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.
1,659
datasets available to search
ShareScore release 0.9.0
Dataset results
1,659 results for “Patient Data”
Data from: Discharge communication for chronic disease patients in three hospitals in India
Open the record for dataset details and reuse information.
Patient-reported outcomes via electronic health record portal vs. telephone: process and retention data in a pilot trial of anxiety or depression symptoms in epilepsy
Open the record for dataset details and reuse information.
COVID-19 patient data from a study in Singapore curated for input into an in silico infection model
Open the record for dataset details and reuse information.
Data from: Assessment of polytraumatized patients according to the Berlin Definition: Does the addition of physiological data really improve interobserver reliability?
Open the record for dataset details and reuse information.
Data from: Automatic Laplacian-based shape optimization for patient-specific vascular grafts
Open the record for dataset details and reuse information.
The supplemental files of 'DNA Methylation Data-based prognosis-subtype distinctions in Patients with Esophageal carcinoma'
<p>Our upload is the suplemental files which have been cited in the manuscript 'DNA Methylation Data-based prognosis-subtype distinctions in Patients with Esophageal carcinoma'</p>
R-R HRV data from Biofeedback on 100 patients
<p>Psychiatric patients with adverse childhood experiences (ACE) tend to be dysfunctional in the interoceptive part of their emotional experience. The integration of interoceptive emotional activity in the insular and cingulate cortices is linked to the regulation of sympathovagal balance. This makes heart rate variability (HRV) an ideal measure for providing feedback on emotion regulation in real time. A sample of one hundred (n=100) outpatients is included in this release. Most patient underwent 8 sessions. Se published article for more details.</p>
Could dementia be detected from UK primary care patients' records by simple automated methods earlier than by the treating physician? A retrospective case-control study - Extended Data
<p>Extended data for Article published in Wellcome Open Research (Appendices 1,2 & 3). </p> <p>Abstract of Article: </p> <p><strong>Background:</strong> Timely diagnosis of dementia is a policy priority in the United Kingdom (UK). Primary care physicians receive incentives to diagnose dementia; however, 33% of patients are still not receiving a diagnosis. We explored automating early detection of dementia using data from patients’ electronic health records (EHRs). We investigated: a) how early a machine-learning model could accurately identify dementia before the physician; b) if models could be tuned for dementia subtype; and c) what the best clinical features were for achieving detection.</p> <p><strong>Methods:</strong> Using EHRs from Clinical Practice Research Datalink in a case-control design, we selected patients aged >65y with a diagnosis of dementia recorded 2000-2012 (cases) and matched them 1:1 to controls; we also identified subsets of Alzheimer’s and vascular dementia patients. Using 77 coded concepts recorded in the 5 years before diagnosis, we trained random forest classifiers, and evaluated models using Area Under the Receiver Operating Characteristic Curve (AUC). We examined models by year prior to diagnosis, subtype, and the most important features contributing to classification.</p> <p><strong>Results:</strong> 95,202 patients (median age 83y; 64.8% female) were included (50% dementia cases). Classification of dementia cases and controls was poor 2-5 years prior to physician-recorded diagnosis (AUC range 0.55-0.65) but good in the year before (AUC: 0.84). Features indicating increasing cognitive and physical frailty dominated models 2-5 years before diagnosis; in the final year, initiation of the dementia diagnostic pathway (symptoms, screening and referral) explained the sudden increase in accuracy. No substantial differences were seen between all-cause dementia and subtypes.</p> <p><strong>Conclusions:</strong> Automated detection of dementia earlier than the treating physician may be problematic, if using only primary care data. Future work should investigate more complex modelling, benefits of linking multiple sources of healthcare data and monitoring devices, or contextualising the algorithm to those cases that the GP would need to investigate.</p>
Data from: Increased Dystrophin Production With Golodirsen in Patients with Duchenne Muscular Dystrophy
<p>Objective To report safety, pharmacokinetics, exon 53 skipping, and dystrophin expression in golodirsen-treated patients with Duchenne muscular dystrophy (DMD) amenable to exon 53 skipping. Methods Part 1 was a randomized, double-blind, placebo-controlled, 12-week dose titration of once-weekly golodirsen; Part 2 is an ongoing, open-label evaluation. Safety and pharmacokinetics were primary and secondary objectives of Part 1. Primary biological outcome measures of part 2 were blinded exon skipping and dystrophin protein production on muscle biopsies (baseline, Week 48) evaluated, respectively using reverse transcription PCR and western blot and immunohistochemistry. Results Twelve patients were randomized to receive golodirsen (n=8) or placebo (n=4) in Part 1. All from Part 1 plus 13 additional patients received 30 mg/kg golodirsen in Part 2. Safety findings were consistent with those previously observed in pediatric DMD patients. Most of the study drug was excreted within 4 hours following administration. A significant increase in exon 53 skipping was associated with ~16-fold increase over baseline in dystrophin protein expression at Week 48, with a mean percent normal dystrophin protein standard of 1.019% (range, 0.09%-4.30%). Sarcolemmal localization of dystrophin was demonstrated by significantly increased dystrophin positive fibers (Week 48, p<0.001); and a positive correlation (Spearman-r=0.663; p<0.001) between dystrophin protein change from baseline, measured by western blot and immunohistochemistry.</p>
Synthetic LOS and interarrival time data for COPD patients in the Cwm Taf region
<p>This archive contains two artificial datasets for the length of stay (LOS) and interarrival times of patients with COPD. Each dataset is split amongst four clusters as identified in the work that these datasets support. The rest of the associated paper is available at <a href="https://github.com/daffidwilde/copd-paper">https://github.com/daffidwilde/copd-paper</a></p>
Analysis of laboratory reporting practices using a quality assessment of a 'virtual patient'. (data)
<p>Dataset for paper Analysis of laboratory reporting practices using a quality assessment of a ‘virtual patient', published in Genetics in Medicine.</p> <p>This dataset consists of the FASTQ, BAM, and VCF for the virtual patients as described in the paper.<br> </p>
Data from: Initiating Antiretroviral Therapy for HIV at a Patient's First Clinic Visit: The RapIT Randomized Controlled Trial
<p><strong>Background:</strong> High rates of patient attrition from care between HIV testing and antiretroviral therapy (ART) initiation have been documented in sub-Saharan Africa, contributing to persistently low CD4 cell counts at treatment initiation. One reason for this is that starting ART in many countries is a lengthy and burdensome process, imposing long waits and multiple clinic visits on patients. We estimated the effect on uptake of ART and viral suppression of an accelerated initiation algorithm that allowed treatment-eligible patients to be dispensed their first supply of antiretroviral medications on the day of their first HIV-related clinic visit.</p> <p><strong>Methods and Findings: </strong>RapIT was an unblinded randomized controlled trial of single-visit ART initiation in two public sector clinics in South Africa (a primary health clinic (PHC) and a hospital-based HIV clinic). Adult (≥18), non-pregnant patients receiving a positive HIV test or first treatment-eligible CD4 count were randomized to standard or rapid initiation. Rapid arm patients received a point-of-care (POC) CD4 count if needed; those ART-eligible received a POC TB test if symptomatic, POC blood tests, physical exam, education, counseling, and ARV dispensing. Standard arm patients followed standard clinic procedures (3-5 additional clinic visits over 2-4 weeks prior to ARV dispensing). Follow up was by record review only. The primary outcome was viral suppression, defined as initiated, retained in care, and suppressed (<=400 copies/ml) ≤ 10 months of study enrollment. Secondary outcomes included initiation of ART ≤ 90 days of study enrollment; retention in care; time to ART initiation; patient-level predictors of primary outcomes; prevalence of TB symptoms; and the feasibility and acceptability of the intervention. A survival analysis was conducted comparing attrition from care after ART initiation between the groups among those who initiated within 90 days. 377 patients were enrolled in the study between May 8, 2013 and August 29, 2014 (median CD4 count 210 cells/mm<sup>3</sup>). In the rapid arm, 119/187 patients (64%) initiated and were suppressed at 10 months, compared to 96/190 (51%) in the standard arm (RR 1.26 [1.05-1.50]. In the rapid arm 182/187 (97%) initiated ART ≤ 90 days, compared to 136/190 (72%) in the standard arm (relative risk [95% CI] 1.36 [1.24-1.49]. Among 318 patients who did initiate ART within 90 days, the hazard of attrition within the first 10 months did not differ between the treatment arms (HR 1.06; 95% CI 0.61-1.84). The study was limited by the small number of sites and small sample size and the generalizability of the results to other settings and to non-research conditions is uncertain.</p> <p><strong>Conclusions: </strong>Offering single-visit ART initiation to adult patients in South Africa increased uptake of ART by 36% and viral suppression by 26%. It should be considered for adoption in the public sector in Africa.</p>
Raw single cell mass cytometry data from breast cancer patient derived xenografts
<p>Raw single cell mass cytometry data from breast cancer patient derived xenografts.</p> <p>Data is organised in an expressioset R object</p>
Data from: Development and validation of warning system of ventricular tachyarrhythmia in patients with heart failure with heart rate variability data
Implantable-cardioverter defibrillators (ICD) detect and terminate life-threatening ventricular tachyarrhythmia with electric shocks after they occur. This puts patients at risk if they are driving or in a situation where they can fall. ICD's shocks are also very painful and affect a patient's quality of life. It would be ideal if ICDs can accurately predict the occurrence of ventricular tachyarrhythmia and then issue a warning or provide preventive therapy. Our study explores the use of ICD data to automatically predict ventricular arrhythmia using heart rate variability (HRV). A 5 minute and a 10 second warning system are both developed and compared. The participants for this study consist of 788 patients who were enrolled in the ICD arm of the Sudden Cardiac Death – Heart Failure Trial (SCD-HeFT). Two groups of patient rhythms, regular heart rhythms and pre-ventricular-tachyarrhythmic rhythms, are analyzed and different HRV features are extracted. Machine learning algorithms, including random forests (RF) and support vector machines (SVM), are trained on these features to classify the two groups of rhythms in a subset of the data comprising the training set. These algorithms are then used to classify rhythms in a separate test set. This performance is quantified by the area under the curve (AUC) of the ROC curve. Both RF and SVM methods achieve a mean AUC of 0.81 for 5-minute prediction and mean AUC of 0.87-0.88 for 10-second prediction; an AUC over 0.8 typically warrants further clinical investigation. Our work shows that moderate classification accuracy can be achieved to predict ventricular tachyarrhythmia with machine learning algorithms using HRV features from ICD data. These results provide a realistic view of the practical challenges facing implementation of machine learning algorithms to predict ventricular tachyarrhythmia using HRV data, motivating continued research on improved algorithms and additional features with higher predictive power.
Data from: Long-lasting insecticidal net use and asymptomatic malaria parasitaemia among household members of laboratory-confirmed malaria patients attending selected health facilities in Abuja, Nigeria, 2016: a cross-sectional survey
Introduction: In Nigeria, malaria remains a major burden. There is the presupposition that household members could have common exposure to malaria parasite and use of long-lasting insecticidal net (LLIN) could reduce transmission. This study was conducted to identify factors associated with asymptomatic malaria parasitaemia and LLIN use among households of confirmed malaria patients in Abuja, Nigeria. Methods: A cross-sectional survey was conducted from March to August 2016 in twelve health facilities selected from three area councils in Abuja, Nigeria. Participants were selected using multi-stage sampling technique. Overall, we recruited 602 participants from 107 households linked to 107 malaria patients attending the health facilities. Data on LLIN ownership, utilization, and house characteristics were collected using a semi-structured questionnaire. Blood samples of household members were examined for malaria parasitaemia using microscopy. Data were analyzed using descriptive statistics, Chi-square, and logistic regression (α=0.05). Results: Median age of respondents was 16.5 years (Interquartile range: 23 years); 55.0% were females. Proportions of households that owned and used at least one LLIN were 44.8% and 33.6%, respectively. Parasitaemia was detected in at least one family member of 102 (95.3%) index malaria patients. Prevalence of asymptomatic malaria parasitaemia among study participants was 421/602 (69.9%). No association was found between individual LLIN use and malaria parasitaemia (odds ratio: 0.9, 95% confidence interval (95%CI): 0.6-1.3) among study participants. Having bushes around the homes was associated with having malaria parasitaemia (adjusted OR (aOR): 2.7, 95%CI: 1.7-4.2) and less use of LLIN (aOR: 0.4, 95%CI: 0.2-0.9). Living in Kwali (aOR: 0.1, 95% CI: 0.0-0.2) was associated with less use of LLIN. Conclusion: High prevalence of asymptomatic malaria and low use of LLIN among household members of malaria patients portend the risk of intra-household common source of malaria transmission. We recommend household health education on LLIN use and environmental management. Study to explore the role of preventive treatment of household members of confirmed malaria patient in curbing transmission is suggested. Strategies promoting LLIN use need to be intensified in Kwali.
Data of CP in COVID-19 patients
<p>data source </p>
Data from: Randomized study of the impact of a therapeutic education program on patients suffering from chronic low-back pain who are treated with transcutaneous electrical nerve stimulation
Background: Transcutaneous electrical nerve stimulation (TENS) is often used for the treatment of low-back pain (LBP). However, its effectiveness is controversial. Objective: To determine the efficacy of TENS in the treatment LBP when associated to a therapeutic education program (TEP). Design: Open randomized monocentric study. Setting: University hospital between 2010 and 2014. Patients: A total of 97 patients suffering from LBP. Interventions: Routine care (TENS group) or routine care plus a therapeutic education program (TENS-TEP group) based on consultation support by a pain resource nurse Main outcome measures: EIFEL and Dallas Pain Questionnaire scores. Results: Twenty-two patients (44%) were still assessable at the end-of-study visit, whereas 33 (70%) were assessable at the same time point in the TENS-TEP group (P = 0.013). The EIFEL score and the Dallas score had a similar evolution over time between groups (p = 0.18 and p = 0.50 respectively). Similarly, there were no significant differences between the groups with respect to resting pain scores (p = 0.94 for back pain and p = 0.16 for leg pain) and movement pain scores (p = 0.52 for back pain and p = 0.56 for leg pain). At Month 6, there was no significant difference between the groups (p = 0.85) with regard to analgesics and social impact. Two patients presented a serious adverse event during the study (one in each group) but non-attributable to the treatment studied. Conclusion: This study does not support the use of TENS in the treatment of patients with chronic LBP even though patients benefited from a therapeutic education program by a pain resource nurse. However, the higher number of premature withdrawals in the TENS group may be due to early withdrawal of patients who did not experience improvement of their symptoms.
Data from: Effect of ecological momentary assessment, goal-setting and personalized phone-calls on adherence to interval walking training using the InterWalk application among patients with type 2 diabetes – a pilot randomized controlled trial
Objectives: The objective was to investigate the feasibility and usability of structured text-messages, goal-setting and phone-calls on adherence to a 12-week self-conducted interval walking training (IWT) program, delivered by the InterWalk smartphone among patients with type 2 diabetes (T2D). Methods: In a two-arm pilot randomized controlled trial (Denmark, March 2014 to February 2015), patients with T2D (18-80 years with a Body Mass Index of 18 and 40 kg/m2) were randomly allocated to 12 weeks of IWT with (intervention) or without additional support (control). The primary outcome was the difference between groups in accumulated time of interval walking training across 12 weeks. All patients were encouraged to use the InterWalk application to perform IWT for ≥90 minute/week. Patients in the intervention group made individual goals regarding lifestyle change, received automated text-messages once a week, inquiring about exercise adherence. In case of consistent non-adherence, the patients would receive a phone-call inquiring about the reason for non-adherence. The control group did not receive additional support. Information about training adherence was assessed objectively. Usability of structured text-messages was assessed based on response rates and self-reported satisfaction after 12-weeks. Results: Thirty-seven patients with T2D (66 years, 65% female, hemoglobin 1Ac 50.3 mmol/mol) where included (n=18 and n=19 in intervention and control group, respectively). The retention rate was 83%. The intervention group accumulated [95%CI] 345 -7, 698 minutes of IWT more than the control group. The response rate for the text-messages was 83% (68% for males and 90% for females). Forty-one percent of the intervention and 25% of the control group were very satisfied with their participation. Conclusion: The combination of structured text-messages, goal-setting with the possibility of follow-up phone calls are considered feasible interventions to attain training adherence when using the InterWalk app during a 12-week period in patients with T2D. Some uncertainty about the effect size of adherence remains.
Data from: Economic costs and health-related quality of life for hand, foot and mouth disease (HFMD) patients in China
Background: Hand, foot and mouth disease (HFMD) is a common illness in China that mainly affects infants and children. The objective of this study is to assess the economic cost and health-related quality of life associated with HFMD in China. Method: A telephone survey of caregivers were conducted in 31 provinces across China. Caregivers of laboratory-confirmed HFMD patients who were registered in the national HFMD enhanced surveillance database during 2012-2013 were invited to participate in the survey. Total costs included direct medical costs (outpatient care, inpatient care and self-medication), direct non-medical costs (transportation, nutrition, accommodation and nursery), and indirect costs for lost income associated with caregiving. Health utility weights elicited using EuroQol EQ-5D-3L and EQ-Visual Analogue Scale (VAS) were used to calculate associated loss in quality adjusted life years (QALYs). Results: The subjects comprised 1136 mild outpatients, 1124 mild inpatients, 1170 severe cases and 61 fatal cases. The mean total costs for mild outpatients, mild inpatients, severe cases and fatal cases were $201 (95%CI $187, $215), $1072 (95%CI $999, $1144), $3051 (95%CI $2905, $3197) and $2819 (95%CI $2068, $3571) respectively. The mean QALY losses per HFMD episode for mild outpatients, mild inpatients and severe cases were 3.6 (95%CI 3.4, 3,9), 6.9 (95%CI 6.4, 7.4) and 13.7 (95%CI 12.9, 14.5) per 1000 persons. Cases who were diagnosed with EV-A71 infection and had longer duration of illness were associated with higher total cost and QALY loss. Conclusion: HFMD poses a high economic and health burden in China. Our results provide economic and health utility data for cost-effectiveness analysis for HFMD vaccination in China.
Data from: Quantifying patient preferences for symptomatic breast clinic referral: a decision analysis study
Objectives: Decision analysis study that incorporates patient preferences and probability estimates to investigate the impact of women's preferences for referral or an alternative strategy of watchful waiting if faced with symptoms that could be due to breast cancer. Setting: Community-based study. Participants: Asymptomatic women aged 30-60 years. Interventions: Participants were presented with 11 health scenarios that represent the possible consequences of symptomatic breast problems. Participants were asked the risk of death that they were willing to take in order to avoid the health scenario using the standard gamble (SG) utility method. This process was repeated for all 11 health scenarios. Formal decision analysis for the preferred individual decision was then estimated for each participant. Primary outcome measure: The preferred diagnostic strategy, either watchful waiting or referral to a breast clinic. Sensitivity analysis was used to examine how each varied according to changes in the probabilities of the health scenarios. Results: A total of 35 participants completed the interviews, with median age 41 years (Interquartile range 35 to 47 years). The majority of the study sample were employed (n=32, 91.4%), with a third-level (university) education (n=32, 91.4%) and with knowledge of someone with breast cancer (n=30, 85.7%). When individual preferences were accounted for, 25 (71.4%) patients preferred watchful waiting to referral for triple assessment as their preferred initial diagnostic strategy. Sensitivity analysis shows that referral for triple assessment becomes the dominant strategy at the upper probability estimate (18%) of breast cancer in the community. Conclusions: Watchful waiting is an acceptable strategy for most women who present to their GP with breast symptoms. These findings suggest that current referral guidelines should take more explicit account of women's preferences in relation in terms of the initial diagnostic strategy for symptomatic breast problems.
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.