The Recovery Process Utilizing Erikson’s Stages of Human Development

Of current interest to the field are clinical frameworks that foster recovery. The authors offer a psycho-developmental model that parallels Erik Erikson’s theory of human development, and theorize that the process of psychiatric recovery involves a psychic reworking of these fundamental steps. Understanding recovery in this context allows the client and the practitioner of psychiatric rehabilitation to design and implement a coherent treatment strategy

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling

Solving the inverse problem is the key step in evaluating the capacity of a physical model to describe real phenomena. In medical image computing, it aligns with the classical theme of image-based model personalization. Traditionally, a solution to the problem is obtained by performing either sampling or variational inference based methods. Both approaches aim to identify a set of free physical model parameters that results in a simulation best matching an empirical observation. When applied to brain tumor modeling, one of the instances of image-based model personalization in medical image computing, the overarching drawback of the methods is the time complexity of finding such a set. In a clinical setting with limited time between imaging and diagnosis or even intervention, this time complexity may prove critical. As the history of quantitative science is the history of compression (Schmidhuber and Fridman, 2018), we align in this paper with the historical tendency and propose a method compressing complex traditional strategies for solving an inverse problem into a simple database query task. We evaluated different ways of performing the database query task assessing the trade-off between accuracy and execution time. On the exemplary task of brain tumor growth modeling, we prove that the proposed method achieves one order speed-up compared to existing approaches for solving the inverse problem. The resulting compute time offers critical means for relying on more complex and, hence, realistic models, for integrating image preprocessing and inverse modeling even deeper, or for implementing the current model into a clinical workflow. The code is available at https://github.com/IvanEz/for-loop-tumor

Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling

Current treatment planning of patients diagnosed with a brain tumor, such as glioma, could significantly benefit by accessing the spatial distribution of tumor cell concentration. Existing diagnostic modalities, e.g. magnetic resonance imaging (MRI), contrast sufficiently well areas of high cell density. In gliomas, however, they do not portray areas of low cell concentration, which can often serve as a source for the secondary appearance of the tumor after treatment. To estimate tumor cell densities beyond the visible boundaries of the lesion, numerical simulations of tumor growth could complement imaging information by providing estimates of full spatial distributions of tumor cells. Over recent years a corpus of literature on medical image-based tumor modeling was published. It includes different mathematical formalisms describing the forward tumor growth model. Alongside, various parametric inference schemes were developed to perform an efficient tumor model personalization, i.e. solving the inverse problem. However, the unifying drawback of all existing approaches is the time complexity of the model personalization which prohibits a potential integration of the modeling into clinical settings. In this work, we introduce a deep learning based methodology for inferring the patient-specific spatial distribution of brain tumors from T1Gd and FLAIR MRI medical scans. Coined as Learn-Morph-Infer the method achieves real-time performance in the order of minutes on widely available hardware and the compute time is stable across tumor models of different complexity, such as reaction-diffusion and reaction-advection-diffusion models. We believe the proposed inverse solution approach not only bridges the way for clinical translation of brain tumor personalization but can also be adopted to other scientific and engineering domains

Identification of risk factors of severe hypersensitivity reactions in general anaesthesia

Background: Hypersensitivity reactions to anaesthetic agents are rare but often severe, with a mortality ranging from 4 to 9% in IgE-mediated events. Identification of the risk factors may contribute to limit the incidence of these reactions. The aim of our study was to search for possible risk factors of severe perioperative hypersensitivity reactions in our study population. Methods: For this study we retrospectively reviewed data from 193 patients who experienced drug hypersensitivity reactions during general anaesthesia. The diagnostic protocol consisted of 1) history of the reaction, 2) measurement of serum baseline tryptase and specific IgE-assays for latex, beta-lactams and succinylcholine, 3) skin tests for the agents listed in the anaesthesia chart and for others likely to be safe for future use, latex, and others medications administered during the perioperative period (i.e. antibiotics), 4) subdivision of our patients on the basis of two criteria: a) grade of severity of clinical reactions according to the Ring and Messmer classification; b) results of skin tests and/or serum specific IgE-assays. Results: One hundred of 193 patients had reactions of grade I, 32/193 patients had reactions of grade II, 55/193 patients had reactions of grade III and 6/193 patients had reactions of grade IV. A diagnosis of IgE-mediated reaction was established in 55 cases (28.50%); the most common causes were neuromuscular blocking agents, followed by latex and beta-lactams. Severe reactions were associated with older age (p = 0.025), asthma (p = 0.042), history of hypertension (p = 0.001), intake of serum angiotensin converting enzyme inhibitor medication (p = 0.012) or serum angiotensin II antagonist (p = 0.033), higher levels of basal tryptase (p = 0.0211). Cardiovascular symptoms (p = 0.006) and history of hypersensitivity to antibiotics (p = 0.029) were more frequently reported in IgE-mediated reactions. Conclusions: We confirmed the relevance of several clinical features as risk factors for anaphylactic reactions induced by anaesthetic agents: older age, asthma, hypertension and antihypertensive drugs. We observed increased levels of serum basal tryptase in severe reactions: this finding may signify that this biomarker is useful for the identification of patients at risk

Increased frequency of the immunoglobulin enhancer HS1,2 allele 2 in coeliac disease

Background: Coeliac disease ( CD) is characterized by increased immunological responsiveness to ingested gliadin in genetically predisposed individuals. This genetic predisposition is not completely defined. A dysregulation of immunoglobulins (Ig) is present in CD: since antiendomysium antibodies (anti-EMA) are of the IgA class. One polymorphic enhancer within the locus control region (LCR) of the immunoglobulin heavy chain cluster at the 3' of the C alpha-1 gene was investigated. The correlation of the penetrance of the four different alleles of the HS1,2-A enhancer of the LCR-1 3' to C alpha-1 in CD patients compared to a control population was analysed. Methods: A total of 115 consecutive CD outpatients, on a gluten-free diet, and 248 healthy donors, age- and sex-matched, from the same geographical area were enrolled in the study. HS1,2-A allele frequencies were investigated by nested polymerase chain reaction (PCR). Results: The frequency of allele 2 of the enhancer HS1,2-A gene was increased by 30.8% as compared to the control frequency. The frequency of homozygosity for allele 2 was significantly increased in CD patients. Crude odds ratio ( OR) showed that those with 2/2 and 2/4 ( OR 2.63, P < 0.001 and OR 2.01, P = 0.03) have a significantly higher risk of developing the disease. In contrast, allele 1/2 may represent a protective genetic factor against CD ( OR 0.52, P = 0.01). Conclusions: These data provide further evidence of a genetic predisposition in CD. Because of the Ig dysregulation in CD, the enhancer HS1,2-A may be involved in the pathogenesis

Personalizing Cancer Pain Therapy: Insights from the Rational Use of Analgesics (RUA) Group

Introduction: A previous Delphi survey from the Rational Use of Analgesics (RUA) project involving Italian palliative care specialists revealed some discrepancies between current guidelines and clinical practice with a lack of consensus on items regarding the use of strong opioids in treating cancer pain. Those results represented the basis for a new Delphi study addressing a better approach to pain treatment in patients with cancer. Methods: The study consisted of a two-round multidisciplinary Delphi study. Specialists rated their agreement with a set of 17 statements using a 5-point Likert scale (0 = totally disagree and 4 = totally agree). Consensus on a statement was achieved if the median consensus score (MCS) (expressed as value at which at least 50% of participants agreed) was at least 4 and the interquartile range (IQR) was 3–4. Results: This survey included input from 186 palliative care specialists representing all Italian territory. Consensus was reached on seven statements. More than 70% of participants agreed with the use of low dose of strong opioids in moderate pain treatment and valued transdermal route as an effective option when the oral route is not available. There was strong consensus on the importance of knowing opioid pharmacokinetics for therapy personalization and on identifying immediate-release opioids as key for tailoring therapy to patients’ needs. Limited agreement was reached on items regarding breakthrough pain and the management of opioid-induced bowel dysfunction. Conclusion: These findings may assist clinicians in applying clinical evidence to routine care settings and call for a reappraisal of current pain treatment recommendations with the final aim of optimizing the clinical use of strong opioids in patients with cancer

Adherence issues related to sublingual immunotherapy as perceived by allergists

Objectives: Sublingual immunotherapy (SLIT) is a viable alternative to subcutaneous immunotherapy to treat allergic rhinitis and asthma, and is widely used in clinical practice in many European countries. The clinical efficacy of SLIT has been established in a number of clinical trials and meta-analyses. However, because SLIT is self-administered by patients without medical supervision, the degree of patient adherence with treatment is still a concern. The objective of this study was to evaluate the perception by allergists of issues related to SLIT adherence. Methods: We performed a questionnaire-based survey of 296 Italian allergists, based on the adherence issues known from previous studies. The perception of importance of each item was assessed by a VAS scale ranging from 0 to 10. Results: Patient perception of clinical efficacy was considered the most important factor (ranked 1 by 54% of allergists), followed by the possibility of reimbursement (ranked 1 by 34%), and by the absence of side effects (ranked 1 by 21%). Patient education, regular follow-up, and ease of use of SLIT were ranked first by less than 20% of allergists. Conclusion: These findings indicate that clinical efficacy, cost, and side effects are perceived as the major issues influencing patient adherence to SLIT, and that further improvement of adherence is likely to be achieved by improving the patient information provided by prescribers. © 2010 Scurati et al, publisher and licensee Dove Medical Press Ltd