Bispectral index versus COMFORT score to determine the level of sedation in paediatric intensive care unit patients: a prospective study

INTRODUCTION: Most clinicians give sedatives and analgesics according to their professional experience and the patient's estimated need for sedation. However, this approach is prone to error. Inadequate monitoring of sedation and analgesia may contribute to adverse outcomes and complications. With this in mind, data obtained continuously using nonstimulating methods such as bispectral index (BIS) may have benefits in comparison with clinical monitoring of sedation. The aim of this prospective observational trial was to evaluate the use of electroencephalographic (EEG) BIS for monitoring sedation in paediatric intensive care unit (PICU) patients. METHODS: Forty paediatric patients (<18 years) were sedated for mechanical ventilation in a cardiac surgical and general PICU. In each paediatric patient BIS and COMFORT score were obtained. The study protocol did not influence ongoing PICU therapy. BIS and corresponding COMFORT score were collected three times for each patient. Measurements with the best starting EEG impedances were analyzed further. Deep sedation was defined as a COMFORT score between 8 and 16, and light sedation as a score between 17 and 26. Biometric and physiological data, and Pediatric Risk of Mortality III scores were also recorded. RESULTS: There was a good correlation (Spearman's rho 0.651; P = 0.001) between BIS and COMFORT score in the presence of deep sedation and low starting impedance. Receiver operating characteristic (ROC) analysis revealed best discrimination between deep and light sedation at a BIS level of 83. CONCLUSION: In the presence of deep sedation, BIS correlated satisfactorily with COMFORT score results if low EEG impedances were guaranteed

Efficacy and safety of intratumoral thermotherapy using magnetic iron-oxide nanoparticles combined with external beam radiotherapy on patients with recurrent glioblastoma multiforme

Therapy options at the time of recurrence of glioblastoma multiforme are often limited. We investigated whether treatment with a new intratumoral thermotherapy procedure using magnetic nanoparticles improves survival outcome. In a single-arm study in two centers, 66 patients (59 with recurrent glioblastoma) received neuronavigationally controlled intratumoral instillation of an aqueous dispersion of iron-oxide (magnetite) nanoparticles and subsequent heating of the particles in an alternating magnetic field. Treatment was combined with fractionated stereotactic radiotherapy. A median dose of 30 Gy using a fractionation of 5 × 2 Gy/week was applied. The primary study endpoint was overall survival following diagnosis of first tumor recurrence (OS-2), while the secondary endpoint was overall survival after primary tumor diagnosis (OS-1). Survival times were calculated using the Kaplan–Meier method. Analyses were by intention to treat. The median overall survival from diagnosis of the first tumor recurrence among the 59 patients with recurrent glioblastoma was 13.4 months (95% CI: 10.6–16.2 months). Median OS-1 was 23.2 months while the median time interval between primary diagnosis and first tumor recurrence was 8.0 months. Only tumor volume at study entry was significantly correlated with ensuing survival (P < 0.01). No other variables predicting longer survival could be determined. The side effects of the new therapeutic approach were moderate, and no serious complications were observed. Thermotherapy using magnetic nanoparticles in conjunction with a reduced radiation dose is safe and effective and leads to longer OS-2 compared to conventional therapies in the treatment of recurrent glioblastoma

The effects of the misspecification of measurement-error correlations on parameter estimation in linear structural equation models in the diagnosis of glaucoma

Strukturgleichungsmodelle (SEMs) kombinieren Pfadanalysen und Faktorenanalysen und erlauben die Analyse von postulierten Kausalstrukturen für latente Variable bzw. nicht messbare Konstrukte. Lineare Strukturgleichungsmodelle sind insbesondere in der medizinischen Diagnostik gut anwendbar. Denn bei der Diagnose von Krankheiten handelt es sich um die Bestimmung von Phänomenen, die sich häufig unmittelbarer Messung (Beobachtung) entziehen und vielfach nur mittelbar über verschiedene Indikatoren (diagnostische Messver-fahren) feststellbar sind. SEMs ermöglichen die Bewertung von Referenz- und neuen Diagnoseverfahren unter Berücksichtigung von Störgrößen und zeigen auf, wie gut diese den globalen Glaukomschaden quantifizieren. Da es in der Glaukomdiagnose bislang keinen allgemeinen "Goldstandard" gibt, ist ein individueller Patientenindex für den Glaukomschweregrad auf Basis von SEMs ist die beste Annäherung an einen solchen. Fehlspezifikation in einem SEM zur Glaukomdiagnose kann jedoch zu Fehlinterpretation und letztlich zu gravierenden medizinischen Fehlentscheidungen führen und ist daher zu vermeiden. Es werden verschiedene Typen von Messmodellen und vollständigen Strukturgleichungsmodellen systematisch untersucht. Zur Durchführung dieser Analyse werden normalverteilte Daten mit vorher festgelegten Stichprobenmomenten erster und zweiter Ordnung erzeugt. Auf diese Weise können Modelle entwickelt und getestet werden, deren modellimplizite Kovarianzmatrix beliebig große Abweichungen zur so generierten "empirischen" Kovarianzmatrix aufweisen und demnach vollkommen richtig oder auch fehlspezifiziert sind. Fehlspezifikation besteht u. a. dann, wenn (latente) Fehlervariable tatsächlich korreliert sind, jedoch im Modell unkorrelierte Fehler angenommen werden. Dies führt zu erwartungsgemäß verzerrten Pfadkoeffizienten sowohl der Messmodelle als auch des Strukturmodells, aber nur unter bestimmten Umständen zur Modellablehnung. Nach mehrfacher Stichprobenziehung aus den generierten Daten (Simulation) werden Standardfehler (SE) von Modellparametern empirisch ermittelt, dem Mittelwert der modellbasiert geschätzten SE gegenübergestellt und in Fortführung der systematischen Untersuchung Ergebnisse erzielt, die a priori nicht zu erwarten gewesen wären. Im Falle der Messmodellpfadkoeffizienten überschätzt selbst in korrekt spezifizierten Modellen der mittlere geschätzte SE den empirischen um mindestens 25 %, so dass ein Korrekturfaktor von 0,8 vorgeschlagen wird. (In Modellen mit fehlspezifizierten Fehlerkorrelationen ist der modellbasiert geschätzte SE konservativer.) Da es sich beim Auge um ein paariges Organ handelt, ist in statistischen Analysen, die beide Augen eines Probanden einbeziehen, die statistische Abhängigkeit der beiden Augen (eines Individuums) voneinander zu berücksichtigen. Dies betrifft zum einen die Schätzung der SE der Pfadkoeffizienten, die in der Modellentwicklung bei der Entscheidung über die ins Modell aufzunehmenden Indikatoren bedeutsam sind, und zum anderen die Interpretation des globalen Tests für die Güte der Modellanpassung an die Daten. Nachdem softwarebedingt eine Berücksichtigung bislang nicht möglich erschien, zeigen nonparametrische Bootstrapping-Analysen auf Basis von synthetischen Daten, wie ein Korrekturfaktor für den SE des Pfadkoeffizienten von der Korrelation der Diagnoseverfahren zwischen linkem und rechtem Auge abhängt: Durch Zerlegung eines jeden dieser Verfahren in einen Anteil des latenten Glaukomschweregrads und einen latenten Messfehleranteil wird demonstriert, dass letzterer einen bedeutend stärkeren Einfluss auf den Korrekturfaktor besitzt. Anschließend werden Bootstrapping-Analysen an Patientendaten durchgeführt, die dem Erlanger Glaukomregister entstammen und auf Basis eines diagnostischen Messmodells mit acht Indikatoren bereits untersucht wurden (Martus, 2001). Bei einer Seitenkorrelation der Messverfahren in Höhe von 0,60 - 0,82 ergibt sich zum einen, dass die nicht nach Paarigkeit adjustierten SE der jeweiligen Pfadkoeffizienten um den Faktor 1,13 - 1,33 zur Berücksichtigung der intraindividuellen Abhängigkeit erhöht werden müssen. Zum anderen stellt sich heraus, dass das o. g. naive Bootstrapping zur Ermittlung eines entsprechenden Korrekturfaktors für den Chi-Quadrat-Wert des globalen Tests der Modellanpassungsgüte nicht geeignet ist. Deshalb wird eine von Bollen und Stine entwickelte Prozedur vorgeschlagen, bei der die Daten zunächst auf Modellkonformität transformiert und erst dann Boostrapping-Analysen durchgeführt werden. Die Methode zur Adjustierung der SE interessierender Pfadkoeffizienten lässt sich auch auf Daten mit komplexeren Clusterstrukturen übertragen (z. B. Messungen von Patienten mit einem oder zwei erkrankten paarigen Organen). Das publizierte Messmodell zur Glaukomdiagnose beinhaltet acht Verfahren, die durch den allgemeinen Glaukomschweregrad beeinflusst werden und in 3 Gruppen zu klassifizieren sind: Morphometrische (1), elektrophysiologische (3) und psychophysische Diagnoseverfahren (4). Letztere und ein elektrophysiologisches Verfahren sind laut Modell zusätzlich von der Konzentration der Probanden abhängig, so dass dieses Modell nicht nur einen Traitfaktor (Glaukomschweregrad) sondern auch einen Methodenfaktor (Konzentration) enthält. Es treten drei Phänomene auf, die die Messung der Reliabilität durch Cronbachs alpha bei dieser Modellstruktur als nicht ratsam erscheinen lassen: Die Korreliertheit der Fehlerterme führt zu Überschätzung, wohingegen Multidimensionalität und die Kongenerizität des Messmodells Unterschätzung bewirken. Die antagonistischen Effekte heben einander gerade auf, so dass die Reliabilität nach Cronbachs alpha hier mit der wahren Reliabilität (Yang et al., 2012) übereinstimmt (85 %). Um die wahre Reliabilität dieses Modells zu erhöhen, werden 2 weitere Methodenfaktoren implementiert. Der erste ersetzt eine von fünf Fehlerkorrelationen und wird mit "Visuell evoziertes Potential" bezeichnet, da er zwei elektrophysiologische Verfahren (Latenzzeit und Amplitude des visuell evozierten Potentials) beeinflusst. Zwei psychophysische Verfahren speisen sich aus der "Automatischen Perimetrie" und sind somit durch den entsprechend benannten zweiten Methodenfaktor beeinflusst. Diese Modelloptimierung bewirkt ein Absinken der wahren Unreliabilität um ein Drittel auf 10 %, so dass die systematische Fehlervarianz weitgehend erfasst ist (und sich eine wahre Reliabilität von 90 % ergibt).Structural Equation Models (SEMs) combine path analyses and factor analyses, thus making it possible to analyze postulated causal structures for latent variables or non-measurable constructs. Linear Structural Equation Models are particularly applicable to medical diagnoses. This is because diagnosing diseases is about identifying phenomena that often defy actual measurement (observation) and can only be detected through various indicators (diagnostic measuring procedures). SEMs permit the evaluation of reference and new diagnostic procedures – taking account of confounding variables – and show how well they can quantitate global glaucoma damage. Since there is still no universal “gold standard” for diagnosing glaucoma, the best approximation for judging its severity is applying SEMs to an individual patient index. However, misspecifications in an SEM used for diagnosing glaucoma can lead to misinterpretations and eventually, to serious medical mistakes. For that reason, they should be avoided. Various types of measurement models and complete SEMs are systematically analyzed and normally distributed data with predetermined sample moments of the first and second order are generated. This way, models can be developed and tested whose implicit covariance matrix will display deviations of any size from the generated “empirical” covariance matrix and are either totally correct or incorrectly specified. Specification error can happen when (latent) error variables are correlated but errors are hypothesized as uncorrelated in the model. This leads to distorted path coefficients both in the measurement models and the structural model. However, only in certain circumstances does specification error lead to rejection of the model. After using the generated data for multiple random samplings (simulation), standard errors (SE) are empirically determined from model parameters and compared with the mean of the model-based estimated SE, which returns a priori unexpected results through systematic testing. When measuring model path coefficients, even in correctly specified models the mean estimated SE over-estimates the empirically determined SE by at least 25%, so that a correction factor of 0.8% is suggested. (In models with misspecified error correlations, the model-based estimated SE is more conservative.) Because the eyes are a paired organ, statistical analyses that involve both eyes of a single test subject must consider the statistical interdependence of the two eyes. This applies to the estimation of the SE of the path coefficients that are significant for deciding which indicators to include in the model being developed, as well as to interpreting the global test about how well the model fits the data. Once it seemed impossible to use software. Now, however, non-parametric bootstrapping analyses based on synthetic data are demonstrating how a correction factor for the SE of the path coefficients is dependent on the correlation between the diagnostic procedures for the left and right eyes. Breaking down all these diagnostic procedures into a share of the glaucoma’s latent severity and a share of latent measurement errors demonstrates that the latter has significantly greater influence on the correction factor. Bootstrapping analyses are then conducted of patient data from the Erlanger Glaucoma Registry that had been tested using diagnostic models with eight measurements (Martus, 2001). A lateral correlation of the measurement procedure at the level of 0.60 – 0.82 reveals the need to increase the SE not adjusted to the pairing of the relevant path coefficients by a factor of 1.13 – 1.32 with regard to the intra-individual dependence. It also becomes clear that such naive bootstrapping is not appropriate for determining a corresponding corrective factor for the chi-squared values of the global test of the model’s goodness-of-fit. A procedure developed by Bollen and Stine is suggested in which data are transformed to conform to the model before bootstrapping analyses are conducted. The methods for adjusting the SE path coefficients can also be applied to data with more complex cluster structures (e.g., measurements of patients with one or two diseased paired organs). The measurement model that has been issued for diagnosing glaucoma contains eight procedures influenced by the glaucoma’s general severity, which can be classified in three groups: morphometric (1 PCR), electrophysiological (3 PCRs) and psychophysical diagnostic procedures (4 PCRs). According to the model, the last four psychophysical procedures, as well as one electrophysiological procedure, are also dependent on the test subject’s concentration. So this model does not just include a trait factor (the severity of the glaucoma), it also includes a method factor (“psychophysical aspects of measurement” or “concentration”). The appearance of three phenomena makes it inadvisable to use Cronbachs Alpha to measure reliability with this model structure: The correlation of error terms leads to over-estimation, while the multidimensionality and congenericity of the measurement model cause the reliability to be under-estimated. The antagonistic effects cancel each other out so that the reliability using Cronbachs Alpha concurs with the true-score reliability (85%) (Yang et al., 2012). Two other method factors are implemented to increase the model’s true-score reliability. Because the first (method factor) influences two electrophysiological procedures (the latency period and the amplitude of the visually evoked potential), it is referred to as “visually evoked potential” and replaces one of the five error correlations. Two psychophysical procedures come from the “automated perimetry” and are thus influenced by the appropriately termed “second method factor”. This optimization model causes the true-score reliability to drop by a third to 10%, so that the systematic error variance is extensively recorded (and results in a true-score reliability of 90%)

Prevalence, Severity, and Severity Risk Factors of Acne in High School Pupils: A Community-Based Study

A cross-sectional, community-based study was performed to determine the prevalence and severity of acne vulgaris in adolescents and of factors influencing the acne severity risk. The presence of acne was clinically determined and the secondary outcome measures of family acne history and the relation of acne to nutrition habits, emotional stress, menstruation, and smoking were recorded in a questionnaire. A representative sample of 1,002 pupils aged 16±0.9 years was enrolled. The overall acne prevalence was 93.3, 94.4% for boys and 92.0% for girls. Moderate to severe acne was observed in 14%. The prevalence of moderate to severe acne was 19.9% in pupils with and 9.8% in those without a family history of acne (P<0.0005; OR: 2.3). Acne severity risk increased with the number of family members with acne history. A mother with acne history influenced the severity of acne the most. Increasing pubertal age, seborrhea, the premenstrual phase, mental stress, and sweet and oily foods were recognized as risk factors for moderate to severe acne. In contrast, gender, spicy foods, and smoking were not associated with acne severity. In conclusion, acne is a common disorder in Iranian adolescents, with a low rate of moderate to severe acne. A genetic background is suggested, with mother's acne history being the most important prognostic factor. Skin quality and certain nutrition habits may affect acne severity

Computer game misuse and addiction of adolescents in a clinically referred study sample

Background: Actually it remains unclear whether specific psychiatric disorders, especially emotional disorders and attention deficit hyperactivity disorder (ADHD), may be meaningful in the pathogenesis of computer game misuse. Objective: In this clinical study with adolescent psychiatric patients we expected a moderate to strong correlation between computer game misuse and emotional, conduct and peer problems, as well as symptoms of ADHD. Method: 183 patients (14.9 +/- 1.5 years) from a child and adolescent psychiatric clinic were assessed for computer game misuse or addiction using the CSV-S scale in order to distinguish between regular and excessive computer gaming. The Strengths and Difficulties Questionnaire (SDQ) was used to screen for actual emotional and behavioral difficulties. Results: Within the patients' group with problematic computer gaming especially male patients with the highest addiction score spent significantly more time on computer gaming and presented more school performance problems as well as other comorbidities. Excessive gaming correlated significantly with conduct and emotional problems. No specific psychiatric disorders correlated to computer game misuse or addiction. Conclusion: Misuse or addiction of computer games in psychiatric patients seems to be related to an increased rate of conduct and emotional problems but related specific psychiatric diagnoses could not be identified. (C) 2015 Elsevier Ltd. All rights reserved

Nicotine and biochanin A, but not cigarette smoke, induce anti-inflammatory effects on keratinocytes and endothelial cells in patients with Behcet's disease

During periods of smoking, patients with Behcet's disease have less oral aphthae than in abstinence. To elucidate this observation, human keratinocytes and dermal microvascular endothelial cells (HMEC-1) were incubated with serum of 20 patients with Behcet's disease and 20 healthy controls for 4 hours. Maximum non-toxic concentrations were determined and the cells were further treated with 6 mu M nicotine, 3.3% cigarette smoke extract (CES), 100 mu M biochanin A, and 6.25/12.5 mu M pyrrolidine dithiocarbamate alone and in combinations for 24 hours. Serum IL-8 levels of patients were significantly lower than those of controls. However, after 4 hours incubation with patients' sera, IL-8 release by both cell types was markedly increased when compared with the corresponding serum levels. The levels of IL-6 and vascular endothelial growth factor (VEGF) release were after 4 hours similar with the corresponding levels in serum. IL-1 was not detected. Nicotine significantly decreased IL-8 and -6 release by HMEC-1 maintained in both patients' and controls' sera, but only IL-6 release by keratinocytes maintained in patients' sera. VEGF release by both cells was markedly increased after nicotine treatment in either serum. CES significantly decreased IL-8 release and increased production of VEGF in keratinocytes maintained in patients' serum. The phytoestrogen biochanin A alone and in combination with nicotine further decreased the secretion of IL-8, -6, and VEGF in all experimental settings. Our data support a specific anti-inflammatory effect of nicotine on keratinocytes and endothelial cells maintained in the serum of patients with Behcet's disease. Moreover, biochanin A is likely to exhibit similar and even more profound results than nicotine