-source databases spanning four neuropathologies: low-grade glioma (LGG, N=76), high-grade glioma (HGG, N=259), stroke (N=28), and multiple sclerosis (MS, N=20). The transformation method was then applied to the open-source data to generate simulated ULF images for each pathology. Convolutional neural networks (DenseNet-121) were trained to detect pathology in axial slices from either 3T or simulated 64 mT images, and their relative performance was compared to characterize the potential diagnostic capabilities of ULF imaging. Algorithm performance was measured using area under the receiver operating characteristic curve. Across all cohorts, pathology detection was similar between 3T and simulated 64mT images (LGG: 0.97 vs. 0.98; HGG: 0.96 vs. 0.95; stroke: 0.94 vs. 0.94; MS: 0.90 vs 0.87). Pathology detection was further characterized as a function of lesion size, intensity, and contrast. Simulated images showed decreasing sensitivity for lesions smaller than 4 cm2 (~2.25 cm in diameter). While simulations cannot replace prospective trials during the evaluation of medical devices, they can provide guidance and justification for prospective studies. Simulated data derived from open-source imaging databases may facilitate testing and validation of new imaging devices.
Catégories: Actus Santé

Adulthood asthma as a consequence of childhood adversity: a systematic review of epigenetically affected genes

There is an accumulating data that shows relation between childhood adversity and vulnerability to chronic diseases as well as epigenetic influences that in turn give rise to these diseases. Asthma is one of the chronic diseases that is influenced from genetic regulation of the inflammatory biomolecules and therefore the hypothesis in this research was childhood adversity might have caused epigenetic differentiation in the asthma related genes in the population who had childhood trauma. To test this hypothesis, the literature was systematically reviewed to extract epigenetically modified gene data of the adults who had childhood adversity, and affected genes were further evaluated for their association with asthma. PRISMA guidelines were adopted and PubMed and Google Scholar were included in the searched databases, to evaluate epigenetic modifications in asthma related genes of physically, emotionally or sexually abused children. After retrieving a total of 12,085 articles, 36 of them were included in the study. Several genes and pathways that may contribute to pathogenesis of asthma development, increased inflammation or response to asthma treatment were found epigenetically affected by childhood traumas. Childhood adversity, causing epigenetic changes in DNA, may lead to asthma development or influence the course of the disease and therefore should be taken into account for the prolonged health consequences.
Catégories: Actus Santé

Attempted Suicide and Criminal Justice System in a Sample of Forensic Psychiatric Patients in Malaysia

Criminalization of suicide attempts is an archaic barrier to suicide prevention. Globally, clinical profiles of prosecuted suicide attempters are an under-researched area. This retrospective study aims to describe the clinical profiles of individuals who were charged for attempted suicide and subsequently sent for criminal responsibility and fitness to plead evaluation in a forensic psychiatric unit in Malaysia from January 1, 2008, to December 31, 2019. We identified 22 cases who were mostly adult males (90.9%). Seventy-three percent have a psychiatric disorder. Mood disorders were more prevalent (32%) followed by psychotic disorders and substance use disorders. For most of these individuals, this was the first contact with any form of mental health services and 41% defaulted their treatment before arrest. This sample illustrates a vulnerable group who has been disengaged with mental healthcare. Future research is warranted to further investigate mechanisms that are effective in addressing unmet needs of persons in suicidal crisis as opposed to utilizing the criminal justice pathway.
Catégories: Actus Santé

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