A rapid review of the pathoetiology, presentation, and management of delirium in adults with COVID-19.

Background COVID-19 causes significant morbidity and mortality. Despite the high prevalence of delirium and delirium-related symptoms in COVID-19 patients, data and evidence-based recommendations on the pathophysiology and management of delirium are limited. Objective We conducted a rapid review of COVID-19-related delirium literature to provide a synthesis of literature on the prevalence, pathoetiology, and management of delirium in these patients. Methods Systematic searches of Medline, Embase, PsycInfo, LitCovid, WHO-COVID-19, and Web of Science electronic databases were conducted. Grey literature was also reviewed, including preprint servers, archives, and websites of relevant organizations. Search results were limited to the English language. We included literature focused on adults with COVID-19 and delirium. Papers were excluded if they did not mention signs or symptoms of delirium. Results 229 studies described prevalence, pathoetiology, and/or management of delirium in adults with COVID-19. Delirium was rarely assessed with validated tools. Delirium affected >50% of all patients with COVID-19 admitted to the ICU. The etiology of COVID-19 delirium is likely multifactorial, with some evidence of direct brain effect. Prevention remains the cornerstone of management in these patients. To date, there is no evidence to suggest specific pharmacological strategies. Discussion Delirium is common in COVID-19 and may manifest from both indirect and direct effects on the central nervous system. Further research is required to investigate contributing mechanisms. As there is limited empirical literature on delirium management in COVID-19, management with non-pharmacological measures and judicious use of pharmacotherapy is suggested.

Depression, anxiety, and associated factors in patients with diabetes: evidence from the anxiety, depression, and personality traits in diabetes mellitus (ADAPT-DM) study.

BACKGROUND: Depression and anxiety are common psychiatric complications affecting patients with diabetes mellitus. However, data on the prevalence of depression, anxiety, and associated factors among Malaysian diabetic patients is scarce. The Anxiety, Depression, and Personality Traits in Diabetes Mellitus (ADAPT-DM) study aimed to determine the prevalence of depression and anxiety, and their associated factors in the Malaysian diabetic population. METHODS: This cross-sectional study recruited 300 diabetic patients via convenience sampling from the Endocrine outpatient clinic of Universiti Kebangsaan Malaysia Medical Centre, a tertiary referral healthcare facility in Kuala Lumpur. Socio-demographic characteristics and clinical history were obtained from each participant. The Generalised Anxiety Disorder-7 (GAD-7) was administered to assess anxiety symptoms, the Beck Depression Inventory (BDI) to assess depressive symptoms, the Big Five Inventory (BFI) to evaluate personality traits, and the World Health Organization Quality of Life-BREF (WHOQOL-BREF) to measure quality of life (QOL). Stepwise multiple logistic regression analyses were performed to determine the association between various factors, and depression and anxiety. RESULTS: The prevalence of depression was 20% (n = 60) while anxiety was 9% (n = 27). Co-morbid depression (adjusted odds ratio [OR] = 9.89, 95% confidence interval [CI] = 2.63-37.14, p = 0.001) and neuroticism (adjusted OR = 11.66, 95% CI = 2.69-50.47, p = 0.001) increased the odds of developing anxiety, while conscientiousness (adjusted OR = 0.45, 95% CI = 0.23-0.80, p = 0.004) and greater psychological-related QOL (adjusted OR = 0.47, 95% CI = 0.29-0.75, p = 0.002) were protective. Co-morbid anxiety (adjusted OR = 19.83, 95% CI = 5.63-69.92, p <  0.001) increased the odds of depression, while older age (adjusted OR = 0.96, 95% CI = 0.93-0.98, p = 0.002), social relationship-related QOL (adjusted OR = 0.84, 95% CI = 0.71-.0.99, p = 0.047), and physical health-related QOL (adjusted OR = 0.69, 95% CI = 0.58-0.83, p <  0.001) were protective. CONCLUSIONS: The study findings signify the need to screen for co-morbid depression and anxiety, as well as personality traits and QOL, and to include psychosocial interventions when planning a multidisciplinary approach to managing diabetes.

How Much Do We Know about the Biopsychosocial Predictors of Glycaemic Control? Age and Clinical Factors Predict Glycaemic Control, but Psychological Factors Do Not.

OBJECTIVE: Diabetes mellitus is one of the most common noncommunicable diseases in Malaysia. It is associated with significant complications and a high cost of treatment, especially when glycaemic control is poor. Despite its negative impact on health, data is still lacking on the possible biopsychosocial predictors of poor glycaemic control among the diabetic population. This study is aimed at determining the prevalence of poor glycaemic control as well as its association with biopsychosocial factors such as personality traits, psychiatric factors, and quality of life (QOL) among Malaysian patients with diabetes. METHODS: A cross-sectional study was conducted at the Universiti Kebangsaan Malaysia Medical Centre (UKMMC) using outpatient population diabetic patients. Demographic data on social and clinical characteristics were collected from participants. Several questionnaires were administered, including the Beck Depression Inventory-II (BDI-II) to measure depressive symptoms, the Generalized Anxiety Disorder-7 (GAD-7) to assess anxiety symptoms, the Big Five Inventory (BFI) to evaluate personality traits, and the WHO Quality of Life-BREF (WHOQOL-BREF) to assess QOL. Multivariate binary logistic regression was performed to determine the predictors of poor glycaemic control. RESULTS: 300 patients with diabetes mellitus were recruited, with the majority (90%) having type 2 diabetes. In this population, the prevalence of poor glycaemic control (HbA1C ≥ 7.0%) was 69%, with a median HbA1C of 7.6% (IQR = 2.7). Longer duration of diabetes mellitus and a greater number of days of missed medications predicted poor glycaemic control, while older age and overall self-perception of QOL protected against poor glycaemic control. No psychological factors were associated with poor glycaemic control. CONCLUSION: This study emphasizes the importance of considering the various factors that contribute to poor glycaemic control, such as duration of diabetes, medication adherence, age, and QOL. These findings should be used by clinicians, particularly when planning a multidisciplinary approach to the management of diabetes.