Ruling out coronary heart disease in primary care: external validation of a clinical prediction rule.

BACKGROUND: The Marburg Heart Score (MHS) aims to assist GPs in safely ruling out coronary heart disease (CHD) in patients presenting with chest pain, and to guide management decisions. AIM: To investigate the diagnostic accuracy of the MHS in an independent sample and to evaluate the generalisability to new patients. DESIGN AND SETTING: Cross-sectional diagnostic study with delayed-type reference standard in general practice in Hesse, Germany. METHOD: Fifty-six German GPs recruited 844 males and females aged ≥ 35 years, presenting between July 2009 and February 2010 with chest pain. Baseline data included the items of the MHS. Data on the subsequent course of chest pain, investigations, hospitalisations, and medication were collected over 6 months and were reviewed by an independent expert panel. CHD was the reference condition. Measures of diagnostic accuracy included the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, likelihood ratios, and predictive values. RESULTS: The AUC was 0.84 (95% confidence interval [CI] = 0.80 to 0.88). For a cut-off value of 3, the MHS showed a sensitivity of 89.1% (95% CI = 81.1% to 94.0%), a specificity of 63.5% (95% CI = 60.0% to 66.9%), a positive predictive value of 23.3% (95% CI = 19.2% to 28.0%), and a negative predictive value of 97.9% (95% CI = 96.2% to 98.9%). CONCLUSION: Considering the diagnostic accuracy of the MHS, its generalisability, and ease of application, its use in clinical practice is recommended.

MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status.

The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.

An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease.

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease.

Identification of human IKK-2 inhibitors of natural origin (Part II): in Silico prediction of IKK-2 inhibitors in natural extracts with known anti-inflammatory activity.

Human inhibitor NF-κB kinase 2 (hIKK-2) is the primary component responsible for activating NF-κB in response to various inflammatory stimuli. Thus, synthetic ATP-competitive inhibitors for hIKK-2 have been developed as anti-inflammatory compounds. We recently reported a virtual screening protocol (doi:10.1371/journal.pone.0016903) that is able to identify hIKK-2 inhibitors that are not structurally related to any known molecule that inhibits hIKK-2 and that have never been reported to have anti-inflammatory activity. In this study, a stricter version of this protocol was applied to an in-house database of 29,779 natural products annotated with their natural source. The search identified 274 molecules (isolated from 453 different natural extracts) predicted to inhibit hIKK-2. An exhaustive bibliographic search revealed that anti-inflammatory activity has been previously described for: (a) 36 out of these 453 extracts; and (b) 17 out of 30 virtual screening hits present in these 36 extracts. Only one of the remaining 13 hit molecules in these extracts shows chemical similarity with known synthetic hIKK-2 inhibitors. Therefore, it is plausible that a significant portion of the remaining 12 hit molecules are lead-hopping candidates for the development of new hIKK-2 inhibitors.

Impact of tight glycemic control on cerebral glucose metabolism after severe brain injury: a microdialysis study.

OBJECTIVES: To analyze the effect of tight glycemic control with the use of intensive insulin therapy on cerebral glucose metabolism in patients with severe brain injury. DESIGN: Retrospective analysis of a prospective observational cohort. SETTING: University hospital neurologic intensive care unit. PATIENTS: Twenty patients (median age 59 yrs) monitored with cerebral microdialysis as part of their clinical care. INTERVENTIONS: Intensive insulin therapy (systemic glucose target: 4.4-6.7 mmol/L [80-120 mg/dL]). MEASUREMENTS AND MAIN RESULTS: Brain tissue markers of glucose metabolism (cerebral microdialysis glucose and lactate/pyruvate ratio) and systemic glucose were collected hourly. Systemic glucose levels were categorized as within the target "tight" (4.4-6.7 mmol/L [80-120 mg/dL]) vs. "intermediate" (6.8-10.0 mmol/L [121-180 mg/dL]) range. Brain energy crisis was defined as a cerebral microdialysis glucose <0.7 mmol/L with a lactate/pyruvate ratio >40. We analyzed 2131 cerebral microdialysis samples: tight systemic glucose levels were associated with a greater prevalence of low cerebral microdialysis glucose (65% vs. 36%, p < 0.01) and brain energy crisis (25% vs.17%, p < 0.01) than intermediate levels. Using multivariable analysis, and adjusting for intracranial pressure and cerebral perfusion pressure, systemic glucose concentration (adjusted odds ratio 1.23, 95% confidence interval [CI] 1.10-1.37, for each 1 mmol/L decrease, p < 0.001) and insulin dose (adjusted odds ratio 1.10, 95% CI 1.04-1.17, for each 1 U/hr increase, p = 0.02) independently predicted brain energy crisis. Cerebral microdialysis glucose was lower in nonsurvivors than in survivors (0.46 +/- 0.23 vs. 1.04 +/- 0.56 mmol/L, p < 0.05). Brain energy crisis was associated with increased mortality at hospital discharge (adjusted odds ratio 7.36, 95% CI 1.37-39.51, p = 0.02). CONCLUSIONS: In patients with severe brain injury, tight systemic glucose control is associated with reduced cerebral extracellular glucose availability and increased prevalence of brain energy crisis, which in turn correlates with increased mortality. Intensive insulin therapy may impair cerebral glucose metabolism after severe brain injury.

Multivariate prediction

The problem of prediction is considered in a multidimensional setting. Extending an idea presented by Barndorff-Nielsen and Cox, a predictive density for a multivariate random variable of interest is proposed. This density has the form of an estimative density plus a correction term. It gives simultaneous prediction regions with coverage error of smaller asymptotic order than the estimative density. A simulation study is also presented showing the magnitude of the improvement with respect to the estimative method.

Treatment of ruptured abdominal aortic aneurysm, a permanent challenge or a waste of resources? Prediction of outcome using a multi-organ-dysfunction score.

OBJECTIVES: in a retrospective study, attempts have been made to identify individual organ-dysfunction risk profiles influencing the outcome after surgery for ruptured abdominal aortic aneurysms. METHODS: out of 235 patients undergoing graft replacement for abdominal aortic aneurysms, 57 (53 men, four women, mean age 72 years [s.d. 8.8]) were treated for ruptured aneurysms in a 3-year period. Forty-eight preoperative, 13 intraoperative and 34 postoperative variables were evaluated statistically. A simple multi-organ dysfunction (MOD) score was adopted. RESULTS: the perioperative mortality was 32%. Three patients died intraoperatively, four within 48 h and 11 died later. A significant influence for pre-existing risk factors was identified only for cardiovascular diseases. Multiple linear-regression analysis indicated that a haemoglobin <90 g/l, systolic blood pressure <80 mmHg and ECG signs of ischaemia at admission were highly significant risk factors. The cause of death for patients, who died more than 48 h postoperatively, was mainly MOD. All patients with a MOD score >/=4 died (n=7). These patients required 27% of the intensive-care unit (ICU) days of all patients and 72% of the ICU days of the non-survivors. CONCLUSION: patients with ruptured aortic aneurysms from treatment should not be excluded. However, a physiological scoring system after 48 h appears justifiable in order to decide on the appropriateness of continual ICU support.

Brain Injury Quick Guide: Information and Resources for Teachers and School Staff, July 2013

The Brain Injury Quick Guide was developed as a resource tool for educators and school staff. Functional challenges (including social, physical, communication, and cognitive) are common following brain injury. This booklet serves as a resource outlining common challenges students may face in the classroom as well as strategies for addressing these challenges. Case studies outlining common challenges with possible strategies are provided with suggestions for IEP/504 plan accommodations. Basic brain anatomy and brain injury statistics are also reviewed.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Changes in cerebral compartmental compliances during mild hypocapnia in patients with traumatic brain injury.

The benefit of induced hyperventilation for intracranial pressure (ICP) control after severe traumatic brain injury (TBI) is controversial. In this study, we investigated the impact of early and sustained hyperventilation on compliances of the cerebral arteries and of the cerebrospinal (CSF) compartment during mild hyperventilation in severe TBI patients. We included 27 severe TBI patients (mean 39.5 ± 3.4 years, 6 women) in whom an increase in ventilation (20% increase in respiratory minute volume) was performed during 50 min as part of a standard clinical CO(2) reactivity test. Using a new mathematical model, cerebral arterial compliance (Ca) and CSF compartment compliance (Ci) were calculated based on the analysis of ICP, arterial blood pressure, and cerebral blood flow velocity waveforms. Hyperventilation initially induced a reduction in ICP (17.5 ± 6.6 vs. 13.9 ± 6.2 mmHg; p < 0.001), which correlated with an increase in Ci (r(2) = 0.213; p = 0.015). Concomitantly, the reduction in cerebral blood flow velocities (CBFV, 74.6 ± 27.0 vs. 62.9 ± 22.9 cm/sec; p < 0.001) marginally correlated with the reduction in Ca (r(2) = 0.209; p = 0.017). During sustained hyperventilation, ICP increased (13.9 ± 6.2 vs. 15.3 ± 6.4 mmHg; p < 0.001), which correlated with a reduction in Ci (r(2) = 0.297; p = 0.003), but no significant changes in Ca were found during that period. The early reduction in Ca persisted irrespective of the duration of hyperventilation, which may contribute to the lack of clinical benefit of hyperventilation after TBI. Further studies are needed to determine whether monitoring of arterial and CSF compartment compliances may detect and prevent an adverse ischemic event during hyperventilation.