Modeling Depression Progression Dynamics from Electronic Health Record

Thesis (Master's)--University of Washington, 2016-06

Depression severity levels and cognitive functions in institutionalized elderly patients

Depression is a highly prevalent illness among institutionalized aged and assumes peculiar characteristics such as the risk for progressing to dementia. The aims of this study was to assess the cognitive functions of institutionalized elderly with clinical diagnosis of depression and compare the severity of depressive symptoms with cognitive performance. From 120 residents at a nursing home in Rio Claro, Brazil, we study 23 individuals (mean age: 74.3 years; mean schooling: 4.0 years) with diagnosis of depression. At first, a clinical diagnosis of depression and measurement of its symptoms using the Geriatric Depression Scale were performed. The patient then underwent a neuropsychological assessment based on the following tests: Mini-Mental Examination, Verbal Fluency, Visual Perception, Immediate Memory, Recent Memory, Recognition, Clock Drawing Test. The patients were divided into two groups: those with less severe depression symptoms (Group 1: N=9) and more severe symptoms (Group 2: N=14). The significant difference between symptom severity of the two groups was p=0.0001. Patients with more severe symptoms revealed a slightly inferior cognitive performance in most of the tests when compared to those with less severe symptoms (p>0.05). In relation to Verbal Fluency, patients with more severe depression symptoms presented a significantly inferior cognitive performance when compared to those with less severe symptoms (p=0.0082). Verbal Fluency revealed to be a more sensitive test for measuring early cognitive alterations in institutionalized aged with depression, and appears to be a useful resource in monitoring the cognitive functions of patients faced with the risk of dementia. © Copyright Moreira Jr. Editora.

Motor Activity and Depression Severity in Adolescent Outpatients

Objectives: The present study investigated the association between motor activity and severity of depression in 6 depressed adolescent outpatients. Method: Motor activity was assessed by actigraphy and the severity of depression was assessed weekly using the CDRS-R. The levels of motor activity were analyzed by considering activity parameters. Results: Among the parameters of motor activity studied, the mean total activity, the mean 24-hour activity levels, the mean waking activity, and the mean activity level between 12:00 and 18:00 h were inversely correlated with severity of depression. The means of the 10 most active hours tended toward a negative correlation with the depressive severity score. Conclusion: The results seem to suggest an association between motor activity level and severity of depression in adolescents. Nevertheless, in order to reach a more conclusive understanding, it would be necessary to replicate this study using a larger number of individuals as well as a longer observation period. Copyright (C) 2009 S. Karger AG, Basel

Talking bodies: nonverbal behavior in the assessment of depression severity

BACKGROUND: Evaluations of clinical depression are traditionally based on verbal information. Nonverbal expressive behavior, however, being associated with a person's reflexive responses, may reveal negative emotional or social processes that are not under complete control of the patients. However, investigations of nonverbal behavior in the evaluation of depressed patients are still scarce. This study examines the nonverbal behaviors of a group of Brazilian patients, associating their nonverbal behavior with severity of depression. METHODS: Forty depressed patients were evaluated at baseline (T0) and after a two-week transcranial direct current stimulation treatment (T1), according to rating scales and through a 21-category Ethogram for assessment of the frequency of nonverbal behaviors displayed during an interview. RESULTS: Behaviors that were related to negative feelings and social disinterest decreased with corresponding clinical improvement and were associated with increased severity of symptoms at T0 and greater negative affect and dissatisfaction at T1. Pro-social behaviors were associated with milder symptoms at T0 and increased after treatment. Facial, head and hand expressive movements stood out as important indicators because of their associations with severity of depression. LIMITATIONS: Duration of behaviors was not assessed and there was not a healthy control group with which to compare the findings. CONCLUSIONS: These results support the usefulness of nonverbal behavior as an evaluation technique in the assessment of clinical depression.

Relative transition probability and pressure broadening parameters of copper atomic lines /

Inserted Report documentation page designates D. W. Boyer ... [et al.] as "authors."

Measured transition probability for the first-positive band system of nitrogen.

"This report covers work performed under Contract no. DA-30-069-ORD-3443, ARPA order number 253-62 [and] is a part of Project Defender."

Urban land use change analysis and modelling: a case study of Setubal-Sesimbra, Portugal

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

A Methodological Framework for Modeling Pavement Maintenance Costs for Projects with Performance-based Contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

Increases in prefrontal cortex activity when regulating negative emotion predicts symptom severity trajectory over six months in depression

Context: Emotion regulation is critically disrupted in depression and use of paradigms tapping these processes may uncover essential changes in neurobiology during treatment. In addition, as neuroimaging outcome studies of depression commonly utilize solely baseline and endpoint data – which is more prone to week-to week noise in symptomatology – we sought to use all data points over the course of a six month trial. Objective: To examine changes in neurobiology resulting from successful treatment. Design: Double-blind trial examining changes in the neural circuits involved in emotion regulation resulting from one of two antidepressant treatments over a six month trial. Participants were scanned pretreatment, at 2 months and 6 months posttreatment. Setting: University functional magnetic resonance imaging facility. Participants: 21 patients with Major Depressive Disorder and without other Axis I or Axis II diagnoses and 14 healthy controls. Interventions: Venlafaxine XR (doses up to 300mg) or Fluoxetine (doses up to 80mg). Main Outcome Measure: Neural activity, as measured using functional magnetic resonance imaging during performance of an emotion regulation paradigm as well as regular assessments of symptom severity by the Hamilton Rating Scale for Depression. To utilize all data points, slope trajectories were calculated for rate of change in depression severity as well as rate of change of neural engagement. Results: Those depressed individuals showing the steepest decrease in depression severity over the six months were those individuals showing the most rapid increases in BA10 and right DLPFC activity when regulating negative affect over the same time frame. This relationship was more robust than when using solely the baseline and endpoint data. Conclusions: Changes in PFC engagement when regulating negative affect correlate with changes in depression severity over six months. These results are buttressed by calculating these statistics which are more reliable and robust to week-to-week variation than difference scores.

Measuring depression with a well-being index: Further evidence for the validity of the WHO Well-Being Index (WHO-5) as a measure of the severity of depression

BACKGROUND: In recent years, the WHO Wellbeing Index (WHO-5) has been used as a screening measure for depression. Nevertheless, research on the validity of this measure in the context of clinical depression is sparse. QUESTIONS: The aim of the present study was to investigate the measurement invariance of the WHO-5 across depressed and non-depressed individuals, as well as the shape and specificity of its relationship to measures of depression severity. METHOD: Of the 414 subjects who completed the WHO-5 and the Beck Depression Inventory-II (BDI-II), 207 had a diagnosis of a major depressive episode (MDE). A subsample also completed the Beck Anxiety Inventory (BAI) and was assessed by clinicians using the Hamilton Depression Rating Scale (HAM-D) and the Hamilton Anxiety Rating Scale (HAM-A). RESULTS: The WHO-5 demonstrated strong measurement invariance regarding the presence or absence of a current MDE. The WHO-5 showed a very high negative association with self- and observer-rated measures of depressive symptoms, especially in the range of mild to moderate symptoms. These associations were still substantial after controlling for measures of anxiety symptoms. LIMITATIONS: In addition to a diagnostic interview, only one measure for self- and observer-rated symptoms of depression was used. Furthermore, the observer-rated measure was only assessed in one subsample that exhibited a somewhat restricted range of depression severity. CONCLUSION: Although this index was originally designed as a measure of well-being, the results support the use of the WHO-5 in the context of depression research.

Using a matrix in life transition research

Life transitions can be planned or can occur unexpectedly. They can cause a major change to a person's life patterns and well-being. Older adulthood is a time for many life transitions as a result of changes in life roles and health status. In this exploratory study, the authors investigate the transition involved in driving cessation for older people. In analyzing and organizing the data, they develop a matrix that incorporated descriptive and temporal factors associated with the transition. This matrix is useful in organizing and communicating the findings as a whole and could be used in describing individual experiences. It might be of use for the organization of qualitative data about other life transitions such as illness, retirement, and the development and adoption of new behaviors.

Pattern recognition analyses of brain activation elicited by happy and neutral faces in unipolar and bipolar depression

Objectives: Recently, pattern recognition approaches have been used to classify patterns of brain activity elicited by sensory or cognitive processes. In the clinical context, these approaches have been mainly applied to classify groups of individuals based on structural magnetic resonance imaging (MRI) data. Only a few studies have applied similar methods to functional MRI (fMRI) data. Methods: We used a novel analytic framework to examine the extent to which unipolar and bipolar depressed individuals differed on discrimination between patterns of neural activity for happy and neutral faces. We used data from 18 currently depressed individuals with bipolar I disorder (BD) and 18 currently depressed individuals with recurrent unipolar depression (UD), matched on depression severity, age, and illness duration, and 18 age- and gender ratio-matched healthy comparison subjects (HC). fMRI data were analyzed using a general linear model and Gaussian process classifiers. Results: The accuracy for discriminating between patterns of neural activity for happy versus neutral faces overall was lower in both patient groups relative to HC. The predictive probabilities for intense and mild happy faces were higher in HC than in BD, and for mild happy faces were higher in HC than UD (all p < 0.001). Interestingly, the predictive probability for intense happy faces was significantly higher in UD than BD (p = 0.03). Conclusions: These results indicate that patterns of whole-brain neural activity to intense happy faces were significantly less distinct from those for neutral faces in BD than in either HC or UD. These findings indicate that pattern recognition approaches can be used to identify abnormal brain activity patterns in patient populations and have promising clinical utility as techniques that can help to discriminate between patients with different psychiatric illnesses.

Impact of severity and type of depression on quality of life in cases identified in the community

BACKGROUND: The impact of different levels of depression severity on quality of life (QoL) is not well studied, particularly regarding ICD-10 criteria. The ICD classification of depressive episodes in three levels of severity is also controversial and the less severe category, mild, has been considered as unnecessary and not clearly distinguishable from non-clinical states. The present work aimed to test the relationship between depression severity according to ICD-10 criteria and several dimensions of functioning as assessed by Medical Outcome Study (MOS) 36-item Short Form general health survey (SF-36) at the population level. METHOD: A sample of 551 participants from the second phase of the Outcome of Depression International Network (ODIN) study (228 controls without depression and 313 persons fulfilling ICD criteria for depressive episode) was selected for a further assessment of several variables, including QoL related to physical and mental health as measured with the SF-36. RESULTS: Statistically significant differences between controls and the depression group were found in both physical and mental markers of health, regardless of the level of depression severity; however, there were very few differences in QoL between levels of depression as defined by ICD-10. Regardless of the presence of depression, disability, widowed status, being a woman and older age were associated with worse QoL in a structural equation analysis with covariates. Likewise, there were no differences according to the type of depression (single-episode versus recurrent). CONCLUSIONS: These results cast doubt on the adequacy of the current ICD classification of depression in three levels of severity.

A numerical study of large sparse matrix exponentials arising in Markov chains

Krylov subspace techniques have been shown to yield robust methods for the numerical computation of large sparse matrix exponentials and especially the transient solutions of Markov Chains. The attractiveness of these methods results from the fact that they allow us to compute the action of a matrix exponential operator on an operand vector without having to compute, explicitly, the matrix exponential in isolation. In this paper we compare a Krylov-based method with some of the current approaches used for computing transient solutions of Markov chains. After a brief synthesis of the features of the methods used, wide-ranging numerical comparisons are performed on a power challenge array supercomputer on three different models. (C) 1999 Elsevier Science B.V. All rights reserved.AMS Classification: 65F99; 65L05; 65U05.

Right Orbitofrontal Corticolimbic and Left Corticocortical White Matter Connectivity Differentiate Bipolar and Unipolar Depression

Objectives: The absence of pathophysiologically relevant diagnostic markers of bipolar disorder (BD) leads to its frequent misdiagnosis as unipolar depression (UD). We aimed to determine whether whole brain white matter connectivity differentiated BD from UD depression. Methods: We employed a three-way analysis of covariance, covarying for age, to examine whole brain fractional anisotropy (FA), and corresponding longitudinal and radial diffusivity, in currently depressed adults: 15 with BD-type I (mean age 36.3 years, SD 12.0 years), 16 with recurrent UD (mean age 32.3 years, SD 10.0 years), and 24 healthy control adults (HC) (mean age 29.5 years, SD 9.43 years). Depressed groups did not differ in depression severity, age of illness onset, and illness duration. Results: There was a main effect of group in left superior and inferior longitudinal fasciculi (SLF and ILF) (all F >= 9.8; p <= .05, corrected). Whole brain post hoc analyses (all t >= 4.2; p <= .05, corrected) revealed decreased FA in left SLF in BD, versus UD adults in inferior temporal cortex and, versus HC, in primary sensory cortex (associated with increased radial and decreased longitudinal diffusivity, respectively); and decreased FA in left ILF in UD adults versus HC. A main effect of group in right uncinate fasciculus (in orbitofrontal cortex) just failed to meet significance in all participants but was present in women. Post hoc analyses revealed decreased right uncinate fasciculus FA in all and in women, BD versus HC. Conclusions: White matter FA in left occipitotemporal and primary sensory regions supporting visuospatial and sensory processing differentiates BD from UD depression. Abnormally reduced FA in right fronto-temporal regions supporting mood regulation, might underlie. predisposition to depression in BD. These measures might help differentiate pathophysiologic processes of BD versus UD depression.