Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,989
datasets available to search
ShareScore release 0.7.1
Dataset results
1,989 results for “Blood pressure”
Protocol for a systematic review: association between airborne pollen, intermittent allergic rhinitis and blood pressure
<p>Previous epidemiological studies have found an increased risk of cardiovascular morbidity and mortality following days with heightened pollen exposure and suggested that intermittent allergic rhinitis might be associated with blood pressure. Pollen sensitization and subsequent pollen exposure cause local inflammation and cytokine release in individuals with intermittent allergic rhinitis (pollen allergy). Inflammatory mediators can travel throughout the body, hence providing the physiologic basis by which pollen allergy may lead to systemic inflammation, which is known to be a risk factor for cardiovascular events. However, the findings regarding the potential association between intermittent allergic rhinitis, pollen exposure, and cardiovascular health are not fully conclusive. To date, no systematic review has been published on this topic.</p> <p>This systematic review seeks to answer: Are exposure to airborne pollen and intermittent allergic rhinitis associated with blood pressure? Secondary questions include: (1) Are there personal characteristics (sex, age) which modify a potential association between intermittent allergic rhinitis or pollen exposure with blood pressure and/or hypertension? (2) What research gaps exist in our understanding of how intermittent allergic rhinitis, pollen exposure, and cardiovascular health are interrelated?</p> <p>Published herein are:</p> <ul> <li>Protocol for the systematic review, including the search strategy</li> <li>Supplement 1: PROSPERO registration</li> <li>Supplement 2: Data extraction table</li> <li>Supplement 3: Risk of bias assessment strategy</li> <li>Supplement 4: Risk of bias assessment tool</li> </ul>
A longitudinal study of the associations of children's body mass index and physical activity with blood pressure – dataset
<p>B-Proact1v is a longitudinal study examining changes in children’s physical activity and sedentary behaviours as they progress through primary school. In 2012-2013, 1299 Year 1 children (median age: 6 years) were recruited from 57 schools in greater Bristol, UK (total number of eligible children: 2600; recruitment rate: 50.0%). Following this, data were collected from 1223 Year 4 children (median age: 9 years) from 47 of the original schools between March 2015 and July 2016 (total number of eligible children: 2047; recruitment rate: 59.7%). This included 685 children from the original sample.</p> <p> </p> <p>This dataset represents a subset of the B-Proact1v data to examine the longitudinal associations of children’s body mass index and physical activity with blood pressure. Included in this repository is the dataset and a data dictionary. The dataset includes the variables that underlie the findings in a manuscript entitled ‘A longitudinal study of the associations of children’s body mass index and physical activity with blood pressure’ that has been submitted to PLOS ONE. This dataset has been made available so that future researchers can replicate the study findings using the data. If you wish to use the data for any purpose other than replicating the study findings, please contact the Principal Investigator Professor Russ Jago (russ.jago@bristol.ac.uk) to discuss this.</p>
The Application of Machine Learning for Classification on Blood Pressure Variability. A New Approach for an Old Idea - Professor Kelvin Tsoi (The Chinese University of Hong Kong, School of Public Health and Primary Care)
<p>This video is the eighth talk from our Future Blood Testing Network Plus Launch that took place on the 23/11/2021.</p> <p>The Application of Machine Learning for Classification on Blood Pressure Variability. A New Approach for an Old Idea - Professor Kelvin Tsoi (The Chinese University of Hong Kong, School of Public Health and Primary Care)</p> <p>Bio: Professor Kelvin Tsoi is an Epidemiologist specialized in Digital Health. His research interests focus on digital innovation in chronic disease management, including mobile and telecare application for hypertension management, technological implementation and social engagement for cognitive screening, artificial intelligent application on electronic health records. He also works as the traditional epidemiologist on evidence-based medicine and population cohort studies. He obtained his Bachler Degree from Department of Statistics and Doctor of Philosophy from School of Public Health in the Chinese University of Hong Kong. He further received post-doctoral training in the Division of Gastroenterology and Hepatology, Department of Medicine and Therapeutics. He was also appointed as a Director of CUHK JC Bowel Cancer Education Centre to promote colorectal cancer screening. In 2011, he worked as a research scientist in Hospital Authority. He led projects covering a wide range of service areas on chronic diseases, such as service demand projection for schizophrenia and dementia. The experience of database management enhanced his understanding of the HA database structures. In 2013, he was invited to join the interdisciplinary team for Big Data research and worked closely with a team of engineers and data scientists. Currently, Professor Tsoi is an Associate Professor in JC School of Public Health and Primary Care, SH big Data Decision Analytics Research Centre and JC Institute of Ageing.</p> <p>Further details on this event can be found at: https://futurebloodtesting.org/event/23-11-21-future-blood-testing-network-launch/</p> <p>This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1</p> <p>YouTube Link: https://youtu.be/liLVKA-JHiI</p>
ACE gene haplotypes and social networks: Using a biocultural framework to investigate blood pressure variation in African Americans
<p>This dataset contains all processed data used in analyses reported in the manuscript, ACE gene haplotypes and social networks: Using a biocultural framework to investigate blood pressure variation in African Americans. This project is part of a larger study focused on investigating the role of stress, discrimination, genetic variants, and other sociocultural factors in hypertension in African Americans.</p> <p> </p> <p> </p> <p>Variable Names and Descriptions:</p> <p>HHID: Participant Identification number</p> <p>sbp-10: Average of two Systolic Blood Pressure readings without 10 point correction for blood pressure medication (mmHg)</p> <p>sbp: Average of two Systolic Blood Pressure readings with 10 point correction for blood pressure medication (mmHg)</p> <p>dbp-5: Average of two Diastolic Blood Pressure readings without 5 point correction for blood pressure medication (mmHg)</p> <p>dbp: Average of two Diastolic Blood Pressure readings with 5 point correction for blood pressure medication (mmHg)</p> <p>ACE.Genotype: ACE genotype (0= Deletion/Deletion, 1= Insertion/Deletion, 2= Insertion/Insertion)</p> <p>WNK1.Genotype: WNK1 Genotype (0= Deletion/Deletion, 1= Insertion/Deletion, 2= Insertion/Insertion)</p> <p>age: age (years)</p> <p>sex: sex (Male =1, Female = 2)</p> <p>bpmedtake: Whether the participant uses blood pressure medication</p> <p>bmi: Body Mass Index (calculated from height and weight)</p> <p>ALTER GENDER|Answer:Male|Value:0|Count: Number of male alters (social network members)</p> <p>Alter Gender Male: Percentage of alters that are male</p> <p>ALTER GENDER|Answer:Female|Value:1|Count: Number of female alters (social network members)</p> <p>Alter Gender Female: Percentage of alters that are female</p> <p>Closeness_Mean: Average closeness centrality of the network</p> <p>Between_Mean: Average between-ness centrality of the network</p> <p>percentage of family in structural percentage: Percentage of central network positions occupied by family members</p> <p>relationship max close family: The most close (centrally) network member is a family member</p> <p>Average distance: Average distance of individuals in a network</p> <p>Hap B: ACE gene haplotypes</p> <p> </p>
Assessment of Non-Invasive Blood Pressure Prediction from PPG and rPPG Signals Using Deep Learning
<p>This dataset is a subset of the MIMIC-III dataset used for non-invasive blood pressure prediction. PPG and ABP data were divided into windows of 7s length (875 data points). Systolic and diastolic blood pressure values were derived from the ABP windows. Each sample of the dataset consists of a PPG signal and blood pressure values as well as a unique subject identifier. The file consists of three datasets:</p> <ul> <li>PPG: PPG data of size 905,400 x 875</li> <li>label: BP data of size 905,400 x 2</li> <li>subject_idx: subject affiliation of each sample (size 905,400 x 1)</li> </ul> <p>Furthermore, this submission contains the following models:</p> <ul> <li>AlexNet</li> <li>ResNet50</li> <li>LSTM</li> <li>Architecture published by Slapnicar et al. 2019</li> </ul> <p>The architectures were trained using a non-mixed dataset derived from the MIMIC-III waveform database. Samples were divided between training, validation and test set based on their subject affiliation preventing contamination of validation and test sets with samples from subjects used for training.</p>
Blood Pressure Checks for Diagnosing Hypertension (BP-CHECK)
ClinicalTrials.gov study NCT03130257. IPD Sharing: YES. Countries: 1. Publications: 7.
A Dose Escalation Study of a Combination Antihypertensive Drug in the Treatment of Various Groups of Patients Who do Not Respond to Single Drug Treatment of Their High Blood Pressure
ClinicalTrials.gov study NCT00791258. IPD Sharing: YES. Countries: 1. Publications: 2.
Gut Butyrate and Blood Pressure in African Americans
ClinicalTrials.gov study NCT04415333. IPD Sharing: YES. Countries: 1. Publications: 5.
CARDIA-Salt Sensitivity of Blood Pressure (SSBP)
ClinicalTrials.gov study NCT04258332. IPD Sharing: YES. Countries: 1. Publications: 1.
Arterial Blood Pressure During Reclining dataset
<p>Dataset taken from https://sites.google.com/site/timeserieschain/home/TiltABP_210_25000.txt who adopted it from https://ieeexplore.ieee.org/document/1291141/authors .</p> <p>Stored on Zenodo as backup for Stumpy Semantic Segmentation turotial tutorials found on https://stumpy.readthedocs.io/en/latest/Tutorial_Semantic_Segmentation.html</p> <p> </p> <p> </p>
Non invasive and minimally intrusive blood pressure estimates
<p>Currently, health disorders related to Blood Pressure (BP) fluctuations are within the most prevalent and of higher social and economic impact in the world. A continuous and routinary monitoring of the BP can contribute to the early identification of risk factors, and consequently, would help to prevent potential cardiovascular diseases. <br> <br> BP measurement methods based on the cuff are of widespread use today. The monitoring based on this technology is intrusive and cannot be made continuously, which is of fundamental importance to diagnose Hypertension accurately. Due to the discomfort, inconvenience and intrusiveness of the cuff-based measurements of BP most people undergo monitoring only when they present symptoms of cardiovascular problems and a high proportion of them do not complete the monitoring protocol. <br> <br> In order to provide a less intrusive technology for non-invasive and continuous BP monitoring, many researchers aimed to estimate the BP from Pulse Waveforms (PW), recorded using plethysmography, ultrasound, and tonometry. Some BP estimation methods based on these technologies have been successfully implemented in commercial products. <br> <br> However, the BP estimation from PW is still an open research problem. The hemodynamic behavior of people is complex and highly variable within and between subjects. This makes the estimation of BP from PW very challenging from the mathematical and computational modeling perspectives. <br> <br> For this reason we provide a dataset from two healthy subjects. The experimental paradigm is explained in advance. Data were acquired by using the Finapres® NOVA which is a non-invasive continuous blood pressure monitor. <br> <br> The data contains the following columns: <br> <br> - Timeline of the acquisition.<br> - The PPG (Photoplethysmography) signal measured in the right hand.<br> - The PPG (Photoplethysmography) signal measured in the foot.<br> - The arterial pressure estimated by Finapres® NOVA.<br> - The ECG signal.<br> - The occurrence of the handgrip maneuver on the specific time instant.</p>
Data from: Blood pressure pulsations modulate central neuronal activity via mechanosensitive ion channels
<p><span>The transmission of heartbeat through the cerebral vascular system is known to cause intracranial pressure pulsations. Here we report that arterial pressure pulsations can directly modulate central neuronal activity. </span><span>In a semi-intact rat brain preparation, vascular pressure pulsations elicit correlated local field oscillations in the olfactory bulb (OB) mitral cell layer. These oscillations do not require synaptic transmission, but reflect baroreceptive transduction in mitral cells. This transduction is mediated by an excitatory mechanosensitive ion channel and modulates neuronal spiking activity. Indeed, in awake animals, the heartbeat entrains the activity of a subset of OB neurons within ~20 ms. Thus, we propose that this fast intrinsic interoceptive mechanism can modulate perception, e.g. during arousal, within the OB and also possibly across various brain areas.</span></p>
Distribution of blood flow oscillation across the Doppler shift evaluated by the proposed approach with local pressure test.
<p>A step-wise increase in local pressure is known to cause a gradual change in the parameters of capillary blood flow in the<br> upper layers of the skin, and can also affect the measurement results of various optical methods. The impact of the procedure has several subsequent effects, such as mechanical compression of vessels, and neurological and metabolic compensating mechanisms like pressure-induced vasodilation, which maintain the homeostasis of the skin during moderate levels of external pressure and tissue hypoxia. To examine how those effects are translated to the blood flow registering in different ranges of the Doppler spectra, we have developed a 3D-printed pressure distribution tool compatible with the developed sensor which was used, and equipped with a set of weights. </p> <p>During the main series of measurements, the weights were placed into the PDT in a step-wise manner to achieve the<br> following values of pressure applied: 10 mmHg, 30 mmHg, 90 mmHg, 150 mmHg, 210 mmHg. At the end of the procedure, the load was reduced back to 30 mmHg. Experiments were conducted with the participation of 7 healthy volunteers with 10 min LDF recording for each step. To estimate the prominence of the observed effects and substantiate the measuring routing, several preliminary experiments were also conducted where the set of values of pressure was applied with a step-wise increase and then decrease with about 2 min of LDF recordings for each step.</p> <p>Published in IEEE Transactions on Biomedical Engineering "Diagnosis of skin vascular complications revealed by time-frequency analysis and laser Doppler spectrum decomposition", Zherebtsov et al.</p>
Deciphering the explanatory potential of blood pressure variables on post-operative length of stay through hierarchical clustering: A retrospective monocentric study
<p><em>Objective:</em> Mean arterial pressure is widely used as the variable to monitor during anesthesia. But there are many other variables proposed to define intraoperative arterial hypotension. The goal of the present study was to search arterial pressure variables linked with prolonged postoperative length of stay (pLOS).</p> <p><em>Design: </em>Retrospective cohort study of adult patients having received general for a scheduled non cardiac surgical procedure between 15<sup>th</sup> July 2017 and 31st December 2019.</p> <p><em>Methods:</em> pLOS was defined as a stay longer than the median (main outcome), adjusted for surgery type and duration. 330 arterial pressure variables were analyzed and organized through a clustering approach. An unsupervised hierarchical aggregation method for optimal cluster determination, employing Kendall's tau coefficients and a penalized Bayes information criterion was used. Variables were ranked using the absolute standardized mean distance (aSMD) to measure their effect on pLOS. Finally, after multivariate independence analysis, the number of variables was reduced to three.</p> <p><em>Results:</em> Our study examined 9,516 patients. When LOS is defined as strictly greater than the median, 34% of patients experienced pLOS. Key arterial pressure variables linked with this definition of pLOS included the difference between the highest and lowest pulse pressure values computed throughout the surgery (aSMD[95%CI] =0.39[0.31-0.40], p<0.001), the accumulated time pulse pressure above 61mmHg (aSMD = 0.21[0.17-0.25], p<0.001), and the lowest MAP during surgery (aSMD= 0.20[0.16-0.24], p<0.001).</p> <p><em>Conclusions: </em>By applying a clustering approach, three arterial pressure variables were associated with pLOS. This scalable method can be applied to various dichotomized outcomes.</p>
Role of nutrition and exercise programs in reducing blood pressure: A systematic review
<p>Supplementary files for Role of nutrition and exercise programs in reducing blood pressure: A systematic review</p>
Blood pressure monitoring during anesthesia induction using PPG morphology features and machine learning
<p>PPG-BP dataset of forty patients undergoing general anesthesia, as described in the corresponding journal publication at PLOS ONE (10.1371/journal.pone.0279419).</p> <p>When using this data, please cite the corresponding journal publication.</p> <p> </p>
Adapting Clinical Practice Guidelines for Chronic Kidney Disease: Blood Pressure Management and Kidney Replacement Therapy in Adults and Children in the Saudi Arabian context using the GRADE-ADOLOPMENT methodology
<p>This compressed ZIP file includes three components</p> <p>The Full Guideline Document (FINAL COPY) for the <strong>2022 Saudi Guideline for Chronic Kidney Disease: Blood Pressure Management and Kidney Replacement Therapy in Adults and Children</strong></p> <p>In addition to two guideline reporting checklists to ensure the quality of this adoloped guideline:-</p> <p><strong>1- AGREE Reporting Checklist</strong></p> <p><strong>2- RIGHT-Ad@pt Checklist</strong></p> <p>As a supplementary to the submitted article entitled:_</p> <p><strong>Adapting Clinical Practice Guidelines for Chronic Kidney Disease: Blood Pressure Management and Kidney Replacement Therapy in Adults and Children in the Saudi Arabian context using the GRADE-ADOLOPMENT methodology</strong></p>
Postural fall in systolic blood pressure is an useful warning sign in Dengue fever
<p><strong>Purpose</strong>: Capillary leak is the hallmark of development of severe dengue. A rise in hematocrit has been a major warning sign in WHO guidelines. Postural hypotension, which could reflect the intravascular volume reduction in capillary leak, has been noted as a warning sign in CDC and Pan American Health Organisation guidelines. We evaluated the diagnostic accuracy of Postural hypotension as a marker of development of severe dengue.</p> <p><strong>Methods</strong>: 150 patients admitted with dengue fever were recruited in this prospective observational study. Diagnostic accuracy of conventional warning signs (<span>abdominal pain, persistent vomiting, fluid accumulation, mucosal bleeding, lethargy, liver enlargement, increasing hematocrit with decreasing platelets)</span> and postural hypotension was evaluated.</p> <p><strong>Result</strong>: 23 (15.3%) subjects developed severe dengue. Multiple logistic regression analysis showed that Ascites/Pleural effusion and postural fall in systolic blood pressure of >10.33% had an odds ratio of 5.024(95%CI:1.11 – 22.75) and 11.369 (95% CI:2.27 – 56.87) respectively. Other parameters did not reach statistical significance. Sensitivity and specificity of Ascites/Pleural effusion were 82.6% and 88.2% for development of severe dengue, whereas postural fall in systolic blood pressure had sensitivity and specificity of 87% and 82.7%.</p> <p><strong>Conclusion</strong>: These findings present a strong case for including postural hypotension as a warning sign in patients with dengue fever, especially in resource-limited settings.</p>
Effectiveness of self-management of medication and self-monitoring of blood pressure, diet, and physical exercise on blood pressure in patients with poorly controlled hypertension (MEDICHY study): randomized and controlled trial
<p>Dataset study medichy ISRCTN144433778</p>
Preventing Weight Gain and Controlling Blood Pressure During Smoking Cessation in Hypertensive Smokers
ClinicalTrials.gov study NCT00113074. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.