Cost-Effectiveness of Low-Dose Compared to Standard-Dose Alteplase for Acute Ischemic Stroke in China: A Within-Trial Economic Evaluation of the ENCHANTED Study.

INTRODUCTION: The Enhanced Control of Hypertension and Thrombolysis Stroke Study (ENCHANTED) showed that a low-dose alteplase was safe but not clearly non-inferior to standard-dose alteplase in acute ischemic stroke (AIS). Given the significant cost of this medicine, we undertook a cost-effectiveness analysis to determine the probability that low-dose is cost-effective relative to standard-dose alteplase in China. METHODS: For ENCHANTED participants in China with available health cost data, cost-effectiveness and cost-utility analyses were undertaken in which death or disability (modified Rankin scale scores 2-6) at 90 days and quality-adjusted life-years (QALYs) were used as outcome measures, respectively. There was adherence to standard guidelines for health economic evaluations alongside non-inferiority trials and according to a health-care payer's perspective. The equivalence margin for cost and effectiveness was set at USD 691 and -0.025 QALYs, respectively, for the base-case analysis. Probabilistic sensitivity analyses were used to evaluate the probability of low-dose alteplase being non-inferior. RESULTS: While the mean cost of alteplase was lower in the low-dose group (USD 1,569 vs. USD 2,154 in the standard-dose group), the total cost was USD 56 (95% confidence interval [CI]: -1,000-1,113) higher compared to the standard-dose group due to higher hospitalization costs in the low-dose group. There were 462 (95% CI: 415-509) and 410 (95% CI: 363-457) patients with death or disability per 1,000 patients in the low-dose and standard-dose groups, respectively. The low-dose group had marginally lower (0.008, 95% CI: -0.016-0.001) QALYs compared to their standard-dose counterparts. The low-dose group was found to have an 88% probability of being non-inferior based on cost-effectiveness versus the standard-dose group. CONCLUSIONS: This health economic evaluation alongside the ENCHANTED indicates that the use of low-dose alteplase does not save overall healthcare costs nor lead to a gain in QALYs in the management of Chinese patients with AIS compared to the use of standard dose. There is little justification on economic grounds to shift from standard-of-care thrombolysis in AIS.

The relation between plasma miR-126 levels and cerebral collateral circulation in patients with intracranial arterial stenosis.

OBJECTIVE: This study aimed to investigate the correlation between the circulating miR-126 regulation pathway and the cerebral collateral circulation (CCC), and to test whether miR-126 could serve as a potential biomarker for CCC formation in patients with intracranial arterial stenosis or occlusion. MATERIAL AND METHODS: This single-centre cross-sectional study enrolled patients who underwent cerebral angiography with severe stenosis (≥70%) or occlusion in at least one major intracranial artery. Collateral degree was graded according to the ASITN/SIR classification. The patients were divided into a good CCC group (grade 3-4) or a poor CCC group (grade 0-2). We investigated the plasma levels of miR-126, VEGF, Spred-1 and PIK3R2 by using qRT-PCR, ELISA and Western blot methods, respectively. In addition, we assessed the correlations of plasma miR-126 with VEGF, Spred-1, PIK3R2 and ASITN/SIR grade using the Spearman correlation test and investigated its predictive power for CCC status by using the receiver operating characteristic curve. RESULTS: A total of 68 patients were enrolled (44 with good CCC and 24 with poor CCC). Data showed that plasma miR-126 and VEGF were significantly higher in the good CCC group than in the poor CCC group. Plasma Spred-1 and PIK3R2 level were lower in the good CCC group than in the poor CCC group. In addition, miR-126 and VEGF were positively correlated with ASITN/SIR (miR-126: R = 0.595, P < 0.01; VEGF: R = 0.595, P < 0.01), whereas Spred-1 and PIK3R2 were negatively correlated with ASITN/SIR (Spred-1: R = -0.817, P < 0.01; PIK3R2: R = -0.513, P=0.01). However, the area under the curve of miR-126 level for CCC status was only 0.328 (95% CI: 0.158-0.498; p = 0.067). CONCLUSIONS: Plasma miR-126 level may be related to better CCC formation, one of the mechanisms that may be explained by upregulation of VEGF and reduction of Spred-1 and PIK3R2 protein expression. However, miR-126 might not be an independent predictor for CCC, given its low predictive value.

Perfusion computed tomography in patients with stroke thrombolysis.

See Saver (doi:10.1093/awx020) for a scientific commentary on this article.Stroke shortens an individual's disability-free life. We aimed to assess the relative prognostic influence of pre- and post-treatment perfusion computed tomography imaging variables (e.g. ischaemic core and penumbral volumes) compared to standard clinical predictors (such as onset-to-treatment time) on long-term stroke disability in patients undergoing thrombolysis. We used data from a prospectively collected international, multicentre, observational registry of acute ischaemic stroke patients who had perfusion computed tomography and computed tomography angiography before treatment with intravenous alteplase. Baseline perfusion computed tomography and follow-up magnetic resonance imaging were analysed to derive the baseline penumbra volume, baseline ischaemic core volume, and penumbra salvaged from infarction. The primary outcome measure was the effect of imaging and clinical variables on Disability-Adjusted Life Year. Clinical variables were age, sex, National Institutes of Health Stroke Scale score, and onset-to-treatment time. Age, sex, country, and 3-month modified Rankin Scale were extracted from the registry to calculate disability-adjusted life-year due to stroke, such that 1 year of disability-adjusted life-year equates to 1 year of healthy life lost due to stroke. There were 772 patients receiving alteplase therapy. The number of disability-adjusted life-year days lost per 1 ml of baseline ischaemic core volume was 17.5 (95% confidence interval, 13.2-21.9 days, P < 0.001). For every millilitre of penumbra salvaged, 7.2 days of disability-adjusted life-year days were saved (ß = -7.2, 95% confidence interval, -10.4 to -4.1 days, P < 0.001). Each minute of earlier onset-to-treatment time resulted in a saving of 4.4 disability-free days after stroke (1.3-7.5 days, P = 0.006). However, after adjustment for imaging variables, onset-to-treatment time was not significantly associated with savings in disability-adjusted life-year days. Pretreatment perfusion computed tomography can (independently of clinical variables) predict significant gains, or loss, of disability-free life in patients undergoing reperfusion therapy for stroke. The effect of earlier treatment on disability-free life appears explained by salvage of penumbra, particularly when the ischaemic core is not too large.

Validating a Predictive Model of Acute Advanced Imaging Biomarkers in Ischemic Stroke.

BACKGROUND AND PURPOSE: Advanced imaging to identify tissue pathophysiology may provide more accurate prognostication than the clinical measures used currently in stroke. This study aimed to derive and validate a predictive model for functional outcome based on acute clinical and advanced imaging measures. METHODS: A database of prospectively collected sub-4.5 hour patients with ischemic stroke being assessed for thrombolysis from 5 centers who had computed tomographic perfusion and computed tomographic angiography before a treatment decision was assessed. Individual variable cut points were derived from a classification and regression tree analysis. The optimal cut points for each assessment variable were then used in a backward logic regression to predict modified Rankin scale (mRS) score of 0 to 1 and 5 to 6. The variables remaining in the models were then assessed using a receiver operating characteristic curve analysis. RESULTS: Overall, 1519 patients were included in the study, 635 in the derivation cohort and 884 in the validation cohort. The model was highly accurate at predicting mRS score of 0 to 1 in all patients considered for thrombolysis therapy (area under the curve [AUC] 0.91), those who were treated (AUC 0.88) and those with recanalization (AUC 0.89). Next, the model was highly accurate at predicting mRS score of 5 to 6 in all patients considered for thrombolysis therapy (AUC 0.91), those who were treated (0.89) and those with recanalization (AUC 0.91). The odds ratio of thrombolysed patients who met the model criteria achieving mRS score of 0 to 1 was 17.89 (4.59-36.35, P<0.001) and for mRS score of 5 to 6 was 8.23 (2.57-26.97, P<0.001). CONCLUSIONS: This study has derived and validated a highly accurate model at predicting patient outcome after ischemic stroke.

[Understanding the reasons behind the low utilization of thrombolysis in hyperacute ischemic stroke].

OBJECTIVE: The study aimed to analyze the influencing factors of thrombolysis therapy in acute ischemic stroke patients with onset time less than 4.5 hours. METHODS: We consecutively prospectively screened acute ischemic stroke patients with onset time less than 4.5 hours from emergency department, outpatients and inpatients of neurology department, and image center in our hospital over a 31-month time period (April 2012-November 2014). The rate of thrombolysis and the reasons for not receiving thrombolysis were analyzed. RESULTS: A total of 538 patients who met the inclusion criteria were included (68.2% males, mean age 67±13 years old). Only 104 (19.3%) patients received thrombolysis. The main reasons for the patients not receiving thrombolysis included minor symptoms (172 cases, 39.6%), rapidly improving symptoms and high possibility of transient ischemic attack (TIA) (59 cases, 13.6%), patients or families refusing thrombolysis (44, 10.1%), in-hospital delay (38, 8.8%), elderly people with age over than 80 years old (38, 8.8%). CONCLUSIONS: The thrombolysis rate within time window of acute ischemic stroke is remarkably higher than that of several years ago in China. The main reasons for not receiving thrombolysis are minor and rapidly improving symptoms, patients or families' refusal, in-hospital delay, elderly people with age over than 80 years old.

Selective refinement and selection of near-native models in protein structure prediction.

In recent years in silico protein structure prediction reached a level where fully automated servers can generate large pools of near-native structures. However, the identification and further refinement of the best structures from the pool of models remain problematic. To address these issues, we have developed (i) a target-specific selective refinement (SR) protocol; and (ii) molecular dynamics (MD) simulation based ranking (SMDR) method. In SR the all-atom refinement of structures is accomplished via the Rosetta Relax protocol, subject to specific constraints determined by the size and complexity of the target. The best-refined models are selected with SMDR by testing their relative stability against gradual heating through all-atom MD simulations. Through extensive testing we have found that Mufold-MD, our fully automated protein structure prediction server updated with the SR and SMDR modules consistently outperformed its previous versions.

A New Hidden Markov Model for Protein Quality Assessment Using Compatibility Between Protein Sequence and Structure.

Protein structure Quality Assessment (QA) is an essential component in protein structure prediction and analysis. The relationship between protein sequence and structure often serves as a basis for protein structure QA. In this work, we developed a new Hidden Markov Model (HMM) to assess the compatibility of protein sequence and structure for capturing their complex relationship. More specifically, the emission of the HMM consists of protein local structures in angular space, secondary structures, and sequence profiles. This model has two capabilities: (1) encoding local structure of each position by jointly considering sequence and structure information, and (2) assigning a global score to estimate the overall quality of a predicted structure, as well as local scores to assess the quality of specific regions of a structure, which provides useful guidance for targeted structure refinement. We compared the HMM model to state-of-art single structure quality assessment methods OPUSCA, DFIRE, GOAP, and RW in protein structure selection. Computational results showed our new score HMM.Z can achieve better overall selection performance on the benchmark datasets.

MUFOLD-DB: a processed protein structure database for protein structure prediction and analysis.

BACKGROUND: Protein structure data in Protein Data Bank (PDB) are widely used in studies of protein function and evolution and in protein structure prediction. However, there are two main barriers in large-scale usage of PDB data: 1) PDB data are highly redundant in terms of sequence and structure similarity; and 2) many PDB files have issues due to inconsistency of data and standards as well as missing residues, so that automated retrieval and analysis are often difficult. DESCRIPTION: To address these issues, we have created MUFOLD-DB http://mufold.org/mufolddb.php, a web-based database, to collect and process the weekly PDB files thereby providing users with non-redundant, cleaned and partially-predicted structure data. For each of the non-redundant sequences, we annotate the SCOP domain classification and predict structures of missing regions by loop modelling. In addition, evolutional information, secondary structure, disorder region, and processed three-dimensional structure are computed and visualized to help users better understand the protein. CONCLUSIONS: MUFOLD-DB integrates processed PDB sequence and structure data and multiple computational results, provides a friendly interface for users to retrieve, browse and download these data, and offers several useful functionalities to facilitate users' data operation.

xMDFF: molecular dynamics flexible fitting of low-resolution X-ray structures.

X-ray crystallography remains the most dominant method for solving atomic structures. However, for relatively large systems, the availability of only medium-to-low-resolution diffraction data often limits the determination of all-atom details. A new molecular dynamics flexible fitting (MDFF)-based approach, xMDFF, for determining structures from such low-resolution crystallographic data is reported. xMDFF employs a real-space refinement scheme that flexibly fits atomic models into an iteratively updating electron-density map. It addresses significant large-scale deformations of the initial model to fit the low-resolution density, as tested with synthetic low-resolution maps of D-ribose-binding protein. xMDFF has been successfully applied to re-refine six low-resolution protein structures of varying sizes that had already been submitted to the Protein Data Bank. Finally, via systematic refinement of a series of data from 3.6 to 7 Šresolution, xMDFF refinements together with electrophysiology experiments were used to validate the first all-atom structure of the voltage-sensing protein Ci-VSP.

Exploring a Potential Causal Link Between Dietary Intake and Chronic Obstructive Pulmonary Disease: A Two-Sample Mendelian Randomization Study.

Background: Chronic Obstructive Pulmonary Disease (COPD), the most prevalent chronic respiratory condition, significantly impairs patients' quality of life. The pivotal element in disease management lies in prevention, underscoring the paramount importance of employing a scientific approach to investigate early prevention strategies for COPD. Methods: This study delved into the causal link between 28 dietary intakes and COPD employing two-sample Mendelian randomization. We primarily utilized the Inverse Variance Weighted (IVW) method as the main outcome, complemented by Weighted Median (WM), MR-Egger method, along with several sensitivity analysis techniques, all accompanied by visual representations. Results: We identified higher odds of COPD following exposure to green beans (OR=1.381, 95% CI=1.119-1.704, P=0.003) and pork intake (OR=2.657, 95% CI=1.203-5.868, P=0.016). In contrast, the odds of developing COPD were lower following exposure to dried fruit (OR=0.481, 95% CI=0.283-0.819, P=0.007), cereal (OR=0.560, 95% CI=0.356-0.880, P=0.012), and whole egg consumption (OR=0.700, 95% CI=0.504-0.972, P=0.033). Conclusion: In light of our study's findings, we anticipate that strategically modifying dietary choices may offer an avenue for early COPD prevention in the future.

PCSK9 Inhibitor with Statin Therapy for Intracranial Artery Stenosis （PISTIAS): Rationale and design of a multicenter randomized controlled trial.

RATIONALE: Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors enable an additional 54% to 75% reduction in low-density lipoprotein cholesterol (LDL-C) in statin-treated patients, demonstrating plaque regression in coronary artery disease. However, the impact of achieving an extremely low level of LDL-C with PCSK9 inhibitors (e.g., evolocumabEvolocumab) on symptomatic intracranial atherosclerosis remains unexplored. AIM AND HYPOTHESIS: To determine if combining evolocumabEvolocumab and statins achieves a more significant symptomatic intracranial plaque reduction than statin therapy solely. SAMPLE SIZE ESTIMATES: With a sample size of 1000 subjects, a two-sided of 0.05, and 20% lost to follow-up, the study will have 83.3% power to detect the difference in intracranial plaque burden. METHODS AND DESIGN: This is an investigator-initiated multicenter, randomized, open-label, outcome assessor-blinded trial, evaluating the impact of evolocumabEvolocumab on intracranial plaque burden assessed by high-resolution magnetic resonance imaging at baseline in patients undergoing a clinically indicated acute stroke or transient ischemic attack due to intracranial artery stenosis, and after 24 weeks of treatment. Subjects (n = 1000) will be randomized 1:1 into two groups to receive either evolocumabEvolocumab 140 mg every two weeks with statin therapy or solely statin therapy. STUDY OUTCOMES: The primary endpoint is the change in plaque burden assessed by high-resolution magnetic resonance imaging, performed at baseline and the end of the 24-week treatment period. DISCUSSION: This trial will explore whether more significant plaque regression is achievable with treatment after combining statins and PCSK9 inhibitors, providing information about important efficacy, mechanism, and safety data.Trial registration number: ChiCTR2300068868; https://www.chictr.org.cn/.

Fast algorithm for population-based protein structural model analysis.

De novo protein structure prediction often generates a large population of candidates (models), and then selects near-native models through clustering. Existing structural model clustering methods are time consuming due to pairwise distance calculation between models. In this paper, we present a novel method for fast model clustering without losing the clustering accuracy. Instead of the commonly used pairwise root mean square deviation and TM-score values, we propose two new distance measures, Dscore1 and Dscore2, based on the comparison of the protein distance matrices for describing the difference and the similarity among models, respectively. The analysis indicates that both the correlation between Dscore1 and root mean square deviation and the correlation between Dscore2 and TM-score are high. Compared to the existing methods with calculation time quadratic to the number of models, our Dscore1-based clustering achieves a linearly time complexity while obtaining almost the same accuracy for near-native model selection. By using Dscore2 to select representatives of clusters, we can further improve the quality of the representatives with little increase in computing time. In addition, for large size (~500 k) models, we can give a fast data visualization based on the Dscore distribution in seconds to minutes. Our method has been implemented in a package named MUFOLD-CL, available at http://mufold.org/clustering.php.

A versatile mass spectrometry-based method to both identify kinase client-relationships and characterize signaling network topology.

While more than a thousand protein kinases (PK) have been identified in the Arabidopsis thaliana genome, relatively little progress has been made toward identifying their individual client proteins. Herein we describe the use of a mass spectrometry-based in vitro phosphorylation strategy, termed Kinase Client assay (KiC assay), to study a targeted-aspect of signaling. A synthetic peptide library comprising 377 in vivo phosphorylation sequences from developing seed was screened using 71 recombinant A. thaliana PK. Among the initial results, we identified 23 proteins as putative clients of 17 PK. In one instance protein phosphatase inhibitor-2 (AtPPI-2) was phosphorylated at multiple-sites by three distinct PK, casein kinase1-like 10, AME3, and a Ser PK-like protein. To confirm this result, full-length recombinant AtPPI-2 was reconstituted with each of these PK. The results confirmed multiple distinct phosphorylation sites within this protein. Biochemical analyses indicate that AtPPI-2 inhibits type 1 protein phosphatase (TOPP) activity, and that the phosphorylated forms of AtPPI-2 are more potent inhibitors. Structural modeling revealed that phosphorylation of AtPPI-2 induces conformational changes that modulate TOPP binding.

Incidence and risks of subarachnoid hemorrhage in China.

BACKGROUND AND PURPOSE: To determine incidence and risks of subarachnoid hemorrhage in China. METHODS: A prospective, population-based, 1:2 matched case-control study in Baotou, Inner Mongolia (≈2 million population) in 2009-2011. Multiple variable models used to determine relative risk and population-attributable risks for exposures. RESULTS: For a total of 226 patients (mean age, 59 years; 65% women; 434 controls), crude annual incidence (per 100 000) of subarachnoid hemorrhage was 6.2 (95% confidence intervals, 5.4-7.0); 4.3 (3.3-5.2) for men and 8.2 (6.9-9.6) for women. Compared with nonsmokers, adjusted relative risk of subarachnoid hemorrhage in current smokers was 2.31 (95% confidence interval, 1.31-4.09) but was 4.00 (1.62-9.89) in women. Population-attributable risk for smoking, hypertension, and low income were 18%, 36% and 59%, respectively. CONCLUSIONS: The incidence of subarachnoid hemorrhage in China is slightly lower than in Western countries and is related to smoking, hypertension, and poor socioeconomic status.

pParse: a method for accurate determination of monoisotopic peaks in high-resolution mass spectra.

Determining the monoisotopic peak of a precursor is a first step in interpreting mass spectra, which is basic but non-trivial. The reason is that in the isolation window of a precursor, other peaks interfere with the determination of the monoisotopic peak, leading to wrong mass-to-charge ratio or charge state. Here we propose a method, named pParse, to export the most probable monoisotopic peaks for precursors, including co-eluted precursors. We use the relationship between the position of the highest peak and the mass of the first peak to detect candidate clusters. Then, we extract three features to sort the candidate clusters: (i) the sum of the intensity, (ii) the similarity of the experimental and the theoretical isotopic distribution, and (iii) the similarity of elution profiles. We showed that the recall of pParse, MaxQuant, and BioWorks was 98-98.8%, 0.5-17%, and 1.8-36.5% at the same precision, respectively. About 50% of tandem mass spectra are triggered by multiple precursors which are difficult to identify. Then we design a new scoring function to identify the co-eluted precursors. About 26% of all identified peptides were exclusively from co-eluted peptides. Therefore, accurately determining monoisotopic peaks, including co-eluted precursors, can greatly increase peptide identification rate.

A multilayer evaluation approach for protein structure prediction and model quality assessment.

Protein tertiary structures are essential for studying functions of proteins at molecular level. An indispensable approach for protein structure solution is computational prediction. Most protein structure prediction methods generate candidate models first and select the best candidates by model quality assessment (QA). In many cases, good models can be produced, but the QA tools fail to select the best ones from the candidate model pool. Because of incomplete understanding of protein folding, each QA method only reflects partial facets of a structure model and thus has limited discerning power with no one consistently outperforming others. In this article, we developed a set of new QA methods, including two QA methods for evaluating target/template alignments, a molecular dynamics (MD)-based QA method, and three consensus QA methods with selected references to reveal new facets of protein structures complementary to the existing methods. Moreover, the underlying relationship among different QA methods were analyzed and then integrated into a multilayer evaluation approach to guide the model generation and model selection in prediction. All methods are integrated and implemented into an innovative and improved prediction system hereafter referred to as MUFOLD. In CASP8 and CASP9, MUFOLD has demonstrated the proof of the principles in terms of both QA discerning power and structure prediction accuracy.

MUFOLD: A new solution for protein 3D structure prediction.

There have been steady improvements in protein structure prediction during the past 2 decades. However, current methods are still far from consistently predicting structural models accurately with computing power accessible to common users. Toward achieving more accurate and efficient structure prediction, we developed a number of novel methods and integrated them into a software package, MUFOLD. First, a systematic protocol was developed to identify useful templates and fragments from Protein Data Bank for a given target protein. Then, an efficient process was applied for iterative coarse-grain model generation and evaluation at the Calpha or backbone level. In this process, we construct models using interresidue spatial restraints derived from alignments by multidimensional scaling, evaluate and select models through clustering and static scoring functions, and iteratively improve the selected models by integrating spatial restraints and previous models. Finally, the full-atom models were evaluated using molecular dynamics simulations based on structural changes under simulated heating. We have continuously improved the performance of MUFOLD by using a benchmark of 200 proteins from the Astral database, where no template with >25% sequence identity to any target protein is included. The average root-mean-square deviation of the best models from the native structures is 4.28 A, which shows significant and systematic improvement over our previous methods. The computing time of MUFOLD is much shorter than many other tools, such as Rosetta. MUFOLD demonstrated some success in the 2008 community-wide experiment for protein structure prediction CASP8.

Exome sequencing study revealed novel susceptibility loci in subarachnoid hemorrhage (SAH).

AIM: To expand our current understanding of the genetic basis of subarachnoid hemorrhage (SAH), and reveal the susceptibility genes in SAH risk. METHODS: We conducted whole-exome sequencing (WES) in a cohort of 196 individuals, including 94 SAH patients and 94 controls, as well as 8 samples that belong to two pedigrees. Systematically examination for rare variations (through direct genotyping) and common variations (through genotyping and imputation) for SAHs were performed in this study. RESULTS: A total of 16,029 single-nucleotide polymorphisms (SNPs) and 108,999 short indels were detected in all samples, and among them, 30 SNPs distributed on 17 genes presented a strong association signal with SAH. Two novel pathogenic gene variants were identified as associated risk loci, including mutation in TPO and PALD1. The statistical analysis for rare, damaging variations in SAHs identified several susceptibility genes which were involved in degradation of the extracellular matrix and transcription factor signal pathways. And 25 putative pathogenic genes for SAH were also identified basic on functional interaction network analysis with the published SAH-associated genes. Additionally, pedigree analysis revealed autosomal dominant inheritance of pathogenic genes. CONCLUSION: Systematical analysis revealed a key role for rare variations in SAH risk and discovered SNPs in new complex loci. Our study expanded the list of candidate genes associated with SAH risk, and will facilitate the investigation of disease-related mechanisms and potential clinical therapies.

Role of health insurance in averting economic hardship in families after acute stroke in China.

BACKGROUND AND PURPOSE: Stroke is a major health burden in China, but there are limited data on its economic effects on households. We aimed to examine the economic impact of stroke and to assess the influence of health insurance. METHODS: In a nationwide, prospective, 62-hospital registry study of acute stroke in China, we recorded information on patient demographics, clinical features, socioeconomic factors, management, and costs of medical care. Information on out-of-pocket health expenses was obtained in surviving patients at 3- and 12-month follow-up. Catastrophic healthcare payments, defined as >or=30% of total household annual income, were estimated from reported household annual income. RESULTS: Among 4739 3-month survivors of stroke with outcome data, average hospital and medication costs were 16,525 Chinese Yuan Renminbi (US $2361) and out-of-pocket costs were 14,478 Chinese Yuan Renminbi (US $2068). Overall, 3384 (71%) patients had experienced catastrophic out-of-pocket expenditure. Workers without health insurance were 7 times (OR, 6.9; 95% CI, 4.6 to 10.3) more likely to experience catastrophic payments than workers with insurance. Health insurance also protected against catastrophic payments in patients who were either retired or not working (no insurance: OR, 4.7; 95% CI, 3.1 to 7.2; OR, 1.82; 95% CI, 1.3 to 2.6, respectively). CONCLUSIONS: Because healthcare costs are high relative to income in China, families face considerable economic hardship after stroke. Health insurance protects families against catastrophic healthcare payments, thus highlighting the need to accelerate the ongoing process of building a comprehensive healthcare system in both urban and rural settings in China.

Isotope pattern vector based tandem mass spectral data calibration for improved peptide and protein identification.

Tandem mass spectra contain noisy peaks which make peak picking for peptide identification difficult. Moreover, all spectral peaks can be shifted due to systematic measurement errors. In this paper, a novel use of an isotope pattern vector (IPV) is proposed for denoising and systematic measurement error prediction. By matching the experimental IPVs with the theoretical IPVs of candidate fragment ions, true ionic peaks can be identified. Furthermore, these identified experimental IPVs and their corresponding theoretical IPVs are used in an optimization process to predict the systematic measurement error associated with the target spectrum. In return, the subsequent spectral data calibration based on the predicted systematic measurement error enhances the data quality. We show that such an integrated denoising and calibration process leads to significantly improved peptide and protein identification. Different from the commonly employed chemical calibration methods, our IPV-based method is a purely computational method for individual spectra analysis and globally optimizes the use of spectral data.