Prednisolone versus placebo addition in the treatment of patients with recent-onset psychotic disorder: a trial design

BACKGROUND: The symptom severity of a substantial group of schizophrenia patients (30-40%) does not improve through pharmacotherapy with antipsychotic medication, indicating a clear need for new treatment options to improve schizophrenia outcome. Meta-analyses, genetic studies, randomized controlled trials, and post-mortem studies suggest that immune dysregulation plays a role in the pathophysiology of schizophrenia. Some anti-inflammatory drugs have shown beneficial effects on the symptom severity of schizophrenia patients. Corticosteroids are effective in various chronic inflammatory and autoimmune disorders. Prednisolone, a potent glucocorticosteroid, has minor mineral-corticosteroid potencies and can adequately pass the blood-brain barrier

Automatic Triage of 12‐Lead ECGs Using Deep Convolutional Neural Networks

Background The correct interpretation of the ECG is pivotal for the accurate diagnosis of many cardiac abnormalities, and conventional computerized interpretation has not been able to reach physician‐level accuracy in detecting (acute) cardiac abnormalities. This study aims to develop and validate a deep neural network for comprehensive automated ECG triage in daily practice. Methods and Results We developed a 37‐layer convolutional residual deep neural network on a data set of free‐text physician‐annotated 12‐lead ECGs. The deep neural network was trained on a data set with 336.835 recordings from 142.040 patients and validated on an independent validation data set (n=984), annotated by a panel of 5 cardiologists electrophysiologists. The 12‐lead ECGs were acquired in all noncardiology departments of the University Medical Center Utrecht. The algorithm learned to classify these ECGs into the following 4 triage categories: normal, abnormal not acute, subacute, and acute. Discriminative performance is presented with overall and category‐specific concordance statistics, polytomous discrimination indexes, sensitivities, specificities, and positive and negative predictive values. The patients in the validation data set had a mean age of 60.4 years and 54.3% were men. The deep neural network showed excellent overall discrimination with an overall concordance statistic of 0.93 (95% CI, 0.92–0.95) and a polytomous discriminatory index of 0.83 (95% CI, 0.79–0.87). Conclusions This study demonstrates that an end‐to‐end deep neural network can be accurately trained on unstructured free‐text physician annotations and used to consistently triage 12‐lead ECGs. When further fine‐tuned with other clinical outcomes and externally validated in clinical practice, the demonstrated deep learning–based ECG interpretation can potentially improve time to treatment and decrease healthcare burden

Hallucinations in borderline personality disorder: Prevalence, characteristics and associations with comorbid symptoms and disorders

textabstractTo establish the point prevalence of hallucinations in borderline personality disorder (BPD), telephone interviews were conducted with 324 outpatients diagnosed with BPD. Then a subgroup (n = 98) was interviewed in person to investigate the co-occurrence of these phenomena with other psychotic symptoms, comorbid psychiatric disorders, prior childhood adversities, and adult life stressors. For hallucinations in general a point prevalence of 43% was found, with rates for hallucinations in separate sensory modalities ranging from 8-21%. Auditory verbal hallucinations consisted mostly of verbal abuse and were generally experienced as distressing. A significant association was found between the severity of hallucinations on the one hand, and delusions and unusual thought content on the other; this association was absent for negative symptoms and disorganization. The presence of hallucinations also correlated with the number of comorbid psychiatric disorders, and with posttraumatic stress disorder (PTSD) specifically. Childhood emotional abuse and adult life stressors were also associated with hallucinations. The latter three associations suggest that patients with BPD might have an etiological mechanism in common with other patient/nonpatient groups who experience hallucinations. Based on these findings, we advise to treat PTSD and hallucinations when found to be present in patients with BPD

The phenomenological features of auditory verbal hallucinations in schizophrenia and across clinical disorders: A state-of-the-art overview and critical evaluation.

Despite a growing interest in auditory verbal hallucinations (AVHs) in different clinical and nonclinical groups, the phenomenological characteristics of such experiences have not yet been reviewed and contrasted, limiting our understanding of these phenomena on multiple empirical, theoretical, and clinical levels. We look at some of the most prominent descriptive features of AVHs in schizophrenia (SZ). These are then examined in clinical conditions including substance abuse, Parkinson’s disease, epilepsy, dementia, late-onset SZ, mood disorders, borderline personality disorder, hearing impairment, and dissociative disorders. The phenomenological changes linked to AVHs in prepsychotic stages are also outlined, together with a review of AVHs in healthy persons. A discussion of key issues and future research directions concludes the review

A prognostic model predicted deterioration in health-related quality of life in older patients with multimorbidity and polypharmacy

Objectives: To develop and validate a prognostic model to predict deterioration in health-related quality of life (dHRQoL) in older general practice patients with at least one chronic condition and one chronic prescription. Study Design and Setting: We used individual participant data from five cluster-randomized trials conducted in the Netherlands and Germany to predict dHRQoL, defined as a decrease in EQ-5D-3 L index score of ≥5% after 6-month follow-up in logistic regression models with stratified intercepts to account for between-study heterogeneity. The model was validated internally and by using internal–external cross-validation (IECV). Results: In 3,582 patients with complete data, of whom 1,046 (29.2%) showed deterioration in HRQoL, and 12/87 variables were selected that were related to single (chronic) conditions, inappropriate medication, medication underuse, functional status, well-being, and HRQoL. Bootstrap internal validation showed a C-statistic of 0.71 (0.69 to 0.72) and a calibration slope of 0.88 (0.78 to 0.98). In the IECV loop, the model provided a pooled C-statistic of 0.68 (0.65 to 0.70) and calibration-in-the-large of 0 (−0.13 to 0.13). HRQoL/functionality had the strongest prognostic value. Conclusion: The model performed well in terms of discrimination, calibration, and generalizability and might help clinicians identify older patients at high risk of dHRQoL. Registration: PROSPERO ID: CRD42018088129