β-Lactam Monotherapy vs β-Lactam-Macrolide Combination Treatment in Moderately Severe Community-Acquired Pneumonia: A Randomized Noninferiority Trial.

IMPORTANCE: The clinical benefit of adding a macrolide to a β-lactam for empirical treatment of moderately severe community-acquired pneumonia remains controversial. OBJECTIVE: To test noninferiority of a β-lactam alone compared with a β-lactam and macrolide combination in moderately severe community-acquired pneumonia. DESIGN, SETTING, AND PARTICIPANTS: Open-label, multicenter, noninferiority, randomized trial conducted from January 13, 2009, through January 31, 2013, in 580 immunocompetent adult patients hospitalized in 6 acute care hospitals in Switzerland for moderately severe community-acquired pneumonia. Follow-up extended to 90 days. Outcome assessors were masked to treatment allocation. INTERVENTIONS: Patients were treated with a β-lactam and a macrolide (combination arm) or with a β-lactam alone (monotherapy arm). Legionella pneumophila infection was systematically searched and treated by addition of a macrolide to the monotherapy arm. MAIN OUTCOMES AND MEASURES: Proportion of patients not reaching clinical stability (heart rate <100/min, systolic blood pressure >90 mm Hg, temperature <38.0°C, respiratory rate <24/min, and oxygen saturation >90% on room air) at day 7. RESULTS: After 7 days of treatment, 120 of 291 patients (41.2%) in the monotherapy arm vs 97 of 289 (33.6%) in the combination arm had not reached clinical stability (7.6% difference, P = .07). The upper limit of the 1-sided 90% CI was 13.0%, exceeding the predefined noninferiority boundary of 8%. Patients infected with atypical pathogens (hazard ratio [HR], 0.33; 95% CI, 0.13-0.85) or with Pneumonia Severity Index (PSI) category IV pneumonia (HR, 0.81; 95% CI, 0.59-1.10) were less likely to reach clinical stability with monotherapy, whereas patients not infected with atypical pathogens (HR, 0.99; 95% CI, 0.80-1.22) or with PSI category I to III pneumonia (HR, 1.06; 95% CI, 0.82-1.36) had equivalent outcomes in the 2 arms. There were more 30-day readmissions in the monotherapy arm (7.9% vs 3.1%, P = .01). Mortality, intensive care unit admission, complications, length of stay, and recurrence of pneumonia within 90 days did not differ between the 2 arms. CONCLUSIONS AND RELEVANCE: We did not find noninferiority of β-lactam monotherapy in patients hospitalized for moderately severe community-acquired pneumonia. Patients infected with atypical pathogens or with PSI category IV pneumonia had delayed clinical stability with monotherapy. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00818610.

Idiopathic desquamative interstitial pneumonia in a child: a case report.

BACKGROUND: Desquamative interstitial pneumonia is a rare form of interstitial lung disease in children. Respiratory symptoms appear progressively, are often subtle, and diagnosis is often delayed by a mean of 6 months after onset. High resolution chest computed tomography is the most sensitive imaging technique for demonstrating and identifying interstitial pneumonia. The typical histologic pattern of desquamative interstitial pneumonia, with prominent clustered alveolar macrophages, diffuse reactive alveolar epithelial hyperplasia and globular proteinaceous material, is diagnostic. Desquamative interstitial pneumonia in children can be idiopathic, though it is mostly related to an inborn error of surfactant metabolism. CASE PRESENTATION: We present the complex clinical course and pathologic findings of a 30-months-old Mauritian and Senegalese girl with idiopathic desquamative interstitial pneumonia and multiple extrapulmonary manifestations. To our knowledge, this is the first case report of desquamative interstitial pneumonia to occur as part of a syndrome with multiple organ involvement. CONCLUSION: We believe that desquamative interstitial pneumonia is not always associated with mutations of the surfactant proteins, and can still be idiopathic, especially when occurring as part of a syndrome with multiple organ involvement, as described in other interstitial lung diseases.

A Pneumocystis jirovecii pneumonia outbreak in a single kidney-transplant center: role of cytomegalovirus co-infection.

Pneumocystis jirovecii pneumonia (PCP) and cytomegalovirus (CMV) infection represent possible complications of medical immunosuppression. Between 2005 and 2010, non-human immunodeficiency virus (HIV) PCP patients admitted to a nephrology unit were analyzed for outcome, CMV comorbidity, and patient-to-patient contacts prior to PCP. In contrast to 2002-2004 (no cases) and 2008-2010 (10 cases), a PCP outbreak of 29 kidney-transplant recipients and one patient with anti-glomerular basement membrane disease occurred between 2005 and 2007. None of the patients were on PCP chemoprophylaxis. In four PCP patients, the genotyping data of bronchoalveolar lavage specimen showed an identical Pneumocystis strain. PCP cases had a higher incidence of CMV infection (12 of 30 PCP patients) and CMV disease (four patients) when compared to matched PCP-free controls (p < 0.05). Cotrimoxazole and, if applicable, ganciclovir were started 2.0 ± 4.0 days following admission, and immunosuppressive medication was reduced. In-hospital mortality was 10% and the three-year mortality was 20%. CMV co-infection did not affect mortality. CMV co-infection more frequently occurred during a cluster outbreak of non-HIV PCP in comparison to PCP-free controls. Here, CMV awareness and specific therapy of both CMV infection and PCP led to a comparatively favorable patient outcome. The role of patient isolation should be further investigated in incident non-HIV PCP.

Developing methodologies to allow the robust prediction dynamic context dominated by perturbations

El principal objectiu del projecte era desenvolupar millores conceptuals i metodològiques que permetessin una millor predicció dels canvis en la distribució de les espècies (a una escala de paisatge) derivats de canvis ambientals en un context dominat per pertorbacions. En un primer estudi, vàrem comparar l'eficàcia de diferents models dinàmics per a predir la distribució de l'hortolà (Emberiza hortulana). Els nostres resultats indiquen que un model híbrid que combini canvis en la qualitat de l'hàbitat, derivats de canvis en el paisatge, amb un model poblacional espacialment explícit és una aproximació adequada per abordar canvis en la distribució d'espècies en contextos de dinàmica ambiental elevada i una capacitat de dispersió limitada de l'espècie objectiu. En un segon estudi abordarem la calibració mitjançant dades de seguiment de models de distribució dinàmics per a 12 espècies amb preferència per hàbitats oberts. Entre les conclusions extretes destaquem: (1) la necessitat de que les dades de seguiment abarquin aquelles àrees on es produeixen els canvis de qualitat; (2) el biaix que es produeix en la estimació dels paràmetres del model d'ocupació quan la hipòtesi de canvi de paisatge o el model de qualitat d'hàbitat són incorrectes. En el darrer treball estudiarem el possible impacte en 67 espècies d’ocells de diferents règims d’incendis, definits a partir de combinacions de nivells de canvi climàtic (portant a un augment esperat de la mida i freqüència d’incendis forestals), i eficiència d’extinció per part dels bombers. Segons els resultats dels nostres models, la combinació de factors antropogènics del regim d’incendis, tals com l’abandonament rural i l’extinció, poden ser més determinants per als canvis de distribució que els efectes derivats del canvi climàtic. Els productes generats inclouen tres publicacions científiques, una pàgina web amb resultats del projecte i una llibreria per a l'entorn estadístic R.

SGP-1: prediction and validation of homologous genes based on sequence alignments

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors.

An assessment of gene prediction accuracy in large DNA sequences

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

Comparative gene prediction in human and mouse

The completion of the sequencing of the mouse genome promises to help predict human genes with greater accuracy. While current ab initio gene prediction programs are remarkably sensitive (i.e., they predict at least a fragment of most genes), their specificity is often low, predicting a large number of false-positive genes in the human genome. Sequence conservation at the protein level with the mouse genome can help eliminate some of those false positives. Here we describe SGP2, a gene prediction program that combines ab initio gene prediction with TBLASTX searches between two genome sequences to provide both sensitive and specific gene predictions. The accuracy of SGP2 when used to predict genes by comparing the human and mouse genomes is assessed on a number of data sets, including single-gene data sets, the highly curated human chromosome 22 predictions, and entire genome predictions from ENSEMBL. Results indicate that SGP2 outperforms purely ab initio gene prediction methods. Results also indicate that SGP2 works about as well with 3x shotgun data as it does with fully assembled genomes. SGP2 provides a high enough specificity that its predictions can be experimentally verified at a reasonable cost. SGP2 was used to generate a complete set of gene predictions on both the human and mouse by comparing the genomes of these two species. Our results suggest that another few thousand human and mouse genes currently not in ENSEMBL are worth verifying experimentally.

Splitting statistical potentials into meaningful scoring functions: testing the prediction of near-native structures from decoy conformations

Background: Recent advances on high-throughput technologies have produced a vast amount of protein sequences, while the number of high-resolution structures has seen a limited increase. This has impelled the production of many strategies to built protein structures from its sequence, generating a considerable amount of alternative models. The selection of the closest model to the native conformation has thus become crucial for structure prediction. Several methods have been developed to score protein models by energies, knowledge-based potentials and combination of both.Results: Here, we present and demonstrate a theory to split the knowledge-based potentials in scoring terms biologically meaningful and to combine them in new scores to predict near-native structures. Our strategy allows circumventing the problem of defining the reference state. In this approach we give the proof for a simple and linear application that can be further improved by optimizing the combination of Zscores. Using the simplest composite score () we obtained predictions similar to state-of-the-art methods. Besides, our approach has the advantage of identifying the most relevant terms involved in the stability of the protein structure. Finally, we also use the composite Zscores to assess the conformation of models and to detect local errors.Conclusion: We have introduced a method to split knowledge-based potentials and to solve the problem of defining a reference state. The new scores have detected near-native structures as accurately as state-of-art methods and have been successful to identify wrongly modeled regions of many near-native conformations.

Prediction of enzyme function by combining sequence similarity and protein interactions

Background: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. Results: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST. Conclusion: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.

Personalized modeling for drug concentration prediction using Support Vector Machine

Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.

Delay of extubation in neonates and children after cardiac surgery: impact of ventilator-associated pneumonia.

OBJECTIVE: This study was undertaken to determine the delay of extubation attributable to ventilator-associated pneumonia (VAP) in comparison to other complications and complexity of surgery after repair of congenital heart lesions in neonates and children. METHODS: Cohort study in a pediatric intensive care unit of a tertiary referral center. All patients who had cardiac operations during a 22-month period and who survived surgery were eligible (n = 272, median age 1.3 years). Primary outcome was time to successful extubation. Primary variable of interest was VAP Surgical procedures were classified according to complexity. Cox proportional hazards models were calculated to adjust for confounding. Potential confounders comprised other known risk factors for delayed extubation. RESULTS: Median time to extubation was 3 days. VAP occurred in 26 patients (9.6%). The rate of VAP was not associated with complexity of surgery (P = 0.22), or cardiopulmonary bypass (P = 0.23). The adjusted analysis revealed as further factors associated with delayed extubation: other respiratory complications (n = 28, chylothorax, airway stenosis, diaphragm paresis), prolonged inotropic support (n = 48, 17.6%), and the need for secondary surgery (n = 51, 18.8%; e.g., re-operation, secondary closure of thorax). Older age promoted early extubation. The median delay of extubation attributable to VAP was 3.7 days (hazards ratio HR = 0.29, 95% CI 0.18-0.49), exceeding the effect size of secondary surgery (HR = 0.48) and other respiratory complications (HR = 0.50). CONCLUSION: VAP accounts for a major delay of extubation in pediatric cardiac surgery.

The role of the New Trauma and Injury Severity Score (NTRISS) for survival prediction

The objective of this study was to verify if replacing the Injury Severity Score (ISS) by the New Injury Severity Score (NISS) in the original Trauma and Injury Severity Score (TRISS) form would improve the survival rate estimation. This retrospective study was performed in a level I trauma center during one year. ROC curve was used to identify the best indicator (TRISS or NTRISS) for survival probability prediction. Participants were 533 victims, with a mean age of 38±16 years. There was predominance of motor vehicle accidents (61.9%). External injuries were more frequent (63.0%), followed by head/neck injuries (55.5%). Survival rate was 76.9%. There is predominance of ISS scores ranging from 9-15 (40.0%), and NISS scores ranging from 16-24 (25.5%). Survival probability equal to or greater than 75.0% was obtained for 83.4% of the victims according to TRISS, and for 78.4% according to NTRISS. The new version (NTRISS) is better than TRISS for survival prediction in trauma patients.

β-Lactam Monotherapy vs β-Lactam-Macrolide Combination Treatment in Moderately Severe Community-Acquired Pneumonia: A Randomized Noninferiority Trial.

IMPORTANCE: The clinical benefit of adding a macrolide to a β-lactam for empirical treatment of moderately severe community-acquired pneumonia remains controversial. OBJECTIVE: To test noninferiority of a β-lactam alone compared with a β-lactam and macrolide combination in moderately severe community-acquired pneumonia. DESIGN, SETTING, AND PARTICIPANTS: Open-label, multicenter, noninferiority, randomized trial conducted from January 13, 2009, through January 31, 2013, in 580 immunocompetent adult patients hospitalized in 6 acute care hospitals in Switzerland for moderately severe community-acquired pneumonia. Follow-up extended to 90 days. Outcome assessors were masked to treatment allocation. INTERVENTIONS: Patients were treated with a β-lactam and a macrolide (combination arm) or with a β-lactam alone (monotherapy arm). Legionella pneumophila infection was systematically searched and treated by addition of a macrolide to the monotherapy arm. MAIN OUTCOMES AND MEASURES: Proportion of patients not reaching clinical stability (heart rate <100/min, systolic blood pressure >90 mm Hg, temperature <38.0°C, respiratory rate <24/min, and oxygen saturation >90% on room air) at day 7. RESULTS: After 7 days of treatment, 120 of 291 patients (41.2%) in the monotherapy arm vs 97 of 289 (33.6%) in the combination arm had not reached clinical stability (7.6% difference, P = .07). The upper limit of the 1-sided 90% CI was 13.0%, exceeding the predefined noninferiority boundary of 8%. Patients infected with atypical pathogens (hazard ratio [HR], 0.33; 95% CI, 0.13-0.85) or with Pneumonia Severity Index (PSI) category IV pneumonia (HR, 0.81; 95% CI, 0.59-1.10) were less likely to reach clinical stability with monotherapy, whereas patients not infected with atypical pathogens (HR, 0.99; 95% CI, 0.80-1.22) or with PSI category I to III pneumonia (HR, 1.06; 95% CI, 0.82-1.36) had equivalent outcomes in the 2 arms. There were more 30-day readmissions in the monotherapy arm (7.9% vs 3.1%, P = .01). Mortality, intensive care unit admission, complications, length of stay, and recurrence of pneumonia within 90 days did not differ between the 2 arms. CONCLUSIONS AND RELEVANCE: We did not find noninferiority of β-lactam monotherapy in patients hospitalized for moderately severe community-acquired pneumonia. Patients infected with atypical pathogens or with PSI category IV pneumonia had delayed clinical stability with monotherapy. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00818610.