A Mindfulness-Based Cognitive Therapy (MBCT) Intervention to Improve Resilience and Mitigate Symptoms of Burnout Syndrome in Critical Care Nurses: Results of a Randomized Trial

Objective: Critical care nurses work in a challenging intensive care (ICU) environment that results in work-related psychological distress. Our objective was to pilot an in-person or virtual mindfulness-based cognitive therapy (MBCT) program enhanced resilience and a similarly designed attention control group. Methods: We randomized ICU nurses with symptoms of burnout syndrome and decreased resilience to an MBCT program or a similarly formatted book club control. Our primary outcome was change in resilience as measured by the Connor-Davidson Resilience Scale (CD-RISC). Results: One-hundred one nurses completed study-related procedures. Overall, 70% had baseline symptoms of anxiety and 26% had symptoms of depression. For the in-person cohorts, there was no statistical difference between intervention and control groups regarding the total number of sessions attended (3.85 days ± 1.4 versus 3.75 days ± 0.15;p = 0.64). Using the Client/Patient Satisfaction Questionnaire-8 (CSQ-8), satisfaction scores were higher in the intervention group for weeks two through four of the program: p = 0.03, 0.0003, 0.007 respectively. There was no difference in the change in CD-RISC scores between the two groups (mean difference: treatment = 5.0, control = 7.0;p = 0.30). The online intervention cohort had greater improvements in the change of their median emotional exhaustion burnout scores when compared to the in-person intervention cohorts (-5 [-8 to -1.5] vs. 2 [-5 to 8], p = 0.049). Conclusions: We developed a feasible and acceptable in-person and online MBCT-ICU intervention that did not increase resilience scores in ICU nurses when compared to an attention control group. These results could help guide the proper design of larger trials to determine the efficacy of other resilience interventions.

Real-time sono-elastography in the diagnosis of diffuse liver diseases

AIM: To analyze whether computer-enhanced dynamic analysis of elastography movies is able to better characterize and differentiate between different degrees of liver fibrosis. METHODS: The study design was prospective. A total of 132 consecutive patients with chronic liver diseases and healthy volunteers were examined by transabdominal ultrasound elastography. All examinations were done by two doctors.RESULTS: Due to the limitations of the method, we obtained high-quality elastography information in only 73.48% of the patients. The κ-means clustering method was applied to assess the inter-observer diagnosis varia- bility, which showed good variability values in accordance with the experience of ultrasound examination of every observer. Cohen’sκ test indicated a moderate agreement between the study observers (κ = 0.4728). Furthermore, we compared the way the two observers clustered the patients, using the test for comparing two proportions (t value, two-sided test). There was no statistically significant difference between the two physicians, regardless of the patients’ real status. CONCLUSION: Transabdominal real-time elastography is certainly a very useful method in depicting liver hard- ness, although it is incompletely tested in large multicenter studies.

Assessing the performance of different outcomes for tumor growth studies with animal models

The consistency of reporting results for patient-derived xenograft(PDX) studies is an area of concern. The PDX method commonly starts by implanting a derivative of a human tumor into a mouse, then comparing the tumor growth under different treatment conditions. Currently, a wide array of statistical methods(e.g., t-test, regression, chi-squared test) are used to analyze these data, which ultimately depend on the outcome chosen(e.g., tumor volume, relative growth, categorical growth). In this simulation study, we provide empirical evidence for the outcome selection process by comparing the performance of both commonly used outcomes and novel variations of common outcomes used in PDX studies. Data were simulated to mimic tumor growth under multiple scenarios, then each outcome of interest was evaluated for 10?000 iterations. Comparisons between different outcomes were made with respect to average bias, variance, type-1 error, and power. A total of 18 continuous, categorical, and time-to-event outcomes were evaluated, with ultimately 2 outcomes outperforming the others: final tumor volume and change in tumor volume from baseline.Notably, the novel variations of the tumor growth inhibition index(TGII)— a commonly used outcome in PDX studies— was found to perform poorly in several scenarios with inflated type-1 error rates and a relatively large bias. Finally, all outcomes of interest were applied to a real-world dataset.

Hands-on Workshops as An Efective Means of Learning Advanced Technologies Including Genomics,Proteomics and Bioinformatics

Genomics and proteomics have emerged as key technologies in biomedical research, resulting in a surge of interest in training by investigators keen to incorporate these technologies into their research. At least two types of training can be envisioned in order to produce meaningful results, quality publications and successful grant applications： （1） immediate short-term training workshops and （2） long-term graduate education or visiting scientist programs. We aimed to fill the former need by providing a comprehensive hands-on training course in genomics, proteomics and informatics in a coherent, experimentally-based framework. This was accomplished through a National Heart, Lung, and Blood Institute （NHLBI）-sponsored 10-day Genomics and Proteomics Hands-on Workshop held at National Jewish Health （NJH） and the University of Colorado School of Medicine （UCD）. The course content included comprehensive lectures and laboratories in mass spectrometry and genomics technologies, extensive hands-on experience with instrumentation and software, video demonstrations, optional workshops, online sessions, invited keynote speakers, and local and national guest faculty. Here we describe the detailed curriculum and present the results of short- and long-term evaluations from course attendees. Our educational program consis- tently received positive reviews from participants and had a substantial impact on grant writing and review, manuscript submissions and publications.

Incidence and consequences of varicella in children treated for cancer in Guatemala

Background:Varicella-zoster virus infection is associated with significant morbidity and mortality in immune-compromised children,despite treatment with antiviral agents.Universal varicella vaccine programs have significantly decreased this risk in many highincome countries,but in most low-income and middleincome countries,the burden of varicella in children treated for malignancy is poorly defi ned.Methods:We retrospectively reviewed records of children at the National Unit of Pediatric Oncology(UNOP)in Guatemala diagnosed with varicella between January 2009 and March 2013 in order to calculate incidence of varicella and evaluate morbidity,mortality,treatment interruption,and cost.Results:Fifty-nine cases of varicella were identified.Incidence was 23.4 cases per 1000 person-years(p-y).66.1%of cases occurred in children with leukemia(median age 5.2 years;interquantile range 3.4-7 years)and 41.0%of these occurred during maintenance therapy.Source of exposure was identified for 14/59(23.7%)children.Most were hospitalized(71.2%)and given intravenous acyclovir(64.4%).Eight(13.6%)children required critical care,and two(3.4%)died from disseminated varicella with multiorgan failure.Chemotherapy was delayed or omitted due to varicella in 50%.No signifi cant differences in outcomes based on nutritional and immunologic status were detected.The minimum average cost of treatment per episode was 598.75 USD.Conclusions:Varicella is a significant problem in children treated for cancer in Guatemala,where effective post-exposure prophylaxis is limited.In the absence of universal varicella vaccination,strategies to improve recognition of exposure and the future use of novel inactivated vaccines currently under investigation in clinical trials could mitigate this burden.

Effect of a Patient Education Intervention on Asthma Control and Patient-Doctor Relationship

To the Editor：Asthma control is the focus of modern asthma management,while only 2％ of Chinese patients are controlled.[1] A good patient-doctor relationship is one of the first steps in the successful management of asthma;patients can know more information about their condition and the processes of their health through talking thoroughly with doctors.Due to large numbers of outpatients,most physicians in China spend no more than 5 min with a patient in clinics,limiting the opportunity to give the appropriate treatment and discuss further knowledge about asthma with the patients.

On the use of kernel machines for Mendelian randomization

Background： Properly adjusting for unmeasured confounders is critical for health studies in order to achieve valid testing and estimation of the exposure＇s causal effect on outcomes. The instrumental variable （IV） method has long been used in econometrics to estimate causal effects while accommodating the effect of unmeasured confounders. Mendefian randomization （MR）, which uses genetic variants as the instrumental variables, is an application of the instrumental variable method to biomedical research fields, and has become popular in recent years. One often-used estimator of causal effects for instrumental variables and Mendelian randomization is the two-stage least square estimator （TSLS）. The validity of TSLS relies on the accurate prediction of exposure based on IVs in its first stage. Results： In this note, we propose to model the link between exposure and genetic IVs using the least-squares kernel machine （LSKM）. Some simulation studies are used to evaluate the feasibility of LSKM in TSLS setting. Conclusions： Our results show that LSKM based on genotype score or genotype can be used effectively in TSLS. It may provide higher power when the association between exposure and genetic IVs is nonlinear.