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opencc-zeroDec 2014View details →

Data from: Comparison of methodological quality of positive versus negative comparative studies published in Indian medical journals: a systematic review

Objectives: Published negative studies should have the same rigour of methodological quality as studies with positive findings. However, the methodological quality of negative versus positive studies is not known. The objective was to assess the reported methodological quality of positive versus negative studies published in Indian medical journals. Design: A systematic review (SR) was performed of all comparative studies published in Indian medical journals with a clinical science focus and impact factor >1 between 2011 and 2013. The methodological quality of randomised controlled trials (RCTs) was assessed using the Cochrane risk of bias tool, and the Newcastle-Ottawa scale for observational studies. The results were considered positive if the primary outcome was statistically significant and negative otherwise. When the primary outcome was not specified, we used data on the first outcome reported in the history followed by the results section. Differences in various methodological quality domains between positive versus negative studies were assessed by Fisher's exact test. Results: Seven journals with 259 comparative studies were included in this SR. 24% (63/259) were RCTs, 24% (63/259) cohort studies, and 49% (128/259) case–control studies. 53% (137/259) of studies explicitly reported the primary outcome. Five studies did not report sufficient data to enable us to determine if results were positive or negative. Statistical significance was determined by p value in 78.3% (199/254), CI in 2.8% (7/254), both p value and CI in 11.8% (30/254), and only descriptive in 6.3% (16/254) of studies. The overall methodological quality was poor and no statistically significant differences between reporting of methodological quality were detected between studies with positive versus negative findings. Conclusions: There was no difference in the reported methodological quality of positive versus negative studies. However, the uneven reporting of positive versus negative studies (72% vs 28%) indicates a publication bias in Indian medical journals with an impact factor of >1.

opencc-zeroDec 2012View details →

Data from: Specialty choice in times of economic crisis: a cross-sectional survey of Spanish medical students

Objective: To investigate the determinants of specialty choice among graduating medical students in Spain, a country that entered into a severe, ongoing economic crisis in 2008. Setting: Since 2008, the percentage of Spanish medical school graduates electing Family and Community Medicine (FCM) has experienced a reversal after more than a decade of decline. Design: A nationwide cross-sectional survey conducted online in April 2011. Participants: We invited all students in their final year before graduation from each of Spain's 27 public and private medical schools to participate. Main outcome measures: Respondents' preferred specialty in relation to their perceptions of: (1) the probability of obtaining employment; (2) lifestyle and work hours; (3) recognition by patients; (4) prestige among colleagues; (5) opportunity for professional development; (6) annual remuneration and (7) the proportion of the physician's compensation from private practice. Results: 978 medical students (25% of the nationwide population of students in their final year) participated. Perceived job availability had the largest impact on specialty preference. Each 10% increment in the probability of obtaining employment increased the odds of preferring a specialty by 33.7% (95% CI 27.2% to 40.5%). Job availability was four times as important as compensation from private practice in determining specialty choice (95% CI 1.7 to 6.8). We observed considerable heterogeneity in the influence of lifestyle and work hours, with students who preferred such specialties as Cardiovascular Surgery and Obstetrics and Gynaecology valuing longer rather than shorter workdays. Conclusions: In the midst of an ongoing economic crisis, job availability has assumed critical importance as a determinant of specialty preference among Spanish medical students. In view of the shortage of practitioners of FCM, public policies that take advantage of the enhanced perceived job availability of FCM may help steer medical school graduates into this specialty.

opencc-zeroDec 2013View details →

Data from: The active participation of German-speaking countries in conferences of the Association for Medical Education in Europe (AMEE) between 2005 and 2013: a reflection of the development of medical education research?

Objectives: Medical education is gaining in significance internationally. A growing interest in the field has been observed in German-speaking countries (Austria, Germany, Switzerland) since the early 2000s. This interest is not, however, reflected in an increase in the number of publications on medical education of German-speaking authors in international professional journals. The following investigation examines the potential use of active participant numbers of German-speaking researchers at AMEE conferences as a means of measuring said development. Methods: The AMEE conference proceedings from the categories poster presentations, short communications, research papers and plenary presentations from the years 2005-2013 were examined for evidence of Austrian, German and Swiss participation. The abstracts were subsequently analysed in terms of content and categorised according to study design, methodology, object of study, and research topic. Results: Of the 9,446 analysed abstracts, 549 contributions show at least one first, last or co-author from Austria, Germany or Switzerland. The absolute number of contributions per conference varied between 44 in 2010 and 77 in 2013. The percentage fluctuated between 10% in 2005 and 4.1% in 2010. From the year 2010 onwards, however, participation increased continually. The research was predominantly descriptive (62.7%). Studies on fundamental questions of teaching and learning (clarification studies) were less frequent (4.0%). For the most part, quantitative methods (51.9%) were implemented in addressing subjects such as learning and teaching methods (33%), evaluation and assessment (22.4%) or curriculum development (14.4%). The study population was usually comprised of students (52.5%). Conclusions: The number of contributions from Austria, Germany and Switzerland peak at the beginning and at the end of the evaluated period of time. A continual increase in active participation since 2005 was not observed. These observations do not reflect the actual increase of interest in medical education research in German-speaking countries.

opencc-zeroDec 2017View details →

Data from: Estimation of inhalation flow profile using audio-based methods to assess inhaler medication adherence

Asthma and chronic obstructive pulmonary disease (COPD) patients are required to inhale forcefully and deeply to receive medication when using a dry powder inhaler (DPI). There is a clinical need to objectively monitor the inhalation flow profile of DPIs in order to remotely monitor patient inhalation technique. Audio-based methods have been previously employed to accurately estimate flow parameters such as the peak inspiratory flow rate of inhalations, however, these methods required multiple calibration inhalation audio recordings. In this study, an audio-based method is presented that accurately estimates inhalation flow profile using only one calibration inhalation audio recording. Twenty healthy participants were asked to perform 15 inhalations through a placebo Ellipta™ DPI at a range of inspiratory flow rates. Inhalation flow signals were recorded using a pneumotachograph spirometer while inhalation audio signals were recorded simultaneously using the Inhaler Compliance Assessment device attached to the inhaler. The acoustic (amplitude) envelope was estimated from each inhalation audio signal. Using only one recording, linear and power law regression models were employed to determine which model best described the relationship between the inhalation acoustic envelope and flow signal. Each model was then employed to estimate the flow signals of the remaining 14 inhalation audio recordings. This process repeated until each of the 15 recordings were employed to calibrate single models while testing on the remaining 14 recordings. It was observed that power law models generated the highest average flow estimation accuracy across all participants (90.89±0.9% for power law models and 76.63±2.38% for linear models). The method also generated sufficient accuracy in estimating inhalation parameters such as peak inspiratory flow rate and inspiratory capacity within the presence of noise. Estimating inhaler inhalation flow profiles using audio based methods may be clinically beneficial for inhaler technique training and the remote monitoring of patient adherence.

zenodo24/100

Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation (Unlabeled Data Part III)

Despite the considerable progress in automatic abdominal multi-organ segmentation from CT/MRI scans in recent years, a comprehensive evaluation of the models' capabilities is hampered by the lack of a large-scale benchmark from diverse clinical scenarios. Constraint by the high cost of collecting and labeling 3D medical data, most of the deep learning models to date are driven by datasets with a limited number of organs of interest or samples, which still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of various methods. To mitigate the limitations, we present AMOS, a large-scale, diverse, clinical dataset for abdominal organ segmentation. AMOS provides 500 CT and 100 MRI scans collected from multi-center, multi-vendor, multi-modality, multi-phase, multi-disease patients, each with voxel-level annotations of 15 abdominal organs, providing challenging examples and test-bed for studying robust segmentation algorithms under diverse targets and scenarios. We further benchmark several state-of-the-art medical segmentation models to evaluate the status of the existing methods on this new challenging dataset. We have made our datasets, benchmark servers, and baselines publicly available, and hope to inspire future research. The paper can be found at https://arxiv.org/pdf/2206.08023.pdf In addition to providing the labeled 600 CT and MRI scans, we expect to provide 2000 CT and 1200 MRI scans without labels to support more learning tasks (semi-supervised, un-supervised, domain adaption, ...). The link can be found in: <ul> <li><a href="https://zenodo.org/deposit/7262581">labeled data (500CT+100MRI)</a></li> <li><a href="https://zenodo.org/record/7262757#.Y2iSQ9JBwYs">unlabeled data Part I (900CT)</a></li> <li><a href="https://zenodo.org/record/7295661#.Y2iR_9JBwYs">unlabeled data Part II (1100CT)</a> (Now there are 1000CT, we will replenish to 1100CT)</li> <li><a href="https://zenodo.org/record/7295816">unlabeled data Part III (1200MRI)</a></li> </ul> if you found this dataset useful for your research, please cite: <blockquote> <pre>@article{ji2022amos, title={AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation}, author={Ji, Yuanfeng and Bai, Haotian and Yang, Jie and Ge, Chongjian and Zhu, Ye and Zhang, Ruimao and Li, Zhen and Zhang, Lingyan and Ma, Wanling and Wan, Xiang and others}, journal={arXiv preprint arXiv:2206.08023}, year={2022} }</pre> </blockquote>

opencc-by-4.0Oct 2022View details →

Construction of Perioperative Medical Data Platform and Its Typical Practice to Predict Postoperative Acute Moderate to Severe Pain With Machine Learning Models

ClinicalTrials.gov study NCT05569460. IPD Sharing: NO. Countries: 1. Publications: 0.

Clinical and Economic Impact of an Electronic Medical Record Interfaced Decision Support System Reinforced With Patient Specific Pharmacogenetic Data for Minimizing Severe Drug-Drug Interactions

ClinicalTrials.gov study NCT01765621. IPD Sharing: Not stated. Countries: 1. Publications: 0.

A Collection of Vital Status and Pulmonary Medication Usage Data for Patients With Chronic Obstructive Pulmonary Disease (COPD) Who Withdrew Prematurely From Tiotropium Inhalation Solution Delivered b

ClinicalTrials.gov study NCT02172560. IPD Sharing: Not stated. Countries: 3. Publications: 0.

Drug Use Investigation Of Effexor (SECONDARY DATA COLLECTION STUDY; SAFETY AND EFFICACY OF EFFEXOR.UNDER JAPANESE MEDICAL PRACTICE)

ClinicalTrials.gov study NCT02958527. IPD Sharing: NO. Countries: 0. Publications: 0.

Biospecimen and Medical Data Collection and Tumor Biopsy in Creating Research Tissue Registry in Patients With Inflammatory or Invasive Breast Cancer

ClinicalTrials.gov study NCT00477100. IPD Sharing: Not stated. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →

Retrospective Analysis of Real-world Data From Medical Records on the Use of MENOPUR for Infertility Treatment

ClinicalTrials.gov study NCT04814940. IPD Sharing: YES. Countries: 1. Publications: 0.

Morphometric Study of the Legs and Feet of Diabetic Patients in Order to Collect Data Intended to be Used to Measure by Dynamometry the Pressures Exerted by Several Medical Compression Socks at the Le

ClinicalTrials.gov study NCT05594446. IPD Sharing: NO. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →

ASA Prediction Using Health Data and Medication Use

ClinicalTrials.gov study NCT06629350. IPD Sharing: YES. Countries: 1. Publications: 0.

Medical Data Collection for the Evaluation of Radiofrequency Ablation and Cement Augmentation for the Treatment of Secondary Metastases to the Spine

ClinicalTrials.gov study NCT04751422. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Retrospective Study on Data Aiming to Establish a Prediction Score for Return Home at the Time of Admission to a Multidisciplinary Medical Department (SCORDOM

ClinicalTrials.gov study NCT06288295. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Testing the Implementation of a Toolbox to Optimize Data Collection and Data Quality of the National Medical Quality Indicators in Long-term Care Facilities: a Pilot Study. (NIP-Q-UPGRADE Subaim 1.8)

ClinicalTrials.gov study NCT06848725. IPD Sharing: NO. Countries: 1. Publications: 0.