Consequences Of Medical Interventions Research Articles

“I’ve had constant fears that I’ll get cancer”: the construction and experience of medical intervention on intersex bodies to reduce cancer risk

ABSTRACT Purpose This paper examines the subjective experience of medical interventions on intersex bodies to reduce cancer risk. Methods Twenty-five individuals with intersex variations took part in semi-structured interviews, analysed through thematic discourse analysis. Results Intersex bodies were positioned as inherently sick and in need of modification, with cancer risk legitimating surgical and hormonal intervention. This resulted in embodied shame, with negative impacts on fertility and sexual wellbeing. However, many participants resisted discourses of bio-pathologisation and embraced intersex status. Some medical interventions, such as HRT, were perceived to have increased the risk of cancer. Absence of informed consent, and lack of information about intersex status and the consequences of medical intervention, was positioned as a human rights violation. This was compounded by ongoing medical mismanagement, including health care professional lack of understanding of intersex variations, and the objectification or stigmatization of intersex people within healthcare. The consequence was non-disclosure of intersex status in health contexts and lack of trust in health care professionals. Conclusions The legitimacy of poorly-evidenced cancer risk discourses to justify medical intervention on intersex bodies needs to be challenged. Healthcare practitioners need to be provided with education and training about cultural safety practices for working with intersex people.

Psychotic disorders in COVID-19: mechanisms of development, clinical and treatment features

The purpose of this review was to study the mechanisms of development, clinical features and treatment of psychotic disorders during the disease caused by the SARS-CoV-2 virus. In the first part of the review, especial attention was paid to the available literature data on the mechanisms of development of mental disorders in COVID-19. Among the main pathogenetic mechanisms of the onset of psychotic disorders in coronavirus infections, there are direct effects of a viral infection (including a brain infection), cerebrovascular diseases, hypoxia, an immunological response, the consequences of medical interventions, social isolation, the psychological impact of a severe and potentially fatal illness, fears of infecting another’s and stigmatization. The second part of the publication is devoted to a review of clinical studies and syndromokinesis in infectious and coronavirus psychoses. Particular attention is paid to delirious syndrome, including pharmacogenic delirium and antibiotic-associated encephalopathy. The article describes the features of therapy for psychotic disorders in COVID-19, taking into account drug‑drug interactions and the effect on the cardiovascular and respiratory systems. The analyzed literature allows us to make a reasonable conclusion that the management of coronavirus psychoses should be aimed at treating the underlying disease while eliminating psychotic symptoms with antipsychotics while ensuring maximum safety of psychopharmacotherapy.

Exploring the Unknown and the Unknowable with Simulation Models

This issue of Medical Decision Making (MDM )i s devoted to simulation modeling in health. The papers were not invited for the issue but are a special collection from the many on modeling that are submitted to MDM every year. Those under ‘‘Exploring Model Structure’’ deal with various aspects of reality that might be modeled: different ways of modeling preclinical disease, the impact of quality of life on health outcomes, correlations among health outcomes, the balance of benefits and harms over different time horizons, and adapting models to the stage of the decision. Those under ‘‘Calibrating Models’’ describe methods for assigning values to model parameters for which no direct evidence is available. And the papers under ‘‘Representing Uncertainty in Models’’ discuss methods for incorporating uncertainty in the data into a model and showing its effects on predicted outcomes. Simulation models are used to predict and compare the consequences of medical interventions. The typical application examines variations of an intervention that have not been, perhaps cannot be, tested in trials. Hlatky 1 recently observed that

Pathophysiological mechanisms, clinical manifestations, and methods of therapy of hypothalamic obesity

The authors present the current literature data concerning pathogenesis and clinical manifestations of hypothalamic obesity along with methods of its treatment. Lesions in the hypothalamus associated with infiltrative processes, neoplastic growth, and consequences of medical interventions not infrequently lead to the development of obesity characterized by the rapid gain of body weight. The major factor contributing to this increase is the compromised function of the regulatory hypothalamic centres controlling the sense of hunger and satiation and the energy balance. This dysregulation is responsible for hyperphagia, vegetative disorders, reduced energy expenditure, and hyperinsulinemia. It is extremely difficult to control the body weight only by adhering to diet guidelines and altering the lifestyle. The weight-losing efficacy of the present-day pharmacotherapy targeted for modulation of insulin secretion and activation of sympathetic nervous system is rather low and does not ensure the desired prevention of the weight gain. More detailed information about the risk factors and pathogenetic mechanisms of hypothalamic obesity is needed to develop efficacious therapeutic strategies for the treatment of this condition.

Allocating health care resources when people are risk averse with respect to life time.

The criterion of cost-effectiveness in health management may be given a welfare-theoretical justification if people are risk neutral with respect to life years. With risk aversion, the optimal allocation of health expenditures changes: Compared to the cost-effective allocation, more resources should be allocated to health conditions for which the expected outcomes even after treatment are worse than average. The consequences of medical interventions are usually not known with certainty. Given this type of uncertainty, simple application of cost-effectiveness analysis would recommend maximization of expected health benefits given the health budget. We show that when people are risk averse with respect to the number of life years they live, the uncertainty associated with different types of interventions should play a role in allocating the health budget.