Synthesising environmental, epidemiological, and genetic data to assist decision making for onchocerciasis elimination
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PROVIDER: PRJEB57094 | ENA |
REPOSITORIES: ENA
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Project description:Background:The number of cases from the coronavirus disease 2019 (COVID-19) global pandemic has overwhelmed existing medical facilities and forced clinicians, patients, and families to make pivotal decisions with limited time and information. Main body:While machine learning (ML) methods have been previously used to augment clinical decisions, there is now a demand for "Emergency ML." Throughout the patient care pathway, there are opportunities for ML-supported decisions based on collected vitals, laboratory results, medication orders, and comorbidities. With rapidly growing datasets, there also remain important considerations when developing and validating ML models. Conclusion:This perspective highlights the utility of evidence-based prediction tools in a number of clinical settings, and how similar models can be deployed during the COVID-19 pandemic to guide hospital frontlines and healthcare administrators to make informed decisions about patient care and managing hospital volume.
| S-EPMC7347420 | biostudies-literature
Project description:Implanting centers often require the identification of a dedicated caregiver before destination therapy left ventricular assist device (DT LVAD) implantation; however, the caregiver experience surrounding this difficult decision is relatively unexplored.From October 2012 through July 2013, we conducted semistructured, in-depth interviews with caregivers of patients considering DT LVAD. Data were analyzed using a mixed inductive and deductive approach. We interviewed 17 caregivers: 10 caregivers of patients living with DT LVAD, 6 caregivers of patients who had died with DT LVAD, and 1 caregiver of a patient who had declined DT LVAD. The themes identified, which could also be considered dialectical tensions, are broadly interpreted under 3 domains mapping to decision context, process, and outcome: (1) the stark decision context, with tension between hope and reality; (2) the challenging decision process, with tension between wanting loved ones to live and wanting to respect loved ones' wishes; and (3) the downstream decision outcome, with tension between gratitude and burden.Decision-making surrounding DT LVAD should incorporate decision support for patients and caregivers. This should include a focus on caregiver burden and the predictable tensions that caregivers experience.
| S-EPMC4365422 | biostudies-literature
Project description:BACKGROUND:Family caregivers (FCGs) often participate in the decision for their loved one to receive a left ventricular assist device (LVAD). Little is known about the contribution of FCGs to this complex decision. OBJECTIVES:To investigate family caregiver-reported outcomes related to decision-making for LVAD implantation and their experiences post-implantation. METHODS:Descriptive thematic analysis was used to analyze longitudinal data. Thematic saturation was achieved. RESULTS:Three key themes emerged from the data. The main theme in the pre-implantation period was: Not a decision. The two themes in the post-implantation period were: More satisfaction than regret and Unanticipated situational change. CONCLUSIONS:Family caregiver-reported outcomes inform clinical practice and future research. FCGs of LVAD recipients did not see viable alternatives to LVAD implantation, were generally satisfied with post-implantation outcomes, and experienced unexpected life changes in the post-implantation period despite feeling prepared preoperatively. Education of both LVAD recipients and their FCGs must be optimized.
| S-EPMC6589365 | biostudies-literature
Project description:Deep learning neural networks, constructed for the prediction of chemical binding at 79 pharmacologically important human biological targets, show extremely high performance on test data (accuracy 92.2 ± 4.2%, MCC 0.814 ± 0.093 and ROC-AUC 0.96 ± 0.04). A new molecular similarity measure, Neural Network Activation Similarity, has been developed, based on signal propagation through the network. This is complementary to standard Tanimoto similarity, and the combined use increases confidence in the computer's prediction of activity for new chemicals by providing a greater understanding of the underlying justification. The in silico prediction of these human molecular initiating events is central to the future of chemical safety risk assessment and improves the efficiency of safety decision making.
| S-EPMC8159362 | biostudies-literature
Project description:OBJECTIVE: To illustrate the use of decision-analytic modeling to assist decision making in organizational innovations. STUDY SETTING/DATA SOURCES: Regarding an organizational innovation (shared care in hearing aid provision) available evidence from different sources was synthesized. STUDY DESIGN: A probabilistic Markov model was constructed. DATA COLLECTION/EXTRACTION: We modeled the long-term cost-effectiveness of different organizational formats of shared care as opposed to the current organization. We assessed the expected value of perfect information (EVPI) for several groups of parameters in the model. PRINCIPAL FINDINGS: The current organization had the highest probability of being cost-effective. Additional research is worthwhile, especially on access to care and safety (sensitivity to detect pathology). CONCLUSIONS: Decision-analytic modeling in an early stage of organizational innovation is a valuable tool to facilitate evidence-based decision making.
| S-EPMC2653881 | biostudies-other
Project description:The Ashanti Dwarf Pig (ADP) of Ghana is an endangered pig breed with hardy and disease resistant traits. Characterisation of animal genetic resources provides relevant data for their conservation and sustainable use for food security and economic development. We investigated the origin and phylogenetic status of the local ADP of Ghana and their crosses with modern commercial breeds based on mtDNA, MC1R and Y-chromosome sequence polymorphisms, and genome-wide SNP genotyping. The study involved 164 local pigs sampled from the three agro-ecological zones of Ghana. Analyses of the mitochondrial D-loop region and Y-chromosome sequences revealed that the ADP of Ghana has both European and Asian genetic signatures. The ADP also displays considerable variation in the MC1R gene. Black coat colour is the most predominant within the breed, with the dominant black alleles of both Asian and European origin contributing to the majority of alleles in the pool. European alleles for spotting are present at a low frequency in the sample set, and may account for the occurrence of spotted piglets in some APD litters. Other colour variants may be due to epistatic interactions with additional coat colour loci, or mutations. The wide variations in coat colour patterns suggest that morphology alone cannot be used to adequately characterise Ghanaian local pigs. PCA analysis of SNP genotyping data revealed a strong location effect on clustering of local Ghanaian pigs. Based on this work, we recommend that further studies be carried out on more local pigs to find out the effect of admixture on important adaptive and economic traits of the ADP and other local Sus breeds in Africa to help develop a sustainable conservation programmes to prevent the decline of this genetic resource.
2017-03-08 | GSE84604 | GEO
Project description:The decision regarding adjuvant therapy for patients with stage II colon cancer remains a challenge. In contrast to stage III colon cancer, for which compelling clinical data support the use of adjuvant chemotherapy, the clinical benefit of systemic therapy in unselected patients with stage II disease is modest at best. Risk stratification based on clinicopathologic features and DNA mismatch repair status is commonly used in adjuvant therapy decisions, but these factors do not have a desired level of precision in identifying patients at high risk. Recently, gene expression platforms have been developed to further define risk and to assist in therapeutic decision making for patients with stage II disease. This review describes those platforms that are furthest along in clinical development, in an effort to place their potential clinical application in context.
| S-EPMC4077445 | biostudies-literature
Project description:We aimed to investigate the effect of lymph node parameters on postoperative hypopharyngeal squamous cell carcinoma (HSCC) and to establish a nomogram to predict its prognosis and assist in adjuvant chemotherapy decisions. A retrospective analysis of postoperative HSCC in the Surveillance, Epidemiology, and End Results database (2004-2019) was performed. Cutoff points for continuous variables were determined by X-tile software. Univariate and multivariate analyses were performed to identify prognostic factors on overall survival (OS), and these variables were used to construct a nomogram. The nomogram's accuracy was internally validated using concordance index, area under the curve, calibration plot, and decision curve analyses. Furthermore, the value of chemotherapy in each risk subgroup was assessed separately based on individualized scores from the nomogram. In total, 404 patients were eligible for analysis, and the median OS was 39 months. Age, origin, primary site, T stage, number of lymph nodes examined, lymph node ratio, and radiotherapy were identified as prognostic factors for OS and incorporated into the nomogram. In both the training and validation cohorts, favorable performance was exhibited compared with the other stage systems, and patients could be classified into low-, intermediate-, and high-risk subgroups. Chemotherapy significantly improved the OS in the high-risk subgroup, whereas chemotherapy did not confer a survival benefit in the low- or intermediate-risk groups. The lymph node parameter-based nomogram model can better stratify the prognosis of HSCC patients and screen out patients who would benefit from chemotherapy, suggesting that the model could be used as a reference for clinical decision making and to avoid overtreatment.
| S-EPMC9573651 | biostudies-literature
Project description:Little progress has been made to advance U.S. federal policy responses to growing scientific findings about cumulative environmental health impacts and risks, which also show that many low income and racial and ethnic minority populations bear a disproportionate share of multiple environmental burdens. Recent scholarship points to a "standard narrative" by which policy makers rationalize their slow efforts on environmental justice because of perceived lack of data and analytical tools. Using a social constructivist approach, ethnographic research methods, and content analysis, we examined the social context of policy challenges related to cumulative risks and impacts in the state of Maryland between 2014 and 2016. We identified three frames about cumulative impacts as a health issue through which conflicts over such policy reforms materialize and are sustained: (a) perceptions of evidence, (b) interpretations of social justice, and (c) expectations of authoritative bodies. Our findings illustrate that policy impasse over cumulative impacts is highly dependent on how policy-relevant actors come to frame issues around legislating cumulative impacts, rather than the "standard narrative" of external constraints. Frame analysis may provide us with more robust understandings of policy processes to address cumulative risks and impacts and the social forces that create health policy change.
| S-EPMC8070174 | biostudies-literature