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Update — December 7, 2014. – Evidence-based medicine (EBM) is not working for many reasons, for example: 1. Incorrect in their foundations (paradox): hierarchical levels of evidence are supported by opinions (i.e., lowest strength of evidence according to EBM) instead of real data collected from different types of study designs (i.e., evidence). http://dx.doi.org/10.6084/m9.figshare.1122534 2. The effect of criminal practices by pharmaceutical companies is only possible because of the complicity of others: healthcare systems, professional associations, governmental and academic institutions. Pharmaceutical companies also corrupt at the personal level, politicians and political parties are on their payroll, medical professionals seduced by different types of gifts in exchange of prescriptions (i.e., bribery) which very likely results in patients not receiving the proper treatment for their disease, many times there is no such thing: healthy persons not needing pharmacological treatments of any kind are constantly misdiagnosed and treated with unnecessary drugs. Some medical professionals are converted in K.O.L. which is only a puppet appearing on stage to spread lies to their peers, a person supposedly trained to improve the well-being of others, now deceits on behalf of pharmaceutical companies. Probably the saddest thing is that many honest doctors are being misled by these lies created by the rules of pharmaceutical marketing instead of scientific, medical, and ethical principles. Interpretation of EBM in this context was not anticipated by their creators. “The main reason we take so many drugs is that drug companies don’t sell drugs, they sell lies about drugs.” ―Peter C. Gøtzsche “doctors and their organisations should recognise that it is unethical to receive money that has been earned in part through crimes that have harmed those people whose interests doctors are expected to take care of. Many crimes would be impossible to carry out if doctors weren’t willing to participate in them.” —Peter C Gøtzsche, The BMJ, 2012, Big pharma often commits corporate crime, and this must be stopped. Pending (Colombia): Health Promoter Entities (In Spanish: EPS ―Empresas Promotoras de Salud).

1. Misinterpretations New technologies or concepts are difficult to understand in the beginning, it doesn’t matter their simplicity, we need to get used to new tools aimed to improve our professional practice. Probably the best explanation is here in these videos (credits to Antonio Villafaina for sharing these videos with me). English https://www.youtube.com/watch?v=pQHX-SjgQvQ&w=420&h=315 Spanish https://www.youtube.com/watch?v=DApozQBrlhU&w=420&h=315 ----------------------- Hypothesis: hierarchical levels of evidence based medicine are wrong Dear Editor, I have data to support the hypothesis described in the title of this letter. Before rejecting the null hypothesis I would like to ask the following open question:Could you support with data that hierarchical levels of evidence based medicine are correct? (1,2) Additional explanation to this question: – Only respond to this question attaching publicly available raw data.– Be aware that more than a question this is a challenge: I have data (i.e., evidence) which is contrary to classic (i.e., McMaster) or current (i.e., Oxford) hierarchical levels of evidence based medicine. An important part of this data (but not all) is publicly available. References
2. Ramirez, Jorge H (2014): The EBM challenge. figshare. http://dx.doi.org/10.6084/m9.figshare.1135873
3. The EBM Challenge Day 1: No Answers. Competing interests: I endorse the principles of open data in human biomedical research Read this letter on The BMJ – August 13, 2014.http://www.bmj.com/content/348/bmj.g3725/rr/762595Re: Greenhalgh T, et al. Evidence based medicine: a movement in crisis? BMJ 2014; 348: g3725. _ Fileset contents Raw data: Excel archive: Raw data, interactive figures, and PubMed search terms. Google Spreadsheet is also available (URL below the article description). Figure 1. Unadjusted (Fig 1A) and adjusted (Fig 1B) PubMed publication trends (01/01/1992 to 30/06/2014). Figure 2. Adjusted PubMed publication trends (07/01/2008 to 29/06/2014) Figure 3. Google search trends: Jan 2004 to Jun 2014 / 1-week periods. Figure 4. PubMed publication trends (1962-2013) systematic reviews and meta-analysis, clinical trials, and observational studies.
   Figure 5. Ramirez, Jorge H (2014): Infographics: Unpublished US phase 3 clinical trials (2002-2014) completed before Jan 2011 = 50.8%. figshare.http://dx.doi.org/10.6084/m9.figshare.1121675 Raw data: "13377 studies found for: Completed | Interventional Studies | Phase 3 | received from 01/01/2002 to 01/01/2014 | Worldwide". This database complies with the terms and conditions of ClinicalTrials.gov: http://clinicaltrials.gov/ct2/about-site/terms-conditions Supplementary Figures (S1-S6). PubMed publication delay in the indexation processes does not explain the descending trends in the scientific output of evidence-based medicine. Acknowledgments I would like to acknowledge the following persons for providing valuable concepts in data visualization and infographics:
4. Maria Fernanda Ramírez. Professor of graphic design. Universidad del Valle. Cali, Colombia.
5. Lorena Franco. Graphic design student. Universidad del Valle. Cali, Colombia. Related articles by this author (Jorge H. Ramírez)
6. Ramirez JH. Lack of transparency in clinical trials: a call for action. Colomb Med (Cali) 2013;44(4):243-6. URL: http://www.ncbi.nlm.nih.gov/pubmed/24892242
7. Ramirez JH. Re: Evidence based medicine is broken (17 June 2014). http://www.bmj.com/node/759181
8. Ramirez JH. Re: Global rules for global health: why we need an independent, impartial WHO (19 June 2014). http://www.bmj.com/node/759151
9. Ramirez JH. PubMed publication trends (1992 to 2014): evidence based medicine and clinical practice guidelines (04 July 2014). http://www.bmj.com/content/348/bmj.g3725/rr/759895 Recommended articles
10. Greenhalgh Trisha, Howick Jeremy,Maskrey Neal. Evidence based medicine: a movement in crisis? BMJ 2014;348:g3725
11. Spence Des. Evidence based medicine is broken BMJ 2014; 348:g22
12. Schünemann Holger J, Oxman Andrew D,Brozek Jan, Glasziou Paul, JaeschkeRoman, Vist Gunn E et al. Grading quality of evidence and strength of recommendations for diagnostic tests and strategies BMJ 2008; 336:1106
13. Lau Joseph, Ioannidis John P A, TerrinNorma, Schmid Christopher H, OlkinIngram. The case of the misleading funnel plot BMJ 2006; 333:597
14. Moynihan R, Henry D, Moons KGM (2014) Using Evidence to Combat Overdiagnosis and Overtreatment: Evaluating Treatments, Tests, and Disease Definitions in the Time of Too Much. PLoS Med 11(7): e1001655. doi:10.1371/journal.pmed.1001655
15. Katz D. A-holistic view of evidence based medicinehttp://thehealthcareblog.com/blog/2014/05/02/a-holistic-view-of-evidence-based-medicine/ ---

BackgroundQuality of reporting for Randomized Clinical Trials (RCTs) in oncology was analyzed in several systematic reviews, but, in this setting, there is paucity of data for the outcomes definitions and consistency of reporting for statistical tests in RCTs and Observational Studies (OBS). The objective of this review was to describe those two reporting aspects, for OBS and RCTs in oncology.MethodsFrom a list of 19 medical journals, three were retained for analysis, after a random selection: British Medical Journal (BMJ), Annals of Oncology (AoO) and British Journal of Cancer (BJC). All original articles published between March 2009 and March 2014 were screened. Only studies whose main outcome was accompanied by a corresponding statistical test were included in the analysis. Studies based on censored data were excluded. Primary outcome was to assess quality of reporting for description of primary outcome measure in RCTs and of variables of interest in OBS. A logistic regression was performed to identify covariates of studies potentially associated with concordance of tests between Methods and Results parts.Results826 studies were included in the review, and 698 were OBS. Variables were described in Methods section for all OBS studies and primary endpoint was clearly detailed in Methods section for 109 RCTs (85.2%). 295 OBS (42.2%) and 43 RCTs (33.6%) had perfect agreement for reported statistical test between Methods and Results parts. In multivariable analysis, variable "number of included patients in study" was associated with test consistency: aOR (adjusted Odds Ratio) for third group compared to first group was equal to: aOR Grp3 = 0.52 0.31–0.89.ConclusionVariables in OBS and primary endpoint in RCTs are reported and described with a high frequency. However, statistical tests consistency between methods and Results sections of OBS is not always noted. Therefore, we encourage authors and peer reviewers to verify consistency of statistical tests in oncology studies.

Objectives: To analyse the total number of newspaper articles citing the four leading general medical journals and to describe national citation patterns. Design: Quantitative content analysis Setting/sample: Full text of 22 general newspapers in 14 countries over the period 2008-2015, collected from LexisNexis. The 14 countries have been categorized into four regions: US, UK, Western World (EU countries other than UK, and Australia, New Zealand and Canada) and Rest of the World (other countries). Main outcome measure: Press citations of four medical journals (two American: NEJM and JAMA; and two British: The Lancet and The BMJ) in 22 newspapers. Results: British and American newspapers cited some of the four analysed medical journals about three times a week in 2008-2015 (weekly mean 3.2 and 2.7 citations respectively); the newspapers from other Western countries did so about once a week (weekly mean 1.1), and those from the Rest of the World cited them about once a month (monthly mean 1.1). The New York Times cited above all other newspapers (weekly mean 4.7). The analysis showed the existence of three national citation patterns in the daily press: American newspapers cited mostly American journals (70.0% of citations), British newspapers cited mostly British journals (86.5%), and the rest of the analysed press cited more British journals than American ones. The Lancet was the most cited journal in the press of almost all Western countries outside the US and the UK. Multivariate correspondence analysis confirmed the national patterns and showed that over 85% of the citation data variability is retained in just one single new variable: the national dimension. Conclusion: British and American newspapers are the ones that cite the four analysed medical journals more often, showing a domestic preference for their respective national journals; non-British and non-American newspapers show a common international citation pattern.

Data from BMJ Open paper "Time to publication for publicly funded clinical trials in Australia: An observational study"Data for 77 funded randomised controlled trials. Data updated 31 January 2016.Variables:members = number of investigatorsmoney = funding awarded ($AUD); scrambled by -/+ $1000funding.years= length of funding in yearsestsampsize = estimated sample size (some missing)time.from.funding.prot = time in years from funding until protocol paper was published (or censored)protocolpaper.event = protocol paper published (1=yes, 0=censored)time.from.funding = time in years from funding until main paper was published (or censored) mainpaper.event =mainpaper published (1=yes, 0=censored)

Background and ObjectiveResearch collaborations in biomedical research have evolved over time. No studies have addressed research collaboration in network meta-analysis (NMA). In this study, we used social network analysis methods to characterize global collaboration patterns of published NMAs over the past decades.MethodsPubMed, EMBASE, Web of Science and the Cochrane Library were searched (at 9th July, 2015) to include systematic reviews incorporating NMA. Two reviewers independently selected studies and cross-checked the standardized data. Data was analyzed using Ucinet 6.0 and SPSS 17.0. NetDraw software was used to draw social networks.Results771 NMAs published in 336 journals from 3459 authors and 1258 institutions in 49 countries through the period 1997–2015 were included. More than three-quarters (n = 625; 81.06%) of the NMAs were published in the last 5-years. The BMJ (4.93%), Current Medical Research and Opinion (4.67%) and PLOS One (4.02%) were the journals that published the greatest number of NMAs. The UK and the USA (followed by Canada, China, the Netherlands, Italy and Germany) headed the absolute global productivity ranking in number of NMAs. The top 20 authors and institutions with the highest publication rates were identified. Overall, 43 clusters of authors (four major groups: one with 37 members, one with 12 members, one with 11 members and one with 10 members) and 21 clusters of institutions (two major groups: one with 62 members and one with 20 members) were identified. The most prolific authors were affiliated with academic institutions and private consulting firms. 181 consulting firms and pharmaceutical industries (14.39% of institutions) were involved in 199 NMAs (25.81% of total publications). Although there were increases in international and inter-institution collaborations, the research collaboration by authors, institutions and countries were still weak and most collaboration groups were small sizes.ConclusionScientific production on NMA is increasing worldwide with research leadership of Western countries (most notably, the UK, the USA and Canada). More authors, institutions and nations are becoming involved in research collaborations, but frequently with limited international collaborations.

This database contains tobacco consumption data from 1970-2015 collected through a systematic search coupled with consultation with country and subject-matter experts. Data quality appraisal was conducted by at least two research team members in duplicate, with greater weight given to official government sources. All data was standardized into units of cigarettes consumed and a detailed accounting of data quality and sourcing was prepared. Data was found for 82 of 214 countries for which searches for national cigarette consumption data were conducted, representing over 95% of global cigarette consumption and 85% of the world’s population. Cigarette consumption fell in most countries over the past three decades but trends in country specific consumption were highly variable. For example, China consumed 2.5 million metric tonnes (MMT) of cigarettes in 2013, more than Russia (0.36 MMT), the United States (0.28 MMT), Indonesia (0.28 MMT), Japan (0.20 MMT), and the next 35 highest consuming countries combined. The US and Japan achieved reductions of more than 0.1 MMT from a decade earlier, whereas Russian consumption plateaued, and Chinese and Indonesian consumption increased by 0.75 MMT and 0.1 MMT, respectively. These data generally concord with modelled country level data from the Institute for Health Metrics and Evaluation and have the additional advantage of not smoothing year-over-year discontinuities that are necessary for robust quasi-experimental impact evaluations. Before this study, publicly available data on cigarette consumption have been limited—either inappropriate for quasi-experimental impact evaluations (modelled data), held privately by companies (proprietary data), or widely dispersed across many national statistical agencies and research organisations (disaggregated data). This new dataset confirms that cigarette consumption has decreased in most countries over the past three decades, but that secular country specific consumption trends are highly variable. The findings underscore the need for more robust processes in data reporting, ideally built into international legal instruments or other mandated processes. To monitor the impact of the WHO Framework Convention on Tobacco Control and other tobacco control interventions, data on national tobacco production, trade, and sales should be routinely collected and openly reported. The first use of this database for a quasi-experimental impact evaluation of the WHO Framework Convention on Tobacco Control is: Hoffman SJ, Poirier MJP, Katwyk SRV, Baral P, Sritharan L. Impact of the WHO Framework Convention on Tobacco Control on global cigarette consumption: quasi-experimental evaluations using interrupted time series analysis and in-sample forecast event modelling. BMJ. 2019 Jun 19;365:l2287. doi: https://doi.org/10.1136/bmj.l2287 Another use of this database was to systematically code and classify longitudinal cigarette consumption trajectories in European countries since 1970 in: Poirier MJ, Lin G, Watson LK, Hoffman SJ. Classifying European cigarette consumption trajectories from 1970 to 2015. Tobacco Control. 2022 Jan. DOI: 10.1136/tobaccocontrol-2021-056627. Statement of Contributions: Conceived the study: GEG, SJH Identified multi-country datasets: GEG, MP Extracted data from multi-country datasets: MP Quality assessment of data: MP, GEG Selection of data for final analysis: MP, GEG Data cleaning and management: MP, GL Internet searches: MP (English, French, Spanish, Portuguese), GEG (English, French), MYS (Chinese), SKA (Persian), SFK (Arabic); AG, EG, BL, MM, YM, NN, EN, HR, KV, CW, and JW (English), GL (English) Identification of key informants: GEG, GP Project Management: LS, JM, MP, SJH, GEG Contacts with Statistical Agencies: MP, GEG, MYS, SKA, SFK, GP, BL, MM, YM, NN, HR, KV, JW, GL Contacts with key informants: GEG, MP, GP, MYS, GP Funding: GEG, SJH SJH: Hoffman, SJ; JM: Mammone J; SRVK: Rogers Van Katwyk, S; LS: Sritharan, L; MT: Tran, M; SAK: Al-Khateeb, S; AG: Grjibovski, A.; EG: Gunn, E; SKA: Kamali-Anaraki, S; BL: Li, B; MM: Mahendren, M; YM: Mansoor, Y; NN: Natt, N; EN: Nwokoro, E; HR: Randhawa, H; MYS: Yunju Song, M; KV: Vercammen, K; CW: Wang, C; JW: Woo, J; MJPP: Poirier, MJP; GEG: Guindon, EG; GP: Paraje, G; GL Gigi Lin Key informants who provided data: Corne van Walbeek (South Africa, Jamaica) Frank Chaloupka (US) Ayda Yurekli (Turkey) Dardo Curti (Uruguay) Bungon Ritthiphakdee (Thailand) Jakub Lobaszewski (Poland) Guillermo Paraje (Chile, Argentina) Key informants who provided useful insights: Carlos Manuel Guerrero López (Mexico) Muhammad Jami Husain (Bangladesh) Nigar Nargis (Bangladesh) Rijo M John (India) Evan Blecher (Nigeria, Indonesia, Philippines, South Africa) Yagya Karki (Nepal) Anne CK Quah (Malaysia) Nery Suarez Lugo (Cuba) Agencies providing assistance: Iranian Tobacco Co. Institut National de la Statistique (Tunisia) HM Revenue & Customs (UK) Eidgenössisches Finanzdepartement EFD/Département...

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Objective: To evaluate the accuracy of a 2015 cross-sectional analysis published in the BMJ Open which reported that pharmaceutical industry compliance with clinical trial registration and results reporting requirements under United States law was suboptimal and varied widely among companies. Design: We performed a re-assessment of the data reported in Miller et al. to evaluate whether statutory compliance analyses and conclusions were valid. Data Sources: Information from the Dryad Digital Repository, ClinicalTrials.gov, Drugs@FDA, and direct communications with sponsors. Main outcome measures: Compliance with the clinical trial registration and results reporting requirements under the Food and Drug Administration Amendments Act (FDAAA). Results: Industry compliance with FDAAA disclosure requirements was notably higher than reported by Miller et al. Among trials subject to FDAAA, Miller et al. reported that, per drug, a median of 67% (middle 50% range: 0–100%) of trials were fully compliant with registration and results reporting requirements. Upon re-analysis of the data, we found that a median of 100% (middle 50% range: 93–100%) of clinical trials for a particular drug fully complied with the law. When looking at overall compliance at the trial level, our re-assessment yields 94% timely registration and 90% timely results reporting among the 49 eligible trials, and an overall FDAAA compliance rate of 86%. Conclusions: The claim by Miller et al. that industry compliance is below legal standards is based on an analysis that relies upon an incomplete dataset and an interpretation of FDAAA that requires disclosure of study results for drugs that have not yet been approved for any indication. Upon re-analysis using a different interpretation of FDAAA that focuses on whether results were disclosed within 30 days of drug approval, we found that industry compliance with U.S. statutory disclosure requirements for the 15 reviewed drugs was consistently high.

The datasets reports baseline and outcome data from the 'Geriatric CO-mAnagement for Cardiology patients in the Hospital (G-COACH)' experimental study. The study evaluated the effectiveness of a geriatric co-management programme on the cardiac care units of the University Hospitals Leuven. Sample included patients aged 75 years or older. Measurements included: demographic, functional status, cognitive status, depressive symptoms, anxiety symptoms, quality of life, physical performance, readmission rates, survival.

Please see Word document for more information.

Please see protocols for more information:

https://clinicaltrials.gov/ct2/show/NCT02890927

https://bmjopen.bmj.com/content/8/10/e023593

The evaluation study is available at https://agsjournals.onlinelibrary.wiley.com/doi/full/10.1111/jgs.17093

Objective: To assess adherence to The Consolidated Standards of Reporting Trials (CONSORT) for Abstracts by five high-impact general medical journals and to assess whether quality of reporting was homogeneous across these journals. Design: Descriptive, cross-sectional study. Setting: Randomized Controlled Trial (RCT) abstracts in five high-impact general medical journals. Participants: We used up to 100 RCT abstracts published between 2011 and 2014 from each of the following journals: The New England Journal of Medicine (NEJM), the Annals of Internal Medicine (Annals IM), The Lancet, the British Medical Journal (The BMJ), and the Journal of the American Medical Association (JAMA). Main Outcome: The primary outcome was percent overall adherence to the 19-item CONSORT for abstracts checklist. Secondary outcomes included percent adherence in checklist subcategories and assessing homogeneity of reporting quality across the individual journals. Results: Search results yielded 466 abstracts, three of which were later excluded as they were not RCTs. Analysis was performed on 463 abstracts (97 from NEJM, 66 from Annals IM, 100 from The Lancet, 100 from The BMJ, 100 from JAMA). Analysis of all scored items showed an overall adherence of 67% (95% CI, 66-68%) to the CONSORT for Abstracts checklist. The Lancet had the highest overall adherence rate (78%; 95% CI, 76-80%) while NEJM had the lowest (55%; 95% CI, 53-57%). Adherence rates to eight of the checklist items differed by greater than 25% between journals. Conclusion: Among the five highest-impact general medical journals, there is variable and incomplete adherence to the CONSORT for Abstracts reporting checklist of randomized trials, with substantial differences between individual journals. Lack of adherence to the CONSORT for Abstracts reporting checklist by high-impact medical journals impedes critical appraisal of important studies. We recommend diligent assessment of adherence to reporting guidelines by authors, reviewers, and editors to promote transparency and unbiased reporting of abstracts.

AbstractObjectives: To assess feasibility, acceptability, and clinical sensibility of a novel survey, the Advance Care Planning (ACP) Engagement Survey in various health care settings. Setting: A target sample of 50 patients from each of primary care, hospital, cancer care, and dialysis care settings. Participants: A convenience sample of patients without cognitive impairment who could speak and read English was recruited. Patients 50 years and older were eligible in primary care; patients 80 and older or 55 years and older with clinical markers of advanced chronic disease were recruited in hospital; patients aged 19 and older were recruited in cancer and renal dialysis centres. Outcomes: We assessed feasibility, acceptability and clinical sensibility of the ACP Engagement Survey using a 6-point scale. The ACP Engagement Survey measures ACP processes (knowledge, contemplation, self-efficacy, readiness) on 5-point Likert scales and actions (yes/no). Results: 196 patients (38 to 96 years old, 50.5% women) participated. Mean (±standard deviation) time to administer was 48.8 ±19.6 minutes. Mean acceptability scores ranged from 3.2±1.3 in hospital to 4.7±0.9 in primary care and mean relevance ranged from 3.5±1.0 in hospital to 4.9±0.9 in dialysis centres (p values <0.001 for both). The mean process score was 3.1±0.6 and the mean action score was 11.2±5.6 (of a possible 25). Conclusions: The ACP Engagement Survey demonstrated feasibility and acceptability in out-patient settings, but was less feasible and acceptable among hospitalized patients due to length. A shorter version may improve feasibility. Engagement in ACP was low to moderate. Usage notesREADMEThe Readme file includes a list of files in this data package, and a description of the variables that were removed from the dataset to protect participant identity. Please see the "Data dictionary" for a description of the variables that were included in the dataset, and the "Summary table of indirect identifier data" for a summary of values reported at removed variables.Data Dictionary - Canadian ACP engagement sample BMJ OpenThis file describes the variables that were included in the dataset, and their allowable values.Canadian ACP engagement sample BMJ Open_data dictionary.xlsxCanadian ACP engagement survey pilotThis file contains the responses of 196 patients in acute care, primary care, cancer care and renal care to a 108-item ACP engagement survey. Process Measures (knowledge, contemplation, self-efficacy, and readiness, 5-point Likert scales) and Action Measures (yes/no whether an ACP behavior was completed) are included.Canadian ACP engagement sample_BMJ Open_indirect identifiers removed.xlsxSummary table of indirect identifier data - Canadian ACP engagement_BMJ OpenThis file contains descriptive analysis summary tables of indirect identifiers that were removed from the dataset.Canadian ACP engagement_BMJ Open_summary table of indirect identifier data.docx

low data BMJ

Abstract accepted for poster presentation at Evidence Live 2015.

Background “Evidence based medicine insists on rigorous standards to appraise clinical interventions. Failure to apply the same rules to its own tools could be equally damaging” - Joseph L, Ioannidis JPA, Norma T, et al. The case of the misleading funnel plot BMJ 2006; 333:597. Aims Hypothesis: Hierarchical levels of evidence based medicine are incorrect. Objective: To analyze the strength of evidence provided by different types of study designs: systematic reviews and meta-analysis, controlled clinical trials, and observational studies (case-control, cohort, and cross-sectional). Methods Analysis of public databases (e.g., ClinicalTrials.gov, PubMed, ISI Web of Knowledge, Embase, and WHO ICTRP) according to the following variables: geographical locations, sponsors (i.e., industry and non-industry), study designs, conditions (diseases), and interventions (pharmacological and non-pharmacological). Estimation of unpublished clinical trials according to the variables listed above. Analysis of publication bias in systematic reviews and meta-analysis. Results Data and analysis supports the hypothesis in the title of this abstract. Conclusions Human pharmacology is a non-linear science created by multiple variables at different levels of complexity: 1. Drug effects at molecular and cellular levels: drug-receptor interaction (pharmacodynamics) and drug disposition (pharmacokinetics) 2. Effects of drugs on human health and disease: safety, efficacy, and effectiveness 3. Effects of drugs in the society: economical aspects (i.e., pharmacoeconomics), epidemiology (i.e., pharmacological surveillance), healthcare systems (i.e., definitions of essential medicines), over the counter availability of medicines, drug addiction, and many other variables. Hierarchical levels of evidence-based medicine (EBM) are over-simplistic to understand complex relationships involved in human pharmacology. The first EBM article matching search terms in PubMed was published in 1992. The model of drug approval into the market, as well as our methods for appraisal of the evidence involving therapeutic interventions in humans, are supported by opinions instead of real data (i.e., evidence). Evidence-based medicine is not "evidence-based". References http://www.bmj.com/content/348/bmj.g3725/rr/762595http://dx.doi.org/10.6084/m9.figshare.1093997

"The majority of US phase 3 trials were retrospectively registered. Only three out of ten studies that were completed before January 2011 have results available, data was submitted to ClinicalTrials.gov within12 months by 34% of the investigators." (1) Analysis of unpublished studies follows (infographics). (2)

Current number of completed US phase 3 trials (registered between 2002-2014) 1. Clinical trials with results and without results Intervention = drug | URL: http://goo.gl/s0JciJIntervention = biological | URL: http://goo.gl/ARQFnJ 2. Clinical trials with results Intervention = drug | URL: http://goo.gl/s0JciJIntervention = biological | URL: http://goo.gl/ARQFnJ References 1. Ramirez JH, Palacios M. Re: The US requirement to deposit trial data within a year is unworkable. March 17, 2014. URL: http://www.bmj.com/node/753103 2. Ramirez, Jorge H (2014): Infographics: Unpublished US phase 3 clinical trials (2002-2012) completed before Jan 2011 = 50.8%. figshare.http://dx.doi.org/10.6084/m9.figshare.1121675Retrieved 23:05, Jul 30, 2014 (GMT) This database complies with the terms and conditions of ClinicalTrials.gov (http://clinicaltrials.gov/ct2/about-site/terms-conditions) and the WHO ICTRP (http://www.who.int/ictrp/search/download/en/) for using downloaded data.

AimsThe health management of end-stage renal disease patients is a complicated process, and mobile health management technology provides a new choice for the health management of end-stage renal disease patients. The scope of clinical studies on mobile health management for patients with end-stage renal disease was reviewed, and found that about mobile health management problems existing in the literature were identified to provide ideas for subsequent mobile health management research.MethodsThe databases Web of Science, PubMed, The Cochrane Library, Embase, CNKI, Wan Fang Data, BMJ, and VIP were systematically searched for studies on Mobile health management among end-stage renal disease in adult and adolescent patients or children undergoing kidney replacement therapy. The search covered the period from the inception of the databases to June 20, 2023. Two independent reviewers conducted the literature screening process. Following eligibility screening, a total of 38 papers were included for data extraction and descriptive analysis.ResultsA total of 38 studies from 14 countries were finally included. The majority of which were interventional trials. The platforms used in these studies included remote monitoring systems, apps, websites, mobile phones or tablets, and social platforms. These platforms provided patients with a wide range of services, including disease management, behavioral intervention, social support, and follow-up care. Most studies focused on patient clinical indicators, patient experience, quality of life, and healthcare costs.ConclusionOur findings that mobile health management has been widely used in disease management of end-stage renal disease patients, with rich management content and many evaluation indicators. Future studies should strengthen the evaluation of patients’ mental health, quality of life, and healthcare costs. Additionally, developing a clinical decision support system would enable mobile health management to play a more effective role in end-stage renal disease patients.

This fileset contains the anonymized dataset for the BMJ Open article titled "A Retrospective Analysis of the Effect of Discussion in Teleconference and Face-to-Face Scientific Peer Review Panels".