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6,512 results for “clinical trial”
HOSENG trial – HOme-based oral SElf-testiNG for absent and refusing individuals during a door-to-door HIV testing campaign: a cluster randomised clinical trial in rural Lesotho
<p>These are pseudo-anonymised data from the HOSENG randomized trial: " HOSENG trial – HOme-based oral SElf-testiNG for absent and refusing individuals during a door-to-door HIV testing campaign: a cluster randomised clinical trial in rural Lesotho". The data dictionary explains the data available in the dataset. Between July 2018 and December 2018, 10516 eligible individuals from 106 consenting villages were enrolled from two districts of Lesotho, and followed up for a maximum of 120 days. Main manuscript reference, DOI: <a href="https://doi.org/10.1016/s2352-3018(20)30233-2">10.1016/S2352-3018(20)30233-2. </a>The protocol was published, DOI:10.1186/s13063-019-3469-2.</p>
Dataset for the IntoValue 1 + 2 studies on results dissemination from clinical trials conducted at German university medical centers completed between 2009 and 2017
<p>The IntoValue dataset contains clinical trials conducted at one of 35 German UMCs and registered on ClinicalTrials.gov or the German Clinical Trials Registry (DRKS). All trials were reported as complete between 2009 and 2017 on the trial registry at the time of data collection. The dataset also includes a results publication found via manual searches; if multiple results publications were found, the earliest was included.</p> <p>Trials were associated with a German UMC by searching for trials with a UMC listed as responsible party or lead sponsor, or with a principle investigator (PI) from a UMC ('lead_city'). Version 1 additionally includes trials with a UMC only as a facility (`facility_city`). A lookup table of regular expressions used to identify German UMCs is available at <a href="https://github.com/quest-bih/IntoValue2/blob/master/data/1_sample_generation/city_search_terms.csv">https://github.com/quest-bih/IntoValue2/blob/master/data/1_sample_generation/city_search_terms.csv</a>.</p> <p>Trials include all interventional studies and are not limited to investigational medical product trials, as regulated by the EU's Clinical Trials Directive or Germany's Arzneimittelgesetz (AMG) or Novelle des Medizinproduktegesetzes (MPG).</p> <p>DRKS data were searched (pre-filtered for completion years and study status as well as Germany as 'Country of recruitment') and downloaded as CSVs from the DRKS website (<a href="https://www.drks.de/">https://www.drks.de/</a>). ClinicalTrials.gov data were downloaded downloaded as pipe files from Clinical Trials Transformation Initiative (CTTI) Aggregate Content of ClinicalTrials.gov (AACT) (<a href="https://aact.ctti-clinicaltrials.org/pipe_files">https://aact.ctti-clinicaltrials.org/pipe_files</a>). DRKS and ClinicalTrials.gov use different terminology for various trial aspects, such as phase and masking; these different levels are captured in the data dictionary as `levels_drks` and `levels_ctgov`. For later analyses requiring parity across registries, levels for some variables were collapsed and a lookup table is provided in `iv_data_lookup_registries.csv`.</p> <p>These data were generated and used for two publications (Wieschowski et al., 2019; Riedel et al. 2021) and therefore comprises two versions (indicated as `iv_version`).</p> <p>For version 1, registry data was collected on April 17, 2017 from ClinicalTrials.gov and on July 27, 2017 for DRKS and was limited to trials with a completion date on DRKS and primary completion date on ClinicalTrials.gov between 2009 and 2013. Version 1 manual searches for results publications were conducted from 2017-07-01 to 2017-12-01.<br> For version 2, registry data was collected on June 3, 2020 and was limited to trials with a completion date on DRKS and ClinicalTrials.gov between 2014 and 2017. Version 2 manual searches for results publications were conducted from 2020-07-01 to 2020-09-01.</p> <p>Raw registry data for versions 1 and 2 is available in `raw-registries.zip`.</p> <p>Publication identifiers (DOI, PMID, URL) were manually entered during the publication search and then further enhanced using the API of Internet Archive's open-source Fatcat catalog of research publications, to add PMIDs based on DOIs, and vice versa.</p> <p>Manual search steps differed slightly in the two versions and are indicated and described in `identification_step`.<br> Version 1 includes trials with a German UMC as either a `lead_city` or a `facility_city`, whereas version 2 is limited to trials a German UMC as a `lead_city`.</p> <p>Each row indicates a single trial registration. Due to changes in completion dates, some trials are duplicated between versions as indicated in `is_dupe`. Cross-registered trials were manually deduplicated, and some cross-registered duplicates remain (e.g., DRKS00004156 and NCT00215683) and are not indicated in the dataset.</p> <p>All dates are provided as `yyyy-mm-dd`.</p> <p>Additional documentation on each variable (type, description, levels) is provided in `iv_data_dictionary.csv`.</p> <p>Additional information on the project and methods for generating the dataset is available in associated publications and at the project's OSF page (<a href="https://osf.io/98j7u/">https://osf.io/98j7u/</a>). Code for the project is available at <a href="https://github.com/quest-bih/IntoValue2">https://github.com/quest-bih/IntoValue2</a>.</p> <p><strong>References:</strong></p> <p>Wieschowski, S., Riedel, N., Wollmann, K., Kahrass, H., Müller-Ohlraun, S., Schürmann, C., Kelley, S., Kszuk, U., Siegerink, B., Dirnagl, U., Meerpohl, J., & Strech, D. (2019). Result dissemination from clinical trials conducted at German university medical centers was delayed and incomplete. Journal of Clinical Epidemiology, 115, 37–45. <a href="https://doi.org/10.1016/j.jclinepi.2019.06.002">https://doi.org/10.1016/j.jclinepi.2019.06.002</a></p> <p>Riedel, N., Wieschowski, S., Bruckner, T., Holst, M. R., Kahrass, H., Nury, E., Meerpohl, J. J., Salholz-Hillel, M., & Strech, D. (2021). Results dissemination from completed clinical trials conducted at German university medical centers remained delayed and incomplete. The 2014-2017 cohort. Journal of Clinical Epidemiology, 0(0). <a href="http://doi.org/10.1016/j.jclinepi.2021.12.012">https://doi.org/10.1016/j.jclinepi.2021.12.012</a><br> </p>
DATA SET: Performance Assessment of a Commercial Continuous-Wave Near-Infrared Spectroscopy Tissue Oximeter for Suitability for Use in an International, Multi-Center Clinical Trial
<p>This repository contains the data sets related to the publication:</p> <p>Cortese, L.; Zanoletti, M.; Karadeniz, U.; Pagliazzi, M.; Yaqub, M.A.; Busch, D.R.; Mesquida, J.; Durduran, T. Performance Assessment of a Commercial Continuous-Wave Near-Infrared Spectroscopy Tissue Oximeter for Suitability for Use in an International, Multi-Center Clinical Trial. <em>Sensors</em> <strong>2021</strong>, <em>21</em>, 6957. https://doi.org/10.3390/s21216957</p>
MiRoR11 - P2 - Annotated corpus for semantic similarity of clinical trial outcomes
<p>Outcome similarity corpus</p> <p>This dataset contains annotations of semantic similarity for pairs of primary and reported outcomes.<br> Tab-separated format is used. The files contain the following columns:<br> filename, sentence pair ID, sentence pair text, primary outcome, primary outcome start position, primary outcome end position, reported outcome, reported outcome start position, reported outcome end position, label</p> <p>The folder out_relations_split contains the dataset splits for 10-fold cross-validation.</p>
Post-trial access practice in Malaria, Tuberculosis, and NTDs Clinical Trial studies in Sub-Saharan African countries, quantitative study
<p>This is the data set used <span>to evaluate post trial access plan and implementation practice on TB, Malaria and NTD clinical trial studies conducted in the sub-Saharan African countries. </span></p>
Offering ART refill through community health workers versus clinic-based follow-up after home-based same-day ART initiation in rural Lesotho: The VIBRA cluster-randomised clinical trial
<p>These are pseudo-anonymised data from the VIBRA randomized trial: "Offering ART refill through community health workers versus clinic-based follow-up after home-based same-day ART initiation in rural Lesotho: The VIBRA cluster-randomised clinical trial". The data dictionary explains the data available in the dataset. Between August 2018 and May 2019, 257 eligible individuals from 117 consenting villages were enrolled from two districts of Lesotho, and followed up for a maximum of 15 months. The protocol was published, doi: 10.1186/s13063-019-3510-5</p>
TomoBreast randomized clinical trial's lung-heart outcomes and mortality through the 2020 COVID-19 pandemic: data and software
<p>Dataset and R script to reproduce the analyses of the manuscript:</p> <p>Vinh-Hung V, Gorobets O, Adriaenssens N, Van Parijs H, Storme G, Verellen D, Nguyen NP, Magne N, De Ridder M.</p> <p><strong>Lung-heart outcomes and mortality through the 2020 COVID-19 pandemic in a prospective cohort of breast cancer radiotherapy patients.</strong></p> <p>Cancers 2022; 14(24):6241. https:// doi.org/10.3390/cancers14246241</p> <p>https://www.mdpi.com/2072-6694/14/24/6241</p> <p>PubMed: PMID: 36551726</p> <p>PMCID: PMC9777311</p> <p>Info on the variables in file "aelq6_public.R"</p> <p>reproduced in "aelq_2_3_readme.txt":</p> <p>"aelq2_base2.txt" = baseline characteristics.</p> <p>"aelq3.txt" = longitudinal maesurements.</p> <p>Variables in "aelq2_base2.txt":</p> <p>"<strong>aelq2_base2.txt</strong>" = baseline characteristics. <br># Age at randomization, years. <br># RTdose: cf TomoBreast papers. <br># 51 Gy = hypofractionated, simultaneous integrated boost<br># 42 Gy = hypofractionated, no boost, mastectomy cases only<br># 50 Gy = conventional, no boost, mastectomy cases only<br># 66 Gy = conventional, sequential boost<br># Weight kg, Height cm, <br># Detection 1=found by screening (senology follow-up/controle)<br># 2=found by symptoms (pain, palpable)<br># 9=unknown<br># Smoker 0= Not smoker<br># 1= Smoker<br># 2=ex-smoker<br># Mastectomy (and other binary coded) 1= yes<br># chemosched 0=none<br># 1= planned after RT (sequential)<br># 2= prior to RT and is finished (sequential)<br># 3= chemo is on-going or is planned to start with RT (concomitant)<br># hormonetherapy 0=no<br># 1=tamoxifen (nolvadex)<br># 2=Femara (Letrozole)<br># 3=zoladex<br># 4=tamoxifen + zoladex<br># Laterality 1,=Right, 2=Left, 3=Bilateral<br># LengthFU: length of follow-up, days from randomization</p> <p>"<strong>aelq3.txt</strong>" = longitudinal maesurements.<br># "Nr" = Case ID<br># "Time" in days from origin (origin =date of randomization), <br># if negative =before randomization<br># "KPS" "Weight" <br># "Died" "LocalRec" "Metast" "NewPrim" = binary code, 0=no, 1=yes<br># "fAEBreast" "fAEHeart" "fAELung" "fAEOther" <br># fAE = freedom from breast, heart, lung, other adverse event score<br># "LVEF2" = ejection fraction, %<br># "MacIver" = estimated cardiac strain</p> <p># the following are pulmonary function tests, untransformed units<br># "FVC", "FEV1", "PEF", "VC", "TLC", "RV", "FRC", "Raw", "sRaw", "DLCO",<br># "VA", "PF"</p> <p># "fDY", "fFA", "fPA" = freedom from dyspnea, from fatigue, from pain<br># range 0 to 100 (best)<br># see papers:</p> <p># Van Parijs, H.; Vinh-Hung, V.; Fontaine, C.; Storme, G.; Verschraegen, C.;<br># Nguyen, D.M.; Adriaenssens, N.; Nguyen, N.P.; Gorobets, O.; De Ridder, M.<br># Cardiopulmonary-related patient-reported outcomes in a randomized clinical<br># trial of radiation therapy for breast cancer. BMC Cancer 2021, 21, 1177,<br># doi:10.1186/s12885-021-08916-z.</p> <p># preprint:<br># Van Parijs, H.; Cecilia-Joseph, E.; Gorobets, O.; Storme, G.; <br># Adriaenssens, N.; Heyndrickx, B.; Verschraegen, C.; Nguyen, N.P.;<br># De Ridder, M.; Vinh-Hung, V. Lung-heart toxicity in a randomized <br># clinical trial of hypofractionated image guided radiation therapy for<br># breast cancer. Preprints 2022, 202212, 0214.<br># https://doi.org/10.20944/preprints202212.0214.v1</p> <p># <br># "Year" = year of the observation<br># example: randomized 1/1/2011, measurement done 1/31/2011, time = 30 days,<br># Year =2011<br>#<br> </p>
Dataset Treatment of early childhood caries with three different topical fluoride treatments: a randomised clinical trial
<p>These files contain the data and the research script about the effectiveness of the 38% silver diamine fluoride (SDF, SDI Riva Star) and Tiefenfluorid (TF, Humanchemie GmbH), using two different application protocols in children ≤71 months of age with early childhood caries, with a focus on patient-centred outcomes including major complications (pain, abscess, extraction) and minor complications (lesion progression).</p> <p>This work was funded by European Regional Development Fund Postdoc Latvia 1.1.1.2/VIAA/3/19/543, Contract No 9.-14.5/27. Uribe was supported by European Union’s Horizon 2020 grant agreement 857287 for the Baltic Biomaterials Centre of Excellence.</p>
Final Dataset for the DIssemination of REgistered COVID-19 Clinical Trials (DIRECCT) Study
<p>The DIRECCT study is a multi-phase examination of clinical trial results dissemination during the COVID-19 pandemic.</p> <p>Interim data for trials completed during the first six months of the pandemic (i.e., 1 January 2020 – 30 June 2020) was previously deposited at https://doi.org/10.5281/zenodo.4669936.<br> This data deposit comprises the results of searches for trials completed during the first 18-months of the pandemic (i.e., 1 January 2020 – 30 June 2021).<br> The data structure for the final phase of the project is not identical to the interim data as it was substantially more complex.<br> The data include datatables (CSVs) that can be treated as relational and joined on the `id` or `trn` columns. See datamodel.png for an overview of the data.</p> <p>Details on data sources and methods for the creation and analysis of this dataset are available in a detailed protocol (Version 3.1, 19 July 2023) : https://osf.io/w8t7r</p> <p>Note: This repository will be updated with additional information including a codebook and archives of raw data.</p> <p>Additional information on the project is available at the project's OSF page: https://doi.org/10.17605/osf.io/5f8j2.</p>
COVID19 - Clinical Trials
<p> </p> <p>The objective of the project is to extract a set of clinical trials carried out for Covid-19 disease around the world in order to carry out statistical and data mining studies .</p> <p>The <a href="https://clinicaltrials.gov/">ClinicalTrials.gov</a> website is a database of privately and publicly clinical trials conducted around the world.</p> <p>The URL of the project to extract the data is the GitHub <a href="https://github.com/jordi-puig/web-scraping">repository</a>.</p>
SMA-TB Clinical trial: video & electronic informed consent
<p>The first SMA-TB video has been produced aiming a better understanding of SMA-TB Randomized Clinical Trial (RCT) objectives and procedures. This RCT is work package 1 of SMA-TB project. It is entitled <em>"Phase 2b Randomized double-blind, placebo controlled trial to estimate the potential efficacy and safety of two repurposed drugs, acetylsalicylic acid and ibuprofen, for use as adjunct therapy added to, and compared with, the standard WHO recommended TB regimen (SMA-TB)”, </em>and is registered in ClinicalTrials.gov data under identifier NCT04575519</p> <p>This video has been conceptualized as an e-informed consent for TB patients aiming their participation in SMA-TB CTs in Georgia and South Africa, as well as for anyone wanting to learn about the SMA-TB CT. The video explains in a very comprehensive way the rationale of SMA-TB concept, how the CT will be performed, what is expected from the patient, which are potential benefits, as well as side effects. The message is produced both in English and in Georgian.</p>
DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resource Entity Extraction Using Clinical Trials Literature
<p><strong>Datasets</strong></p> <ol> <li>DISTANT-CTO is a weakly-labelled dataset of 'Intervention' and 'Comparator' entity annotated sentences. The dataset was obtained using candidate generation the approach described in "DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low Resource Entity Extraction Using Clinical Trials Literature". <ol> <li>distantcto_high_conf.txt - ds conf 1.0 (full dataset)</li> <li>extraction1_pos_posnegtrail_conf09.txt - ds conf 0.9 (partial dataset)</li> </ol> </li> <li>The physio test set is a dataset comprising 153 PICO annotated randomized controlled trial abstracts from Physiotherapy and Rehabilitation. This dataset was used as an additional benchmark to evaluate the generalization power of the weakly annotated dataset and NER model for this sub-domain.</li> </ol> <p> </p> <p><strong>Utility</strong></p> <p>The dataset could be used as an input for training 'Intervention' named-entity recognition (NER) models.</p> <p> </p> <p><strong>Availability</strong></p> <p>This directory includes extraction1_pos_posnegtrail_conf09.txt - This text data file contains all the weak annotations (source intervention terms mapped onto target sentences) from clinicaltrials.org (CTO) with a confidence score of 0.9 and above.</p> <p>The directory also includes ‘physio_sent_annot2POS_posnegtrail.txt’ – This data file contains manually annotated (Intervention entity) data from the physiotherapy and rehabilitation domain. It follows a roughly similar structure as described in the ‘Description for long targets’ section. (‘Participant’ and ‘Outcome’ annotations are removed from this file)</p>
Global Trends in Clinical Trials Involving Engineered Biomaterials
<p><span>The study aimed to conduct a comprehensive analysis of all clinical trials involving engineered biomaterials by utilizing the ClinicalTrials.gov database. The search was executed in August 2023, and the analysis encompassed various attributes of the included studies, including the study title, URL, target disease, condition, intervention, biomaterial category, biomaterial type, specific biomaterial used, biomaterial properties, incorporation of cells, participant age and gender, clinical study phase, enrollment figures, study location, and the study's start and end dates. The corresponding data was systematically collected from the included studies and organized into dataset </span><span>(</span><span>Dataset </span><span>S1 and </span><span>Dataset </span><span>S2).</span></p>
CT-EBM-SP - Corpus of Clinical Trials for Evidence-Based-Medicine in Spanish (version 2)
<p>A collection of <strong>1200 texts</strong> (292173 tokens) about<strong> clinical trials studies</strong> and <strong>clinical trials announcements</strong> in <strong>Spanish</strong>:</p> <p>- 500 abstracts from journals published under a Creative Commons license, e.g. available in PubMed or the Scientific Electronic Library Online (SciELO).<br>- 700 clinical trials announcements published in the European Clinical Trials Register and Repositorio Español de Estudios Clínicos.</p> <p>Texts were annotated with the following entities types:</p> <p>- <strong>Semantic groups from the Unified Medical Language System</strong>: <br> • ANAT: anatomy<br> • CHEM: pharmacological and chemical substances<br> • DEVI: medical devices<br> • DISO: pathologic conditions <br> • LIVB: living beings, included the human being<br> • PHYS: physiological processes<br> • PROC: lab tests, diagnostic or therapeutic procedures<br>- <strong>Medical drug information</strong>:<br> • Contraindicated: a contraindicated drug or treatment<br> • Dose: dose or strength<br> • Form: dosage form<br> • Route: administration route or mode<br>- <strong>Temporal expressions</strong> <br> • Age<br> • Date<br> • Duration<br> • Frequency<br> • Time<br>- <strong>Miscellaneous medical entities</strong>: <br> • Concept: abstract concepts, statistical tests or measurement scales<br> • Food: foods or drinks<br> • Observation: medical observations or clinical findings<br> • Quantifier_or_Qualifier: quantifier or qualifier adjective<br> • Result_or_Value: result or value of a measurement, laboratory analysis or procedure<br>- <strong>Negation/Speculation</strong>: <br> • Neg_cue: negation cue<br> • Negated: negated event<br> • Spec_cue: speculation cue<br> • Speculated: speculated or uncertain event<br>- <strong>Attributes</strong>: <br> • Temporality:<br> ◦ History_of: past event<br> ◦ Future: future event<br> • Experiencer:<br> ◦ Patient: patient or participant on a clinical trial<br> ◦ Family_member<br> ◦ Other: other person different from the patient or the family member</p> <p>86 389 entities and 16 590 attributes were annotated. 10% of the corpus was doubly annotated, and high inter-annotator agreement (IAA) values were achieved: F1-score = 0.84% for entities; and F1-score = 0.88% for attributes (both in strict match). </p> <p>The dataset includes the <strong>texts and annotations used for the human evaluation</strong> of the medical named entity tool:</p> <p>- 100 clinical trial announcements from EudraCT not used for system development: we provide files of the version revised by medical professionals (Reference folder)<br>- 100 clinical cases with Creative Commons license: we provide files with the files revised by medical professionals (Reference folder). These data come from:</p> <p> • Urgencias Bidasoa (https://urgenciasbidasoa.wordpress.com/casos-clinicos-3/)<br> • Hipocampo.org (https://www.hipocampo.org/)<br> • Cases published by Sociedad Andaluza de Medicina Familiar y Comunitaria (SAMFyC): we are greatly thankful for giving us permission to use these cases and we acknowledge that the copyright belongs to the authors' contents. Clinical cases were extracted from books published from 2016 to 2022 (https://www.samfyc.es/tipos-publicacion/publicaciones/).<br> <br>If you use these data, please, acknowledge the copyright and intellectual property rights to the authors' contents.</p> <p>The dataset is freely distributed for research and educational purposes under a Creative Commons Non-Commercial Attribution (CC-BY-NC-A) License.</p> <p>If you use the CT-EBM-SP vs. 2 dataset, please, cite as follows:</p> <p>Campillos-Llanos, L., A. Valverde-Mateos & A. Capllonch-Carrion (2024) Hybrid natural language processing tool for semantic annotation of medical texts in Spanish. BMC Bioinformatics. BioMed Central.</p>
Dataset and codebook for the article by Gaume J, Bertholet N, McCambridge J, et al. Effect of a Novel Brief Motivational Intervention for Alcohol-Intoxicated Young Adults in the Emergency Department: A Randomized Clinical Trial. JAMA Netw Open. 2022;5(10):e2237563. doi: 10.1001/jamanetworkopen.2022.37563
<p>Dataset and codebook for the article Gaume J, Bertholet N, McCambridge J, et al. <strong>Effect of a Novel Brief Motivational Intervention for Alcohol-Intoxicated Young Adults in the Emergency Department: A Randomized Clinical Trial</strong>. JAMA Netw Open. 2022;5(10):e2237563. doi: <a href="http://jamanetwork.com/article.aspx?doi=10.1001/jamanetworkopen.2022.37563">10.1001/jamanetworkopen.2022.37563</a></p> <p>The dataset contains all data needed to reproduce the results in the above cited article.</p> <p>Variable description and labels can be found in the codebook.</p> <p>Please refer to the published article and supplemental online content for further information about the data and the study procedures.</p>
Geographic Scope of Randomized Clinical Trials from Africa
<p><strong>Overview</strong></p> <p>This map reports the geographic scope of randomized controlled trials (RCTs) conducted in Africa, as found in PubMed. The map highlights a discrepancy between actual trial location and how trials are reported: although reports of research from Africa are often labeled as being "African" in scope, RCTs are rarely continent-wide and many countries are not represented in even a single study. The intent of the map is to visualize actual trial locations, hopefully leading to a more accurate portrayal of RCT study sites on the African continent.</p> <p><strong>Data Source and Tools</strong></p> <p>Data for the map was extracted from PubMed and the map was created in ArcGIS Online.</p> <p><strong>Audience</strong></p> <p>The map was created for an original research poster at the 2022 International Congress on Peer Review and Scientific Publication (see "Attribution" below). Its audience is researchers, clinicians, policy makers, librarians, scholarly communications stakeholders, and editors in chief interested in improving the accuracy of the reported scope of research in Africa to better inform health care research, policy, and resource distribution.</p> <p><strong>Design</strong></p> <p>A PubMed search using Medical Subject Headings and keywords representing Africa, African, and RCTs was run to identify citations published between 1968 and February 2022. The citation titles and abstracts were screened against established inclusion/exclusion criteria, with included studies continuing through a full text review and data extraction process. Total RCT representation per country was then mapped in ArcGIS with higher RCT counts represented by darker shading. The map highlights the variance in RCT representation across the continent, with some countries represented in up to 80 RCTs and many countries represented in none.</p> <p><strong>Attribution</strong></p> <p>Folafoluwa Olutobi Odetola and Marisa L. Conte conceived the research question, crafted the PubMed search, and analyzed the citation data; Tyler Nix created the map. Special thanks to Caroline Kayko (University of Michigan) for her input in the creation of the map. </p> <p>See the original research poster at:</p> <p>Odetola, FO; Conte, ML. Geographical Scope of Randomized Clinical Trials from Africa. [Poster]. 9th International Congress on Peer Review and Scientific Publication, September 8-10, 2022, Chicago, IL. Available from: <a href="https://peerreviewcongress.org/abstract/geographical-scope-of-randomized-clinical-trials-from-africa/">https://peerreviewcongress.org/abstract/geographical-scope-of-randomized-clinical-trials-from-africa/</a></p> <p>The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.</p>
MiRoR4_P1_A systematic review describes models for recruitment prediction at the design stage of a clinical trial
<p>This dataset is related to the publication "A systematic review describes models for recruitment prediction at the design stage of a clinical trial".</p>
Nordic trial reporting project: Raw data from EU Clinical Trials Registry (EUCTR) and ClinicalTrials.gov
<p>Uploaded on behalf of the author team for the research project "<strong>Systematic evaluation of clinical trial reporting at medical universities and university hospitals in the Nordic countries</strong>".</p><p><strong>Raw data</strong> from EU Clinical Trials Registry (EUCTR) and ClinicalTrials.gov:</p><p><strong>EUCTR</strong>: We retrieved the latest dataset for the EU Trials Tracker of EUCTR trials on Nov 27, 2022, reflecting data from Nov 7, 2022 (1,2). We also used a custom web scraper that automatically extracts data from EUCTR country protocols and results sections (variables described in Appendix Table 2), developed by the EU Trials Tracker team (2).<br>References: <br>1. Goldacre B, DeVito NJ, Heneghan C, Irving F, Bacon S, Fleminger J, Curtis H. Compliance with requirement to report results on the EU Clinical Trials Register: cohort study and web resource. BMJ. 2018 Sep 12;362:k3218.<br>2. EU Trials Tracker — Who's not sharing clinical trial results? [Internet]. [cited 2022 Aug 30]. Available from: http://eu.trialstracker.net/</p><p><strong>ClinicalTrials.gov</strong>: We downloaded the complete Aggregate Analysis of ClinicalTrials.gov dataset (AACT, http://aact.ctti-clinicaltrials.org/) on Nov 27, 2022, reflecting data from Nov 9, 2022. </p><p>See our GitHub and preregistered protocol for more details:<br>https://github.com/cathrineaxfors/nordic-trial-reporting<br>https://osf.io/97qkv/</p>
The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS
<p>The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry .</p> <p>Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0).</p> <p>The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release).</p> <p>The data set is curated and organized by test and item for each experimental phase and also has a dictionary to define the variables measured.</p> <p> </p> <p>If you require more information about data or scales, please contact us. </p> <p><em>LANIREM (</em><em>National MRI Laboratory)</em><em>, Institute of Neurobiology, </em></p> <p><em>Universidad Nacional Autónoma de México (UNAM), </em><em>Querétaro, México.</em></p> <p><strong>Diego Angeles Valdez, M. Sc. </strong></p> <ul> <li>diego.ang.val@gmail.com</li> <li>diego.ang.val@inb.unam.mx</li> </ul> <p><br> <strong>Eduardo A. Garza-Villarreal, M.D., Ph.D.</strong></p> <ul> <li>egarza@gmail.com</li> <li>egarza@comunidad.unam.mx</li> </ul>
List of all proteins and chemicals mentioned in COVID-19 clinical trials
<p>A record of all COVID-19 related clinical trials is provided in the database hosted at https://ClinicalTrials.gov. This is an important resource that tracks worldwide research efforts directed towards improvements in treating the pandemic. To help unlock the insights buried in this database, in this work we have created an automated text mining pipeline that dynamically tags chemical, protein, and gene names in all COVID-19 related database entries, as the database is updated. We plan to publish further details in a subsequent publication. </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.