ASTRAL-R score predicts non-recanalisation after intravenous thrombolysis in acute ischaemic stroke.

Intravenous thrombolysis (IVT) as treatment in acute ischaemic strokes may be insufficient to achieve recanalisation in certain patients. Predicting probability of non-recanalisation after IVT may have the potential to influence patient selection to more aggressive management strategies. We aimed at deriving and internally validating a predictive score for post-thrombolytic non-recanalisation, using clinical and radiological variables. In thrombolysis registries from four Swiss academic stroke centres (Lausanne, Bern, Basel and Geneva), patients were selected with large arterial occlusion on acute imaging and with repeated arterial assessment at 24 hours. Based on a logistic regression analysis, an integer-based score for each covariate of the fitted multivariate model was generated. Performance of integer-based predictive model was assessed by bootstrapping available data and cross validation (delete-d method). In 599 thrombolysed strokes, five variables were identified as independent predictors of absence of recanalisation: Acute glucose > 7 mmol/l (A), significant extracranial vessel STenosis (ST), decreased Range of visual fields (R), large Arterial occlusion (A) and decreased Level of consciousness (L). All variables were weighted 1, except for (L) which obtained 2 points based on β-coefficients on the logistic scale. ASTRAL-R scores 0, 3 and 6 corresponded to non-recanalisation probabilities of 18, 44 and 74 % respectively. Predictive ability showed AUC of 0.66 (95 %CI, 0.61-0.70) when using bootstrap and 0.66 (0.63-0.68) when using delete-d cross validation. In conclusion, the 5-item ASTRAL-R score moderately predicts non-recanalisation at 24 hours in thrombolysed ischaemic strokes. If its performance can be confirmed by external validation and its clinical usefulness can be proven, the score may influence patient selection for more aggressive revascularisation strategies in routine clinical practice.

Local Salmonella immunostimulation recruits vaccine-specific CD8 T cells and increases regression of bladder tumor.

NlmCategory="UNASSIGNED">The efficacy of antitumoral responses can be increased using combinatorial vaccine strategies. We recently showed that vaccination could be optimized by local administration of diverse molecular or bacterial agents to target and augment antitumoral CD8 T cells in the genital mucosa (GM) and increase regression of cervical cancer in an animal model. Non muscle-invasive bladder cancer is another disease that is easily amenable to local therapies. In contrast to data obtained in the GM, in this study we show that intravesical (IVES) instillation of synthetic toll-like receptor (TLR) agonists only modestly induced recruitment of CD8 T cells to the bladder. However, IVES administration of Ty21a, a live bacterial vaccine against typhoid fever, was much more effective and increased the number of total and vaccine-specific CD8 T cells in the bladder approximately 10 fold. Comparison of chemokines induced in the bladder by either CpG (a TLR-9 agonist) or Ty21a highlighted the preferential increase in complement component 5a, CXCL5, CXCL2, CCL8, and CCL5 by Ty21a, suggesting their involvement in the attraction of T cells to the bladder. IVES treatment with Ty21a after vaccination also significantly increased tumor regression compared to vaccination alone, resulting in 90% survival in an orthotopic murine model of bladder cancer expressing a prototype tumor antigen. Our data demonstrate that combining vaccination with local immunostimulation may be an effective treatment strategy for different types of cancer and also highlight the great potential of the Ty21a vaccine, which is routinely used worldwide, in such combinatorial therapies.

Systematic analysis of factors associated with progression and regression of ulcerative colitis in 918 patients.

BACKGROUND: Studies that systematically assess change in ulcerative colitis (UC) extent over time in adult patients are scarce. AIM: To assess changes in disease extent over time and to evaluate clinical parameters associated with this change. METHODS: Data from the Swiss IBD cohort study were analysed. We used logistic regression modelling to identify factors associated with a change in disease extent. RESULTS: A total of 918 UC patients (45.3% females) were included. At diagnosis, UC patients presented with the following disease extent: proctitis [199 patients (21.7%)], left-sided colitis [338 patients (36.8%)] and extensive colitis/pancolitis [381 (41.5%)]. During a median disease duration of 9 [4-16] years, progression and regression was documented in 145 patients (15.8%) and 149 patients (16.2%) respectively. In addition, 624 patients (68.0%) had a stable disease extent. The following factors were identified to be associated with disease progression: treatment with systemic glucocorticoids [odds ratio (OR) 1.704, P = 0.025] and calcineurin inhibitors (OR: 2.716, P = 0.005). No specific factors were found to be associated with disease regression. CONCLUSIONS: Over a median disease duration of 9 [4-16] years, about two-thirds of UC patients maintained the initial disease extent; the remaining one-third had experienced either progression or regression of the disease extent.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Clinically-relevant threshold of preformed donor-specific anti-HLA antibodies in kidney transplantation.

BACKGROUND: Pretransplant anti-HLA donor-specific antibodies (DSA) are recognized as a risk factor for acute antibody-mediated rejection (AMR) in kidney transplantation. The predictive value of C4d-fixing capability by DSA or of IgG DSA subclasses for acute AMR in the pretransplant setting has been recently studied. In addition DSA strength assessed by mean fluorescence intensity (MFI) may improve risk stratification. We aimed to analyze the relevance of preformed DSA and of DSA MFI values. METHODS: 280 consecutive patients with negative complement-dependent cytotoxicity crossmatches received a kidney transplant between 01/2008 and 03/2014. Sera were screened for the presence of DSA with a solid-phase assays on a Luminex flow analyzer, and the results were correlated with biopsy-proven acute AMR in the first year and survival. RESULTS: Pretransplant anti-HLA antibodies were present in 72 patients (25.7%) and 24 (8.6%) had DSA. There were 46 (16.4%) acute rejection episodes, 32 (11.4%) being cellular and 14 (5.0%) AMR. The incidence of acute AMR was higher in patients with pretransplant DSA (41.7%) than in those without (1.6%) (p<0.001). The median cumulative MFI (cMFI) of the group DSA+/AMR+ was 5680 vs 2208 in DSA+/AMR- (p=0.058). With univariate logistic regression a threshold value of 5280 cMFI was predictive for acute AMR. DSA cMFI's ability to predict AMR was also explored by ROC analysis. AUC was 0.728 and the best threshold was a cMFI of 4340. Importantly pretransplant DSA>5280 cMFI had a detrimental effect on 5-year graft survival. CONCLUSIONS: Preformed DSA cMFI values were clinically-relevant for the prediction of acute AMR and graft survival in kidney transplantation. A threshold of 4300-5300 cMFI was a significant outcome predictor.