Evaluation of a pilot cooperative medical scheme in rural China: impact on gender patterns of health care utilization and prescription practices

<p>Abstract</p> <p>Background</p> <p>In 2003 the Chinese government introduced voluntary cooperative medical schemes (CMS), soon to be in place throughout rural China. Families who chose to enroll do so as a single unit and nothing is known about any differential effect of these new schemes on family members. This study evaluates the impact of one pilot CMS in Anhui Province on health care use by girls aged less than 5 years and women 65 years or older, and on the pattern and cost of prescriptions.</p> <p>Methods</p> <p>Health care records were extracted covering a 10 year period, before, during and after the pilot CMS in 4 townships, one with the intervention and 3 comparison townships without. The impact of the intervention on the age and gender distribution of patients presenting for health care and on the prescription of certain drugs was assessed by logistic regression. The cost of prescriptions before, during and after the intervention period was also assessed.</p> <p>Results</p> <p>203,058 registration and 643,588 prescription records were identified. During the intervention there was a reduced likelihood overall that a patient was female (OR = 0.92: 95%CI 0.87 - 0.97) at the intervention site. Girls aged < 5 years had an increased likelihood of health care (OR = 1.41: 95%CI 1.23 - 1.59) during the CMS, but women ≥ 65 years were relatively disadvantaged (OR = 0.84: 95%CI 0.75 - 0.95). The use of antibiotics and systemic steroids increased disproportionately at the intervention site for patients ≥ 5 years. Prescription costs at the township hospital also increased at the intervention site, particularly for older men.</p> <p>Conclusions</p> <p>This evaluation suggests that all family members did not benefit equally from the pilot CMS and that women ≥ 65 years may be disadvantaged by the newly available reimbursements of health care costs through the CMS. It points to the need, in future evaluations, to use individuals rather than families as the unit of analysis, in order to determine whether such health care inequalities are wide-spread and persistent or are reduced in the longer term. The results also support earlier concerns about the influence of new funding resources on prescription practices and the need for regulation of for-profit prescribing.</p

Lipidomic Evaluation of Feline Neurologic Disease after AAV Gene Therapy

GM1 gangliosidosis is a fatal lysosomal disorder, for which there is no effective treatment. Adeno-associated virus (AAV) gene therapy in GM1 cats has resulted in a greater than 6-fold increase in lifespan, with many cats remaining alive at \u3e 5.7 years of age, with minimal clinical signs. Glycolipids are the principal storage product in GM1 gangliosidosis whose pathogenic mechanism is not completely understood. Targeted lipidomics analysis was performed to better define disease mechanisms and identify markers of disease progression for upcoming clinical trials in humans. 36 sphingolipids and subspecies associated with ganglioside biosynthesis were tested in the cerebrospinal fluid of untreated GM1 cats at a humane endpoint ( approximately 8 months), AAV-treated GM1 cats ( approximately 5 years old), and normal adult controls. In untreated GM1 cats, significant alterations were noted in 16 sphingolipid species, including gangliosides (GM1 and GM3), lactosylceramides, ceramides, sphingomyelins, monohexosylceramides, and sulfatides. Variable degrees of correction in many lipid metabolites reflected the efficacy of AAV gene therapy. Sphingolipid levels were highly predictive of neurologic disease progression, with 11 metabolites having a coefficient of determination (R(2)) \u3e 0.75. Also, a specific detergent additive significantly increased the recovery of certain lipid species in cerebrospinal fluid samples. This report demonstrates the methodology and utility of targeted lipidomics to examine the pathophysiology of lipid storage disorders

Predicting polycystic ovary syndrome with machine learning algorithms from electronic health records

INTRODUCTION: Predictive models have been used to aid early diagnosis of PCOS, though existing models are based on small sample sizes and limited to fertility clinic populations. We built a predictive model using machine learning algorithms based on an outpatient population at risk for PCOS to predict risk and facilitate earlier diagnosis, particularly among those who meet diagnostic criteria but have not received a diagnosis. METHODS: This is a retrospective cohort study from a SafetyNet hospital's electronic health records (EHR) from 2003-2016. The study population included 30,601 women aged 18-45 years without concurrent endocrinopathy who had any visit to Boston Medical Center for primary care, obstetrics and gynecology, endocrinology, family medicine, or general internal medicine. Four prediction outcomes were assessed for PCOS. The first outcome was PCOS ICD-9 diagnosis with additional model outcomes of algorithm-defined PCOS. The latter was based on Rotterdam criteria and merging laboratory values, radiographic imaging, and ICD data from the EHR to define irregular menstruation, hyperandrogenism, and polycystic ovarian morphology on ultrasound. RESULTS: We developed predictive models using four machine learning methods: logistic regression, supported vector machine, gradient boosted trees, and random forests. Hormone values (follicle-stimulating hormone, luteinizing hormone, estradiol, and sex hormone binding globulin) were combined to create a multilayer perceptron score using a neural network classifier. Prediction of PCOS prior to clinical diagnosis in an out-of-sample test set of patients achieved an average AUC of 85%, 81%, 80%, and 82%, respectively in Models I, II, III and IV. Significant positive predictors of PCOS diagnosis across models included hormone levels and obesity; negative predictors included gravidity and positive bHCG. CONCLUSION: Machine learning algorithms were used to predict PCOS based on a large at-risk population. This approach may guide early detection of PCOS within EHR-interfaced populations to facilitate counseling and interventions that may reduce long-term health consequences. Our model illustrates the potential benefits of an artificial intelligence-enabled provider assistance tool that can be integrated into the EHR to reduce delays in diagnosis. However, model validation in other hospital-based populations is necessary.R01 GM135930 - NIGMS NIH HHS; 000000000000000000000000000000000000000000000000000007726917 - Lawrence Berkeley National Laboratory; CCF-2200052 - National Science Foundation; IIS-1914792 - National Science FoundationAccepted manuscrip

Murine Typhus and Leptospirosis as Causes of Acute Undifferentiated Fever, Indonesia

To investigate rickettsioses and leptospirosis among urban residents of Semarang, Indonesia, we tested the blood of 137 patients with fever. Evidence of Rickettsia typhi, the agent of murine typhus, was found in 9 patients. Another 9 patients showed inconclusive serologic results. Thirteen patients received a diagnosis of leptospirosis. No dual infections were detected

Genetic, environmental and stochastic factors in monozygotic twin discordance with a focus on epigenetic differences

PMCID: PMC3566971This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Bortezomib plus melphalan and prednisone compared with melphalan and prednisone in previously untreated multiple myeloma: updated follow-up and impact of subsequent therapy in the phase III VISTA trial

[EN]The purpose of this study was to confirm overall survival (OS) and other clinical benefits with bortezomib, melphalan, and prednisone (VMP) versus melphalan and prednisone (MP) in the phase III VISTA (Velcade as Initial Standard Therapy in Multiple Myeloma) trial after prolonged follow-up, and evaluate the impact of subsequent therapies. Previously untreated symptomatic patients with myeloma ineligible for high-dose therapy received up to nine 6-week cycles of VMP (n = 344) or MP (n = 338). With a median follow-up of 36.7 months, there was a 35% reduced risk of death with VMP versus MP (hazard ratio, 0.653; P < .001); median OS was not reached with VMP versus 43 months with MP; 3-year OS rates were 68.5% versus 54.0%. Response rates to subsequent thalidomide- (41% v 53%) and lenalidomide-based therapies (59% v 52%) appeared similar after VMP or MP; response rates to subsequent bortezomib-based therapy were 47% versus 59%. Among patients treated with VMP (n = 178) and MP (n = 233), median survival from start of subsequent therapy was 30.2 and 21.9 months, respectively, and there was no difference in survival from salvage among patients who received subsequent bortezomib, thalidomide, or lenalidomide. Rates of adverse events were higher with VMP versus MP during cycles 1 to 4, but similar during cycles 5 to 9. With VMP, 79% of peripheral neuropathy events improved within a median of 1.9 months; 60% completely resolved within a median of 5.7 months. VMP significantly prolongs OS versus MP after lengthy follow-up and extensive subsequent antimyeloma therapy. First-line bortezomib use does not induce more resistant relapse. VMP used upfront appears more beneficial than first treating with conventional agents and saving bortezomib- and other novel agent-based treatment until relapse

QUANTITATIVE VS. CONVENTIONAL PCR FOR DETECTION OF HUMAN ADENOVIRUSES IN WATER AND SEDIMENT SAMPLES

SUMMARY Human Adenoviruses (HAdV) are notably resistant in the environment. These agents may serve as effective indicators of fecal contamination, and may act as causative agents of a number of different diseases in human beings. Conventional polymerase chain reaction (PCR) and, more recently, quantitative PCR (qPCR) are widely used for detection of viral agents in environmental matrices. In the present study PCR and SYBR(r)Green qPCR assays were compared for detection of HAdV in water (55) and sediments (20) samples of spring and artesian wells, ponds and streams, collected from dairy farms. By the quantitative methodology HAdV were detected in 87.3% of the water samples and 80% of the sediments, while by the conventional PCR 47.3% and 35% were detected in water samples and sediments, respectively

Metabolic alterations during the growth of tumour spheroids

Solid tumours undergo considerable alterations in their metabolism of nutrients in order to generate sufficient energy and biomass for sustained growth and proliferation. During growth, the tumour microenvironment exerts a number of influences (e.g. hypoxia and acidity) that affect cellular biology and the flux or utilisation of fuels including glucose. The tumour spheroid model was used to characterise the utilisation of glucose and describe alterations to the activity and expression of key glycolytic enzymes during the tissue growth curve. Glucose was avidly consumed and associated with the production of lactate and an acidified medium, confirming the reliance on glycolytic pathways and a diminution of oxidative phosphorylation. The expression levels and activities of hexokinase, phosphofructokinase-1, pyruvate kinase and lactate dehydrogenase in the glycolytic pathway were measured to assess glycolytic capacity. Similar measurements were made for glucose-6-phosphate dehydrogenase, the entry point and regulatory step of the pentose-phosphate pathway (PPP) and for cytosolic malate dehydrogenase, a key link to TCA cycle intermediates. The parameters for these key enzymes were shown to undergo considerable variation during the growth curve of tumour spheroids. In addition, they revealed that the dynamic alterations were influenced by both transcriptional and posttranslational mechanisms