Univariate Statistical Approaches Research Articles

Complement and coagulation cascades activation is the main pathophysiological pathway in early-onset severe preeclampsia revealed by maternal proteomics

Preeclampsia is a pregnancy-specific multisystem disorder and a leading cause of maternal and perinatal morbidity and mortality. The exact pathogenesis of this multifactorial disease remains poorly defined. We applied proteomics analysis on maternal blood samples collected from 14 singleton pregnancies with early-onset severe preeclampsia and 6 uncomplicated pregnancies to investigate the pathophysiological pathways involved in this specific subgroup of preeclampsia. Maternal blood was drawn at diagnosis for cases and at matched gestational age for controls. LC–MS/MS proteomics analysis was conducted, and data were analyzed by multivariate and univariate statistical approaches with the identification of differential pathways by exploring the global human protein–protein interaction network. The unsupervised multivariate analysis (the principal component analysis) showed a clear difference between preeclamptic and uncomplicated pregnancies. The supervised multivariate analysis using orthogonal partial least square discriminant analysis resulted in a model with goodness of fit (R2X = 0.99, p < 0.001) and a strong predictive ability (Q2Y = 0.8, p < 0.001). By univariate analysis, we found 17 proteins statistically different after 5% FDR correction (q-value < 0.05). Pathway enrichment analysis revealed 5 significantly enriched pathways whereby the activation of the complement and coagulation cascades was on top (p = 3.17e−07). To validate these results, we assessed the deposits of C5b-9 complement complex and on endothelial cells that were exposed to activated plasma from an independent set of 4 cases of early-onset severe preeclampsia and 4 uncomplicated pregnancies. C5b-9 and Von Willbrand factor deposits were significantly higher in early-onset severe preeclampsia. Future studies are warranted to investigate potential therapeutic targets for early-onset severe preeclampsia within the complement and coagulation pathway.

An Innovative Lipidomic Workflow to Investigate the Lipid Profile in a Cystic Fibrosis Cell Line.

Altered lipid metabolism has been associated to cystic fibrosis disease, which is characterized by chronic lung inflammation and various organs dysfunction. Here, we present the validation of an untargeted lipidomics approach based on high-resolution mass spectrometry aimed at identifying those lipid species that unequivocally sign CF pathophysiology. Of n.13375 mass spectra recorded on cystic fibrosis bronchial epithelial airways epithelial cells IB3, n.7787 presented the MS/MS data, and, after software and manual validation, the final number of annotated lipids was restricted to n.1159. On these lipids, univariate and multivariate statistical approaches were employed in order to select relevant lipids for cellular phenotype discrimination between cystic fibrosis and HBE healthy cells. In cystic fibrosis IB3 cells, a pervasive alteration in the lipid metabolism revealed changes in the classes of ether-linked phospholipids, cholesterol esters, and glycosylated sphingolipids. Through functions association, it was evidenced that lipids variation involves the moiety implicated in membrane composition, endoplasmic reticulum, mitochondria compartments, and chemical and biophysical lipids properties. This study provides a new perspective in understanding the pathogenesis of cystic fibrosis and strengthens the need to use a validated mass spectrometry-based lipidomics approach for the discovery of potential biomarkers and perturbed metabolism.

ANALISIS UNIVARIAT DAN MULTIVARIAT CONTO SEDIMEN SUNGAI DALAM PENENTUAN POTENSI MINERALISASI LOGAM DI HALMAHERA BAGIAN TIMUR, PROVINSI MALUKU UTARA

Penelitian geokimia dengan mengunakan metode analisis kandungan unsur dari conto endapan sungai aktif -80 mesh merupakan salah satu fase awal eksplorasi terutama untuk menemukan cebakan mineral logam. Halmahera bagian timur dengan tataan geologi yang kompleks dan berada dalam jalur metalogenik yang berpotensi membentuk cebakan logam, menghasilkan rona geokimia yang sangat bervariasi dan menarik. Data geokimia sedimen sungai aktif yang tertuang dalam bentuk peta sebaran unsur menyajikan informasi awal yang penting tentang indikasi mineralisasi untuk ditindaklanjuti ke tahap penelitian lebih rinci, khususnya mineralisasi nikel yang berasosiasi dengan litologi Komplek Ultrabasa.&#x0D; &#x0D; Penafsiran data geokimia di wilayah penelitian dengan pendekatan analisis statistik univariat dan multivariat yang terdiri dari unsur Cu, Pb, Zn, Co, Ni, Mn, Ag, Fe, Cr, dan Au, proses pengayaan unsur geokimia di lingkungan permukaan diperlihatkan oleh asosiasi spasial Co, Ni, Fe dan Mn, yaitu pengayaan unsur disebabkan pengikatan kimiawi (scavenging) oleh oksida Fe dan Mn. Berdasarkan kekerabatan unsur atau hubungan antar unsur diperoleh dua kelompok unsur yaitu ikatan unsur Cu-Pb-Zn-Ag-Cr dan Co-Ni-Mn-Fe-Au, akan tetapi tidak semua kelompok asosiasi unsur dapat dihubungkan dengan litologi di daerah penelitian.

Extracellular volatilomic alterations induced by hypoxia in breast cancer cells.

The metabolic shift induced by hypoxia in cancer cells has notbeen explored at volatilomic level so far. The volatile organic metabolites (VOMs) constitute an important part of the metabolome and their investigation could provide us crucial aspects of hypoxia driven metabolic reconfiguration in cancer cells. To identify the altered volatilomic response induced by hypoxia in metastatic/aggressive breast cancer (BC) cells. BC cells were cultured under normoxic and hypoxic conditions and VOMs were extracted using HS-SPME approach and profiled by standard GC-MS system. Univariate and multivariate statistical approaches (p < 0.05, Log2 FC ≥ 0.58/≤ - 0.58, PC1 > 0.13/< - 0.13) were applied to select the VOMs differentially altered after hypoxic treatment. Metabolic pathway analysis was also carried out in orderto identify altered metabolic pathways induced by the hypoxia in the selected BC cells. Overall, 20 VOMs were found to besignificantly altered (p < 0.05, PC1 > 0.13/< - 0.13) upon hypoxic exposure to BC cells. Further, cell line specific volatilomic alterations were extracted by comparative metabolic analysis of aggressive (MDA-MB-231) vs. non-aggressive (MCF-7) cells incubated under hypoxia and normoxia. In this case, 15 and 12 VOMs each were found to be significantly altered in aggressive cells when exposed to hypoxic and normoxic condition respectively. Out of these, 9 VOMs were found to be uniquely associated with hypoxia, 6 were specific to normoxia and 6 were found common to both the conditions. Formic acid was identified as the most prominent molecule with higher abundance levels in aggressive as compared to non-aggressive cells in both conditions. Furthermore, metabolic pathway analyses revealed that fatty acid biosynthesis and nicotinate and nicotinamide metabolism were significantly altered in aggressive as compared to non-aggressive cells in normoxia and hypoxia respectively. Higher formate overflow was observed in aggressive cells compared to non-aggressive cells incubated under both the conditions, reinforcing its correlation with aggressive and invasive cancer type. Moreover, under hypoxia, aggressive cells preferred to be bioenergetically more efficient whereas, under normoxia, fatty acid biosynthesis was favoured when compared to non-aggressive cells.

Benefit of Anakinra in Treating Pediatric Secondary Hemophagocytic Lymphohistiocytosis.

To assess the benefit of the recombinant human interleukin-1 receptor antagonist anakinra in treating pediatric patients with secondary hemophagocytic lymphohistiocytosis (HLH)/macrophage activation syndrome (MAS) associated with rheumatic and nonrheumatic conditions. A retrospective chart review of all anakinra-treated patients with secondary HLH/MAS was performed at Children's of Alabama from January 2008 through December 2016. Demographic, clinical, laboratory, and genetic characteristics, outcomes data, and information on concurrent treatments were collected from the records and analyzed using appropriate univariate statistical approaches to assess changes following treatment and associations between patient variables and outcomes. Forty-four patients with secondary HLH/MAS being treated with anakinra were identified in the electronic medical records. The median duration of hospitalization was 15 days. The mean pretreatment serum ferritin level was 33,316 ng/ml and dropped to 14,435 ng/ml (57% decrease) within 15 days of the start of anakinra treatment. The overall mortality rate in the cohort was 27%. Earlier initiation of anakinra (within 5 days of hospitalization) was associated with reduced mortality (P = 0.046), whereas thrombocytopenia (platelet count <100,000/μl) and STXBP2 mutations were both associated with increased mortality (P = 0.008 and P = 0.012, respectively). In considering patients according to their underlying diagnosis, those with systemic juvenile idiopathic arthritis (JIA) had the lowest mortality rate, with no deaths among the 13 systemic JIA patients included in the study (P = 0.006). In contrast, those with an underlying hematologic malignancy had the highest mortality rate, at 100% (n = 3). These findings suggest that anakinra appears to be effective in treating pediatric patients with non-malignancy-associated secondary HLH/MAS, especially when it is given early in the disease course and when administered to patients who have an underlying rheumatic disease.

Microbial assemblages and bioindicators as proxies for ecosystem health status: potential and limitations.

Microorganisms play fundamental roles in the diversity and functional stability of environments, including nutrient and energy cycling. However, microbial biodiversity loss and change because of global climate and land use change remain poorly understood. Many microbial taxa exhibit fast growth rates and are highly sensitive to environmental change. This suggests they have potential to be efficient biological indicators to assess and monitor the state of the habitats within which they occur. Here, we describe and illustrate a range of univariate and multivariate statistical approaches that can be used to identify effective microbial indicators of environmental perturbations and quantify changes in microbial communities. We show that the integration of multiple approaches, such as linear discriminant analysis effect size and indicator value analysis, is optimal for the quantification of the effects of perturbation on microbial communities. We demonstrate the most prevalent techniques using microbial community data derived from soils under different land uses. We discuss the limitations to the development and use of microbial bioindicators and identify future research directions, such as the creation of reliable, standardised reference databases to provide baseline metrics that are indicative of healthy microbial communities. If reliable and globally-relevant microbial indicators of environmental health can be developed, there is enormous potential for their use, both as a standalone monitoring tool and via their integration with existing physical, chemical and biological measures of environmental health.

Remotely Sensed Vegetation Indices to Discriminate Field-Grown Olive Cultivars

The application of spectral sensors mounted on unmanned aerial vehicles (UAVs) assures high spatial and temporal resolutions. This research focused on canopy reflectance for cultivar recognition in an olive grove. The ability in cultivar recognition of 14 vegetation indices (VIs) calculated from reflectance patterns (green520–600, red630–690 and near-infrared760–900 bands) and an image segmentation process was evaluated on an open-field olive grove with 10 different scion/rootstock combinations (two scions by five rootstocks). Univariate (ANOVA) and multivariate (principal components analysis—PCA and linear discriminant analysis—LDA) statistical approaches were applied. The efficacy of VIs in scion recognition emerged clearly from all the approaches applied, whereas discrimination between rootstocks appeared unclear. The results of LDA ascertained the efficacy of VI application to discriminate between scions with an accuracy of 90.9%, whereas recognition of rootstocks failed in more than 68.2% of cases.

Otoliths as a tool to study reef fish population structure from coastal islands of South Brazil

ABSTRACTTo promote marine conservation and sustainable resources use it is highly important to understand reef fish population structure and dynamics. The sergeant major, Abudefduf saxatilis, is a common and abundant fish usually found in the Brazilian coasts, being considered a keystone-species for structuring benthic communities on reef habitats in the Atlantic Ocean. This study examined the morphology (shape indices and elliptic Fourier descriptors) and chemistry (Element:Ca) of A. saxatilis sagittal otoliths, collected in seven locations along the coast of South Brazil. Otolith morphology and chemistry were compared at short (range 0.5–2 km) and large (range 70–140 km) spatial scales using univariate and multivariate statistical approaches. Reclassification accuracy rates obtained from linear discrimination function analyses using both morphology and chemistry of otoliths were 61% and 82% for short and large spatial scales, respectively. No clear separation for individuals collected in islands within the Tamboretes Archipelago were observed suggesting that water masses are relatively homogeneous and/or that individuals could be highly mixed over short spatial scales. However, the higher reclassification success of the individuals belonging to Bom Abrigo, Galheta and Paz islands, indicates a limited movement of adults between habitats, a larval retention mechanism or a self-recruitment process occurring at large spatial scales.

Understanding biogeographical patterns in the western Balkan Peninsula using environmental niche modelling and geostatistics in polymorphic Edraianthus tenuifolius.

The Balkan Peninsula represents one of the three southern European glacial refugia where biodiversity persisted throughout the climatically unstable Quaternary. This study considered the ‘refugia within refugia’ model, which assumes the environmental heterogeneity over time and space in larger refugia. To better understand patterns shaped during the Quaternary climatic oscillations, the present and last glacial maximum (LGM) environmental conditions and current morphological variability of Edraianthus tenuifolius, an endemic plant of the western Balkans with a well-known therphical structure, were considered. Potential present and LGM distributions were studied through environmental niche modelling using 161 data of occurrences and six bioclimatic variables, hindcasting the model to LGM conditions using three different global circulation models. To test the geographical variability of the reproductive region, 41 characters of 667 inflorescences from 35 populations within the distribution range were measured. Geographical patterns, using geostatistics together with univariate and multivariate statistical approaches, were analysed. The environmental niche model suggested the current potential distribution in correspondence to its known occurrences. The hindcast to LGM conditions suggested two separate areas of environmental suitability, one in the present-day northern Adriatic coast of Croatia (Istrian Peninsula, Kvarner) and another on the present-day south-eastern Adriatic coast (southern Dalmatia, Montenegro and northern Albania). Morphological variability showed a similar pattern, where southern populations separated from northern populations according to a major split in the central part of its distribution range (central Dalmatia). On other levels, stronger barriers were predicted to separate northern populations from the eastern Istrian Peninsula and the Kvarner area. The results suggested congruent biogeographical patterns to the already known phylogeographical structure. Both environmental niche modelling and the geographical variability of morphological characters suggested spatial partitioning, indicating the potential presence of two separate refugia during the LGM.

Morphological variation among Persian walnut (Juglans regia) genotypes within the population and depending on climatic year

Abstract The main goals of this study were to compare walnut genotypes of spontaneous flora of Romania, based on main sources of phenotypic variability, using both univariate (ANOVA and Tukey tests) and multivariate (PCA) statistical approaches. Six main sources of phenotypic variability (nut length, nut diameter I, nut diameter II, nut weight, kernel weight, kernel ratio) were used for the study. Based on this analysis, the aim is to provide a recommendation for culture, and to find out which of the analyzed walnut genotypes have the optimal values for all the observed traits. The results of the study indicate that the conclusions based on the use of univariate and multivariate statistical methods can be used successfully in identifying genotypes with superior characteristics in genetic diversity assessment studies. Six walnut genotypes (B29, B40, B8, B5, B6, B11) were determined to possess optimal values for all six main sources of phenotypic variability. These results show large phenotypic diversity among the selected walnut genotypes.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (rc = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Evaluation of targeted and untargeted effects-based monitoring tools to assess impacts of contaminants of emerging concern on fish in the South Platte River, CO

Rivers in the arid Western United States face increasing influences from anthropogenic contaminants due to population growth, urbanization, and drought. To better understand and more effectively track the impacts of these contaminants, biologically-based monitoring tools are increasingly being used to complement routine chemical monitoring. This study was initiated to assess the ability of both targeted and untargeted biologically-based monitoring tools to discriminate impacts of two adjacent wastewater treatment plants (WWTPs) on Colorado's South Platte River. A cell-based estrogen assay (in vitro, targeted) determined that water samples collected downstream of the larger of the two WWTPs displayed considerable estrogenic activity in its two separate effluent streams. Hepatic vitellogenin mRNA expression (in vivo, targeted) and NMR-based metabolomic analyses (in vivo, untargeted) from caged male fathead minnows also suggested estrogenic activity downstream of the larger WWTP, but detected significant differences in responses from its two effluent streams. The metabolomic results suggested that these differences were associated with oxidative stress levels. Finally, partial least squares regression was used to explore linkages between the metabolomics responses and the chemical contaminants that were detected at the sites. This analysis, along with univariate statistical approaches, identified significant covariance between the biological endpoints and estrone concentrations, suggesting the importance of this contaminant and recommending increased focus on its presence in the environment. These results underscore the benefits of a combined targeted and untargeted biologically-based monitoring strategy when used alongside contaminant monitoring to more effectively assess ecological impacts of exposures to complex mixtures in surface waters.

Mixed-origins of channel catfish in a large-river tributary

Abstract An understanding of factors responsible for population structure including the origins of individuals from among habitats is fundamental to conservation and management of large-river fishes. The prevalence of population mixing of channel catfish Ictalurus punctatus was evaluated within a large-river tributary environment using information from recent environmental history and natal origin derived from otolith microchemistry. Trace elements in water and otoliths were assessed using univariate and multivariate statistical approaches. Water and otolith trace elements differed among river segments facilitating classification of channel catfish to the river segment of capture. Accuracy of the classification tree model for juvenile channel catfish ranged from 44% to 88%. Recent environmental and natal origin microchemistry signatures suggested the channel catfish population within a large-river tributary comprises individuals from multiple locations. Population demographics of channel catfish is likely influenced by mixing of individuals from across the riverine-network. Consideration of the importance of connectivity between main-stem and tributary systems may, therefore, benefit conservation and management of channel catfish and other large-river fishes displaying similar life-history strategies.

Investigation of urinary volatomic alterations in head and neck cancer: a non-invasive approach towards diagnosis and prognosis

Head and neck cancer (HNC), like many other forms of cancer, is usually detected in advanced stages, causing poor survival outcomes. Lack of specific and sensitive screening markers for early detection of HNC has worsened the scenario for the patients as well as the clinicians. Therefore, identification of efficient, noninvasive and affordable screening marker/methodology with high specificity and sensitivity is imminent need of situation. This study aims to identify and characterize urinary volatomic alterations specific to HNC. Volatomic analysis of urine samples collected from HNC patients (n = 29) and healthy controls (n = 31) was performed using headspace solid phase microextraction coupled to gas chromatography mass spectrometry (GC–MS). Both univariate and multivariate statistical approaches were used to investigate HNC specific volatomic alterations. Statistical analysis revealed a total of 28 metabolites with highest contribution towards discrimination of HNC patients from healthy controls (VIP >1, p < 0.05, Log2 FC ≥0.58/≤−0.57). The discrimination efficiency and accuracy of urinary VOCs was ascertained by ROC curve analysis that allowed the identification of four metabolites viz. 2,6-dimethyl-7-octen-2-ol, 1-butanol, p-xylene and 4-methyl-2-heptanone with highest sensitivity and specificity to discriminate HNC patients from healthy controls. Further, the metabolic pathway analysis identified several dysregulated pathways in HNC patients and their detailed investigations could unravel novel mechanistic insights into the disease pathophysiology. Overall, this study provides valuable fingerprint of the volatile profile of HNC patients, which in turn, might help in improving the current understanding of this form of cancer and lead to the development of non-invasive approaches for HNC diagnosis.

Variations in leopard cat (Prionailurus bengalensis) skull morphology and body size: sexual and geographic influences.

The leopard cat, Prionailurus bengalensis (Kerr, 1792), is one of the most widespread Asian cats, occurring in continental eastern and southeastern Asia. Since 1929, several studies have focused on the morphology, ecology, and taxonomy of leopard cats. Nevertheless, hitherto there has been no agreement on basic aspects of leopard cat biology, such as the presence or absence of sexual dimorphism, morphological skull and body differences between the eleven recognized subspecies, and the biogeography of the different morphotypes. Twenty measurements on 25 adult leopard cat skulls from different Asian localities were analyzed through univariate and multivariate statistical approaches. Skull and external body measurements from studies over the last 77 years were assembled and organized in two categories: full data and summary data. Most of this database comprises small samples, which have never been statistically tested and compared with each other. Full data sets were tested with univariate and multivariate statistical analyses; summary data sets (i.e., means, SDs, and ranges) were analyzed through suitable univariate approaches. The independent analyses of the data from these works confirmed our original results and improved the overview of sexual dimorphism and geographical morphological variation among subspecies. Continental leopard cats have larger skulls and body dimensions. Skulls of Indochinese morphotypes have broader and higher features than those of continental morphotypes, while individuals from the Sunda Islands have skulls with comparatively narrow and low profiles. Cranial sexual dimorphism is present in different degrees among subspecies. Most display subtle sex-related variations in a few skull features. However, in some cases, sexual dimorphism in skull morphology is absent, such as in P. b. sumatranus and P. b. borneoensis. External body measurement comparisons also indicate the low degree of sexual dimorphism. Apart from the gonads, the longer hind foot of male leopard cats is the main feature of sexual dimorphism among P. b. bengalensis (and probably among P. b. horsfieldii too). External body measurements also indicated the absence of sexual dimorphism among individuals of P. b. borneoensis. Inter-subspecific skull comparisons provided a morphometric basis for differentiating some subspecies. Prionailurus b. horsfieldii and P. b. bengalensis were distinguished only by a subtle difference in PM4 size, indicating that overall skull morphology does not appear to support their separate taxonomical status, in spite of the marked differences reported in their coat patterns. Geological events affecting the Sunda Shelf connection between the Sunda Islands and the mainland during the Last Glacial Maximum seem to have influenced directly the morphological pattern shown by leopard cat subspecies nowadays.

Soil nematode assemblages in an acid soil as affected by lime application

Liming can affect soil biota through alterations in soil pH and soil structure. Many earlier studies monitored the responses of soil nematode communities to lime application but they did not come to a consensus and did not use indices of soil nematode community and multivariate statistical approaches developed over the past two decades. The present research explored the short-term effects of lime application on soil nematode communities in an acrisol in threeEucalyptusplantations in southern China. Nematodes were sampled from control and lime-treated plots at three periods from October 2011 to February 2012 at 0-10 cm and 10-20 cm soil depths. Repeated measures ANOVA showed that lime application significantly reduced the abundance of herbivores at 10-20 cm depth during the study. Lime application tended to increase the bacterivore index at 0-10 cm depth over time. Principal response curves of soil nematode community structure, in terms of nematode trophic group composition, revealed that the differences between control and lime application treatments increased over time, primarily because of the decline of fungivores in plots treated with lime. The decline in fungivores resulted mainly from declines ofFilenchusandDitylenchus. The results suggest that the fungal-mediated decomposition channel in the soil food web was suppressed by lime application. Our study also demonstrated that the sensitivity of different nematode genera to lime application varied widely, even for genera within the same trophic group. In particular, the abundance of several bacterivorous genera (Prismatolaimus,Plectus,Wilsonema,Protorhabditis,DiploscapterandHeterocephalobus) gradually declined and that ofRhabditonemaat 0-10 cm depth gradually increased following lime application during the study; two herbivorous genera,TrophotylenchulusandHelicotylenchus, had opposite responses to lime application at 0-10 cm depth. Integrating univariate statistical approaches with multivariate approaches facilitated the analysis of soil nematode responses to lime application.

Dam risk assessment based on univariate versus bivariate statistical approaches: a case study for Argentina

Considering floods as multivariate events allows a better statistical representation of their complexity. In this work the relevance of multivariate analysis of floods for designing or assessing the safety of hydraulic structures is discussed. A flood event is characterized by its peak flow and volume. The dependence between the variables is modelled with a copula. One thousand random pairs of variables are transformed to hydrographs, applying the Beta distribution function. Synthetic floods are routed through a reservoir to assess the risk of overtopping a dam. The resulting maximum water levels are compared to estimations considering the peak flow and volume separately. The analysis is performed using daily flows observed in the River Agrio in Neuquén Province, Argentina, a catchment area of 7300 km2. The bivariate approach results in higher maximum water level values. Therefore the multivariate approach should be preferred for the estimation of design variables.Editor D. Koutsoyiannis; Associate editor S. Grimaldi

Idiopathic sudden sensorineural hearing loss in elderly patients: Univariate and multivariate analysis of potential clinical prognostic factors

Objective: With an estimated incidence of 77 new cases per 100,000 population aged 65 years or above, idiopathic sudden sensorineural hearing loss (ISSNHL) is a common clinical finding in elderly patients. There is a shortage of information on the clinical factors capable of predicting hearing recovery and response to therapy. The aim of the present study was to retrospectively investigate the prognostic value of clinical variables in relation to hearing recovery in a cohort of consecutive elderly patients with ISSNHL. Study design: This investigation considered 49 consecutive elderly patients (≥ 65 years of age) treated for ISSNHL. Clinical parameters (signs, symptoms, comorbidities and treatments) and audiometric data were analysed using univariate and multivariate statistical approaches for prognostic purposes, i.e. to identify any correlation with hearing recovery, expressed according to Wilson's criteria. Results/Conclusions: No clinical signs and symptoms, and no specific therapeutic approaches correlated significantly with hearing recovery after ISSNHL in our multivariate model (p > 0.05). In the univariate analysis, vascular disease correlated significantly with hearing gain after treatment (p = 0.01). Further studies based on larger cohorts (especially in a prospective setting) are needed to further elucidate the prognostic role of clinical parameters in ISSNHL involving elderly patients.

Uni- and multivariate models for investigating potential prognostic factors in idiopathic sudden sensorineural hearing loss

With a worldwide incidence estimated at 8-15 per 100,000 population a year, idiopathic sudden sensorineural hearing loss (ISSHL) is a common clinical finding for otologists. There is a shortage of information on the clinical factors capable of predicting hearing recovery and response to therapy. The aim of the present study was to retrospectively investigate the prognostic value of clinical variables in relation to hearing recovery, in a cohort of 117 consecutive patients with ISSHL. Clinical parameters (signs, symptoms, comorbidities and treatments) and audiometric data were analyzed with univariate and multivariate statistical approaches for prognostic purposes to identify any correlation with hearing recovery, also expressed according to the Wilson criteria. Univariate analysis showed that age and hypertension were significantly related to hearing outcome (p = 0.004 and p = 0.015, respectively). Elderly patients and those with hypertension were at higher risk of experiencing no hearing recovery (OR = 3.25 and OR = 2.89, respectively). Age was an independent prognostic factor on multivariate analysis (p = 0.007). Tinnitus as a presenting symptom showed a trend towards an association with hearing recovery (p = 0.07). The treatment regimen, the time elapsing between the onset of symptoms and the start of therapy (p = 0.34), and the duration of the treatment (p = 0.83) were unrelated to recovery on univariate analysis. Among the parameters considered, only age was significantly and independently related to hearing outcome. There is a need for well-designed, randomized clinical trials to enable an evidence-based protocol to be developed for the treatment of ISSHL.

Recent Findings and Newer Paradigms of Neuroimaging Research in Geriatric Psychiatry

Over the past several decades, there has been a significant increase in the population of older adults and associated mental health problems throughout the world. For older adults, mental health problems such as dementia, depression, psychosis, and anxiety disorders can be debilitating and reduce the overall health and quality of life. Moreover, as most of the geriatric psychiatric disorders are not easily diagnosed and treated, it is important to understand the neurobiological mechanisms of these disorders, as this understanding promises to improve clinical care. In this regard, a large number of neuroimaging techniques are being developed and are used for research, with some ultimately entering clinical practice. In 1999, the special issue of the Journal of Geriatric Psychiatry and Neurology reviewed a broad spectrum of neuroimaging and related modalities such as magnetic resonance imaging (MRI), magnetic resonance spectroscopy, positron emission tomography (PET), quantitative electroencephalogram, and computed tomography with comprehensive articles describing methods and observations in normal aging and related psychopathologic states. Since 1999, there has been even further significant progress in neuroimaging research. Molecular imaging using PET can detect detrimental effects occurring in the brain on a molecular basis. The recent advances in structural and functional MRI methodologies open the ways to application of neuroimaging techniques to common clinical situations such as diagnosis and personalized treatment. Moreover, advances in network theory may enable us to understand the pathophysiological mechanisms in the brain as a disruption to a network. This special issue of the Journal of Geriatric Psychiatry and Neurology brings together internationally recognized experts in the imaging field to address these key issues. Reza Tadayonnejad and Olusola Ajilore discuss brain network dysfunction in late-life depression. To date, several studies have highlighted structural and functional abnormalities of frontal, striatal, temporal, and parietal areas in late-life depression. These abnormalities might result in a broad range of negative impacts on mood, cognition, and global functioning in patients with late-life depression. Although the widespread nature of structural damage in latelife depression is suggestive of a system disorder resulting in disrupted networks, studies based on the univariate statistical approaches for analyzing functional and structural imaging have a limited ability to test such hypotheses. In this regard, multivariate and patternwise perspectives using network theory provide a new paradigm for understanding the complex neurobiological mechanisms of late-life depression. In this review, a network dysfunction model is used as a conceptual framework for reviewing recent neuroimaging findings in late-life depression. Kentaro Hirao and Gwen Smith discuss recent developments in the molecular imaging using PET in late-life depression. With the development of sensitive and accurate instrumentation and radiotracer chemistry, molecular PET imaging can detect in vivo the precise neurobiological process of various geriatric neuropsychiatric disorders including Alzheimer disease, Parkinson disease, and late-life depression. They review the recent advances and literature in molecular imaging in geriatric psychiatric disease, with a focus on late-life depression. Interestingly, they provide the future directions of the molecular imaging studies integrating molecular imaging with genetic, neuropsychiatric, and cognitive outcomes, multimodality neuroimaging. Howard Aizenstein and colleagues discuss the clinical application of the neuroimaging methods to predict the treatment response to antidepressant medications. A number of imaging studies have demonstrated that pretreatment structural and functional MRI markers are predictive of an individual’s response to standard antidepressant pharmacotherapy. This article reviews the literature on MRI prediction of treatment response and discusses how these findings can be relevant to personalizing treatment of late-life depression. Chris Abott discusses the several reports of neuroimaging studies on longitudinal electroconvulsive therapy (ECT). The ECT is known to be one of the most effective treatments for refractory depression and other psychiatric disorders; however, the precise neurobiological mechanism of action and neural correlates of treatment response are poorly understood.