21 research outputs found

    Variation of cataract surgery costs in four different graded providers of China

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    <p>Abstract</p> <p>Background</p> <p>China has the largest population of cataract patients in the world. However, the cataract surgery rate per million remains low in China. We carried out a survey on costs of cataract surgery from four different graded providers in China and analyzed differences in cost among these clinics.</p> <p>Methods</p> <p>1,189 patients were recruited for the study in four eye clinics, located in two provinces, Guangdong province in southern China and Hubei province in central China. The average cost of each cataract surgery episode was calculated including cost of intraocular lens, cost of drugs and facility cost. We also collected information on reimbursement and disposable annual income of local residents.</p> <p>Results</p> <p>Mean total cost per cataract intervention of four different providers varied considerably, ranging from US1,293inUnionHospitaltoUS 1,293 in Union Hospital to US 536 in Jingshan County Hospital. In all providers, except for Jingshan County Hospital, the cost exceeded annual disposable income of local rural residents. As to the proportion of patients with reimbursement, the figure for Union Hospital was only 36%, while for other three clinics it was more than 60%. There was a significant difference between mean reimbursement ratios, with the highest ratio in Zhongshan Ophthalmic Center being 71%.</p> <p>Conclusions</p> <p>Significant differences in costs of cataract surgery were found among the 4 different graded providers. A part of the cost was borne by patients. Proportion of patients with reimbursement and mean reimbursement ratios were higher in economically developed regions than in economically developing regions. Much more financial support should be directed into the rural New Cooperative Medical Scheme to raise the reimbursement ratio in rural China.</p

    Integrative analysis identifies an immune-relevant epigenetic signature for prognostication of non-G-CIMP glioblastomas

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    National audienceThe clinical and molecular implications of DNA methylation alterations remain unclear among the majority of glioblastomas (GBMs) without glioma-CpGs island methylator phenotype (G-CIMP); integrative multi-level molecular profiling may provide useful information. Independent cohorts of non-G-CIMP GBMs or IDH wild type (wt) lower-grade gliomas (LGGs) from local and public databases with DNA methylation and gene expression microarray data were included for discovery and validation of a multimarker signature, combined using a RISK score model. Bioinformatic and in vitro functional analyses were employed for biological validation. Using a strict multistep selection approach, we identified eight CpGs, each of which was significantly correlated with overall survival (OS) of non-G-CIMP GBMs, independent of age, the O-6-methylguanine-DNA methyltransferase (MGMT) methylation status, treatments and other identified CpGs. An epigenetic RISK signature of the 8 CpGs was developed and validated to robustly and independently prognosticate prognosis in different cohorts of not only non-G-GIMP GBMs, but also IDHwt LGGs. It also showed good discriminating value in stratified cohorts by current clinical and molecular factors. Bioinformatic analysis revealed consistent correlation of the epigenetic signature to distinct immune-relevant transcriptional profiles of GBM bulks. Functional experiments showed that S100A2 appeared to be epigenetically regulated by one identified CpG and was associated with GBM cell proliferation, apoptosis, invasion, migration and immunosuppression. The prognostic 8-CpGs RISK score signature may be of promising value for refining current glioma risk classification, and its potential links to distinct immune phenotypes make it a promising biomarker candidate for predicting response to anti-glioma immunotherapy

    Spatial distribution of the terrain feature points under different thresholds.

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    <p>The basic DEM image is original didn’t generalization and the dots in orange are the terrain feature points.</p

    Overlapped contours extracted from the reconstructed DEMs.

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    <p>The thin lines are the contours that are converted from the actual 1:50000 DEM, whereas the thick lines are converted from the 1:50000 DEM and generalized from the 1:10000 DEM through different methods. And the black arrows pointing to the regions indicate the examples of effectiveness of overlaps using difference algorithms.</p
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