Mathematical coupling and the true role of baseline severity in acute mania trials

Individual cardiovascular responsiveness to work-matched exercise within the moderate- and severe-intensity domains

Purpose

We investigated the cardiovascular individual response to 6 weeks (3×/week) of work-matched within the severe-intensity domain (high-intensity interval training, HIIT) or moderate-intensity domain (moderate-intensity continuous training, MICT). In addition, we analyzed the cardiovascular factors at baseline underlying the response variability.

Methods

42 healthy sedentary participants were randomly assigned to HIIT or MICT. We applied the region of practical equivalence-method for identifying the levels of responders to the maximal oxygen uptake (V̇O_2max) response. For investigating the influence of cardiovascular markers, we trained a Bayesian machine learning model on cardiovascular markers.

Results

Despite that HIIT and MICT induced significant increases in V̇O_2max, HIIT had greater improvements than MICT (p < 0.001). Greater variability was observed in MICT, with approximately 50% classified as “non-responder” and “undecided”. 20 “responders”, one “undecided” and no “non-responders” were observed in HIIT. The variability in the ∆V̇O_2max was associated with initial cardiorespiratory fitness, arterial stiffness, and left-ventricular (LV) mass and LV end-diastolic diameter in HIIT; whereas, microvascular responsiveness and right-ventricular (RV) excursion velocity showed a significant association in MICT.

Conclusion

Our findings highlight the critical influence of exercise-intensity domains and biological variability on the individual V̇O_2max response. The incidence of “non-responders” in MICT was one third of the group; whereas, no “non-responders” were observed in HIIT. The incidence of “responders” was 11 out of 21 participants in MICT, and 20 out of 21 participants in HIIT. The response in HIIT showed associations with baseline fitness, arterial stiffness, and LV-morphology; whereas, it was associated with RV systolic function in MICT.

Combining threshold analysis and GRADE to assess sensitivity to bias in antidepressant treatment recommendations adjusted for depression severity

Threshold analysis has recently been proposed to be used in combination with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) in order to assess the sensitivity to plausible bias of treatment recommendations derived from Bayesian network meta-analysis (NMA). Here, it was aimed to apply the combination of threshold analysis and GRADE to judge quantitative and qualitative information on risk of bias in antidepressant treatment recommendations. The analysis was based on the data set provided by Cipriani et al. (The Lancet 2018) comparing 21 antidepressants in adult major depressive disorder (MDD). Primary outcomes were efficacy (response rate) and acceptability (dropout rate) adjusted for the covariate depression severity. The combined approach suggested sensitivity to plausible bias to be largest for antidepressant recommendations top ranked by Cipriani et al., that is, amitriptyline, duloxetine, paroxetine, and venlafaxine in terms of efficacy and agomelatine, escitalopram, paroxetine, and venlafaxine in terms of acceptability. Covariate ranges within which recommendations were most sensitive to plausible bias were very severe depression in terms of efficacy (smallest threshold, ie, the largest sensitivity, around 39 Hamilton Depression Rating Scale [HDRS]) and moderate depression in terms of acceptability (smallest thresholds around 16 and 35 HDRS). This indicates that treatment recommendations within these ranges may likely change if plausible bias adjustments take place. The present findings may support decision makers in judging the sensitivity to plausible bias of current antidepressant treatment recommendations to accurately guide treatment decisions in MDD depending on depression severity.

The International College of Neuro-Psychopharmacology (CINP) Treatment Guidelines for Bipolar Disorder in Adults (CINP-BD-2017), Part 2: Review, Grading of the Evidence, and a Precise Algorithm

Background

The current paper includes a systematic search of the literature, a detailed presentation of the results, and a grading of treatment options in terms of efficacy and tolerability/safety.

Material and Methods

The PRISMA method was used in the literature search with the combination of the words 'bipolar,' 'manic,' 'mania,' 'manic depression,' and 'manic depressive' with 'randomized,' and 'algorithms' with 'mania,' 'manic,' 'bipolar,' 'manic-depressive,' or 'manic depression.' Relevant web pages and review articles were also reviewed.

Results

The current report is based on the analysis of 57 guideline papers and 531 published papers related to RCTs, reviews, posthoc, or meta-analysis papers to March 25, 2016. The specific treatment options for acute mania, mixed episodes, acute bipolar depression, maintenance phase, psychotic and mixed features, anxiety, and rapid cycling were evaluated with regards to efficacy. Existing treatment guidelines were also reviewed. Finally, Tables reflecting efficacy and recommendation levels were created that led to the development of a precise algorithm that still has to prove its feasibility in everyday clinical practice.

Conclusions

A systematic literature search was conducted on the pharmacological treatment of bipolar disorder to identify all relevant random controlled trials pertaining to all aspects of bipolar disorder and graded the data according to a predetermined method to develop a precise treatment algorithm for management of various phases of bipolar disorder. It is important to note that the some of the recommendations in the treatment algorithm were based on the secondary outcome data from posthoc analyses.

From Randomized Controlled Trials of Antidepressant Drugs to the Meta-Analytic Synthesis of Evidence: Methodological Aspects Lead to Discrepant Findings

During the last decade, several meta-analytic studies employing different methodological approaches have had inconsistent conclusions regarding antidepressant efficacy. Herein, we aim to comment on methodological aspects that may have contributed to disparate findings. We initially discuss methodological inconsistencies and limitations related to the conduct of individual antidepressant randomized controlled trials (RCTs), including differences in allocated samples, limitations of psychometric scales, possible explanations for the heightened placebo response rates in antidepressant RCTs across the past two decades as well as the reporting of conflicts of interest. In the second part of this article, we briefly describe the various meta-analyses techniques (e.g., simple random effects meta-analysis and network meta-analysis) and the application of these methods to synthesize evidence related to antidepressant efficacy. Recently published antidepressant metaanalyses often provide discrepant results and similar results often lead to different interpretations. Finally, we propose strategies to improve methodology considering real-world clinical scenarios.

Burning issues in the meta-analysis of pharmaceutical trials for depression

During the last decade a number of meta-analytic studies have been published and they triggered a debate on the true clinical usefulness of antidepressants. The current article comments on problems within the randomized controlled trials design, the study samples, the psychometric scales, the methods of meta-analysis, the interpretation of the results, and the reporting of conflicts of interest. Although the meta-analyses published so far agree that medication works in severe depression, they question its efficacy in mild cases. However, several methodological issues should be clarified before conclusions are definite. Different methods give different results and similar results seem to entertain a variety of interpretations. In the future it is important to address all of these problems, and to improve methodology on the basis of clinically informed choices. Otherwise, meta-analysis risks alienation from clinical reality and thus risks becoming the 21(st) century psychoanalysis.

No differences between drug naive and drug experienced unipolar depressed patients in terms of neurobiological testing: a cross sectional study

Successful antidepressant treatment has been associated with concomitant changes in brain function, consolidated as long as treatment is continued and remission is preserved. The present study aimed at assessing the impact of prior antidepressant treatment on brain function in currently depressed but unmedicated individuals by investigating for any differences between antidepressant-naïve vs. antidepressant-experienced subjects. Fifty right-handed patients (22 medication-naïve vs. 28 medication-experienced), suffering from major depression participated in the study. They all underwent a standardised clinical interview and psychometric assessment combined with neurobiological tests (brain SPECT, Dexamethasone Suppression Test, Dexfenfluramine Challenge Test, electro-oculogram, flash-electroretinogram and flash-visual evoked potentials and pattern-reversal visual evoked potentials). No significant differences between medication-naïve and medication-experienced depressed subjects were found in terms of the neurobiological markers assessed, after controlling for age, sex, age at onset, number of depressive episodes, depression subtype (melancholic, atypical or undifferentiated) and severity of current episode. Unmedicated currently depressed patients, no matter their previous exposure to antidepressants, show similar changes in brain function. This does not necessarily mean that antidepressants do not have a long term effect on brain physiology, since not all patients relapse. However, it seems that those patients who relapse after stopping medication, seem to 'regress' to an 'as if never medicated' state, with regard to brain function. These findings might suggest that continuous maintenance treatment with antidepressants is essential for patients at high risk to relapse. Alternatively, they might suggest that our methodology assesses only a shallow and mainly state part of the pathophysiology of depression.