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BackgroundThe delivery of standardized self-report assessments is essential for measurement-based care in mental health. Paper-based methods of measurement-based care data collection may result in transcription errors, missing data, and other data quality issues when entered into patient electronic health records (EHRs). ObjectiveThis study aims to help address these issues by using a dedicated instance of REDCap (Research Electronic Data Capture; Vanderbilt University)—a free, widely used electronic data capture platform—that was established to enable the deployment of digitized self-assessments in clinical care pathways to inform clinical decision making. MethodsREDCap was integrated with the primary clinical information system to facilitate the real-time transfer of discrete data and PDF reports from REDCap into the EHR. Both technical and administrative components were required for complete implementation. A technology acceptance survey was also administered to capture physicians’ and clinicians’ attitudes toward the new system. ResultsThe integration of REDCap with the EHR transitioned clinical workflows from paper-based methods of data collection to electronic data collection. This resulted in significant time savings, improved data quality, and valuable real-time information delivery. The digitization of self-report assessments at each appointment contributed to the clinic-wide implementation of the major depressive disorder integrated care pathway. This digital transformation facilitated a 4-fold increase in the physician adoption of this integrated care pathway workflow and a 3-fold increase in patient enrollment, resulting in an overall significant increase in major depressive disorder integrated care pathway capacity. Physicians’ and clinicians’ attitudes were overall positive, with almost all respondents agreeing that the system was useful to their work. ConclusionsREDCap provided an intuitive patient interface for collecting self-report measures and accessing results in real time to inform clinical decisions and an extensible backend for system integration. The approach scaled effectively and expanded to high-impact clinics throughout the hospital, allowing for the broad deployment of complex workflows and standardized assessments, which led to the accumulation of harmonized data across clinics and care pathways. REDCap is a flexible tool that can be effectively leveraged to facilitate the automatic transfer of self-report data to the EHR; however, thoughtful governance is required to complement the technical implementation to ensure that data standardization, data quality, patient safety, and privacy are maintained.

We report the draft genome sequence of Mycobacterium elephantis strain Lipa from a sputum sample of a patient with pulmonary disease. This is the first draft genome sequence of M. elephantis, a rapidly growing mycobacterium.

We report the draft genome sequence of Mycobacterium arupense strain GUC1 from a sputum sample of a patient with bronchiectasis. This is the first draft genome sequence of Mycobacterium arupense, a rapidly growing nonchromogenic mycobacteria.

We report the draft genome sequence of Mycobacterium obuense strain UC1 from a patient sputum sample. This is the first draft genome sequence of Mycobacterium obuense, a rapidly growing scotochromogenic mycobacterium.

Studies of clinical populations that combine MRI data generated at multiple sites are increasingly common. The Canadian Biomarker Integration Network in Depression (CAN-BIND; www.canbind.ca) is a national depression research program that includes multimodal neuroimaging collected at several sites across Canada. The purpose of the current paper is to provide detailed information on the imaging protocols used in a number of CAN-BIND studies. The CAN-BIND program implemented a series of platform-specific MRI protocols, including a suite of prescribed structural and functional MRI sequences supported by real-time monitoring for adherence and quality control. The imaging data are retained in an established informatics and databasing platform. Approximately 1300 participants are being recruited, including almost 1000 with depression. These include participants treated with antidepressant medications, transcranial magnetic stimulation, cognitive behavioural therapy and cognitive remediation therapy. Our ability to analyze the large number of imaging variables available may be limited by the sample size of the substudies. The CAN-BIND program includes a multimodal imaging database supported by extensive clinical, demographic, neuropsychological and biological data from people with major depression. It is a resource for Canadian investigators who are interested in understanding whether aspects of neuroimaging--alone or in combination with other variables--can predict the outcomes of various treatment modalities., Introduction Treatment of major depressive disorder (MDD) is evidence-based, but treatment selection is not personalized to the features of an individual's illness. (1) The discovery of biomarkers --or predictors--of treatment [...]

One of the biggest challenges in treating depression is the ability to select the most appropriate and effective treatment for a particular individual from among the many available options. This [...]

The body centered group additivity methd (BCGA) method for the estimation of the thermochemical properties of polycyclic aromatic molecules is expanded to aromatic molecules containing furan ring(s) and ortho-arynes. Two new atom-centered groups are defined for the description of furan ring(s) and ortho-arynes, leading to the addition of 17 new bond-centered groups to the BCGA method.

Molecular components of the glomerular filtration mechanism play critical roles in renal diseases. Many of these components are produced during the final stages of differentiation of glomerular visceral epithelial cells, also known as podocytes. While basic domain leucine zipper (bZip) transcription factors of the Maf subfamily have been implicated in cellular differentiation processes, Kreisler (Krml1/MafB), the gene affected in the mouse kreisler (kr) mutation, is known for its role in hindbrain patterning. Here we show that mice homozygous for the k[r.sup.enu] mutation develop renal disease and that Kreisler is essential for cellular differentiation of podocytes. Consistent with abnormal podocyte differentiation, k[r.sup.enu] homozygotes show proteinuria, and fusion and effacement of podocyte foot processes, which are also observed in the nephrotic syndrome. Kreisler acts during the final stages of glomerular development--the transition between the capillary loop and mature stages--and downstream of the Pod1 basic domain helix-loop-helix transcription factor. The levels of Podocin, the gene mutated in autosomal recessive steroid-resistant nephrotic syndrome (NPHS2), and Nephrin, the gene mutated in congenital nephrotic syndrome of the Finnish type (NPHS1), are slightly reduced in k[r.sup.enu]/k[r.sup.enu] podocytes However, these observations alone are unlikely to account for the aberrant podocyte foot process formation. Thus, Kreisler must regulate other unknown genes required for podocyte function and with possible roles in kidney disease. Key Words: Kreisler (Krml1/MafB); Pod1 (epicardin/capsulin); podocyte; kidney disease; cellular differentiation; proteinuria.

Taiwan's prolonged process of health care reform may provide lessons for the US. Originally a market-based system similar to that in the US, Taiwan's health care industry has been regulated more and more by the government since the early 1980s. In 1995, a plan for universal health insurance is to be implemented. Previously, only 54% of Taiwanese were insured under three government programs. Combining these plans into one should lower costs and streamline administration. The universal coverage plan includes substantial co-payments by patients. This is seen as one way to limit utilization and control costs. In contrast to the US, however, Taiwan does not have a large private health insurance industry to contend with. Slow but careful progress in health care reform may make the political and social transition to universal coverage easier to achieve than a major system overhaul.

Background: Birth-weight is an important determinant of perinatal outcome with low birth-weight being a particular risk factor for adverse consequences. Aim: To investigate the impact of neonatal sex, mode of birth and gestational age at birth according to birth-weight centile on serious adverse neonatal outcomes in singleton term pregnancies. Materials and methods: This was a retrospective cohort study of singleton term births at the Mater Mother's Hospital, Brisbane, Australia. Serious adverse neonatal outcome was defined as a composite of severe acidosis at birth (pH ≤7.0 and/or lactate ≥6 mmol/L and/or base excess ≤−12 mmol/L), Apgar <3 at 5 min, neonatal intensive-care unit admission and antepartum or neonatal death. The main exposure variable was birth-weight centile. Results: Of the 69,210 babies in our study, the overall proportion of serious adverse neonatal outcomes was 9.1% (6327/69,210). Overall, neonates in the <3rd birth-weight centile category had the highest adjusted odds ratio (OR) for serious adverse neonatal outcomes [OR 3.53, 95% confidence interval (CI) 3.06–4.07], whilst those in the ≥97th centile group also had elevated odds (OR 1.51, 95% CI 1.30–1.75). Regardless of birth modality, smaller babies in the <3rd centile group had the highest adjusted OR and predicted probability for serious adverse neonatal outcomes. When stratified by sex, male babies consistently demonstrated a higher predicted probability of serious adverse neonatal outcomes across all birth-weight centiles. The adjusted odds, when stratified by gestational age at birth, were the highest from 37+0 to 38+6 weeks in the <3rd centile group (OR 5.97, 95% CI 4.60–7.75). Conclusions: Low and high birth-weights are risk factors for serious adverse neonatal outcomes. The adjusted OR appears to be greatest for babies in the <3rd birth-weight centile group, although an elevated risk was also found in babies within the ≥97th centile category. [ABSTRACT FROM AUTHOR]

Objective: To report the symptomatic and functional outcomes in patients with major depressive disorder (MDD) during a 2-phase treatment trial and to estimate the value of early improvement after 2 weeks in predicting clinical response to escitalopram and subsequently to adjunctive treatment with aripiprazole., Methods: Participants with MDD (N = 211) identified with the Montgomery-Asberg Depression Rating Scale (MADRS) and confirmed with the Mini-International Neuropsychiatric Interview were recruited from 6 outpatient centers across Canada (August 2013 through December 2016) and treated with open-label escitalopram (10-20 mg) for 8 weeks (Phase 1). Clinical and functional outcomes were evaluated using the MADRS, Quick Inventory of Depressive Symptomatology-Self-Rated (QIDS-SR), Sheehan Disability Scale (SDS), and Lam Employment Absence and Productivity Scale (LEAPS). Participants were evaluated at 8 and 16 weeks for clinical and functional response and remission. Phase 1 responders continued escitalopram while nonresponders received adjunctive aripiprazole (2-10 mg) for a further 8 weeks (Phase 2)., Results: After Phase 1, MADRS response (≥ 50% decrease from baseline) and remission (score ≤ 10) were, respectively, 47% and 31%, and SDS response (score ≤ 12) and remission (score ≤ 6) were, respectively, 53% and 24%. Response to escitalopram was maintained in 91% of participants at week 16, while 61% of the adjunctive aripiprazole group achieved MADRS response during Phase 2. Response and remission rates with the QIDS-SR were lower than with the MADRS. The LEAPS demonstrated significant occupational improvement (P < .05). Early symptomatic improvement predicted outcomes with modest accuracy., Conclusions: This study demonstrates comparable symptomatic and functional outcomes to those of other large practical-design studies. There was a high response rate with the adjunctive use of aripiprazole in escitalopram nonresponders. Given the limited value of early clinical improvement to predict outcome, integration of clinical and biological markers deserves further exploration., Trial Registration: ClinicalTrials.gov identifier: NCT01655706., (© Copyright 2019 Physicians Postgraduate Press, Inc.)

A self-consistent estimation method for the thermochemical properties of polycyclic aromatic hydrocarbons (PAH) is presented. This method is based on enthalpies of formation (DeltaHf(degrees), entropies (S(degrees)298, and heat capacities (C(degrees)p obtained from B3LYP/6-31G(d) calculations of the total energies and frequencies for 139 PAHs, including C(60) and C(70) fullerenes. The enthalpies of formation were calculated using an optimized set of homodesmic reactions given the available experimental DeltaHf(degrees) of PAHs. The theoretical entropies were compared with the existing experimental entropies, and some inconsistencies in the experimental data were identified. The estimation method presented here is a systematic extension of the widely employed atom-centered group additivity method originally proposed by Benson. This new method is based on bond-centered groups that define bonds linking two atom-centered groups and specify the size of the rings to which they belong. In addition, a term to describe the resonance energy is included. The thermochemical properties of PAHs up to C(70) fullerene are estimated with a mean average deviation of 2.8 kcal mol(-1) in DeltaHf(degrees), 0.7 cal K(-1) mol(-1) in S(degrees)298, and about 0.5 cal K(-1) mol(-1) in the C(degrees)p. This bond-centered group additivity method for the thermochemical properties of PAHs significantly expands both the range of systems that can be estimated and the accuracy of the estimations. The results of this work also allow us to assess the quality of available experimental data. For example, there are strong indications that the literature DeltaHf(degrees)of benzo[k]fluoranthene is about 10 kcal mol(-1) too low.