Prediction of hearing recovery in sudden deafness treated with intratympanic steroids

The present study aims to obtain a probability model allowing the prediction of the auditory recovery in patients affected by sudden sensorineural hearing loss treated exclusively with intratympanic steroids. A monocentric retrospective chart review of three-hundred eighty-one patients has been performed. A Probit model was used to investigate the correlation between the success of the treatment (marked or total recovery according to Furuashi's criteria), and the delay between the onset of disease and the beginning of therapy. The age of the patients and the audiometric curve shapes were included in the analysis. Results show that delay is negatively correlated with the variable success. Considering the entire sample, each day of delay decreases by 3% the probability of success. The prediction model shows that for every day that passes from the onset of the disease the probability of success declines in absence of the medical treatment, hence we conclude that early treatment is strongly recommended

Imaging predictors of incident heart failure: a systematic review and meta-analysis

BACKGROUND: Preventing the evolution of subclinical cardiac disease into overt heart failure is of paramount importance. Imaging techniques, particularly transthoracic echocardiography (TTE), are well suited to identify abnormalities in cardiac structure and function that precede the development of heart failure. METHODS: This meta-analysis provides a comprehensive evaluation of 32 studies from 11 individual cohorts, which assessed cardiac indices from TTE (63%), cardiovascular magnetic resonance (CMR; 34%) or cardiac computed tomography (CCT; 16%). Eligible studies focused on measures of left ventricular geometry and function and were highly heterogeneous. RESULTS: Among the variables that could be assessed through a meta-analytic approach, left ventricular systolic dysfunction, defined as left ventricular ejection fraction (LVEF) lower than 50%, and left ventricular dilation were associated with a five-fold [hazard ratio (HR) 4.76, 95% confidence interval (95% CI) 1.85-12.26] and three-fold (HR 3.14, 95% CI 1.37 -7.19) increased risk of heart failure development, respectively. Any degree of diastolic dysfunction conveyed an independent, albeit weaker, association with heart failure (HR 1.48, 95% CI 1.11-1.96), although there was only a trend for left ventricular hypertrophy in predicting incident heart failure (hazard ratio 2.85, 95% CI 0.82-9.85). CONCLUSION: LVEF less than 50%, left ventricular dilation and diastolic dysfunction are independent predictors of incident heart failure among asymptomatic individuals, while left ventricular hypertrophy seems less predictive. These findings may serve as a framework for implementing imaging-based screening strategies in patients at risk of heart failure and inform future studies testing preventive or therapeutic approaches aiming at thwarting or halting the progression from asymptomatic (preclinical) to overt heart failure

Allergy in total knee replacement surgery: Is it a real problem?

Total knee arthroplasty is a common procedure, with extremely good clinical results. Despite this success, it produces 20% unsatisfactory results. Among the causes of these failures is metal hypersensitivity. Metal sensitization is higher in patients with a knee arthroplasty than in the general population and is even higher in patients undergoing revision surgery. However, a clear correlation between metal sensitization and symptomatic knee after surgery has not been ascertained. Surely, patients with a clear history of metal allergy must be carefully examined through dermatological and laboratory testing before surgery. There is no globally accepted diagnostic algorithm or laboratory test to diagnose metal hypersensitivity or metal reactions. The patch test is the most common test to determine metal hypersensitivity, though presenting some limitations. Several laboratory assays have been developed, with a higher sensitivity compared to patch testing, yet their clinical availability is not widespread, due to high costs and technical complexity. Symptoms of a reaction to metal implants present across a wide spectrum, ranging from pain and cutaneous dermatitis to aseptic loosening of the arthroplasty. However, although cutaneous and systemic hypersensitivity reactions to metals have arisen, thereby increasing concern after joint arthroplasties, allergies against implant materials remain quite rare and not a well-known problem. The aim of the following paper is to provide an overview on diagnosis and management of metal hypersensitivity in patients who undergo a total knee arthroplasty in order clarify its real importance

The Population of Tiny Near-Earth Objects Observed by NEOWISE

Only a very small fraction of the asteroid population at size scales comparable to the object that exploded over Chelyabinsk, Russia has been discovered to date, and physical properties are poorly characterized. We present previously unreported detections of 106 close approaching near-Earth objects (NEOs) by the Wide-field Infrared Survey Explorer mission's NEOWISE project. These infrared observations constrain physical properties such as diameter and albedo for these objects, many of which are found to be smaller than 100 m. Because these objects are intrinsically faint, they were detected by WISE during very close approaches to the Earth, often at large apparent on-sky velocities. We observe a trend of increasing albedo with decreasing size, but as this sample of NEOs was discovered by visible light surveys, it is likely that selection biases against finding small, dark NEOs influence this finding.Comment: Accepted to Ap

A hot and fast ultra-stripped supernova that likely formed a compact neutron star binary

Compact neutron star binary systems are produced from binary massive stars through stellar evolution involving up to two supernova explosions. The final stages in the formation of these systems have not been directly observed. We report the discovery of iPTF 14gqr (SN 2014ft), a type Ic supernova with a fast-evolving light curve indicating an extremely low ejecta mass (≈0.2 solar masses) and low kinetic energy (≈2 × 10^(50) ergs). Early photometry and spectroscopy reveal evidence of shock cooling of an extended helium-rich envelope, likely ejected in an intense pre-explosion mass-loss episode of the progenitor. Taken together, we interpret iPTF 14gqr as evidence for ultra-stripped supernovae that form neutron stars in compact binary systems

ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks

Hash codes are efficient data representations for coping with the ever growing amounts of data. In this paper, we introduce a random forest semantic hashing scheme that embeds tiny convolutional neural networks (CNN) into shallow random forests, with near-optimal information-theoretic code aggregation among trees. We start with a simple hashing scheme, where random trees in a forest act as hashing functions by setting `1' for the visited tree leaf, and `0' for the rest. We show that traditional random forests fail to generate hashes that preserve the underlying similarity between the trees, rendering the random forests approach to hashing challenging. To address this, we propose to first randomly group arriving classes at each tree split node into two groups, obtaining a significantly simplified two-class classification problem, which can be handled using a light-weight CNN weak learner. Such random class grouping scheme enables code uniqueness by enforcing each class to share its code with different classes in different trees. A non-conventional low-rank loss is further adopted for the CNN weak learners to encourage code consistency by minimizing intra-class variations and maximizing inter-class distance for the two random class groups. Finally, we introduce an information-theoretic approach for aggregating codes of individual trees into a single hash code, producing a near-optimal unique hash for each class. The proposed approach significantly outperforms state-of-the-art hashing methods for image retrieval tasks on large-scale public datasets, while performing at the level of other state-of-the-art image classification techniques while utilizing a more compact and efficient scalable representation. This work proposes a principled and robust procedure to train and deploy in parallel an ensemble of light-weight CNNs, instead of simply going deeper.Comment: Accepted to ECCV 201

To Learn or Not to Learn Features for Deformable Registration?

Feature-based registration has been popular with a variety of features ranging from voxel intensity to Self-Similarity Context (SSC). In this paper, we examine the question on how features learnt using various Deep Learning (DL) frameworks can be used for deformable registration and whether this feature learning is necessary or not. We investigate the use of features learned by different DL methods in the current state-of-the-art discrete registration framework and analyze its performance on 2 publicly available datasets. We draw insights into the type of DL framework useful for feature learning and the impact, if any, of the complexity of different DL models and brain parcellation methods on the performance of discrete registration. Our results indicate that the registration performance with DL features and SSC are comparable and stable across datasets whereas this does not hold for low level features.Comment: 9 pages, 4 figure

Impact of bileaflet mitral valve prolapse on quantification of mitral regurgitation with cardiac magnetic resonance: a single-center study.

To quantify mitral regurgitation (MR) with CMR, the regurgitant volume can be calculated as the difference between the left ventricular (LV) stroke volume (SV) measured with the Simpson's method and the reference SV, i.e. the right ventricular SV (RVSV) in patients without tricuspid regurgitation. However, for patients with prominent mitral valve prolapse (MVP), the Simpson's method may underestimate the LV end-systolic volume (LVESV) as it only considers the volume located between the apex and the mitral annulus, and neglects the ventricular volume that is displaced into the left atrium but contained within the prolapsed mitral leaflets at end systole. This may lead to an underestimation of LVESV, and resulting an over-estimation of LVSV, and an over-estimation of mitral regurgitation. The aim of the present study was to assess the impact of prominent MVP on MR quantification by CMR. In patients with MVP (and no more than trace tricuspid regurgitation) MR was quantified by calculating the regurgitant volume as the difference between LVSV and RVSV. LVSV <sub>uncorr</sub> was calculated conventionally as LV end-diastolic (LVEDV) minus LVESV. A corrected LVESV <sub>corr</sub> was calculated as the LVESV plus the prolapsed volume, i.e. the volume between the mitral annulus and the prolapsing mitral leaflets. The 2 methods were compared with respect to the MR grading. MR grades were defined as absent or trace, mild (5-29% regurgitant fraction (RF)), moderate (30-49% RF), or severe (≥50% RF). In 35 patients (44.0 ± 23.0y, 14 males, 20 patients with MR) the prolapsed volume was 16.5 ± 8.7 ml. The 2 methods were concordant in only 12 (34%) patients, as the uncorrected method indicated a 1-grade higher MR severity in 23 (66%) patients. For the uncorrected/corrected method, the distribution of the MR grades as absent-trace (0 vs 11, respectively), mild (20 vs 18, respectively), moderate (11 vs 5, respectively), and severe (4 vs 1, respectively) was significantly different (p < 0.001). In the subgroup without MR, LVSV <sub>corr</sub> was not significantly different from RVSV (difference: 2.5 ± 4.7 ml, p = 0.11 vs 0) while a systematic overestimation was observed with LVSV <sub>uncorr</sub> (difference: 16.9 ± 9.1 ml, p = 0.0007 vs 0). Also, RVSV was highly correlated with aortic forward flow (n = 24, R <sup>2</sup>  = 0.97, p < 0.001). For patients with severe bileaflet prolapse, the correction of the LVSV for the prolapse volume is suggested as it modified the assessment of MR severity by one grade in a large portion of patients

Red Parkes-Quasars: Evidence for Soft X-ray Absorption

The Parkes Half-Jansky Flat Spectrum Sample contains a large number of sources with unusually red optical-to-near-infrared continua. If this is to be interpreted as extinction by dust in the line-of-sight, then associated material might also give rise to absorption in the soft X-ray regime. This hypothesis is tested using broadband (0.1-2.4 keV) data from the {\it ROSAT} All-Sky Survey provided by Siebert et al. (1998). Significant ($>3\sigma$ confidence level) correlations between optical (and near-infrared)--to--soft X-ray continuum slope and optical extinction are found in the data, consistent with absorption by material with metallicity and a range in gas-to-dust ratio as observed in the local ISM. Under this simple model, the soft X-rays are absorbed at a level consistent with the range of extinctions ($0< A_{V}< 6$ magnitudes) implied by the observed optical reddening. Excess X-ray absorption by warm (ionised) gas, (ie. a `warm absorber') is not required.Comment: 23 pages of text, 3 figures, to appear in Jan 10 (1999) issue of The Astrophysical Journa