Risk factors for depression and anxiety in painful and painless diabetic polyneuropathy: A multicentre observational cross-sectional study.

BACKGROUND: Despite the high prevalence of depression and anxiety in chronic pain conditions, current knowledge concerning emotional distress among painful diabetic polyneuropathy (pDSPN) and other diabetes mellitus (DM) sufferers is limited. METHODS: This observational multicentre cohort study employed the Hospital Anxiety and Depression Scale, the Beck Depression Inventory II and the State-Trait Anxiety Inventory to assess symptoms of depression and anxiety in several groups with diabetes, as well as in a control group. The study cohort included 347 pDSPN patients aged 63.4 years (median), 55.9% males; 311 pain-free diabetic polyneuropathy (nDSPN) patients aged 63.7 years, 57.9% males; 50 diabetes mellitus (DM) patients without polyneuropathy aged 61.5 years, 44.0% males; and 71 healthy controls (HC) aged 63.0 years, 42.3% males. The roles played in emotional distress were explored in terms of the biological, the clinical (diabetes-, neuropathy- and pain-related), the socio-economic and the cognitive factors (catastrophizing). RESULTS: The study disclosed a significantly higher prevalence of the symptoms of depression and anxiety not only in pDSPN (46.7% and 60.7%, respectively), but also in patients with nDSPN (24.4% and 44.4%) and DM without polyneuropathy (22.0% and 30.0%) compared with HCs (7.0% and 14.1%, p < 0.001). Multiple regression analysis demonstrated the severity of pain and neuropathy, catastrophic thinking, type 2 DM, lower age and female sex as independent contributors to depression and anxiety. CONCLUSIONS: In addition to the severity of neuropathic pain and its cognitive processing, the severity of diabetic polyneuropathy and demographic factors are key independent contributors to emotional distress in diabetic individuals. SIGNIFICANCE: In large cohorts of well-defined painless and painful diabetic polyneuropathy patients and diabetic subjects without polyneuropathy, we found a high prevalence of the symptoms of depression and anxiety, mainly in painful individuals. We have confirmed neuropathic pain, its severity and cognitive processing (pain catastrophizing) as dominant risk factors for depression and anxiety. Furthermore, some demographic factors (lower age, female sex), type 2 diabetes mellitus and severity of diabetic polyneuropathy were newly identified as important contributors to emotional distress independent of pain.

Déjà Vu Experiences in Healthy Czech Adults.

The study examines the prevalence of déjà vu in healthy Czech adults and explores its relationships with a number of variables: age, sex, neuroticism, depression, the degree of irritability in the limbic system, perceived stress, and finally attachment avoidance and anxiety. The participants were 365 healthy adults ranging from 18 to 70 years recruited in the Czech Republic (mean age = 29.05; SD = 11.17) who filled out online questionnaires. Déjà vu experiences were reported by 324 (88.8%) of them. Persons who experienced déjà vu were younger than the persons who had not experienced it. We found that sex, levels of neuroticism, depression, perceived stress, and attachment did not serve as predictors of experiences of déjà vu phenomena. Finally, those who had reported déjà vu experiences reported more limbic system irritability symptoms. We discuss the possibility that déjà vu reports together with other studied variables mainly reflect the participants' willingness to report "extraordinal" experiences.

Towards a predictive model for post-stroke delirium.

PRIMARY OBJECTIVE: To assess predisposing and precipitating risk factors and create a predictive model for post-stroke delirium. RESEARCH DESIGN: A prospective observational study in a cohort of consecutive patients with ischemic stroke or intracerebral haematoma admitted within 24 hours of stroke onset. METHODS: Patients were assessed daily for delirium during the first week by means of DSM-IV criteria and risk factors were recorded. RESULTS: One hundred patients completed a 7-day evaluation (47 women and 53 men, median age 77 years). An episode of delirium was detected in 43 patients (43%). Using multivariate logistic regression, a predictive statistical model was developed that utilized independent risk factors: age (OR = 1.08; 95% CI = 1.02-1.15); intracerebral haemorrhage (OR = 6.11; 95% CI = 1.62-22.98), lesion volume > 40 ccm (OR = 3.99; 95% CI = 1.29-12.39) and either elevated gamma-glytamyl transferase (OR = 4.88; 95% CI = 1.45-16.35) and elevated serum bilirubin (OR = 3.70; 95% CI = 1.32-10.38) or maximum sequential organ failure assessment score >2 (OR = 3.33; 95% CI = 1.06-10.45) with acceptable sensitivity and specificity (69.0% and 80.7%). In ischemic strokes, total anterior circulation infarctions were more frequently associated with delirium (73.3% developed delirium) compared with the remainder of the groups combined (p = 0.004; OR = 6.66; 95% CI = 1.85-24.01). CONCLUSION: Higher age, metabolic disturbances, intracerebral haemorrhage and larger ischemic hemispheric strokes increase the risk of post-stroke delirium.

Poststroke delirium incidence and outcomes: validation of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU).

OBJECTIVE: To describe the epidemiology and time spectrum of delirium using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria and to validate a tool for delirium assessment in patients in the acute poststroke period. DESIGN: A prospective observational cohort study. SETTING: The stroke unit of a university hospital. PATIENTS: A consecutive series of 129 patients with stroke (with infarction or intracerebral hemorrhage, 57 women and 72 men; mean age, 72.5 yrs; age range, 35-93 yrs) admitted to the stroke unit of a university hospital were evaluated for delirium incidence. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Criterion validity and overall accuracy of the Czech version of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) were determined using serial daily delirium assessments with CAM-ICU by a junior physician compared with delirium diagnosis by delirium experts using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria that began the first day after stroke onset and continued for at least 7 days. Cox regression models using time-dependent covariate analysis adjusting for age, gender, prestroke dementia, National Institutes of Stroke Health Care at admission, first-day Sequential Organ Failure Assessment, and asphasia were used to understand the relationships between delirium and clinical outcomes. An episode of delirium based on reference Diagnostic and Statistical Manual assessment was detected in 55 patients with stroke (42.6%). In 37 of these (67.3%), delirium began within the first day and in all of them within 5 days of stroke onset. A total of 1003 paired CAM-ICU/Diagnostic and Statistical Manual of Mental Disorders daily assessments were completed. Compared with the reference standard for diagnosing delirium, the CAM-ICU demonstrated a sensitivity of 76% (95% confidence interval [CI] 55% to 91%), a specificity of 98% (95% CI 93% to 100%), an overall accuracy of 94% (95% CI 88% to 97%), and high interrater reliability (κ = 0.94; 95% CI 0.83-1.0). The likelihood ratio of the CAM-ICU in the diagnosis of delirium was 47 (95% CI 27-83). Delirium was an independent predictor of increased length of hospital stay (hazard ratio 1.63; 95% CI 1.11-2.38; p = .013). CONCLUSIONS: Poststroke delirium may frequently be detected provided that the testing algorithm is appropriate to the time profile of poststroke delirium. Early (first day after stroke onset) and serial screening for delirium is recommended. CAM-ICU is a valid instrument for the diagnosis of delirium and should be considered an aid in delirium screening and assessment in future epidemiologic and interventional studies in patients with stroke.