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Background: The painDETECT questionnaire (PD-Q) has been used as a tool to characterize sensory abnormalities in patients with persistent pain. This study investigated whether the self-reported sensory descriptors of patients with painful cervical radiculopathy (CxRAD) and patients with fibromyalgia (FM), as characterized by responses to verbal sensory descriptors from PD-Q (sensitivity to light touch, cold, heat, slight pressure, feeling of numbness in the main area of pain), were associated with the corresponding sensory parameters as demonstrated by quantitative sensory testing (QST).
Methods: Twenty-three patients with CxRAD (eight women, 46.3 ± 9.6 years) and 22 patients with FM (20 women, 46.1 ± 11.5 years) completed the PD-Q. Standardized QST of dynamic mechanical allodynia, cold and heat pain thresholds, pressure pain thresholds, mechanical and vibration detection thresholds, was recorded from the maximal pain area. Comparative QST data from 31 age-matched healthy controls (HCs; 15 women) were obtained.
Results: Patients with CxRAD demonstrated a match between their self-reported descriptors and QST parameters for all sensory parameters except for sensitivity to light touch, and these matches were statistically significant compared with HC data (p ≤ 0.006). The FM group demonstrated discrepancies between the PD-Q and QST sensory phenotypes for all sensory descriptors, indicating that the self-reported sensory descriptors did not consistently match the QST parameters (p = ≤0.017).
Conclusion: Clinicians and researchers should be cautious about relying on PD-Q as a stand-alone screening tool to determine sensory abnormalities in patients with FM.
Identification of differences in clinical presentation and underlying pain mechanisms may assist the classification of patients with neck–arm pain which is important for the provision of targeted best evidence based management. The aim of this study was to: (i) assess the inter-examiner agreement in using specific systems to classify patients with cervical radiculopathy and patients with non-specific neck–arm pain associated with heightened nerve mechanosensitivity (NSNAP); (ii) assess the agreement between two clinical examiners and two clinical experts in classifying these patients, and (iii) assess the diagnostic accuracy of the two clinical examiners. Forty patients with unilateral neck–arm pain were examined by two clinicians and classified into (i) cervical radiculopathy, (ii) NSNAP, (iii) other. The classifications were compared to those made independently by two experts, based on a review of patients' clinical assessment notes. The experts' opinion was used as the reference criterion to assess the diagnostic accuracy of the clinical examiners in classifying each patient group. There was an 80% agreement between clinical examiners, and between experts and 70%–80% between clinical examiners and experts in classifying patients with cervical radiculopathy (kappa between 0.41 and 0.61). Agreement was 72.5%–80% in classifying patients with NSNAP (kappa between 0.43 and 0.52). Clinical examiners' diagnostic accuracy was high (radiculopathy: sensitivity 79%–84%; specificity 76%–81%; NSNAP: sensitivity 78%–100%; specificity 71%–81%). Compared to expert opinion, clinicians were able to identify patients with cervical radiculopathy and patients with NSNAP in 80% of cases, our data supporting the reliability of these classification systems.
"The limits of my language are the limits of my mind. All I know is what I have words for" (Wittgenstein). When learning something completely new, we connect the unknown term to an already existing part of our knowledge. We can only build new ideas and insights upon an existing conceptual foundation. In the field of statistics, we educators frequently find ourselves met with great confusion when teaching novices. These students, entirely unfamiliar with even basic statistics, must connect the introduced statistical terms within their personal existing networks of largely non-statistical knowledge. Lecturers, on the other hand, who are well versed in statistics, have deeply internalized the content to be taught and its relevant context. The juxtaposition of the two roles may produce amusement in a lecturer upon gaining insight into the word associations made by the statistical novices. For example, a ‘logistic regression’ does not involve the ‘shipping of goods in economically difficult times,’ though this might seem entirely reasonable and intuitive to the statistics learner. Other times, these different perspectives can lead to headaches and frustration for both learners and their lecturers. In this article, we illustrate how simple statistical terms are initially connected to a student’s pre-exiting knowledge and how these associations change after completing an introductory course in applied statistics. Furthermore, we emphasize the important difference between “term”, “approach”, and “context”. Understanding this fundamental distinction may help improve the communication between the lecturer and the learner. We offer a collection of practical tools for instructors to help promote students’ conceptual understanding in a supportive, mutually-beneficial learning environment.
Background
In mucosal barrier interfaces, flexible responses of gene expression to long-term environmental changes allow adaptation and fine-tuning for the balance of host defense and uncontrolled not-resolving inflammation. Epigenetic modifications of the chromatin confer plasticity to the genetic information and give insight into how tissues use the genetic information to adapt to environmental factors. The oral mucosa is particularly exposed to environmental stressors such as a variable microbiota. Likewise, persistent oral inflammation is the most important intrinsic risk factor for the oral inflammatory disease periodontitis and has strong potential to alter DNA-methylation patterns. The aim of the current study was to identify epigenetic changes of the oral masticatory mucosa in response to long-term inflammation that resulted in periodontitis.
Methods and results
Genome-wide CpG methylation of both inflamed and clinically uninflamed solid gingival tissue biopsies of 60 periodontitis cases was analyzed using the Infinium MethylationEPIC BeadChip. We validated and performed cell-type deconvolution for infiltrated immune cells using the EpiDish algorithm. Effect sizes of DMPs in gingival epithelial and fibroblast cells were estimated and adjusted for confounding factors using our recently developed “intercept-method”. In the current EWAS, we identified various genes that showed significantly different methylation between periodontitis-inflamed and uninflamed oral mucosa in periodontitis patients. The strongest differences were observed for genes with roles in wound healing (ROBO2, PTP4A3), cell adhesion (LPXN) and innate immune response (CCL26, DNAJC1, BPI). Enrichment analyses implied a role of epigenetic changes for vesicle trafficking gene sets.
Conclusions
Our results imply specific adaptations of the oral mucosa to a persistent inflammatory environment that involve wound repair, barrier integrity, and innate immune defense.
Background
In DNA methylation analyses like epigenome-wide association studies, effects in differentially methylated CpG sites are assessed. Two kinds of outcomes can be used for statistical analysis: Beta-values and M-values. M-values follow a normal distribution and help to detect differentially methylated CpG sites. As biological effect measures, differences of M-values are more or less meaningless. Beta-values are of more interest since they can be interpreted directly as differences in percentage of DNA methylation at a given CpG site, but they have poor statistical properties. Different frameworks are proposed for reporting estimands in DNA methylation analysis, relying on Beta-values, M-values, or both.
Results
We present and discuss four possible approaches of achieving estimands in DNA methylation analysis. In addition, we present the usage of M-values or Beta-values in the context of bioinformatical pipelines, which often demand a predefined outcome. We show the dependencies between the differences in M-values to differences in Beta-values in two data simulations: a analysis with and without confounder effect. Without present confounder effects, M-values can be used for the statistical analysis and Beta-values statistics for the reporting. If confounder effects exist, we demonstrate the deviations and correct the effects by the intercept method. Finally, we demonstrate the theoretical problem on two large human genome-wide DNA methylation datasets to verify the results.
Conclusions
The usage of M-values in the analysis of DNA methylation data will produce effect estimates, which cannot be biologically interpreted. The parallel usage of Beta-value statistics ignores possible confounder effects and can therefore not be recommended. Hence, if the differences in Beta-values are the focus of the study, the intercept method is recommendable. Hyper- or hypomethylated CpG sites must then be carefully evaluated. If an exploratory analysis of possible CpG sites is the aim of the study, M-values can be used for inference.
Background
Postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) are frequent and serious complications after surgery. We aim to investigate the association between genetic variants in cholinergic candidate genes according to the Kyoto encyclopedia of genes and genomes - pathway: cholinergic neurotransmission with the development of POD or POCD in elderly patients.
Methods
This analysis is part of the European BioCog project (www.biocog.eu), a prospective multicenter observational study with elderly surgical patients. Patients with a Mini-Mental-State-Examination score ≤ 23 points were excluded. POD was assessed up to seven days after surgery using the Nursing Delirium Screening Scale, Confusion Assessment Method and a patient chart review. POCD was assessed three months after surgery with a neuropsychological test battery. Genotyping was performed on the Illumina Infinium Global Screening Array. Associations with POD and POCD were analyzed using logistic regression analysis, adjusted for age, comorbidities and duration of anesthesia (for POCD analysis additionally for education). Odds ratios (OR) refer to minor allele counts (0, 1, 2).
Results
745 patients could be included in the POD analysis, and 452 in the POCD analysis. The rate of POD within this group was 20.8% (155 patients), and the rate of POCD was 10.2% (46 patients). In a candidate gene approach three genetic variants of the cholinergic genes CHRM2 and CHRM4 were associated with POD (OR [95% confidence interval], rs8191992: 0.61[0.46; 0.80]; rs8191992: 1.60[1.22; 2.09]; rs2067482: 1.64[1.10; 2.44]). No associations were found for POCD.
Conclusions
We found an association between genetic variants of CHRM2 and CHRM4 and POD. Further studies are needed to investigate whether disturbances in acetylcholine release and synaptic plasticity are involved in the development of POD.
A comparison study on modeling of clustered and overdispersed count data for multiple comparisons
(2021)
Data collected in various scientific fields are count data. One way to analyze such data is to compare the individual levels of the factor treatment using multiple comparisons. However, the measured individuals are often clustered – e.g. according to litter or rearing. This must be considered when estimating the parameters by a repeated measurement model. In addition, ignoring the overdispersion to which count data is prone leads to an increase of the type one error rate. We carry out simulation studies using several different data settings and compare different multiple contrast tests with parameter estimates from generalized estimation equations and generalized linear mixed models in order to observe coverage and rejection probabilities. We generate overdispersed, clustered count data in small samples as can be observed in many biological settings. We have found that the generalized estimation equations outperform generalized linear mixed models if the variance-sandwich estimator is correctly specified. Furthermore, generalized linear mixed models show problems with the convergence rate under certain data settings, but there are model implementations with lower implications exists. Finally, we use an example of genetic data to demonstrate the application of the multiple contrast test and the problems of ignoring strong overdispersion.
BACKGROUND:
Intraoperative electroencephalography (EEG) signatures related to the development of postoperative delirium (POD) in older patients are frequently studied. However, a broad analysis of the EEG dynamics including preoperative, postinduction, intraoperative and postoperative scenarios and its correlation to POD development is still lacking. We explored the relationship between perioperative EEG spectra-derived parameters and POD development, aiming to ascertain the diagnostic utility of these parameters to detect patients developing POD.
METHODS:
Patients aged ≥65 years undergoing elective surgeries that were expected to last more than 60 minutes were included in this prospective, observational single center study (Biomarker Development for Postoperative Cognitive Impairment [BioCog] study). Frontal EEGs were recorded, starting before induction of anesthesia and lasting until recovery of consciousness. EEG data were analyzed based on raw EEG files and downloaded excel data files. We performed multitaper spectral analyses of relevant EEG epochs and further used multitaper spectral estimate to calculate a corresponding spectral parameter. POD assessments were performed twice daily up to the seventh postoperative day. Our primary aim was to analyze the relation between the perioperative spectral edge frequency (SEF) and the development of POD.
RESULTS:
Of the 237 included patients, 41 (17%) patients developed POD. The preoperative EEG in POD patients was associated with lower values in both SEF (POD 13.1 ± 4.6 Hz versus no postoperative delirium [NoPOD] 17.4 ± 6.9 Hz; P = .002) and corresponding γ-band power (POD −24.33 ± 2.8 dB versus NoPOD −17.9 ± 4.81 dB), as well as reduced postinduction absolute α-band power (POD −7.37 ± 4.52 dB versus NoPOD −5 ± 5.03 dB). The ratio of SEF from the preoperative to postinduction state (SEF ratio) was ~1 in POD patients, whereas NoPOD patients showed a SEF ratio >1, thus indicating a slowing of EEG with loss of unconscious. Preoperative SEF, preoperative γ-band power, and SEF ratio were independently associated with POD (P = .025; odds ratio [OR] = 0.892, 95% confidence interval [CI], 0.808–0.986; P = .029; OR = 0.568, 95% CI, 0.342–0.944; and P = .009; OR = 0.108, 95% CI, 0.021–0.568, respectively).
CONCLUSIONS:
Lower preoperative SEF, absence of slowing in EEG while transitioning from preoperative state to unconscious state, and lower EEG power in relevant frequency bands in both these states are related to POD development. These findings may suggest an underlying pathophysiology and might be used as EEG-based marker for early identification of patients at risk to develop POD.
Objective:
The cervical mucus plugs are enriched with proteins of known immunological functions. We aimed to characterize the anti-HIV-1 activity of the cervical mucus plugs against a panel of different HIV-1 strains in the contexts of cell-free and cell-associated virus.
Design:
A cohort of consenting HIV-1-negative and HIV-1-positive pregnant women in labour was recruited from Mthatha General Hospital in the Eastern Cape province of South Africa, from whom the cervical mucus plugs were collected in 6 M guanidinium chloride with protease inhibitors and transported to our laboratories at −80 °C.
Methods:
Samples were centrifuged to remove insoluble material and dialysed before freeze--drying and subjecting them to the cell viability assays. The antiviral activities of the samples were studied using luminometric reporter assays and flow cytometry. Time-of-addition and BlaM-Vpr virus-cell fusion assays were used to pin-point the antiviral mechanisms of the cervical mucus plugs, before proteomic profiling using liquid chromatography-tandem mass spectrometry.
Results:
The proteinaceous fraction of the cervical mucus plugs exhibited anti-HIV-1 activity with inter-individual variations and some degree of specificity among different HIV-1 strains. Cell-associated HIV-1 was less susceptible to inhibition by the potent samples whenever compared with the cell-free HIV-1. The samples with high antiviral potency exhibited a distinct proteomic profile when compared with the less potent samples.
Conclusion:
The crude cervical mucus plugs exhibit anti-HIV-1 activity, which is defined by a specific proteomic profile.