Upper and lower respiratory tract viral infections and acute graft rejection in lung transplant recipients.

Background: Lung transplant recipients are frequently exposed to respiratory viruses and are particularly at risk for severe complications. The aim of this study was to assess the association among the presence of a respiratory virus detected by molecular assays in bronchoalveolar lavage (BAL) fluid, respiratory symptoms, and acute rejection in adult lung transplant recipients. Methods: Upper (nasopharyngeal swab) and lower (BAL) respiratory tract specimens from 77 lung transplant recipients enrolled in a cohort study and undergoing bronchoscopy with BAL and transbronchial biopsies were screened using 17 different polymerase chain reaction-based assays. Result: BAL fluid and biopsy specimens from 343 bronchoscopic procedures performed in 77 patients were analyzed. We also compared paired nasopharyngeal and BAL fluid specimens collected in a subgroup of 283 cases. The overall viral positivity rate was 29.3% in the upper respiratory tract specimens and 17.2% in the BAL samples (). We observed a significant association P < .001 between the presence of respiratory symptoms and positive viral detection in the lower respiratory tract (Pp. 012). Conversely, acute rejection was not associated with the presence of viral infection (odds ratio, 0.41; 95% confidence interval, 0.20-0.88). The recovery of lung function was significantly slower when acute rejection and viral infection were both present. Conclusions: A temporal relationship exists between acute respiratory symptoms and positive viral nucleic acid detection in BAL fluid from lung transplant recipients. We provide evidence suggesting that respiratory viruses are not associated with acute graft rejection during the acute phase of infection.

Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

BACKGROUND: Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. METHODS: We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). RESULTS: The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result <or= 2 points), which had a sensitivity of 87.1% (95% CI 79.9%-94.2%) and a specificity of 80.8% (77.6%-83.9%). INTERPRETATION: The prediction rule for coronary artery disease in primary care proved to be robust in the validation cohort. It can help to rule out coronary artery disease in patients presenting with chest pain in primary care.

Complications of Valve Lung Volume Reduction in a Case of Previous Pleurodesis.

Lung volume reduction with valves is increasingly used to treat selected patients with severe emphysema. The indications for this procedure have been previously described; however, its contraindications have not yet been conclusively established. This case highlights the potentially severe complications of endobronchial one-way valve placement in the setting of a previous pleurodesis.

Antigen presentation in the lung: dendritic cells and macrophages.

Antigen presentation is a required prime event before T-cell activation can occur. Cells which constitutively express major histocompatibility antigen class I or II are responsible for presenting antigens. These are essentially alveolar macrophages (AM) residing mostly in the air spaces, and dendritic cells (DC), which create a tight surveillance network just below the epithelial cells of the airways and in the loose connective tissue around the vessels or in the pleura. AM are poor antigen presenting cells compared to DC. AM when encountering foreign particles or organisms may, however, influence the degree of activity or maturation of neighbouring DC, by releasing cytokines. Thus, we will describe how the innate immune processes may influence specific immunity and perhaps Th1 and Th2 differentiation. Following the description of the differences in phenotype and functions of AM and DC, we will provide data showing that in some pathological conditions, such as sarcoidosis, AM can acquire some specificities of DC.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Multicenter phase II trial of gefitinib first-line therapy followed by chemotherapy in advanced non-small-cell lung cancer (NSCLC): SAKK protocol 19/03.

BACKGROUND: Gefitinib is active in patients with pretreated non-small-cell lung cancer (NSCLC). We evaluated the activity and toxicity of gefitinib first-line treatment in advanced NSCLC followed by chemotherapy at disease progression. PATIENTS AND METHODS: In all, 63 patients with chemotherapy-naive stage IIIB/IV NSCLC received gefitinib 250 mg/day. At disease progression, gefitinib was replaced by cisplatin 80 mg/m(2) on day 1 and gemcitabine 1250 mg/m(2) on days 1, 8 for up to six 3-week cycles. Primary end point was the disease stabilization rate (DSR) after 12 weeks of gefitinib. RESULTS: After 12 weeks of gefitinib, the DSR was 24% and the response rate (RR) was 8%. Median time to progression (TtP) was 2.5 months and median overall survival (OS) 11.5 months. Never smokers (n = 9) had a DSR of 56% and a median OS of 20.2 months; patients with epidermal growth factor receptor (EGFR) mutation (n = 4) had a DSR of 75% and the median OS was not reached after the follow-up of 21.6 months. In all, 41 patients received chemotherapy with an overall RR of 34%, DSR of 71% and median TtP of 6.7 months. CONCLUSIONS: First-line gefitinib monotherapy led to a DSR of 24% at 12 weeks in an unselected patients population. Never smokers and patients with EGFR mutations tend to have a better outcome; hence, further trials in selected patients are warranted.

Outcome Prediction after Cardiac Arrest Treated with Hypothermia

Rationale: Clinical and electrophysiological prognostic markers of brain anoxia have been mostly evaluated in comatose survivors of out hospital cardiac arrest (OHCA) after standard resuscitation, but their predictive value in patients treated with mild induced hypothermia (IH) is unknown. The objective of this study was to identify a predictive score of independent clinical and electrophysiological variables in comatose OHCA survivors treated with IH, aiming at a maximal positive predictive value (PPV) and a high negative predictive value (NPV) for mortality. Methods: We prospectively studied consecutive adult comatose OHCA survivors from April 2006 to May 2009, treated with mild IH to 33-34_C for 24h at the intensive care unit of the Lausanne University Hospital, Switzerland. IH was applied using an external cooling method. As soon as subjects passively rewarmed (body temperature >35_C) they underwent EEG and SSEP recordings (off sedation), and were examined by experienced neurologists at least twice. Patients with status epilepticus were treated with AED for at least 24h. A multivariable logistic regression was performed to identify independent predictors of mortality at hospital discharge. These were used to formulate a predictive score. Results: 100 patients were studied; 61 died. Age, gender and OHCA etiology (cardiac vs. non-cardiac) did not differ among survivors and nonsurvivors. Cardiac arrest type (non-ventricular fibrillation vs. ventricular fibrillation), time to return of spontaneous circulation (ROSC) >25min, failure to recover all brainstem reflexes, extensor or no motor response to pain, myoclonus, presence of epileptiform discharges on EEG, EEG background unreactive to pain, and bilaterally absent N20 on SSEP, were all significantly associated with mortality. Absent N20 was the only variable showing no false positive results. Multivariable logistic regression identified four independent predictors (Table). These were used to construct the score, and its predictive values were calculated after a cut-off of 0-1 vs. 2-4 predictors. We found a PPV of 1.00 (95% CI: 0.93-1.00), a NPV of 0.81 (95% CI: 0.67-0.91) and an accuracy of 0.93 for mortality. Among 9 patients who were predicted to survive by the score but eventually died, only 1 had absent N20. Conclusions: Pending validation in a larger cohort, this simple score represents a promising tool to identify patients who will survive, and most subjects who will not, after OHCA and IH. Furthermore, while SSEP are 100% predictive of poor outcome but not available in most hospitals, this study identifies EEG background reactivity as an important predictor after OHCA. The score appears robust even without SSEP, suggesting that SSEP and other investigations (e.g., mismatch negativity, serum NSE) might be principally needed to enhance prognostication in the small subgroup of patients failing to improve despite a favorable score.

Surface Complexation Modeling in Variable Charge Soils: Prediction of Cadmium Adsorption

ABSTRACT Intrinsic equilibrium constants for 22 representative Brazilian Oxisols were estimated from a cadmium adsorption experiment. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. Intrinsic equilibrium constants were optimized by FITEQL and by hand calculation using Visual MINTEQ in sweep mode, and Excel spreadsheets. Data from both models were incorporated into Visual MINTEQ. Constants estimated by FITEQL and incorporated in Visual MINTEQ software failed to predict observed data accurately. However, FITEQL raw output data rendered good results when predicted values were directly compared with observed values, instead of incorporating the estimated constants into Visual MINTEQ. Intrinsic equilibrium constants optimized by hand calculation and incorporated in Visual MINTEQ reliably predicted Cd adsorption reactions on soil surfaces under changing environmental conditions.

Rgtsp: a generalized top scoring pairs package for class prediction.

SUMMARY: A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance. AVAILABILITY AND IMPLEMENTATION: Full C++ source code and R package Rgtsp are freely available from http://lausanne.isb-sib.ch/~vpopovic/research/. The implementation relies on existing OpenMP libraries.

[Hematological malignancy: management of anemia and leukopenia by primary care physicians]

In hematological malignancies, the occurrence of anemia is very common and can have significant consequences on daily life. Treatment includes essentially red blood cell transfusions. The prescription of erythropoietic agents and/or iron is exceptionnal and often not registered in Switzerland. The onset of neutropenia is also frequently encountered and in some situations may require the prescription of myeloid growth factors. The purpose of this article is to focus on the current recommendations of these two issues for practitioners.

Survival impact of lung transplantation for COPD.

Chronic obstructive pulmonary disease (COPD) is the primary indication for lung transplantation (LTx), but survival benefit is still under debate. We analysed the survival impact of LTx in COPD with a new approach, using the BODE (body mass index, airway obstruction, dyspnoea, exercise capacity) index. We retrospectively reviewed 54 consecutive lung transplants performed for COPD. The pre-transplant BODE score was calculated for each patient and a predicted survival was derived from the survival functions of the original BODE index validation cohort. Predicted and observed post-transplant survival was then compared. In the subgroups with a BODE score >or=7 and <7, a majority of patients (66% and 69%, respectively) lived for longer after LTx than predicted by their individual BODE index. The median survival was significantly improved in the entire cohort and in the subgroup with a BODE score >or=7. 4 yrs after LTx a survival benefit was only apparent in patients with a pre-transplant BODE score of >or=7. In conclusion, while a majority of COPD patients had an individual survival benefit from LTx regardless of their pre-transplant BODE score, a global survival benefit was seen only in patients with more severe disease. This supports the use of the BODE index as a selection criteria for LTx candidates.