Associations of Menstrual Cycle and Progesterone-to-Estradiol Ratio With Alcohol Consumption in Alcohol Use Disorder: A Sex-Separated Multicenter Longitudinal Study.

OBJECTIVE: Alcohol use disorder (AUD) constitutes a critical public health issue and has sex-specific characteristics. Initial evidence suggests that progesterone and estradiol might reduce or increase alcohol intake, respectively. However, there is a need for a better understanding of how the menstrual cycle in females and the ratio of progesterone to estradiol in females and males influence alcohol use patterns in individuals with AUD. METHODS: In this sex-separated multicenter longitudinal study, the authors analyzed 12-month data on real-life alcohol use (from 21,460 smartphone entries), menstrual cycle, and serum progesterone-to-estradiol ratios (from 667 blood samples at four individual study visits) in 74 naturally cycling females and 278 males with AUD between 2020 and 2022, using generalized and general linear mixed modeling. RESULTS: Menstrual cycle phases were significantly associated with binge drinking and progesterone-to-estradiol ratio. During the late luteal phase, females showed a lower predicted binge drinking probability of 13% and a higher predicted marginal mean of progesterone-to-estradiol ratio of 95 compared with during the menstrual, follicular, and ovulatory phases (binge drinking probability and odds ratios vs. late luteal phase, respectively: 17%, odds ratio=1.340, 95% CI=1.031, 1.742; 19%, odds ratio=1.523, 95% CI=1.190, 1.949; and 20%, odds ratio=1.683, 95% CI=1.285, 2.206; difference in progesterone-to-estradiol ratios, respectively: -61, 95% CI=-105.492, -16.095; -78, 95% CI=-119.322, -37.039; and -71, 95% CI=-114.568, -27.534). In males, a higher progesterone-to-estradiol ratio was related to lower probabilities of binge drinking and of any alcohol use, with a 10-unit increase in the hormone ratio resulting in odds ratios of 0.918 (95% CI=0.843, 0.999) and 0.914 (95% CI=0.845, 0.988), respectively. CONCLUSIONS: These ecologically valid findings suggest that high progesterone-to-estradiol ratios can have a protective effect against problematic alcohol use in females and males with AUD, highlighting the progesterone-to-estradiol ratio as a promising treatment target. Moreover, the results indicate that females with AUD may benefit from menstrual cycle phase-tailored treatments.

Measuring self-regulation in everyday life: Reliability and validity of smartphone-based experiments in alcohol use disorder.

Self-regulation, the ability to guide behavior according to one's goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test-retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures' construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks.

Patterns of Alcohol Consumption Among Individuals With Alcohol Use Disorder During the COVID-19 Pandemic and Lockdowns in Germany.

Importance: Alcohol consumption (AC) leads to death and disability worldwide. Ongoing discussions on potential negative effects of the COVID-19 pandemic on AC need to be informed by real-world evidence. Objective: To examine whether lockdown measures are associated with AC and consumption-related temporal and psychological within-person mechanisms. Design, Setting, and Participants: This quantitative, intensive, longitudinal cohort study recruited 1743 participants from 3 sites from February 20, 2020, to February 28, 2021. Data were provided before and within the second lockdown of the COVID-19 pandemic in Germany: before lockdown (October 2 to November 1, 2020); light lockdown (November 2 to December 15, 2020); and hard lockdown (December 16, 2020, to February 28, 2021). Main Outcomes and Measures: Daily ratings of AC (main outcome) captured during 3 lockdown phases (main variable) and temporal (weekends and holidays) and psychological (social isolation and drinking intention) correlates. Results: Of the 1743 screened participants, 189 (119 [63.0%] male; median [IQR] age, 37 [27.5-52.0] years) with at least 2 alcohol use disorder (AUD) criteria according to the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) yet without the need for medically supervised alcohol withdrawal were included. These individuals provided 14 694 smartphone ratings from October 2020 through February 2021. Multilevel modeling revealed significantly higher AC (grams of alcohol per day) on weekend days vs weekdays (ß = 11.39; 95% CI, 10.00-12.77; P < .001). Alcohol consumption was above the overall average on Christmas (ß = 26.82; 95% CI, 21.87-31.77; P < .001) and New Year's Eve (ß = 66.88; 95% CI, 59.22-74.54; P < .001). During the hard lockdown, perceived social isolation was significantly higher (ß = 0.12; 95% CI, 0.06-0.15; P < .001), but AC was significantly lower (ß = -5.45; 95% CI, -8.00 to -2.90; P = .001). Independent of lockdown, intention to drink less alcohol was associated with lower AC (ß = -11.10; 95% CI, -13.63 to -8.58; P < .001). Notably, differences in AC between weekend and weekdays decreased both during the hard lockdown (ß = -6.14; 95% CI, -9.96 to -2.31; P = .002) and in participants with severe AUD (ß = -6.26; 95% CI, -10.18 to -2.34; P = .002). Conclusions and Relevance: This 5-month cohort study found no immediate negative associations of lockdown measures with overall AC. Rather, weekend-weekday and holiday AC patterns exceeded lockdown effects. Differences in AC between weekend days and weekdays evinced that weekend drinking cycles decreased as a function of AUD severity and lockdown measures, indicating a potential mechanism of losing and regaining control. This finding suggests that temporal patterns and drinking intention constitute promising targets for prevention and intervention, even in high-risk individuals.

Low predictive power of clinical features for relapse prediction after antidepressant discontinuation in a naturalistic setting.

The risk of relapse after antidepressant medication (ADM) discontinuation is high. Predictors of relapse could guide clinical decision-making, but are yet to be established. We assessed demographic and clinical variables in a longitudinal observational study before antidepressant discontinuation. State-dependent variables were re-assessed either after discontinuation or before discontinuation after a waiting period. Relapse was assessed during 6 months after discontinuation. We applied logistic general linear models in combination with least absolute shrinkage and selection operator and elastic nets to avoid overfitting in order to identify predictors of relapse and estimated their generalisability using cross-validation. The final sample included 104 patients (age: 34.86 (11.1), 77% female) and 57 healthy controls (age: 34.12 (10.6), 70% female). 36% of the patients experienced a relapse. Treatment by a general practitioner increased the risk of relapse. Although within-sample statistical analyses suggested reasonable sensitivity and specificity, out-of-sample prediction of relapse was at chance level. Residual symptoms increased with discontinuation, but did not relate to relapse. Demographic and standard clinical variables appear to carry little predictive power and therefore are of limited use for patients and clinicians in guiding clinical decision-making.

Residential green space and air pollution are associated with brain activation in a social-stress paradigm.

We examined the influence of three major environmental variables at the place of residence as potential moderating variables for neurofunctional activation during a social-stress paradigm. Data from functional magnetic resonance imaging of 42 male participants were linked to publicly accessible governmental databases providing information on amount of green space, air pollution, and noise pollution. We hypothesized that stress-related brain activation in regions important for emotion regulation were associated positively with green space and associated negatively with air pollution and noise pollution. A higher percentage of green space was associated with stronger parietal and insular activation during stress compared with that in the control condition. More air pollution was associated with weaker activation in the same (but also extended) brain regions. These findings may serve as an important reference for future studies in the emerging field of "neuro-urbanism" and emphasize the importance of environmental factors in urban planning.

Precuneus connectivity and symptom severity in chronic depression✰.

Although abnormal resting state connectivity within several brain networks has been repeatedly reported in depression, little is known about connectivity in patients with early onset chronic depression. We compared resting state connectivity in a homogenous sample of 32 unmedicated patients with early onset chronic depression and 40 healthy control participants in a seed-to-voxel-analysis. According to previous meta-analyses on resting state connectivity in depression, 12 regions implicated in default mode, limbic, frontoparietal and ventral attention networks were chosen as seeds. We also investigated associations between connectivity values and severity of depression. Patients with chronic depression exhibited stronger connectivity between precuneus and right pre-supplementary motor area than healthy control participants, possibly reflecting aberrant information processing and emotion regulation deficits in depression. Higher depression severity scores (Hamilton Rating Scale for Depression) were strongly and selectively associated with weaker connectivity between the precuneus and the subcallosal anterior cingulate. Our findings correspond to results obtained in studies including both episodic and chronic depression. This suggests that there may be no strong differences between subtypes of depression regarding the seeds analyzed here. To further clarify this issue, future studies should directly compare patients with different courses of depression.

The relationship between resting-state functional connectivity, antidepressant discontinuation and depression relapse.

The risk of relapsing into depression after stopping antidepressants is high, but no established predictors exist. Resting-state functional magnetic resonance imaging (rsfMRI) measures may help predict relapse and identify the mechanisms by which relapses occur. rsfMRI data were acquired from healthy controls and from patients with remitted major depressive disorder on antidepressants. Patients were assessed a second time either before or after discontinuation of the antidepressant, and followed up for six months to assess relapse. A seed-based functional connectivity analysis was conducted focusing on the left subgenual anterior cingulate cortex and left posterior cingulate cortex. Seeds in the amygdala and dorsolateral prefrontal cortex were explored. 44 healthy controls (age: 33.8 (10.5), 73% female) and 84 patients (age: 34.23 (10.8), 80% female) were included in the analysis. 29 patients went on to relapse and 38 remained well. The seed-based analysis showed that discontinuation resulted in an increased functional connectivity between the right dorsolateral prefrontal cortex and the parietal cortex in non-relapsers. In an exploratory analysis, this functional connectivity predicted relapse risk with a balanced accuracy of 0.86. Further seed-based analyses, however, failed to reveal differences in functional connectivity between patients and controls, between relapsers and non-relapsers before discontinuation and changes due to discontinuation independent of relapse. In conclusion, changes in the connectivity between the dorsolateral prefrontal cortex and the posterior default mode network were associated with and predictive of relapse after open-label antidepressant discontinuation. This finding requires replication in a larger dataset.

Computational Mechanisms of Effort and Reward Decisions in Patients With Depression and Their Association With Relapse After Antidepressant Discontinuation.

Importance: Nearly 1 in 3 patients with major depressive disorder who respond to antidepressants relapse within 6 months of treatment discontinuation. No predictors of relapse exist to guide clinical decision-making in this scenario. Objectives: To establish whether the decision to invest effort for rewards represents a persistent depression process after remission, predicts relapse after remission, and is affected by antidepressant discontinuation. Design, Setting, and Participants: This longitudinal randomized observational prognostic study in a Swiss and German university setting collected data from July 1, 2015, to January 31, 2019, from 66 healthy controls and 123 patients in remission from major depressive disorder in response to antidepressants prior to and after discontinuation. Study recruitment took place until January 2018. Exposure: Discontinuation of antidepressants. Main Outcomes and Measures: Relapse during the 6 months after discontinuation. Choice and decision times on a task requiring participants to choose how much effort to exert for various amounts of reward and the mechanisms identified through parameters of a computational model. Results: A total of 123 patients (mean [SD] age, 34.5 [11.2] years; 94 women [76%]) and 66 healthy controls (mean [SD] age, 34.6 [11.0] years; 49 women [74%]) were recruited. In the main subsample, mean (SD) decision times were slower for patients (n = 74) compared with controls (n = 34) (1.77 [0.38] seconds vs 1.61 [0.37] seconds; Cohen d = 0.52; P = .02), particularly for those who later relapsed after discontinuation of antidepressants (n = 21) compared with those who did not relapse (n = 39) (1.95 [0.40] seconds vs 1.67 [0.34] seconds; Cohen d = 0.77; P < .001). This slower decision time predicted relapse (accuracy = 0.66; P = .007). Patients invested less effort than healthy controls for rewards (F1,98 = 33.970; P < .001). Computational modeling identified a mean (SD) deviation from standard drift-diffusion models that was more prominent for patients than controls (patients, 0.67 [1.56]; controls, -0.71 [1.93]; Cohen d = 0.82; P < .001). Patients also showed higher mean (SD) effort sensitivity than controls (patients, 0.31 [0.92]; controls, -0.08 [1.03]; Cohen d = 0.51; P = .05). Relapsers differed from nonrelapsers in terms of the evidence required to make a decision for the low-effort choice (mean [SD]: relapsers, 1.36 [0.35]; nonrelapsers, 1.17 [0.26]; Cohen d = 0.65; P = .02). Group differences generally did not reach significance in the smaller replication sample (27 patients and 21 controls), but decision time prediction models from the main sample generalized to the replication sample (validation accuracy = 0.71; P = .03). Conclusions and Relevance: This study found that the decision to invest effort was associated with prospective relapse risk after antidepressant discontinuation and may represent a persistent disease process in asymptomatic remitted major depressive disorder. Markers based on effort-related decision-making could potentially inform clinical decisions associated with antidepressant discontinuation.

Airway management techniques in a restricted-access situation: a manikin study.

BACKGROUND: Access to patients can be restricted in emergency situations. A variety of techniques and devices are available for use in patients who require oxygenation in a restricted-access situation. OBJECTIVES: The aim of this study was to investigate whether there is one ventilation technique that is superior to others. MATERIALS AND METHODS: Fifty-four emergency medical services providers including emergency medical technicians, paramedics and physicians were asked to use a bag-valve mask (BVM), a laryngeal mask airway (LMA), and a laryngeal tube (LT) to ventilate a full-scale manikin sitting upright in the driver's seat of a motor vehicle. Access to the manikin was gained through the side window and from the backseat. RESULTS: There were significant differences in time to first successful ventilation between the two approaches for access to the airway. The fastest median time to ventilation was obtained with the BVM (7 and 8 s), followed by the LT (13 and 14 s) and the LMA (15 s for both types of access). Overall success rates were 97.2% for the BVM, 96.3% for the LMA, and 100% for the LT. Most participants needed two attempts for each device. There were no significant differences between participants depending on the level of qualification or professional experience. The BVM was rated the lowest and the LT was rated the highest for ease of use. CONCLUSION: Supraglottic airway devices appear to offer advantages in restricted-access situations.