The information and education environment refers to: 1) the presence of information infrastructures such as broadband Internet access and public libraries in a location; 2) a person’s proximity to information infrastructures and sources; 3) the distribution of information infrastructures, sources and in a specific location; and 4) exposure to specific messages (information content) within a specific location.
Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
Contained within is a subset of the larger dataset collected in La Paz, Bolivia in 2014. This data contains the analytic dataset (cross-sectional/descriptive) that includs the PACIC, Morisky, PHQ8, AUDIT, and a subset of socidemographic characteristics for NCD patients in La Paz.
The dataset represents the complete search strategies for all literature databases searched during the systematic review. The Endnote and Excel files of all citations considered for inclusion in the review are also included.
The dataset represents the complete search strategies for all literature databases searched during the systematic review. The Endnote library that contains all citations is also included.
The dataset includes the reproducible search strategies for all literature databases searched during the review, the key articles used to generate relevant search terms and test the effectiveness of the searches, the Endnote library that has all citations considered for inclusion, a flow chart describing the screening process, and the screening forms used for inclusion and exclusion.
Bennett K, Berlin N, MacEachern MP, Buchman S, Vercler C. (2018). The ethical and professional use of social media in surgery - A systematic review of the literature. Plastic and Reconstructive Surgery, 142(3), 388e-398e. PMID: 30148789. https://doi.org/10.1097/prs.0000000000004692
The dataset represents the complete, reproducible search strategies for all literature databases searched during the systematic review. The Endnote file and the Endnote import files contain all citations considered for inclusion in the review.
Smothers, Zachary MBS; Reynolds, Victoria PharmD; McEachern, Mark MLIS; Derouin, Anne L. DNP, RN, CPNP, FAANP; Carter, Brigit M. PhD, RN, CCRN; Muzyk, Andrew PharmD Substance Use Education in Schools of Nursing, Nurse Educator: May/June 2018 - Volume 43 - Issue 3 - p 136-139. https://doi.org/10.1097/NNE.0000000000000449 and https://www.ncbi.nlm.nih.gov/pubmed/28858952
This dataset includes census tract-level data concerning housing in Metropolitan Detroit. The data includes: 1) Total housing units and total mortgages in the tract; 2) Land use; 3) Real estate information (foreclosures, sales transactions, and home values); 4) Vacant housing; 5) Housing age and available facilities; 6) Housing condition; and 7) Spatial measures of subsidized housing in the tract.
Data coverage should say 2006 to 2015.
Health status data includes data about the health of persons within a census tract in Metropolitan Detroit, measured at the census tract level. This includes data about 1) mortality by condition; 2) exposures to toxic substances; and 3) disability.
Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
This systematic review and meta-analysis assesses decision aids in the context of patients considering post-mastectomy breast reconstruction. and NOTE: An updated Read Me file was added to this data set on May 24, 2018 replacing the original.
Berlin NL, Tandon VJ, Hawley ST, et al. Feasibility and Efficacy of Decision Aids to Improve Decision Making for Postmastectomy Breast Reconstruction: A Systematic Review and Meta-analysis. Med Decis Making. 2019;39(1):5–20. https://doi.org/10.1177/0272989X18803879
Data reflect the knowledge, attitudes, and beliefs of health care providers regarding neonatal near-misses in Neonatal Intensive Care Units (NICUs) in southern Ghana.
This data is part of a large program to translate detection and interpretation of HFOs into clinical use. A zip file is included which contains hfo detections, metadata, and Matlab scripts. The matlab scripts analyze this input data and produce figures as in the referenced paper (note: the blind source separation method is stochastic, and so the figures may not be exactly the same). A file "README.txt" provides more detail about each individual file within the zip file.
Gunn AH, Smothers ZPW, Schramm-Sapyta N, Freiermuth CE, MacEachern M, Muzyk AJ. (2018). The emergency department as an opportunity for naloxone distribution. Western Journal of Emergency Medicine, 19(6), 1036-42. doi: 10.5811/westjem.2018.8.38829 https://doi.org/10.5811/westjem.2018.8.38829
Investigating minimum human reaction times is often confounded by the motivation, training, and state of arousal of the subjects. We used the reaction times of athletes competing in the shorter sprint events in the Athletics competitions in recent Olympics (2004-2016) to determine minimum human reaction times because there's little question as to their motivation, training, or state of arousal.
The reaction times of sprinters however are only available on the IAAF web page for each individual heat, in each event, at each Olympic. Therefore we compiled all these data into two separate excel sheets which can be used for further analyses.
Mirshams Shahshahani P, Lipps DB, Galecki AT, Ashton-Miller JA (2018) On the apparent decrease in Olympic sprinter reaction times. PLoS ONE 13(6): e0198633. https://doi.org/10.1371/journal.pone.0198633
Data include variables used to run mixed effects models examining the association between the nose/throat microbiome and influenza virus infection. Certain individual participant data have been excluded due to identifiability concerns. Data also include the oligotype count table and taxonomic classifications. and Curation Notes: Readme updated Nov. 29, 2018 with context for oligotype and taxonomy files, and citation to associated article.
Lee KH, Gordon A, Shedden K, Kuan G, Ng S, Balmaseda A, Foxman B. The respiratory microbiome and susceptibility to influenza virus infection. PloS One. 2019;14:e0207898. https://doi.org/10.1371/journal.pone.0207898
Three sensitivity analyses were performed. First, a second matching step was performed in which two controls were selected for each case, where possible using a nearest neighbor and caliper metric. Controls needed to have propensity scores within 0.1 of the case to be selected. Thirty-eight of the 39 cases had at least one control using this method and for 36 cases two controls could be selected. The average difference between case and control propensity adjuvant RT was 0.008 (range 0.00003-0.095).
A second sensitivity analysis was performed to guard against immortal time bias. In order to mitigate the possibility of this effect, cases known not to have undergone adjuvant RT have been screened for suitable follow-up without a recurrence (local or regional recurrence, metastatic failure, and/or death) to ensure that if adjuvant RT had been prescribed as part of the multi-modality treatment regimen, that it would have been initiated. Three months was selected as the mandatory follow-up time. One to one matching was carried out and all 39 cases were matched to a control. A third sensitivity analysis was performed to account for stage migration seen in control patients that presented to the University of Michigan with more advanced disease. Patients that underwent adjuvant radiation were matched one to one with control group patients who did not receive adjuvant radiation, and who had the same stage at diagnosis as compared to stage at University of Michigan presentation.
Interest in quantitative imaging of Y-90 is growing because transarterial radioembolization (RE) with Y-90 loaded microspheres is a promising and minimally invasive treatment that is FDA approved for unresectable primary and metastatic liver tumors. These cancers are a leading cause of cancer mortality and morbidity. Radioembolization is a therapy that irradiates liver tumors with radioactive microspheres administered through
a microcatheter placed in the hepatic arterial vasculature. Radioembolization is based on the principle that healthy liver and tumor are mainly vascularized by the portal vein and the hepatic artery respectively. As a result, radioactive microspheres are preferentially located in the lesions after they are administered via the hepatic artery.
Van, B. J., Dewaraja, Y. K., Sangogo, M. L., & Mikell, J. K. (2021). Y-90 SIRT: Evaluation of TCP variation across dosimetric models. EJNMMI Physics, 8(1), 45. https://doi.org/10.1186/s40658-021-00391-6
The dataset includes all citations considered for inclusion in the systematic review. The citations are accessible in Endnote (enlx), as well as through the primary citation export files from each database. The literature search strategies are included for reproducibility and transparency purposes. See the published methods for more information.
DeLong MR, Tandon VJ, Farajzadeh M, Berlin NL, MacEachern MP, Rudkin GH, Da Lio AL, Cederna PS. (2019). Systematic review of the impact of acellular dermal matrix on aesthetics and patient satisfaction in tissue expander-to-implant breast reconstructions. Plastic and Reconstructive Surgery. and https://doi.org/10.1097/PRS.0000000000006212
This repository contains the source code for the CRIMSON GUI, as required in the PLOS Computational Biology publication:
CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation by the same authors., This is a snapshot of the software; build dependencies can be found at
https://doi.org/10.7302/ssj9-n788. Please visit
https://github.com/carthurs/CRIMSONGUI/releases/tag/PLOS_Comp_Bio & www.crimson.software for more general information and the most up to date version of the software., and Software can be compiled in Windows.
CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation C.J. Arthurs, R. Khlebnikov, A. Melville, M. Marčan, A. Gomez, D. Dillon-Murphy, F. Cuomo, M.S. Vieira, J. Schollenberger, S.R. Lynch, C. Tossas-Betancourt, K. Iyer, S. Hopper, E. Livingston, P. Youssefi, A. Noorani, S. Ben Ahmed, F.J.H. Nauta, T.M.J. van Bakel, Y. Ahmed, P.A.J. van Bakel, J. Mynard, P. Di Achille, H. Gharahi, K. D. Lau, V. Filonova, M. Aguirre, N. Nama, N. Xiao, S. Baek, K. Garikipati, O. Sahni, D. Nordsletten, C.A. Figueroa bioRxiv 2020.10.14.339960; doi: https://doi.org/10.1101/2020.10.14.339960 and Computational Vascular Biomechanics Lab @ the University of Michigan and other collaborators, The Qt Company, NSIS Team and contributors, PostgreSQL Global Development Group, Oracle Corporation, Kitware. CRIMSON open source project - Build Dependencies [Data set], (2021). University of Michigan - Deep Blue. https://doi.org/10.7302/ssj9-n788