EFFICACY OF MULTI-MODEL INTERVENTION ON REDUCING PERCEIVED BURDEN AMONG CAREGIVERS OF INDIVIDUAL WITH PSYCHIATRIC ISSUES: A SINGLE GROUP PILOT STUDY

Abstract Background: Despite the crucial role of caregivers in handling psychiatric patients, addressing caregivers burden in the home or hospital setting is remains a significant challenge in the psychiatric nursing. Objective: The purpose of this study is aimed to examine the efficacy of a newly developed Multi-Model Intervention for the caregivers who handling / taking care of psychiatric patients, specifically in Salem District. Methods: This is a single-group pretest-posttest study utilized with randomization. The Zarit Caregiver Burden Scale (ZCBS/CBS) was administered to 261 caregivers of patients with psychiatric illness for early screening. Thirty (30) caregivers were randomly selected who have scored higher in CBS for this study. Results: The results revealed that there is no significant gender difference on burden score on the baseline measure. On comparing pretest-posttest of burden score, it was found that the Multi-Model Intervention program significantly reduced the burden score of caregiver (t-value=6.39).Conclusion: This newly developed Multi-Model Intervention was significantly helped to reduce the burden of the caregivers and gains in handling skills, relaxed mood, reduced stress level, and were found as well. These findings provide promising evidence of the effectiveness of this newly developed Multi-Model Intervention for the caregivers as a strategy to promote caregiver’s personal and psychosocial well-being

A Study on Medication Adherence and Quality of Life in Patients with Chronic Kidney Disease

Back ground: Chronic Kidney Disease (CKD) is the most common health related problem. Poor long term adherence is the major clinical issue in the management of CKD. Therefore good medication adherence is important to obtain desired therapeutic outcome which in turn improves the quality of life of the patient. The aim of the study is to carry out a study on medication adherence and to improve health related quality of life in patients with CKD. Objectives: To evaluate medication adherence and to assess the factors associated with non adherence and to provide patient counselling to improve medication adherence and to improve their quality of life. Methods: A prospective study conducted for a period of six months in NU Hospitals Bengaluru. A total of 140 patients (62 were undergoing hemodialysis, 66 were CKD stage 3-5 and 12 were post-transplant patients) were enrolled for the study. Patient’s adherence to medication was assessed with the help of Modified Morisky, Green, Levine Medication Adherence Scale and Quality of life was assessed with the help of Kidney Disease Quality of Life-Short Form 36 questionnaire. One to one follow up was done after 3 months of initial data collection. Results: During the study 140 patients were enrolled for the study with 103 males and 37 females. Patient with low and medium adherence during the first visit were 7 (5%) and 21 (45%) respectively and patients with high adherence during baseline visit were 80%, which later improved to 85.7% in the final review after patient counselling. Quality of life is decreased in patients with CKD. The domain with highest average score was emotional well being (8.4) and lowest average score was role limitation due to physical health (4.12). There was a slight improvement in Quality of Life of the patients after patient counselling. Conclusion: Study suggests that patient counselling by clinical pharmacists can improve the medication adherence by improving awareness about medication which in turn helps them to achieve a better quality of life

Ophthalmic and clinical factors that predict four-year development and worsening of diabetic retinopathy in type 1 diabetes

To investigate the role of ophthalmic imaging markers - namely retinal thickness measures and corneal nerve morphology - in predicting four-year development and worsening of diabetic retinopathy (DR) in type 1 diabetes (T1DM).126 eyes of 126 participants with T1DM were examined at baseline and after four years. Diabetic retinopathy (DR) was graded using the Early Treatment Diabetic Retinopathy Study scale. HbA1c, nephropathy, neuropathy, cardiovascular factors, and retinal thickness using optical coherence tomography (OCT) and corneal nerve fiber length (CNFL) using corneal confocal microscopy at baseline were assessed by univariate and step-wise multiple logistic regression, and their diagnostic capabilities for single and combined measures.Four-year development of DR was 19% (13 of 68 without DR at baseline). Worsening of DR was seen in 43% (25 of 58 with DR at baseline). When adjusted for potential confounders, a lower CNFL (AUC=0.637, p=0.040, 64% sensitivity and 64% specificity at 14.9mm/mm(2) cut-off), higher triglycerides (AUC=0.669, p=0.012, 64% sensitivity, 62% specificity at 0.85mmol/L) and an elevated vibration threshold (AUC=0.708, p=0.002, 96% sensitivity, 40% specificity at 3.55Hz) were significant predictors for four-year worsening of DR.Reduced CNFL, elevated vibration perception threshold and higher triglycerides can predict future worsening of DR

Reproducibility of linear and angular cephalometric measurements obtained by an artificial-intelligence assisted software (WebCeph) in comparison with digital software (AutoCEPH) and manual tracing method

ABSTRACT Introduction: It has been suggested that human errors during manual tracing of linear/angular cephalometric parameters can be eliminated by using computer-aided analysis. The landmarks, however, are located manually and the computer system completes the analysis. With the advent of Artificial Intelligence in the field of Dentistry, automatic location of the landmarks has become a promising tool in digital Orthodontics. Methods: Fifty pretreatment lateral cephalograms obtained from the Orthodontic department of SRM dental college (India) were used. Analysis were done by the same investigator using the following methods: WebCeph™, AutoCEPH© for Windows or manual tracing. Landmark identification was carried out automatically by Artificial Intelligence in WebCeph™ and with a mouse driven cursor in AutoCEPH©, and manually using acetate sheet and 0.3-mm pencil, ruler and a protractor. The mean differences of the cephalometric parameters obtained between the three methods were calculated using ANOVA with statistical significance set at p0.75 indicated good agreement. Results: Intraclass correlation coefficient between the three groups was >0.830, showing good level of agreement, and the value within each group was >0.950, indicating high intrarater reliability. Conclusion: Artificial Intelligence assisted software showed good agreement with AutoCEPH© and manual tracing for all the cephalometric measurements

Supersymmetric dS/CFT

We put forward new explicit realisations of dS/CFT that relate ${\cal N}=2$ supersymmetric Euclidean vector models with reversed spin-statistics in three dimensions to specific supersymmetric Vasiliev theories in four-dimensional de Sitter space. The partition function of the free supersymmetric vector model deformed by a range of low spin deformations that preserve supersymmetry appears to specify a well-defined wave function with asymptotic de Sitter boundary conditions in the bulk. In particular we find the wave function is globally peaked at undeformed de Sitter space, with a low amplitude for strong deformations. This suggests that supersymmetric de Sitter space is stable in higher-spin gravity and in particular free from ghosts. We speculate this is a limiting case of the de Sitter realizations in exotic string theories.Comment: V2: references and comments added, typos corrected, version published in JHEP; 27 pages, 3 figures, 1 tabl

Blood cancer care in a resource limited setting during the Covid-19 outbreak; a single center experience from Sri Lanka

BackgroundThe Covid-19 pandemic has caused significant morbidity and mortality among patients with cancer. Most countries employed measures to prevent spread of Covid-19 infection which include shielding, quarantine, lockdown, travel restrictions, physical distancing and the use of personal protective equipment. This study was carried out to assess the change in patient attendance and the efficacy of newly implemented strategies to mitigate the impact of Covid-19 on services at the Lanka Hospital Blood Cancer Centre (LHBCC) in Colombo, Sri Lanka.MethodologyTelephone consultation, infection control, personal protective measures and emergency admission policy were implemented with the aim of having a Covid-19 free ward and to prevent cross-infections. This descriptive cross-sectional study was conducted with 1399 patient episodes (in-patient care or day-case review). We analysed patients treated as in-patient as well as day-case basis between 01st April 2020 and 31st December 2020.ResultsThere were 977 day-case based episodes and 422 in-patient based episodes. There was a 14% drop in episode numbers compared to same period in 2019. There was no cross infection and no patients with Covid-19 related symptoms or positive test results entered the LHBCC during the study period.ConclusionServices in blood cancer care were maintained to prevent late stage presentation and adverse outcome. Measures implemented to prevent Covid-19 were effective to allow continuation of treatment. This study highlights the importance of implementing strict protocols, clinical screening, use of appropriate personal protective equipment in delivering blood cancer care during the Covid-19 pandemic. This is the only documented study relating to outcome and successful applicability of measures to prevent spread of Covid-19 infection and maintaining services among blood cancer patients in Sri Lanka

Diabetic peripheral neuropathy and retinal tissue thickness

Using retinal imaging, the nature and extent of compromise of retinal structural integrity has been characterized in individuals suffering from diabetic peripheral neuropathy. These findings extend our understanding of the pathological processes involved in diabetic neuropathy and offer novel ophthalmic approaches to the diagnosis and monitoring of this debilitating condition

Essays on fitting factor models for asset returns

Thesis (Ph.D.)--University of Washington, 2018Factor models are used to describe the fundamental drivers of financial asset returns. There are 3 types: time-series factor, statistical factor and fundamental factor models. While factor models have existed for almost 60 years, industry-wide adoption with factor-based investing has surged in the last decade. This dissertation is centered on factorAnalytics, an open source R package co-developed with other UW students and faculty members, that demystifies the industry black-box models, making model fitting tools readily available for any interested academic or practitioner. Chapter 1 compares the characteristics of the three types of models in terms of model specification, estimation, interpretation and various in-sample and out-of-sample performance metrics using S&P 500 stock returns. Like Connor (1995), we find that the fundamental factor model outperforms the time-series and statistical factor models since it makes use of additional information on asset-specific characteristics. Moreover, we find that adding statistical factor(s) extracted from the residuals of time-series or fundamental factor models, or, fitting fundamental factors to the residuals of a time-series factor model, to create hybrid models, further improves performance. Investment management firms need to understand peer positioning for a variety of reasons, including risk management. Factor models provide a framework to estimate peer exposures, especially useful when holdings-based information is lacking. Chapter 2 presents a multi-asset time-series factor model constructed from long-short portfolios of asset class index returns, applied to peer-average returns from the Morningstar U.S. fund allocation categories. We show that factors are better than asset classes for assessing unknown exposures and decomposing risk in multi-asset portfolios. Furthermore, there is an opportunity to create more efficient, better risk-diversified portfolios using factors when making allocation decisions. We use the multi-factor model to construct equal-asset-risk and equal-factor-risk portfolios and compare them to the equal-weighted and minimum-variance portfolios. We also show that a zero-investment equal-factor-risk portfolio sleeve helps bridge the gap between pure risk parity and traditional portfolios, enhancing Sharpe ratio across all risk categories. Chapters 3-5 contain vignettes for each type of factor model that describe and demonstrate model fitting, factor risk (volatility, value-at-risk and expected shortfall) decomposition, and related S3 generic methods

Conditioning dendritic cell responses using engineered biomaterials for immunotherapy

Pivotal discoveries in the field of immunology over the last five decades have changed the way new therapies are designed for applications as varied as organ transplantation, autoimmune diseases or even cancer. In this regard, dendritic cells (DCs) were identified to play an important role in the orchestration of the adaptive immune response. Importantly, the phenotype of DCs is a powerful indicator of their downstream effector functions. In the recent years, parallel advancements made in biomaterial design and biocompatibility considerations are being directly translated into developing improved immunotherapies. Interestingly, biomaterials also elicit differential effects on the host immune response and the phenotypic state of DCs. The first objective of this doctoral thesis was to validate the role of DCs in supporting antigen presentation for a proliferative antigen-specific T cell response in the presence of PLGA, consistent with the previously observed adjuvant effect of PLGA. Herein, by conditionally ablating DCs in a murine CD11c-DTR model, the adjuvant effect of PLGA towards co-delivered OVA was revisited. The diminished proliferation of adoptively transferred OVA-reactive T-cells in these mice was suggestive of mitigated antigen presentation due to the absence of CD11c+ DCs; thereby we demonstrated that the effect of PLGA in vivo on the antigen-specific proliferative T-cell response, a likely early precursor to antibody response, was indeed due to its effects on DC presence and phenotype. The second objective of this thesis was to design, develop and validate a multicomponent, multifunctional immunomodulatory (MI) scaffold comprised of macroporous agarose as the base scaffold material into which were embedded crosslinked gelatin microparticles (MPs), pre-loaded with immunomodulators, for their controlled release to mimic tolerogenic human or murine DC culture conditions. Aided by empirical modeling, using the Weibull equation, of experimental data using ‘model’ proteins, we identified parameters of gelatin MP crosslinking density and number of embedded MPs in agarose to achieve prescribed temporal controlled release of immunomodulators for induction of tolerogenic DCs. The prescribed MI scaffold aimed to release granulocyte monocyte colony-stimulating factor (GM-CSF; delivered within 0-3 days) to induce differentiation of monocyte precursors into DCs after dexamethasone (DEX, delivered within 3-6 days) addition would induce regulatory properties to these cells as well as peptidoglycan (PGN, delivered on days 5-6) to induce an alternative activated phenotype in DCs. Such alternatively activated DCs (aaDCs), are endowed with immunosuppressive as well as directed lymph node migratory properties to effectively exert their tolerogenic effect. Ability of this MI scaffold to induce tolerogenic phenotype in human blood-derived as well as murine bone marrow-derived cells was demonstrated upon in vitro treatment using a large cadre of immunological assessments. In summary, the work in this thesis documents the importance of DCs in the effect of PLGA in enhancing antigen-specific adaptive immunity in vivo and provides a construct formulation that can be used to generate aaDCs with tolerogenic and migratory properties that are highly relevant in designing future immunotherapies targeting autoimmune diseases as well as in alleviating allograft rejection.Ph.D

Optical coherence tomography in the investigation of systemic neurologic disease

Optical coherence tomography (OCT) is a well-established technique for the clinical examination, diagnosis, severity staging and monitoring of ophthalmic disorders. The application of this technology has more recently been extended beyond ophthalmic disease, whereby it has been demonstrated that OCT can serve as an ophthalmic marker for a range of systemic neurodegenerative disorders, such as Parkinson's disease, multiple sclerosis, Alzheimer's disease and diabetic peripheral neuropathy. This review will focus on the clinical utility of OCT-derived retinal measures for the investigation of these conditions.</p