41 research outputs found

    Analysis and Quantification of Chronic Obstructive Pulmonary Disease Based on HRCT Images

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    Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images

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    A method for automatically quantifying emphysema regions using High-Resolution Computed Tomography (HRCT) scans of patients with chronic obstructive pulmonary disease (COPD) that does not require manually annotated scans for training is presented. HRCT scans of controls and of COPD patients with diverse disease severity are acquired at two different centers. Textural features from co-occurrence matrices and Gaussian filter banks are used to characterize the lung parenchyma in the scans. Two robust versions of multiple instance learning (MIL) classifiers, miSVM and MILES, are investigated. The classifiers are trained with the weak labels extracted from the forced expiratory volume in one minute (FEV1_1) and diffusing capacity of the lungs for carbon monoxide (DLCO). At test time, the classifiers output a patient label indicating overall COPD diagnosis and local labels indicating the presence of emphysema. The classifier performance is compared with manual annotations by two radiologists, a classical density based method, and pulmonary function tests (PFTs). The miSVM classifier performed better than MILES on both patient and emphysema classification. The classifier has a stronger correlation with PFT than the density based method, the percentage of emphysema in the intersection of annotations from both radiologists, and the percentage of emphysema annotated by one of the radiologists. The correlation between the classifier and the PFT is only outperformed by the second radiologist. The method is therefore promising for facilitating assessment of emphysema and reducing inter-observer variability.Comment: Accepted at PLoS ON

    Transfer learning for multicenter classification of chronic obstructive pulmonary disease

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    Chronic obstructive pulmonary disease (COPD) is a lung disease which can be quantified using chest computed tomography (CT) scans. Recent studies have shown that COPD can be automatically diagnosed using weakly supervised learning of intensity and texture distributions. However, up till now such classifiers have only been evaluated on scans from a single domain, and it is unclear whether they would generalize across domains, such as different scanners or scanning protocols. To address this problem, we investigate classification of COPD in a multi-center dataset with a total of 803 scans from three different centers, four different scanners, with heterogenous subject distributions. Our method is based on Gaussian texture features, and a weighted logistic classifier, which increases the weights of samples similar to the test data. We show that Gaussian texture features outperform intensity features previously used in multi-center classification tasks. We also show that a weighting strategy based on a classifier that is trained to discriminate between scans from different domains, can further improve the results. To encourage further research into transfer learning methods for classification of COPD, upon acceptance of the paper we will release two feature datasets used in this study on http://bigr.nl/research/projects/copdComment: Accepted at Journal of Biomedical and Health Informatic

    Clustering treatment outcomes in women with gambling disorder

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    The rising prevalence of gambling disorder (GD) among women has awakened considerable interest in the study of therapeutic outcomes in females. This study aimed to explore profles of women seeking treatment for GD based on a set of indicators including sociodemographic features, personality traits, clinical state at baseline, and cognitive behavioral therapy (CBT) outcomes. Two-step clustering, an agglomerative hierarchical classifcation system, was applied to a sample of n=163 women of ages ranging from 20 to 73 yearsold, consecutively attended to by a clinical unit specialized in the treatment of G. Three mutually exclusive clusters were identifed. Cluster C1 (n=67, 41.1%) included the highest proportion of married, occupationally active patients within the highest social status index. This cluster was characterized by medium GD severity levels, the best psychopathological functioning, and the highest mean in the self-directedness trait. C1 registered 0% dropouts and only 14.9% relapse. Cluster C2 (n=63; 38.7%) was characterized by the lowest GD severity, medium scores for psychopathological measures and a high risk of dropout during CBT. Cluster C3 (n=33; 20.2%) registered the highest GD severity, the worst psychopathological state, the lowest self-directedness level and the highest harm-avoidance level, as well as the highest risk of relapse. These results provide new evidence regarding the heterogeneity of women diagnosed with GD and treated with CBT, based on the profle at preand post-treatment. Person-centered treatments should include specifc strategies aimed at increasing self-esteem, emotional regulation capacities and self-control of GD women

    Anandamide and 2-arachidonoylglycerol baseline plasma concentrations and their clinical correlate in gambling disorder

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    Introduction Different components of the endocannabinoid (eCB) system such as their most well-known endogenous ligands, anandamide (AEA) and 2-arachidonoylglycerol (2-AG), have been implicated in brain reward pathways. While shared neurobiological substrates have been described among addiction-related disorders, information regarding the role of this system in behavioral addictions such as gambling disorder (GD) is scarce.AimsFasting plasma concentrations of AEA and 2-AG were analyzed in individuals with GD at baseline, compared with healthy control subjects (HC). Through structural equation modeling, we evaluated associations between endocannabinoids and GD severity, exploring the potentially mediating role of clinical and neuropsychological variables.MethodsThe sample included 166 adult outpatients with GD (95.8% male, mean age 39 years old) and 41 HC. Peripheral blood samples were collected after overnight fasting to assess AEA and 2-AG concentrations (ng/ml). Clinical (i.e., general psychopathology, emotion regulation, impulsivity, personality) and neuropsychological variables were evaluated through a semi-structured clinical interview and psychometric assessments.ResultsPlasma AEA concentrations were higher in patients with GD compared with HC (p = .002), without differences in 2-AG. AEA and 2-AG concentrations were related to GD severity, with novelty-seeking mediating relationships.ConclusionsThis study points to differences in fasting plasma concentrations of endocannabinoids between individuals with GD and HC. In the clinical group, the pathway defined by the association between the concentrations of endocannabinoids and novelty-seeking predicted GD severity. Although exploratory, these results could contribute to the identification of potential endophenotypic features that help optimize personalized approaches to prevent and treat GD

    Does Confinement Affect Treatment Dropout Rates in Patients With Gambling Disorder? A Nine-Month Observational Study

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    Background and Aims: COVID-19 pandemic and confinement have represented a challenge for patients with gambling disorder (GD). Regarding treatment outcome, dropout may have been influenced by these adverse circumstances. The aims of this study were: (a) to analyze treatment dropout rates in patients with GD throughout two periods: during and after the lockdown and (b) to assess clinical features that could represent vulnerability factors for treatment dropout. Methods: The sample consisted of n=86 adults, mostly men (n=79, 91.9%) and with a mean age of 45years old (SD=16.85). Patients were diagnosed with GD according to DSM-5 criteria and were undergoing therapy at a Behavioral Addiction Unit when confinement started. Clinical data were collected through a semi-structured interview and protocolized psychometric assessment. A brief telephone survey related to COVID-19 concerns was also administered at the beginning of the lockdown. Dropout data were evaluated at two moments throughout a nine-month observational period (T1: during the lockdown, and T2: after the lockdown). Results: The risk of dropout during the complete observational period was R=32/86=0.372 (37.2%), the Incidence Density Rate (IDR) ratio T2/T1 being equal to 0.052/0.033=1.60 (p=0.252). Shorter treatment duration (p=0.007), lower anxiety (p=0.025), depressive symptoms (p=0.045) and lower use of adaptive coping strategies (p=0.046) characterized patients who abandoned treatment during the lockdown. Briefer duration of treatment Baenas et al. Lockdown and GD: Treatment Dropout Frontiers in Psychology | www.frontiersin.org 2 December 2021 | Volume 12 | Article 761802 (p=0.001) and higher employment concerns (p=0.044) were highlighted in the individuals who dropped out after the lockdown. Treatment duration was a predictor of dropout in both periods (p=0.005 and p<0.001, respectively). Conclusion: The present results suggest an impact of the COVID-19 pandemic on treatment dropout among patients with GD during and after the lockdown, being treatment duration a predictor of dropout. Assessing vulnerability features in GD may help clinicians identify high-risk individuals and enhance prevention and treatment approaches in future similar situations

    The influence of chronological age on cognitive biases and impulsivity levels in male patients with gambling disorder

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    Background and aims: due to the contribution of age to the etiology of gambling disorder (GD), there is a need to assess the moderator effect of the aging process with other features that are highly related with the clinical profile. The objective of this study is to examine the role of the chronological age into the relationships between cognitive biases, impulsivity levels and gambling preference with the GD profile during adulthood. Methods: sample included n = 209 patients aged 18-77 years-old recruited from a Pathological Gambling Outpatients Unit. Orthogonal contrasts explored polynomial patterns in data, and path analysis implemented through structural equation modeling assessed the underlying mechanisms between the study variables. Results: compared to middle-age patients, younger and older age groups reported more impairing irrational beliefs (P = 0.005 for interpretative control and P = 0.043 for interpretative bias). A linear trend showed that as people get older sensation seeking (P = 0.006) and inability to stop gambling (P = 0.018) increase. Path analysis showed a direct effect between the cognitive bias and measures of gambling severity (standardized effects [SE] between 0.12 and 0.17) and a direct effect between impulsivity levels and cumulated debts due to gambling (SE = 0.22). Conclusion: screening tools and intervention plans should consider the aging process. Specific programs should be developed for younger and older age groups, since these are highly vulnerable to the consequences of gambling activities and impairment levels of impulsivity and cognitive biases

    Plasma concentration of leptin is related to food addiction in gambling disorder: Clinical and neuropsychological implications

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    Background: Data implicate overlaps in neurobiological pathways involved in appetite regulation and addictive disorders. Despite different neuroendocrine measures having been associated with both gambling disorder (GD) and food addiction (FA), how appetite-regulating hormones may relate to the co-occurrence of both entities remain incompletely understood. Aims: To compare plasma concentrations of ghrelin, leptin, adiponectin, and liver-expressed antimicrobial peptide 2 (LEAP-2) between patients with GD, with and without FA, and to explore the association between circulating hormonal concentrations and neuropsychological and clinical features in individuals with GD and FA. Methods: The sample included 297 patients diagnosed with GD (93.6% males). None of the patients with GD had lifetime diagnosis of an eating disorder. FA was evaluated with the Yale Food Addiction Scale 2.0. All patients were assessed through a semi-structured clinical interview and a psychometric battery including neuropsychological tasks. Blood samples to measure hormonal variables and anthropometric variables were also collected. Results: From the total sample, FA was observed in 23 participants (FA+) (7.7% of the sample, 87% males). When compared participants with and without FA, those with FA+ presented both higher body mass index (BMI) (p < 0.001) and leptin concentrations, after adjusting for BMI (p = 0.013). In patients with FA, leptin concentrations positively correlated with impulsivity, poorer cognitive flexibility, and poorer inhibitory control. Other endocrine measures did not differ between groups. Discussion and conclusions: The present study implicates leptin in co-occurring GD and FA. Among these patients, leptin concentration has been associated with clinical and neuropsychological features, such as impulsivity and cognitive performance in certain domains

    Suicidal behavior in patients with gambling disorder and their response to psychological treatment: The roles of gender and gambling preference

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    Suicidal ideation and attempts are prevalent among patients with gambling disorder (GD). However, patients with GD and a history of lifetime suicidal events are not a homogeneous group. The main objective of this study was to compare sociodemographic, clinical, personality, and psychopathological features among different profiles of adults with GD with and without a history of suicidal behavior, taking into account two relevant variables: gender and gambling preference. The second aim was to examine how the different profiles of patients with a history of suicidal events responded to cognitive-behavioral therapy (CBT). A total of 1112 treatment-seeking adults who met the criteria for GD were assessed at a hospital specialized unit for the treatment of behavioral addictions. The participants completed self-reported questionnaires to explore GD, personality traits, and psychopathological symptomatology. The lifetime histories of suicidal ideation and attempts, and gambling preferences, were assessed during semi-structured face-to-face clinical interviews. Of the total sample, 229 patients (26.6%) reported suicidal ideation and 74 patients (6.7%), suicide attempts. The likelihood of presenting suicidal ideation was higher for women than men, but no differences were observed based on gambling preference. Regarding suicide attempts, the odds were higher among women with non-strategic forms of gambling. Suicidal ideation and attempts were associated with higher GD severity, a worse psychopathological state and higher self-transcendence levels. In terms of treatment outcomes, neither gambling preference nor past suicidal behavior had an influence on dropouts and relapses. Nevertheless, female gender and a lack of family support constitute two good predictors of a worse treatment outcome

    Exploring the Association between Gambling-Related Offenses, Substance Use, Psychiatric Comorbidities, and Treatment Outcome

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    Several studies have explored the association between gambling disorder (GD) and gambling-related crimes. However, it is still unclear how the commission of these offenses influences treatment outcomes. In this longitudinal study we sought: (1) to explore sociodemographic and clinical differences (e.g., psychiatric comorbidities) between individuals with GD who had committed gambling-related illegal acts (differentiating into those who had had legal consequences (n = 31) and those who had not (n = 55)), and patients with GD who had not committed crimes (n = 85); and (2) to compare the treatment outcome of these three groups, considering dropouts and relapses. Several sociodemographic and clinical variables were assessed, including the presence of substance use, and comorbid mental disorders. Patients received 16 sessions of cognitive-behavioral therapy. Patients who reported an absence of gambling-related illegal behavior were older, and showed the lowest GD severity, the most functional psychopathological state, the lowest impulsivity levels, and a more adaptive personality profile. Patients who had committed offenses with legal consequences presented the highest risk of dropout and relapses, higher number of psychological symptoms, higher likelihood of any other mental disorders, and greater prevalence of tobacco and illegal drugs use. Our findings uphold that patients who have committed gambling-related offenses show a more complex clinical profile that may interfere with their adherence to treatment
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