Factors influencing intracranial pressure (ICP) during percutaneous tracheostomy.

OBJECTIVES: Percutaneous tracheostomy (PT) is common on ICUs. An increase of intracranial pressure (ICP) can be observed in patients with acute cerebral diseases. Factors determining ICP increase remain unclear. PATIENTS AND METHODS: Data for all PTs were collected prospectively. ICP, cerebral perfusion pressure (CPP), mean arterial pressure (MAP), peripheral oxygen saturation (SpO2), and heart rate (HR) were monitored continuously every minute. Primary outcome parameter was an increase of ICP during PT (ICP > 20 mmHg). Influencing factors were evaluated by the means of logistic regression analysis: Body mass index (BMI), age, gender, physician performing the procedure (neurologist vs. neurosurgeon), duration of the procedure, underlying disease, duration of mechanical ventilation, and baseline ICP value before the procedure. RESULTS: A total of 175 PTs were performed during the observation period between 2010 and 2013. Of these, 54 received ICP monitoring and were included into this study. Median initial ICP value was 10.4 mmHg and rose significantly to a median value of 18.4 mmHg (p < 0.05). In 21 patients (38,9%) an increase of median ICP above 20 mmHg was seen during at least one interval. Comparing patients with and without pathological ICP increase a significant difference between the two groups was only observed for patients with an increased baseline ICP above 15 mmHg. All other factors had no significant influence on the development of a pathological ICP peaks during PT. CONCLUSION: Percutaneous tracheostomies in patients with cerebral injury leads to a significant increase of ICP during the procedure. Patients with a baseline ICP > 15 mmHg are at risk to develop harmful ICP crises.

EcR recruits dMi-2 and increases efficiency of dMi-2-mediated remodelling to constrain transcription of hormone-regulated genes.

Gene regulation by steroid hormones plays important roles in health and disease. In Drosophila, the hormone ecdysone governs transitions between key developmental stages. Ecdysone-regulated genes are bound by a heterodimer of ecdysone receptor (EcR) and Ultraspiracle. According to the bimodal switch model, steroid hormone receptors recruit corepressors in the absence of hormone and coactivators in its presence. Here we show that the nucleosome remodeller dMi-2 is recruited to ecdysone-regulated genes to limit transcription. Contrary to the prevalent model, recruitment of the dMi-2 corepressor increases upon hormone addition to constrain gene activation through chromatin remodelling. Furthermore, EcR and dMi-2 form a complex that is devoid of Ultraspiracle. Unexpectedly, EcR contacts the dMi-2 ATPase domain and increases the efficiency of dMi-2-mediated nucleosome remodelling. This study identifies a non-canonical EcR-corepressor complex with the potential for a direct regulation of ATP-dependent nucleosome remodelling by a nuclear hormone receptor.

Relationship of Prolonged Operative Time and Comorbidities With Complications After Geriatric Ankle Fractures.

BACKGROUND: The incidence of geriatric ankle fractures has increased during the last few decades. In contrast to younger patients, increased complication rates have been observed. Thus, the goal of the present study was to identify risk factors for perioperative complications following open reduction and internal fixation of geriatric ankle fractures. METHODS: Two hundred thirty-seven patients over the age of 65 years (mean, 72.5 ± 6.1 years) treated for ankle fractures in our institution between 2004 and 2014 were included. Complications associated with operative treatment as well as complications requiring revision surgery were analyzed. In a multivariate analysis, risk factors were determined. RESULTS: In 68 patients (28.7%), 74 complications were documented. The most common complications were impaired wound healing and operative site infections. The multivariate analysis revealed that the operative time was the only independent risk factor for the development of a complication. The operative time as well as the presence of an open fracture represented risk factors for needing revision surgery. Comorbidities did not influence the development of complications. CONCLUSION: The operative management of geriatric ankle fractures was associated with a high complication rate. In the present study, the operative time was the only modifiable factor for the development of a complication that required revision surgery. During preoperative preparation, we believe that perfusion of the affected limb should be optimized to reduce the incidence of wound complications. LEVEL OF EVIDENCE: Level III, retrospective cohort study.

Effect of percutaneous tracheostomy on intracerebral pressure and perfusion pressure in patients with acute cerebral dysfunction (TIP Trial): an observational study.

BACKGROUND: Bedside percutaneous tracheostomy (PT) is very commonly used for patients who require prolonged mechanical ventilation. The effect of tracheostomy on intracranial pressure (ICP) is currently a subject of controversy. The aim of our study is to clarify the relation between PT and its effect on ICP and cerebral perfusion pressure. METHODS: 38 patients on our intensive care unit were included prospectively in an observational study. We examined mean values of HF, SpO(2), ICP, CPP, and MAP for changes over five different phases of the procedure using paired Mann-Whitney U tests. A p value of <0.05 was considered significant. p values were Bonferroni corrected for multiple testing. RESULTS: PT was performed on 38 patients (f = 19, m = 19; mean = 56 years). Median ICP before intervention was 9 mmHg. During positioning of the patient, ICP had risen to 14, during bronchoscopy to 16, and during tracheostomy to 18 mmHg, all being significantly higher than baseline level. Monitoring of MAP showed a significant increase to 101 mmHg only during tracheostomy. SpO(2) and HF did not show any significant changes. Mean duration of positioning, bronchoscopy and tracheostomy was 19, 10, and 17 min. 8 patients received osmotherapy due to a rise of ICP of more than 30 mmHg. CONCLUSION: PT only leads to a significant rise of ICP during the procedure. Nevertheless, therapy of ICP is necessary in some patients. From our point of view, therefore, tracheostomy should only be performed under continuous monitoring of ICP and CPP in patients with severe cerebral dysfunctions and critically elevated ICP.

PERMORY-MPI: a program for high-speed parallel permutation testing in genome-wide association studies.

UNLABELLED: PERMORY is software for accelerated permutation testing of genome-wide association studies (GWAS). We have parallelized PERMORY using the Message-Passing Interface resulting in a nearly linear speedup. Furthermore, we added accelerated analysis of GWAS using quantitative phenotypes, and an accurate estimation of the effective number of independent tests. AVAILABILITY AND IMPLEMENTATION: Free download from http://permory.org.

PERMORY: an LD-exploiting permutation test algorithm for powerful genome-wide association testing.

MOTIVATION: In genome-wide association studies (GWAS) examining hundreds of thousands of genetic markers, the potentially high number of false positive findings requires statistical correction for multiple testing. Permutation tests are considered the gold standard for multiple testing correction in GWAS, because they simultaneously provide unbiased type I error control and high power. At the same time, they demand heavy computational effort, especially with large-scale datasets of modern GWAS. In recent years, the computational problem has been circumvented by using approximations to permutation tests, which, however, may be biased. RESULTS: We have tackled the original computational problem of permutation testing in GWAS and herein present a permutation test algorithm one or more orders of magnitude faster than existing implementations, which enables efficient permutation testing on a genome-wide scale. Our algorithm does not rely on any kind of approximation and hence produces unbiased results identical to a standard permutation test. A noteworthy feature of our algorithm is a particularly effective performance when analyzing high-density marker sets. AVAILABILITY: Freely available on the web at http://www.permory.org.

Optimal robust two-stage designs for genome-wide association studies.

Optimal robust two-stage designs for genome-wide association studies are proposed using the maximum of the recessive, additive and dominant linear trend test statistics. These designs combine cost-saving two-stage genotyping with robustness against misspecification of the genetic model and are much more efficient than designs based on a single model specific test statistic in detecting multiple loci with different modes of inheritance. For given power of 90%, typical cost savings of 34% can be realised by increasing the total sample size by about 13% but genotyping only about half of the sample for the full marker set in the first stage and carrying forward about 0.06% of the markers to the second stage analysis. We also present robust two-stage designs providing optimal allocation of a limited budget for pre-existing samples. If a sample is available which would yield a power of 90% when fully genotyped, genotyping only half of the sample due to a limited budget will typically cause a loss of power of more than 55%. Using an optimal two-stage approach in the same sample under the same budget restrictions will limit the loss of power to less than 10%. In general, the optimal proportion of markers to be followed up in the second stage strongly depends on the cost ratio for chips and individual genotyping, while the design parameters of the optimal designs (total sample size, first stage proportion, first and second stage significance limit) do not much depend on the genetic model assumptions.

Optimal multistage designs--a general framework for efficient genome-wide association studies.

Genome-wide association studies (GWAS) have become increasingly affordable but they are still costly. Therefore, cost saving 2-stage designs were proposed in the literature. The restriction to 2 stages, however, seems artificial and does not exploit the full potential of the underlying methods. We extend the 2-stage approach to the general framework of any number of stages. Based on the theory of group sequential methods, we derive optimal multistage designs. With current genotyping cost structures, our results suggest that up to 4 stages are sufficient in order to get feasible and efficient designs. Furthermore, we consider the problem of choosing the optimal number of stages depending on the costs of the statistical interim analysis at each stage and provide guidelines for planning the number of stages in practice. In particular, we found that in the majority of cases both 3-stage designs and 4-stage designs are more efficient than 2-stage designs. Although prices for marker panels are showing a continuing downward trend, we still recommend implementing and using optimal multistage designs in practice. In addition to the immediate benefit, it will be necessary to acquire know-how regarding the application of multistage designs in order to be able to adapt the general framework of multistage designs to upcoming technologies in the area of GWAS.

Including sampling and phenotyping costs into the optimization of two stage designs for genomewide association studies.

We propose optimized two-stage designs for genome-wide case-control association studies, using a hypothesis testing paradigm. To save genotyping costs, the complete marker set is genotyped in a sub-sample only (stage I). On stage II, the most promising markers are then genotyped in the remaining sub-sample. In recent publications, two-stage designs were proposed which minimize the overall genotyping costs. To achieve full design optimization, we additionally include sampling costs into both the cost function and the design optimization. The resulting optimal designs differ markedly from those optimized for genotyping costs only (partially optimized designs), and achieve considerable further cost reductions. Compared with partially optimized designs, fully optimized two-stage designs have higher first-stage sample proportion. Furthermore, the increment of the sample size over the one-stage design, which is necessary in two-stage designs in order to compensate for the loss of power due to partial genotyping, is less pronounced for fully optimized two-stage designs. In addition, we address the scenario where the investigator is interested to gain as much information as possible, however is restricted in terms of a budget. In that we develop two-stage designs that maximize the power under a certain cost constraint.