Nevin Manimala

Diabet Med. 2021 Aug 18:e14671. doi: 10.1111/dme.14671. Online ahead of print.

ABSTRACT

AIM: To investigate whether there is a bidirectional longitudinal association of depression with HbA_1c .

METHODS: We conducted a systematic literature search in PubMed, PsycINFO, CINAHL and EMBASE for observational, longitudinal studies published from January 2000 to September 2020, assessing the association between depression and HbA_1c in adults. We assessed study quality with the Newcastle-Ottawa-Scale. Pooled effect estimates were reported as partial correlation coefficients (r_p ) or odds ratios (OR).

RESULTS: We retrieved 1,642 studies; 26 studies were included in the systematic review and eleven in the meta-analysis. Most studies (16/26) focused on type 2 diabetes. Study quality was rated as good (n=19), fair (n=2) and poor (n=5). Of the meta-analysed studies, six investigated the longitudinal association between self-reported depressive symptoms and HbA_1c and five the reverse longitudinal association, with a combined sample size of n=48,793 and a mean follow-up of 2 years. Higher levels of baseline depressive symptoms were associated with subsequent higher levels of HbA_1c (partial r=0.07;[95%CI0.03,0.12]; I² 38%). Higher baseline HbA_1c values were also associated with 18% increased risk of (probable) depression (OR=1.18;[95%CI1.12,1.25]; I² 0.0%).

CONCLUSIONS: Our findings support a bidirectional longitudinal association between depressive symptoms and HbA_1c . However, the observed effect sizes were small and future research in large-scale longitudinal studies is needed to confirm this association. Future studies should investigate the role of type of diabetes and depression, diabetes distress and diabetes self-management behaviours. Our results may have clinical implications, as depressive symptoms and HbA_1c levels could be targeted concurrently in the prevention and treatment of diabetes and depression.

PMID:34407250 | DOI:10.1111/dme.14671

Biometrics. 2021 Aug 18. doi: 10.1111/biom.13548. Online ahead of print.

ABSTRACT

Multivariate interval-censored data arise when each subject under study can potentially experience multiple events and the onset time of each event is not observed exactly but is known to lie in a certain time interval formed by adjacent examination times with changed statuses of the event. This type of incomplete and complex data structure poses a substantial challenge in practical data analysis. In addition, many potential risk factors exist in numerous studies. Thus, conducting variable selection for event-specific covariates simultaneously becomes useful in identifying important variables and assessing their effects on the events of interest. In this paper, we develop a variable selection technique for multivariate interval-censored data under a general class of semiparametric transformation frailty models. The minimum information criterion (MIC) method is embedded in the optimization step of the proposed expectation-maximization (EM) algorithm to obtain the parameter estimator. The proposed EM algorithm greatly reduces the computational burden in maximizing the observed likelihood function, and the MIC naturally avoids selecting the optimal tuning parameter as needed in many other popular penalties, making the proposed algorithm promising and reliable. The proposed method is evaluated through extensive simulation studies and illustrated by an analysis of patient data from the Aerobics Center Longitudinal Study. This article is protected by copyright. All rights reserved.

PMID:34407218 | DOI:10.1111/biom.13548

Biometrics. 2021 Aug 18. doi: 10.1111/biom.13547. Online ahead of print.

ABSTRACT

We introduce binacox, a prognostic method to deal with the problem of detecting multiple cut-points per feature in a multivariate setting where a large number of continuous features are available. The method is based on the Cox model and combines one-hot encoding with the binarsity penalty, which uses total-variation regularization together with an extra linear constraint, and enables feature selection. Original nonasymptotic oracle inequalities for prediction (in terms of Kullback-Leibler divergence) and estimation with a fast rate of convergence are established. The statistical performance of the method is examined in an extensive Monte Carlo simulation study, and then illustrated on three publicly available genetic cancer datasets. On these high-dimensional datasets, our proposed method outperforms state-of-the-art survival models regarding risk prediction in terms of the C-index, with a computing time orders of magnitude faster. In addition, it provides powerful interpretability from a clinical perspective by automatically pinpointing significant cut-points in relevant variables. This article is protected by copyright. All rights reserved.

PMID:34407216 | DOI:10.1111/biom.13547

Med Phys. 2021 Aug 18. doi: 10.1002/mp.15150. Online ahead of print.

ABSTRACT

Recently, deep learning (DL)-based methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones. We present here a systematic review of these methods by grouping them into three categories, according to their clinical applications: I) to replace CT in magnetic resonance (MR)-based treatment planning, II) facilitate cone-beam computed tomography (CBCT)-based image-guided adaptive radiotherapy, and III) derive attenuation maps for the correction of positron emission tomography (PET). Appropriate database searching was performed on journal articles published between January 2014 and December 2020. The DL methods’ key characteristics were extracted from each eligible study, and a comprehensive comparison among network architectures and metrics was reported. A detailed review of each category was given, highlighting essential contributions, identifying specific challenges, and summarising the achievements. Lastly, the statistics of all the cited works from various aspects were analysed, revealing the popularity and future trends and the potential of DL-based sCT generation. The current status of DL-based sCT generation was evaluated, assessing the clinical readiness of the presented methods.

PMID:34407209 | DOI:10.1002/mp.15150

Angle Orthod. 2021 Sep 1;91(5):619-625. doi: 10.2319/112420-956.1.

ABSTRACT

OBJECTIVE: To assess the efficiency of low-intensity pulsed ultrasound (LIPUS) and photobiomodulation (PBM) interventions in accelerating orthodontic tooth movement during clear aligner therapy (CAT).

MATERIALS AND METHODS: This retrospective study was carried out on the records of 84 subjects who were treated using CAT. Twenty-eight patients were treated using CAT with a daily use of LIPUS for 20 minutes, 28 patients were treated using CAT with a daily use of PBM for 10 minutes, and 28 patients were treated using CAT alone. The total duration of treatment was recorded for all patients. One-way analysis of variance and post hoc Tukey test were used to assess whether there was any significant difference in total treatment duration among the three groups (P < .05).

RESULTS: The mean treatment durations in days were 719 ± 220, 533 ± 242, and 528 ± 323 for the control, LIPUS, and PBM groups, respectively. The LIPUS group showed a 26% reduction, on average, in treatment duration when compared with the control group, whereas the PBM group showed an average 26.6% reduction in the treatment duration when compared with the control group. The results showed that there were statistically significant differences among the groups (P = .011). Treatment durations were significantly reduced in the LIPUS and PBM groups as compared with the control (P = .027 and P = .023, respectively), with no statistically significant differences between the LIPUS and PBM groups (P = .998).

CONCLUSIONS: Daily use of LIPUS or PBM as adjunctive interventions during CAT could reduce the duration of orthodontic treatment.

PMID:34407180 | DOI:10.2319/112420-956.1

Rev Esc Enferm USP. 2021 Aug 18;55:e20200408. doi: 10.1590/1980-220X-REEUSP-2020-0408. eCollection 2021.

ABSTRACT

OBJECTIVE: To assess the context of work and analyze their repercussions on the quality of life of rural workers in soybean agribusiness.

METHOD: Cross-sectional study, with an intentional sample of rural workers, conducted between the months of October and December 2019, with the application of the instruments World Health Organization Quality Life-bref and Scales of Assessment of Context and Human Cost of Work. The data were analyzed through bivariate and multivariate descriptive statistics.

RESULTS: The participants amounted to 299 rural workers. The scores of Work Conditions and Socioprofessional Relations were satisfactory and Organization of Work was critical. The scores of Physical and Cognitive costs were considered critical and of the Affective Cost was satisfactory. The Socioprofessional Relations have negatively impacted the overall quality of life and the Physical and Psychological, the Social Relations and the Environmental Domains, whereas Cognitive Cost positively impacted the Physical and the Environmental Domain and the Affective Cost positively impacted the Social Relations Domain.

CONCLUSION: Although the Work Context and Human Cost indicated adverse conditions, only the Socioprofessional Relations exerted negative influences on the quality of life of rural workers.

PMID:34407158 | DOI:10.1590/1980-220X-REEUSP-2020-0408

PLoS One. 2021 Aug 18;16(8):e0256157. doi: 10.1371/journal.pone.0256157. eCollection 2021.

ABSTRACT

Subcontractors depend heavily on their prime contractor and thus find it very risky to enter a new business on their own. This study proposes a framework for these subcontractors to develop blue ocean technologies related to their prime contractor. First, the primary technologies predicted to be promising are extracted from the business reports of the prime contractor. Sub-technologies are then selected through a patent-based search using keywords and International Patent Classification codes of the primary technologies. From them, blue ocean technologies are proposed by optimizing the weighted mean of the min-max normalized market value, degree of competition in the technology market, and subcontractors’ potential technological capabilities for each sub-technology. This study shows that subcontractors can enhance their technology competitiveness by finding a low-risk blue ocean technology. Our empirical research on the subcontractors of a semiconductor firm identified technological patent fields for them to pursue. From our framework, subcontractors can identify blue ocean technologies by considering their prime contractor’s future industrial areas and technologies of interest as well as their own technological capabilities. Furthermore, the prime contractors can gain the synergy effect of technology expansion through cooperation.

PMID:34407130 | DOI:10.1371/journal.pone.0256157

PLoS One. 2021 Aug 18;16(8):e0256327. doi: 10.1371/journal.pone.0256327. eCollection 2021.

ABSTRACT

Production landscapes play an important role in conserving biodiversity outside protected areas. Socio-ecological production landscapes (SEPL) are places where people use for primary production that conserve biodiversity. Such places can be found around the world, but a lack of geographic information on SEPL has resulted in their potential for conservation being neglected in policies and programs. We tested the global applicability of the Satoyama Index for identifying SEPL in multi-use cultural landscapes using global land use/cover data and two datasets of known SEPL. We found that the Satoyama Index, which was developed with a focus on biodiversity and tested in Japan, could be used globally to identify landscapes resulting from complex interactions between people and nature with statistical significance. This makes SEPL more relevant in the global conservation discourse. As the Satoyama Index mapping revealed that approximately 80% of SEPL occur outside recognized conservation priorities, such as protected areas and key biodiversity areas, identifying SEPL under the scheme of other area-based conservation measures (OECM) may bring more conservation attention to SEPL. Based on the issues identified in the SEPL mapping, we discuss ways that could improve the Satoyama Index mapping at global scale with the longitudinal temporal dimension and at more local scale with spatial and thematic resolution.

PMID:34407125 | DOI:10.1371/journal.pone.0256327

PLoS One. 2021 Aug 18;16(8):e0255237. doi: 10.1371/journal.pone.0255237. eCollection 2021.

ABSTRACT

BACKGROUND: Telomere length (TL) in peripheral blood mononuclear cells (PBMC) from fresh venous blood is increasingly used to estimate molecular impacts of accumulated social adversity on population health. Sometimes, TL extracted from saliva or dried blood spots (DBS) are substituted as less invasive and more scalable specimen collection methods; yet, are they interchangeable with fresh blood? Studies find TL is correlated across tissues, but have not addressed the critical question for social epidemiological applications: Do different specimen types show the same association between TL and social constructs?

METHODS: We integrate expertise in social epidemiology, molecular biology, and the statistical impact of measurement error on parameter estimates. Recruiting a diverse sample of 132 Metro-Detroit women, we measure TL for each woman from fresh blood PBMC, DBS, and saliva. Using regression methods, we estimate associations between social characteristics and TL, comparing estimates across specimen types for each woman.

RESULTS: Associations between TL and social characteristics vary by specimen type collected from the same woman, sometimes qualitatively altering estimates of the magnitude or direction of a theorized relationship. Being Black is associated with shorter TL in PBMC, but longer TL in saliva or DBS. Education is positively associated with TL in fresh blood, but negatively associated with TL using DBS.

CONCLUSION: Findings raise concerns about the use of TL measures derived from different tissues in social epidemiological research. Investigators need to consider the possibility that associations between social variables and TL may be systematically related to specimen type, rather than be valid indicators of socially-patterned biopsychosocial processes.

PMID:34407110 | DOI:10.1371/journal.pone.0255237

PLoS One. 2021 Aug 18;16(8):e0255445. doi: 10.1371/journal.pone.0255445. eCollection 2021.

ABSTRACT

Pharmaceuticals and their packaging have a significant negative impact on the environment providing a very strong argument for action on the part of pharmacists and pharmacy technicians to engage with pro-environmental behaviours (PEBs) in their workplaces. The aims of this research were therefore to investigate in hospital pharmacists and pharmacy technicians, 1) factors affecting engagement with workplace PEBs, and 2) determine if legislated carbon reduction targets in the UK influenced workplace PEBs in the UK compared with Australia which does not have legislated carbon reduction targets. The environmentally responsible disposal of pharmaceutical waste was the PEB of interest in this study. A mixed methods research design was utilised and a conceptual model (key variables: environmental attitude, concern, and knowledge, and organisational factors) was developed to identify factors influencing workplace PEBs. Participants were from five hospitals in Queensland, Australia and five NHS hospitals in England, UK. There was no statistically significant difference in environmental attitude or concern between the two groups-most had a mid-environmental attitude score and low levels of environmental concern. Participants lacked knowledge of the issue and the link between the environment and public health. Both Australian and UK participants reported recycling packaging waste was not a priority in the hospital pharmacy workplace (even in hospitals with recycling capability) as hospitals focused on compliance with clinical (contaminated) and confidential waste streams. Environmental attitude, knowledge, and concern therefore appeared to be weak influences on intention to perform workplace PEBs with workplace social norms (compliance due to audits) appearing to be a significant mediator of action. The key difference between the cohorts was that UK pharmacists felt waste was not in the scope of their role, and therefore not their responsibility. This study identified that legislated carbon reduction targets did not influence hospital pharmacy workplace PEBs-neither cohort reported engaging significantly in workplace PEBs. UK Government and NHS sustainability policy did not appear to have disseminated to pharmacy department level of UK public hospitals to any great extent.

PMID:34407108 | DOI:10.1371/journal.pone.0255445