Raising awareness of uncertain choices in empirical data analysis: A teaching concept toward replicable research practices.

Throughout their education and when reading the scientific literature, students may get the impression that there is a unique and correct analysis strategy for every data analysis task and that this analysis strategy will always yield a significant and noteworthy result. This expectation conflicts with a growing realization that there is a multiplicity of possible analysis strategies in empirical research, which will lead to overoptimism and nonreplicable research findings if it is combined with result-dependent selective reporting. Here, we argue that students are often ill-equipped for real-world data analysis tasks and unprepared for the dangers of selectively reporting the most promising results. We present a seminar course intended for advanced undergraduates and beginning graduate students of data analysis fields such as statistics, data science, or bioinformatics that aims to increase the awareness of uncertain choices in the analysis of empirical data and present ways to deal with these choices through theoretical modules and practical hands-on sessions.

Long-term benefits and harms of early colorectal cancer screening in German individuals with familial cancer risk.

Individuals with a family history of colorectal cancer (CRC) may benefit from early screening with colonoscopy or immunologic fecal occult blood testing (iFOBT). We systematically evaluated the benefit-harm trade-offs of various screening strategies differing by screening test (colonoscopy or iFOBT), interval (iFOBT: annual/biennial; colonoscopy: 10-yearly) and age at start (30, 35, 40, 45, 50 and 55 years) and end of screening (65, 70 and 75 years) offered to individuals identified with familial CRC risk in Germany. A Markov-state-transition model was developed and used to estimate health benefits (CRC-related deaths avoided, life-years gained [LYG]), potential harms (eg, associated with additional colonoscopies) and incremental harm-benefit ratios (IHBR) for each strategy. Both benefits and harms increased with earlier start and shorter intervals of screening. When screening started before age 50, 32-36 CRC-related deaths per 1000 persons were avoided with colonoscopy and 29-34 with iFOBT screening, compared to 29-31 (colonoscopy) and 28-30 (iFOBT) CRC-related deaths per 1000 persons when starting age 50 or older, respectively. For iFOBT screening, the IHBRs expressed as additional colonoscopies per LYG were one (biennial, age 45-65 vs no screening), four (biennial, age 35-65), six (biennial, age 30-70) and 34 (annual, age 30-54; biennial, age 55-75). Corresponding IHBRs for 10-yearly colonoscopy were four (age 55-65), 10 (age 45-65), 15 (age 35-65) and 29 (age 30-70). Offering screening with colonoscopy or iFOBT to individuals with familial CRC risk before age 50 is expected to be beneficial. Depending on the accepted IHBR threshold, 10-yearly colonoscopy or alternatively biennial iFOBT from age 30 to 70 should be recommended for this target group.

Addressing researcher degrees of freedom through minP adjustment.

When different researchers study the same research question using the same dataset they may obtain different and potentially even conflicting results. This is because there is often substantial flexibility in researchers' analytical choices, an issue also referred to as "researcher degrees of freedom". Combined with selective reporting of the smallest p-value or largest effect, researcher degrees of freedom may lead to an increased rate of false positive and overoptimistic results. In this paper, we address this issue by formalizing the multiplicity of analysis strategies as a multiple testing problem. As the test statistics of different analysis strategies are usually highly dependent, a naive approach such as the Bonferroni correction is inappropriate because it leads to an unacceptable loss of power. Instead, we propose using the "minP" adjustment method, which takes potential test dependencies into account and approximates the underlying null distribution of the minimal p-value through a permutation-based procedure. This procedure is known to achieve more power than simpler approaches while ensuring a weak control of the family-wise error rate. We illustrate our approach for addressing researcher degrees of freedom by applying it to a study on the impact of perioperative p a O 2 on post-operative complications after neurosurgery. A total of 48 analysis strategies are considered and adjusted using the minP procedure. This approach allows to selectively report the result of the analysis strategy yielding the most convincing evidence, while controlling the type 1 error-and thus the risk of publishing false positive results that may not be replicable.

Lifetime cumulative activity burden is associated with symptomatic heart failure and arrhythmic risk in patients with arrhythmogenic right ventricular cardiomyopathy: a retrospective cohort study.

AIMS: Sports-related physical activity is associated with an increased risk of ventricular dysfunction and arrhythmias in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC). However, there are currently no standardized strategies for activity assessment. Thresholds for harmful levels of physical activity suggested by previous studies vary substantially and neither lifetime activity burden nor continuous modelling approaches were considered. METHODS AND RESULTS: For this single-centre retrospective study, ARVC patients were interviewed to assess sports-related and non-sports-related physical activity between the age of 10 years and the last follow-up. Activity data were aggregated to the median metabolic equivalent of task-hours (METh) per week for each year. The association between cumulative physical activity burden and clinical study endpoints was investigated using Cox regression models. A total of 124 patients (median age: 39.5 years, 48% male) were included in the analysis, of whom 93 had been diagnosed with definite ARVC. Study participants reported a median overall activity of 202.3 METh/week, with 38.7 METh/week attributed to sports-related activity. In the continuous model, cumulative overall activity burden was associated with the occurrence of symptomatic heart failure [hazard ratio (HR) per 100 METh/week: 1.017, 95% CI (1.003, 1.032), P = 0.015], sustained ventricular tachycardia [HR: 1.021, 95% CI (1.006, 1.037), P = 0.007], and implantable cardioverter defibrillator interventions [HR: 1.017, 95%CI (1.000, 1.034), P = 0.048]. This finding was consistent when considering sports-related activity separately as a predictor variable, whereas the resulting hazard ratios did not show a significant association for non-sports-related physical activity. CONCLUSION: This study demonstrates for the first time that cumulative physical activity as a continuous predictor variable is associated with symptomatic heart failure and arrhythmic risk in ARVC patients. Collaborative research is required in larger cohorts to investigate the influence of potential confounders on event occurrence and to develop threshold recommendations for clinical practice.

Alcohol does not influence trust in others or oxytocin, but increases positive affect and risk-taking: a randomized, controlled, within-subject trial.

BACKGROUND: Alcohol consumption to facilitate social interaction is an important drinking motive. Here, we tested whether alcohol influences trust in others via modulation of oxytocin and/or androgens. We also aimed at confirming previously shown alcohol effects on positive affect and risk-taking, because of their role in facilitating social interaction. METHODS: This randomized, controlled, within-subject, parallel group, alcohol-challenge experiment investigated the effects of alcohol (versus water, both mixed with orange juice) on perceived trustworthiness via salivary oxytocin (primary and secondary endpoint) as well as testosterone, dihydrotestosterone, positive affect, and risk-taking (additional endpoints). We compared 56 male participants in the alcohol condition (1.07 ± 0.18 per mille blood alcohol concentration) with 20 in the control condition. RESULTS: The group (alcohol versus control condition) × time (before [versus during] versus after drinking) interactions were not significantly associated with perceived trustworthiness (η2 < 0.001) or oxytocin (η2 = 0.003). Bayes factors provided also substantial evidence for the absence of these effects (BF01 = 3.65; BF01 = 7.53). The group × time interactions were related to dihydrotestosterone (η2 = 0.018 with an increase in the control condition) as well as positive affect and risk-taking (η2 = 0.027 and 0.007 with increases in the alcohol condition), but not significantly to testosterone. DISCUSSION: The results do not verify alcohol effects on perceived trustworthiness or oxytocin in male individuals. However, they indicate that alcohol (versus control) might inhibit an increase in dihydrotestosterone and confirm that alcohol amplifies positive affect and risk-taking. This provides novel mechanistic insight into social facilitation as an alcohol-drinking motive.

Explaining the optimistic performance evaluation of newly proposed methods: A cross-design validation experiment.

The constant development of new data analysis methods in many fields of research is accompanied by an increasing awareness that these new methods often perform better in their introductory paper than in subsequent comparison studies conducted by other researchers. We attempt to explain this discrepancy by conducting a systematic experiment that we call "cross-design validation of methods". In the experiment, we select two methods designed for the same data analysis task, reproduce the results shown in each paper, and then reevaluate each method based on the study design (i.e., datasets, competing methods, and evaluation criteria) that was used to show the abilities of the other method. We conduct the experiment for two data analysis tasks, namely cancer subtyping using multiomic data and differential gene expression analysis. Three of the four methods included in the experiment indeed perform worse when they are evaluated on the new study design, which is mainly caused by the different datasets. Apart from illustrating the many degrees of freedom existing in the assessment of a method and their effect on its performance, our experiment suggests that the performance discrepancies between original and subsequent papers may not only be caused by the nonneutrality of the authors proposing the new method but also by differences regarding the level of expertise and field of application. Authors of new methods should thus focus not only on a transparent and extensive evaluation but also on comprehensive method documentation that enables the correct use of their methods in subsequent studies.

A Bayesian hierarchical approach to account for evidence and uncertainty in the modeling of infectious diseases: An application to COVID-19.

Infectious disease models can serve as critical tools to predict the development of cases and associated healthcare demand and to determine the set of nonpharmaceutical interventions (NPIs) that is most effective in slowing the spread of an infectious agent. Current approaches to estimate NPI effects typically focus on relatively short time periods and either on the number of reported cases, deaths, intensive care occupancy, or hospital occupancy as a single indicator of disease transmission. In this work, we propose a Bayesian hierarchical model that integrates multiple outcomes and complementary sources of information in the estimation of the true and unknown number of infections while accounting for time-varying underreporting and weekday-specific delays in reported cases and deaths, allowing us to estimate the number of infections on a daily basis rather than having to smooth the data. To address dynamic changes occurring over long periods of time, we account for the spread of new variants, seasonality, and time-varying differences in host susceptibility. We implement a Markov chain Monte Carlo algorithm to conduct Bayesian inference and illustrate the proposed approach with data on COVID-19 from 20 European countries. The approach shows good performance on simulated data and produces posterior predictions that show a good fit to reported cases, deaths, hospital, and intensive care occupancy.

[Factors influencing hospital readmission rates in alcohol use disorder]. / Einflussfaktoren auf die Rehospitalisierungsrate bei Alkoholabhängigkeit.

BACKGROUND: According to data from the Federal Statistical Office, the diagnosis of alcohol use disorder (AUD) (F 10) is the second most common main diagnosis for hospital treatment. Those affected by this disorder are often repeatedly hospitalized at short intervals due to relapses; however, little is known about the factors that influence readmission rates after initial treatment. AIM OF THE STUDY: The aim of this retrospective analysis is to analyze the effects of treatment type (qualified withdrawal treatment (QE) versus physical detoxification) and discharge mode on the probability of readmission in alcohol-dependent patients after inpatient treatment. MATERIAL AND METHODS: Data from 981 male and female alcohol-dependent patients who completed either qualified withdrawal treatment (QE) (68% men; mean age 47.6 years) or inpatient detoxification (74% men; mean age 48.0 years) were analyzed. Predictors of regular discharge were determined separately for both types of treatment using stepwise logistic regression. RESULTS: Patients who had completed a qualified withdrawal treatment were significantly more likely to be regularly discharged. Regular completion of the qualified withdrawal treatment (QE) led to a relative reduction in the readmission rate of 25.64% within 1 year compared to a physical detoxification. CONCLUSION: In order to prevent readmission and chronic courses of alcohol use disorder (AUD), qualified withdrawal treatment should always be recommended to affected patients instead of physical detoxification. Aktuelle Daten des Statistischen Bundesamtes für das Jahr 2022 zeigen, dass die Diagnose "Psychische und Verhaltensstörungen durch Alkohol (F 10.X)" die zweithäufigste Hauptdiagnose bei Krankenhausbehandlungen darstellt [13]. Im Gesundheitssystem entstehen durch dieses Erkrankungsbild und seine somatischen und psychischen Folgeerkrankungen jährlich ca. 10 Mrd. € direkte Kosten [13]. Dieser Sachverhalt wird dadurch kontrastiert, dass die Krankenkassen die qualifizierte Entzugsbehandlung (QE) als leitliniengerechte Goldstandardtherapie [4] wiederholt infrage stellen [10].

[Long-term courses of alcohol dependence]. / Langzeitverläufe der Alkoholabhängigkeit.

BACKGROUND: Descriptions of long-term histories of alcohol dependence provide insight into the etiology, prevention and care. OBJECTIVE: Report of empirical findings about the development into and remission from alcohol dependence. METHOD: Narrative literature review, analysis of findings from cohort studies in the general population. RESULTS: Risk factors provide the opportunity to estimate increased probabilities of developing an alcohol dependence. Adolescents disclosed symptoms of alcohol dependence within 8 years after the first alcohol consumption. Alcohol dependence is related to a life expectancy 17.6 years fewer than in the general population. Data of a general population sample revealed a risk of early death 2.8 times higher than among people without mental disorders. The severity of alcohol dependence was shown to be a predictor of premature death. Nicotine dependence can add to the shortening of life in addition to alcohol dependence. Among the alcohol dependent residents in a general population sample, 90.2% did not have utilized detoxification treatment that included motivational treatment and 78.4% did not have utilized standard detoxification treatment in a psychiatric treatment facility. Remission without formal help has been proven. It is the main route of remission. CONCLUSION: To reduce unfavorable courses of alcohol dependence, prevention and treatment should be focused more on the needs in the general population. In psychiatric and other medical routine care, screening and an appropriate brief intervention should be carried out.

Psychometric properties of the German Penn Alcohol Craving Scale.

Craving for alcohol is an important diagnostic criterion in alcohol use disorder (AUD) and an established predictor of future relapse. The 5-item Penn Alcohol Craving Scale (PACS) is one of the most widely used questionnaires to quantify craving and has been translated into different languages. It is assumed that the PACS constitutes one factor, although theoretical considerations suggest an additional second factor. We conducted stability and factor analyses (principal component and confirmatory factor analyses) of the German PACS (PACS-G) in samples of patients with AUD from the following three German study sites: Erlangen, N = 188 (mean age: 47.1 years, 43.5% female); Mannheim, N = 440 (45.5 years, 28.6% female); Hannover, N = 107 (48.1 years, 48.6% female). In our samples, the 2-factor solution of the PACS-G version is more stable than the internationally assumed 1-factor solution. The resulting two PACS-G subscores 'difficulty to resist' (items 4 and 5) and 'thoughts about alcohol' (items 1, 2, and 3) have an internal consistency (Cronbach's alpha) of 0.80 ≤ α ≤ 0.90, m = 0.86 and 0.86 ≤ α ≤ 0.91, m = 0.89 with an overlap of R2 = 62%. We found good convergent validity assessed via the Craving Automatized Scale-Alcohol and the Obsessive-Compulsive Drinking Scale, but also correlations with depression and anxiety assessed via the Beck's Depression and Anxiety Inventories. This study is the first to provide evidence for a 2-factor solution ('difficulty to resist' and 'thoughts about alcohol') underlying the PACS-G version.

Body mass index interacts with sex to predict readmission in in-patients with alcohol use disorder.

A previous highly controlled pilot study revealed that body mass index (BMI) predicts outcome of in-patients with alcohol use disorder (AUD) in a sex-specific manner. We here provide translational evidence from a daily clinical routine setting and investigated whether BMI and sex interact to predict 24-month readmission risk in four naturalistic cohorts of a specialized addiction clinic (i.e., all patients admitted to the clinic from 2016 to 2020): (i) in-patients (443 males and 197 females) and (ii) day clinic patients (241 males and 103 females) with a primary diagnosis of AUD; (iii) in-patients (175 males and 98 females) and (iv) day clinic patients (174 males and 64 females) with a primary substance use disorder (SUD) other than alcohol. In the in-patients with AUD, BMI interacted with sex to predict the 24-month readmission risks (p = 0.008; after adjustment for age and liver enzyme activities: p = 0.012); with higher BMI, the risk increases significantly in males, whereas for females, the risk tends to decrease. In the group of overweight in-patients, we found higher readmission rates in males relative to females with an odds ratio of 1.8 (p = 0.038). No such significant effects were found in the other cohorts. This study's findings support previous results, suggesting that the easily accessible BMI may serve as a predictive and sex-sensitive biomarker for outcome in in-patients with AUD. Future studies are necessary to elucidate the underlying aetiopathological mechanisms.

Does the Augmentation of Trauma Informed Hatha Yoga Increase the Effect of Dialectical Behavior Therapy for Substance Use Disorders on Psychopathological Strain of Patients with Borderline Personality Disorder and Comorbid Substance Use Disorder? Results of a Quasi-Experimental Study.

BACKGROUND: Borderline personality disorder (BPD) is one of the most common personality disorders among persons with substance use disorders (SUDs) and is characterized by severe clinical symptoms. The aim of this study was to investigate if the effect of dialectical behavior therapy for substance use disorders (DBT-S) inpatient treatment on psychopathological symptom load in patients suffering from both BPD and SUD can be augmented by weekly 60-min "Trauma Informed Hatha Yoga" sessions. MATERIALS AND METHODS: Thirty-nine patients suffering from comorbid BPD and SUD were consecutively in time included in this quasi-experimental pilot study (first intervention then control group). In the intervention group, weekly Trauma Informed Hatha Yoga sessions were added to standard DBT-S for 8 weeks. The participants of the control group received standard DBT-S. All participants completed several self-report questionnaires to assess symptoms of depression, anxiety, symptoms of BPD, and their subjective stress perception at three points in time during the study course. RESULTS: A repeated measures analysis of variance with patients' psychopharmacological medication as covariate revealed a significant main effect of time for each of the psychometric scales (State and Trait Anxiety Inventory subscale for state anxiety [STAI-S] p = 0.001, Beck Depression Inventory [BDI] p < 0.001; Borderline Symptom List 23 [BSL] p = 0.036) indicating that the psychopathological symptom load of the patients was significantly lower at the end of the DBT-S therapy compared to the beginning in both study groups. Moreover, there was a significant interaction effect of group*time on the psychometric scales STAI-T (subscale for trait anxiety) sum score (p = 0.010) and the sum score of the Perceived Stress Scale (PSS) (p = 0.043). This was expressed by the fact that the participants of the intervention group showed a significant reduction of the STAI-T sum score as well as the sum score of the Perceived Stress Scale (PSS), while the control group did not. Due to the exploratory nature of this study, correction for multiple testing was omitted. CONCLUSION: Although they are very preliminary, our results suggest that practicing Trauma Informed Hatha Yoga on a regular basis in addition to DBT-S inpatient treatment seems to reduce the level of trait anxiety and perceived stress significantly more than DBT-S inpatient treatment alone. Nevertheless, the effectiveness of Trauma Informed Hatha Yoga in reducing trait anxiety and perceived stress in patients suffering from SUD und BPD must be tested in large randomized controlled trials.

Increased network centrality of the anterior insula in early abstinence from alcohol.

Abnormal resting-state functional connectivity, as measured by functional magnetic resonance imaging (MRI), has been reported in alcohol use disorders (AUD), but findings are so far inconsistent. Here, we exploited recent developments in graph-theoretical analyses, enabling improved resolution and fine-grained representation of brain networks, to investigate functional connectivity in 35 recently detoxified alcohol dependent patients versus 34 healthy controls. Specifically, we focused on the modular organization, that is, the presence of tightly connected substructures within a network, and on the identification of brain regions responsible for network integration using an unbiased approach based on a large-scale network composed of more than 600 a priori defined nodes. We found significant reductions in global connectivity and region-specific disruption in the network topology in patients compared with controls. Specifically, the basal brain and the insular-supramarginal cortices, which form tightly coupled modules in healthy subjects, were fragmented in patients. Further, patients showed a strong increase in the centrality of the anterior insula, which exhibited stronger connectivity to distal cortical regions and weaker connectivity to the posterior insula. Anterior insula centrality, a measure of the integrative role of a region, was significantly associated with increased risk of relapse. Exploratory analysis suggests partial recovery of modular structure and insular connectivity in patients after 2 weeks. These findings support the hypothesis that, at least during the early stages of abstinence, the anterior insula may drive exaggerated integration of interoceptive states in AUD patients with possible consequences for decision making and emotional states and that functional connectivity is dynamically changing during treatment.

German Guidelines on Screening, Diagnosis, and Treatment of Alcohol Use Disorders: Update 2021.

INTRODUCTION: Alcohol consumption in Germany is associated with considerable health and economic consequences. In addition to prevention, the early detection and differential treatment of those affected play an important role. The guideline "Screening, Diagnosis, and Treatment of Alcohol Use Disorders" forms the basis of this care for people suffering from alcohol use disorders. Regular updates integrate the current state of research evidence and clinical expertise. METHODS: Under the auspices of the German Society for Psychiatry, Psychotherapy, Psychosomatics, and Neurology and the German Society for Addiction Research and Addiction Therapy e.V. (DG-Sucht), the 2019-2020 S3 guideline on alcohol was revised by eight working groups. Thirty-five professional societies participated in a structured consensus process to deliberate the recommendations. Potential conflicts of interest were examined in advance, documented, and taken into account during the voting on the recommendations. RESULTS: The guideline provides recommendations on screening and brief interventions for different groups of people, as well as on treatment of individuals in the acute and post-acute phases of withdrawal. Special emphasis was placed on the treatment of comorbid somatic and psychological disorders. In addition, recommendations for specific groups of people (e.g., children and adolescents, pregnant women) have been made and adapted to the German care landscape.

[Screening for Problematic Alcohol Consumption - A Survey on Guideline Implementation in Transdisciplinary Health Care of a Model Region]. / Screening auf problematischen Alkoholkonsum ­ Erhebung zur Umsetzung der S3-Leitlinienempfehlungen in der transdisziplinären Versorgung einer Modellregion.

AIM: Recording the frequency of screenings for problematic alcohol consumption by professionals involved in the health care of respective patients. The German S3-guideline "screening, diagnosis and treatment of alcohol-related disorders" recommends the use of questionnaire-based screenings for all patients in all settings. METHODS: Cross-sectional survey on screening frequency among general practitioners, gynecologists, psychiatrists, child- and adolescent therapists, psychotherapists, social workers and midwives. Logistic regression was used to explore how healthcare professionals' attributes were associated with the implementation of screenings. RESULTS: With response rates of about 20%, health care professionals reported using screening instruments for an average of 6.9% of all patients during the previous four weeks. Most of the time, custom-made questions were used instead of the recommended instruments (AUDIT, AUDIT-C). Higher screening rates were reported for patients with newly diagnosed hypertension (21.2%), alcohol-related disorders (43.3%) and mental disorders (39.3%). Knowledge of the guideline was associated with implementation of screenings (OR=4.67; 95% KI 1.94-11.25, p<0.001). CONCLUSIONS: Comprehensive screening for problematic alcohol use with questionnaire-based instruments in accordance with guidelines is far from being routinely implemented in the studied health care settings. Measures to increase the knowledge of the guidelines are necessary in order to increase the frequency of alcohol screening in health care.

FMRI-based prediction of naltrexone response in alcohol use disorder: a replication study.

Pharmacological treatment in alcohol use disorder suffers from modest effect sizes. Efforts have been undertaken to identify patient characteristics that help to select individuals that benefit from pharmacological treatment. Previous studies indicated that neural alcohol cue-reactivity (CR) might provide a marker that identifies patients, which benefit from naltrexone treatment.We investigated the reproducibility of the association between ventral striatum (VS) activation and naltrexone (NTX) treatment response by analyzing data from a recent longitudinal clinical trial in N = 44 abstinent treatment-seeking alcohol-dependent patients. A follow-up was conducted over 3 months. We computed the percentage of significant voxels in VS and tested main effects and interactions with NTX treatment on relapse risk using Cox Regression models.We found a significant interaction effect between pre-treatment cue reactivity in the VS and NTX treatment on time to first heavy relapse (Hazard Ratio = 7.406, 95% CI 1.17-46.56, p = 0.033), such that the patient group with high VS activation (defined by a mean split) showed a significant medication effect (Hazard Ratio = 0.140, 95% CI 0.02-0.75, p = 0.022) with a number needed to treat of 3.4 [95% CI 2.413.5], while there was no significant effect in the group with low VS activation (Hazard Ratio = 0.726, p = 0.454).Thus, using an independent sample we replicated the previously described positive association between VS activation and NTX efficacy. Although our results should be considered cautiously in light of the small sample size, our results support the potential of neural alcohol CR as a tool for precision medicine approaches in alcohol dependence.

International travel-related control measures to contain the COVID-19 pandemic: a rapid review.

BACKGROUND: In late 2019, the first cases of coronavirus disease 2019 (COVID-19) were reported in Wuhan, China, followed by a worldwide spread. Numerous countries have implemented control measures related to international travel, including border closures, travel restrictions, screening at borders, and quarantine of travellers. OBJECTIVES: To assess the effectiveness of international travel-related control measures during the COVID-19 pandemic on infectious disease transmission and screening-related outcomes. SEARCH METHODS: We searched MEDLINE, Embase and COVID-19-specific databases, including the Cochrane COVID-19 Study Register and the WHO Global Database on COVID-19 Research to 13 November 2020. SELECTION CRITERIA: We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across international borders during the COVID-19 pandemic. In the original review, we also considered evidence on severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). In this version we decided to focus on COVID-19 evidence only. Primary outcome categories were (i) cases avoided, (ii) cases detected, and (iii) a shift in epidemic development. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome. DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles and abstracts and subsequently full texts. For studies included in the analysis, one review author extracted data and appraised the study. At least one additional review author checked for correctness of data. To assess the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for observational studies concerned with screening, and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed the certainty of evidence with GRADE, and several review authors discussed these GRADE judgements. MAIN RESULTS: Overall, we included 62 unique studies in the analysis; 49 were modelling studies and 13 were observational studies. Studies covered a variety of settings and levels of community transmission. Most studies compared travel-related control measures against a counterfactual scenario in which the measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of stringency of the measures (including relaxation of restrictions), or a combination of measures. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to the selection of travellers and the reference test, and unclear reporting of certain methodological aspects. Below we outline the results for each intervention category by illustrating the findings from selected outcomes. Travel restrictions reducing or stopping cross-border travel (31 modelling studies) The studies assessed cases avoided and shift in epidemic development. We found very low-certainty evidence for a reduction in COVID-19 cases in the community (13 studies) and cases exported or imported (9 studies). Most studies reported positive effects, with effect sizes varying widely; only a few studies showed no effect. There was very low-certainty evidence that cross-border travel controls can slow the spread of COVID-19. Most studies predicted positive effects, however, results from individual studies varied from a delay of less than one day to a delay of 85 days; very few studies predicted no effect of the measure. Screening at borders (13 modelling studies; 13 observational studies) Screening measures covered symptom/exposure-based screening or test-based screening (commonly specifying polymerase chain reaction (PCR) testing), or both, before departure or upon or within a few days of arrival. Studies assessed cases avoided, shift in epidemic development and cases detected. Studies generally predicted or observed some benefit from screening at borders, however these varied widely. For symptom/exposure-based screening, one modelling study reported that global implementation of screening measures would reduce the number of cases exported per day from another country by 82% (95% confidence interval (CI) 72% to 95%) (moderate-certainty evidence). Four modelling studies predicted delays in epidemic development, although there was wide variation in the results between the studies (very low-certainty evidence). Four modelling studies predicted that the proportion of cases detected would range from 1% to 53% (very low-certainty evidence). Nine observational studies observed the detected proportion to range from 0% to 100% (very low-certainty evidence), although all but one study observed this proportion to be less than 54%. For test-based screening, one modelling study provided very low-certainty evidence for the number of cases avoided. It reported that testing travellers reduced imported or exported cases as well as secondary cases. Five observational studies observed that the proportion of cases detected varied from 58% to 90% (very low-certainty evidence). Quarantine (12 modelling studies) The studies assessed cases avoided, shift in epidemic development and cases detected. All studies suggested some benefit of quarantine, however the magnitude of the effect ranged from small to large across the different outcomes (very low- to low-certainty evidence). Three modelling studies predicted that the reduction in the number of cases in the community ranged from 450 to over 64,000 fewer cases (very low-certainty evidence). The variation in effect was possibly related to the duration of quarantine and compliance. Quarantine and screening at borders (7 modelling studies; 4 observational studies) The studies assessed shift in epidemic development and cases detected. Most studies predicted positive effects for the combined measures with varying magnitudes (very low- to low-certainty evidence). Four observational studies observed that the proportion of cases detected for quarantine and screening at borders ranged from 68% to 92% (low-certainty evidence). The variation may depend on how the measures were combined, including the length of the quarantine period and days when the test was conducted in quarantine. AUTHORS' CONCLUSIONS: With much of the evidence derived from modelling studies, notably for travel restrictions reducing or stopping cross-border travel and quarantine of travellers, there is a lack of 'real-world' evidence. The certainty of the evidence for most travel-related control measures and outcomes is very low and the true effects are likely to be substantially different from those reported here. Broadly, travel restrictions may limit the spread of disease across national borders. Symptom/exposure-based screening measures at borders on their own are likely not effective; PCR testing at borders as a screening measure likely detects more cases than symptom/exposure-based screening at borders, although if performed only upon arrival this will likely also miss a meaningful proportion of cases. Quarantine, based on a sufficiently long quarantine period and high compliance is likely to largely avoid further transmission from travellers. Combining quarantine with PCR testing at borders will likely improve effectiveness. Many studies suggest that effects depend on factors, such as levels of community transmission, travel volumes and duration, other public health measures in place, and the exact specification and timing of the measure. Future research should be better reported, employ a range of designs beyond modelling and assess potential benefits and harms of the travel-related control measures from a societal perspective.

COVID-19 mitigation measures and nitrogen dioxide - A quasi-experimental study of air quality in Munich, Germany.

BACKGROUND: In response to the COVID-19 pandemic, the Bavarian State government announced several COVID-19 mitigation measures beginning on March 16, 2020, which likely led to a reduction in traffic and a subsequent improvement in air quality. In this study, we evaluated the short-term effect of COVID-19 mitigation measures on NO2 concentrations in Munich, Germany. METHODS: We applied two quasi-experimental approaches, a controlled interrupted time-series (c-ITS) approach and a synthetic control (SC) approach. Each approach compared changes occurring in 2020 to changes occurring in 2014-2019, and accounted for weather-related and other potential confounders. We hypothesized that the largest reductions in NO2 concentrations would be observed at traffic sites, with smaller reductions at urban background sites, and even small reductions, if any, at background sites. All hypotheses, as well as the main and additional analyses were defined a priori. We also conducted post-hoc analyses to ensure that observed effects were not due to factors other than the intervention. RESULTS: Main analyses largely supported our hypotheses. Specifically, at the two traffic sites, using the c-ITS approach we observed reductions of 9.34 µg/m3 (95% confidence interval: -23.58; 4.90) and 10.02 µg/m3 (-19.25; -0.79). Using the SC approach we observed reductions of 15.65 µg/m3 (-27.58; -4.09) and 15.1 µg/m3 (-24.82; -9.83) at these same sites. We observed effects ranging from smaller in magnitude to no effect at urban background and background sites. Additional analyses showed that the effect was largest in the first two weeks following introduction of measures, and that a 3-day lagged intervention time also showed a larger effect. Post-hoc analyses suggested that at least some of the observed effects may have been attributable to changes in air quality occurring before the intervention, as well as unusually high concentrations in January 2020. CONCLUSION: We applied two quasi-experimental approaches in assessing the impact of the COVID-19 mitigation measures on NO2 concentrations in Munich. Taking the 2020 pre-intervention average concentrations as a reference, we observed reductions in NO2 concentrations of approximately 15-25% and 24-36% at traffic sites, suggesting that reducing traffic may be an effective measure to reduce NO2 concentrations in heavily trafficked areas by margins which could translate to public health benefits.

Calcium Carbonate Attenuates Withdrawal and Reduces Craving: A Randomized Controlled Trial in Alcohol-Dependent Patients.

INTRODUCTION: Preclinical studies have shown that calcium seems to be the active component of the anti-craving drug acamprosate (Ca2+ bis-acetyl-homotaurinate). Clinical effects in humans have also indicated an association between increased calcium plasma concentration due to acamprosate treatment and better outcome relating to time to relapse and cumulative abstinence. In contrast, low calcium concentration in alcohol-dependent patients was related with craving for alcohol. The main goal of the trial was to investigate whether an oral calcium administration is able to affect craving, withdrawal, and relapse risk in alcohol-dependent patients. METHODS: We conducted a single-blind, randomized, monocentric, controlled clinical two-arm trial in alcohol-dependent patients (Clinical Trials Registration: DRKS00011293). A total of 55 alcohol-dependent subjects received calcium carbonate (800 mg + 5 µg vitamin D) versus sodium bicarbonate (1,000 mg) daily during the 14 days of inpatient alcohol-withdrawal treatment. RESULTS: Based on an intention-to-treat protocol, withdrawal intensity (assessed with CIWA-Ar) in the calcium carbonate group attenuated faster than in the sodium bicarbonate subgroup. Alcohol craving (assessed with OCDS) in the calcium carbonate subgroup was also significantly reduced versus the sodium bicarbonate subgroup. CONCLUSION: Our data support earlier findings and show that treatment with calcium carbonate during alcohol withdrawal reduces symptoms of alcohol withdrawal as well as alcohol craving in a controlled clinical pilot study. Mode of actions will need to be determined to allow the further development of pharmacological interventions beyond Ca2+ bis-acetyl-homotaurinate.

Statistical learning approaches in the genetic epidemiology of complex diseases.

In this paper, we give an overview of methodological issues related to the use of statistical learning approaches when analyzing high-dimensional genetic data. The focus is set on regression models and machine learning algorithms taking genetic variables as input and returning a classification or a prediction for the target variable of interest; for example, the present or future disease status, or the future course of a disease. After briefly explaining the basic motivation and principle of these methods, we review different procedures that can be used to evaluate the accuracy of the obtained models and discuss common flaws that may lead to over-optimistic conclusions with respect to their prediction performance and usefulness.