Prioritizing otological surgery during the COVID-19 Pandemic

The initial cases of pulmonary infection with the novel corona virus SARS-CoV-2, causing COVID-19, occurred in Wuhan, Hubei Province, China in December 2019 and January 2020 (1). The spread through human-to-human transmission has led to a pandemic with disastrous consequences all over the world. The exponential rate of transmission and no existing vaccine has been a great challenge for all health care systems. A strategy to flatten the curve of transmission was put forward to adjust to the capacities of hospitals and particularly the intensive care units. Governments implemented isolation and social distancing upon societies either with laws or with strong recommendations

Considering Polymorphism in Change-Based Test Suite Reduction

With the increasing popularity of continuous integration, algorithms for selecting the minimal test-suite to cover a given set of changes are in order. This paper reports on how polymorphism can handle false negatives in a previous algorithm which uses method-level changes in the base-code to deduce which tests need to be rerun. We compare the approach with and without polymorphism on two distinct cases ---PMD and CruiseControl--- and discovered an interesting trade-off: incorporating polymorphism results in more relevant tests to be included in the test suite (hence improves accuracy), however comes at the cost of a larger test suite (hence increases the time to run the minimal test-suite).Comment: The final publication is available at link.springer.co

Peroxisome Proliferator-Activated Receptor gamma enhances the activity of a insulin degrading enzyme-like metalloprotease for amyloid-beta clearance.

Peroxisome proliferator-activated receptor gamma (PPARgamma) activation results in an increased rate of amyloid-beta (Abeta) clearance from the media of diverse cells in culture, including primary neurons and glial cells. Here, we further investigate the mechanism for Abeta clearance and found that PPARgamma activation modulates a cell surface metalloprotease that can be inhibited by metalloprotease inhibitors, like EDTA and phenanthroline, and also by the peptide hormones insulin and glucagon. The metalloprotease profile of the Abeta-degrading mechanism is surprisingly similar to insulin-degrading enzyme (IDE). This mechanism is maintained in hippocampal and glia primary cultures from IDE loss-of-function mice. We conclude that PPARgamma activates an IDE-like Abeta degrading activity. Our work suggests a drugable pathway that can clear Abeta peptide from the brain

The Functional Head Impulse Test to Assess Oscillopsia in Bilateral Vestibulopathy

Introduction: Bilateral vestibulopathy (BV) is a chronic condition in which vestibular function is severely impaired or absent on both ears. Oscillopsia is one of the main symptoms of BV. Oscillopsia can be quantified objectively by functional vestibular tests, and subjectively by questionnaires. Recently, a new technique for testing functionally effective gaze stabilization was developed: the functional Head Impulse Test (fHIT). This study compared the fHIT with the Dynamic Visual Acuity assessed on a treadmill (DVAtreadmill) and Oscillopsia Severity Questionnaire (OSQ) in the context of objectifying the experience of oscillopsia in patients with BV.Methods: Inclusion criteria comprised: (1) summated slow phase velocity of nystagmus of <20°/s during bithermal caloric tests, (2) torsion swing tests gain of <30% and/or phase <168°, and (3) complaints of oscillopsia and/or imbalance. During the fHIT (Beon Solutions srl, Italy) patients were seated in front of a computer screen. During a passive horizontal head impulse a Landolt C optotype was shortly displayed. Patients reported the seen optotype by pressing the corresponding button on a keyboard. The percentage correct answers was registered for leftwards and rightwards head impulses separately. During DVAtreadmill patients were positioned on a treadmill in front of a computer screen that showed Sloan optotypes. Patients were tested in static condition and in dynamic conditions (while walking on the treadmill at 2, 4, and 6 km/h). The decline in LogMAR between static and dynamic conditions was registered for each speed. Every patient completed the Oscillopsia Severity Questionnaire (OSQ).Results: In total 23 patients were included. This study showed a moderate correlation between OSQ outcomes and the fHIT [rightwards head rotations (rs = −0.559; p = 0.006) leftwards head rotations (rs = −0.396; p = 0.061)]. No correlation was found between OSQ outcomes and DVAtreadmill, or between DVAtreadmill and fHIT. All patients completed the fHIT, 52% of the patients completed the DVAtreadmill on all speeds.Conclusion: The fHIT seems to be a feasible test to quantify oscillopsia in BV since, unlike DVAtreadmill, it correlates with the experienced oscillopsia measured by the OSQ, and more BV patients are able to complete the fHIT than DVAtreadmill

Diagnostic accuracy and usability of the EMBalance decision support system for vestibular disorders in primary care: proof of concept randomised controlled study results

BACKGROUND: Dizziness and imbalance are common symptoms that are often inadequately diagnosed or managed, due to a lack of dedicated specialists. Decision Support Systems (DSS) may support first-line physicians to diagnose and manage these patients based on personalised data. AIM: To examine the diagnostic accuracy and application of the EMBalance DSS for diagnosis and management of common vestibular disorders in primary care. METHODS: Patients with persistent dizziness were recruited from primary care in Germany, Greece, Belgium and the UK and randomised to primary care clinicians assessing the patients with (+ DSS) versus assessment without (- DSS) the EMBalance DSS. Subsequently, specialists in neuro-otology/audiovestibular medicine performed clinical evaluation of each patient in a blinded way to provide the "gold standard" against which the + DSS, - DSS and the DSS as a standalone tool (i.e. without the final decision made by the clinician) were validated. RESULTS: One hundred ninety-four participants (age range 25-85, mean = 57.7, SD = 16.7 years) were assigned to the + DSS (N = 100) and to the - DSS group (N = 94). The diagnosis suggested by the + DSS primary care physician agreed with the expert diagnosis in 54%, compared to 41.5% of cases in the - DSS group (odds ratio 1.35). Similar positive trends were observed for management and further referral in the + DSS vs. the - DSS group. The standalone DSS had better diagnostic and management accuracy than the + DSS group. CONCLUSION: There were trends for improved vestibular diagnosis and management when using the EMBalance DSS. The tool requires further development to improve its diagnostic accuracy, but holds promise for timely and effective diagnosis and management of dizzy patients in primary care. TRIAL REGISTRATION NUMBER: NCT02704819 (clinicaltrials.gov)

Multinational development and validation of an early prediction model for delirium in ICU patients

Rationale Delirium incidence in intensive care unit (ICU) patients is high and associated with poor outcome. Identification of high-risk patients may facilitate its prevention. Purpose To develop and validate a model based on data available at ICU admission to predict delirium development during a patient’s complete ICU stay and to determine the predictive value of this model in relation to the time of delirium development. Methods Prospective cohort study in 13 ICUs from seven countries. Multiple logistic regression analysis was used to develop the early prediction (E-PRE-DELIRIC) model on data of the first two-thirds and validated on data of the last one-third of the patients from every participating ICU. Results In total, 2914 patients were included. Delirium incidence was 23.6 %. The E-PRE-DELIRIC model consists of nine predictors assessed at ICU admission: age, history of cognitive impairment, history of alcohol abuse, blood urea nitrogen, admission category, urgent admission, mean arterial blood pressure, use of corticosteroids, and respiratory failure. The area under the receiver operating characteristic curve (AUROC) was 0.76 [95 % confidence interval (CI) 0.73–0.77] in the development dataset and 0.75 (95 % CI 0.71–0.79) in the validation dataset. The model was well calibrated. AUROC increased from 0.70 (95 % CI 0.67–0.74), for delirium that developed 6 days. Conclusion Patients’ delirium risk for the complete ICU length of stay can be predicted at admission using the E-PRE-DELIRIC model, allowing early preventive interventions aimed to reduce incidence and severity of ICU delirium

Recalibration of the delirium prediction model for ICU patients (PRE-DELIRIC): a multinational observational study

Purpose Recalibration and determining discriminative power, internationally, of the existing delirium prediction model (PRE-DELIRIC) for intensive care patients. Methods A prospective multicenter cohort study was performed in eight intensive care units (ICUs) in six countries. The ten predictors (age, APACHE-II, urgent and admission category, infection, coma, sedation, morphine use, urea level, metabolic acidosis) were collected within 24 h after ICU admission. The confusion assessment method for the intensive care unit (CAM-ICU) was used to identify ICU delirium. CAM-ICU screening compliance and inter-rater reliability measurements were used to secure the quality of the data. Results A total of 2,852 adult ICU patients were screened of which 1,824 (64 %) were eligible for the study. Main reasons for exclusion were length of stay <1 day (19.1 %) and sustained coma (4.1 %). CAM-ICU compliance was mean (SD) 82 ± 16 % and inter-rater reliability 0.87 ± 0.17. The median delirium incidence was 22.5 % (IQR 12.8–36.6 %). Although the incidence of all ten predictors differed significantly between centers, the area under the receiver operating characteristic (AUROC) curve of the eight participating centers remained good: 0.77 (95 % CI 0.74–0.79). The linear predictor and intercept of the prediction rule were adjusted and resulted in improved re-calibration of the PRE-DELIRIC model. Conclusions In this multinational study, we recalibrated the PRE-DELIRIC model. Despite differences in the incidence of predictors between the centers in the different countries, the performance of the PRE-DELIRIC-model remained good. Following validation of the PRE-DELIRIC model, it may facilitate implementation of strategies to prevent delirium and aid improvements in delirium management of ICU patients