Relemed: sentence-level search engine with relevance score for the MEDLINE database of biomedical articles

How prepared are newly qualified allied health professionals for practice in the UK? A systematic review

OBJECTIVES

It is important that allied health professionals (AHPs) are prepared for clinical practice from the very start of their working lives to provide quality care for patients, for their personal well-being and for retention of the workforce. The aim of this study was to understand how well newly qualified AHPs were prepared for practice in the UK.

DESIGN

Systematic review.

DATA SOURCES

Embase, MEDLINE, CINAHL, ERIC and BEI were searched from 2012 to 2024. Grey literature searching and citation chasing were also conducted.

ELIGIBILITY CRITERIA

We included primary studies reporting the preparedness for practice of UK graduates across 15 professions; all study types; participants included graduates who were up to 2 years postgraduation, their supervisors, trainers, practice educators and employers; and all outcome measures.

DATA EXTRACTION AND SYNTHESIS

A standardised data extraction form was used. Studies were quality assessed using the Quality Appraisal for Diverse Studies tool. 10% of articles were independently double-screened, extracted and quality assessed; 90% was completed by one researcher.

RESULTS

14 reports were included (9 qualitative, 3 mixed-method and 2 quantitative). Six papers focused on radiographers, three on a mixture of professions, two on paramedics, and one each on physiotherapists, clinical psychologists and orthotists. An important finding of the review is the paucity and low-medium quality of research on the topic. The narrative synthesis tentatively suggests that graduates are adequately prepared for practice with different professions having different strengths and weaknesses. Common areas of underpreparedness across the professions were responsibility and decision-making, leadership and research. Graduates were generally well prepared in terms of their knowledge base.

CONCLUSION

High-quality in-depth research is urgently needed across AHPs to elucidate the specific roles, their nuances and the areas of underpreparedness. Further work is also needed to understand the transition into early clinical practice, ongoing learning opportunities through work, and the supervision and support structures in place.

PROSPERO REGISTRATION NUMBER

CRD42022382065.

Health economic evaluations of preventative care for perinatal anxiety and associated disorders: a rapid review

OBJECTIVES

Perinatal mental health problems affect one in five women and cost the UK £8.1 billion for every year of births, with 72% of this cost due to the long-term impact on the child. We conducted a rapid review of health economic evaluations of preventative care for perinatal anxiety and associated disorders.

DESIGN

This study adopted a rapid review approach, using principles of the standard systematic review process to generate quality evidence. This methodology features a systematic database search, Preferred Reporting Items for Systematic Reviews and Meta-Analyses diagram, screening of evidence, data extraction, critical appraisal and narrative synthesis.

DATA SOURCES

PubMed, Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, Applied Social Sciences Index and Abstracts, PsycINFO and MEDLINE.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies that evaluated the costs and cost-effectiveness of preventative care for perinatal anxiety and associated disorders carried out within the National Health Service and similar healthcare systems.

DATA EXTRACTION AND SYNTHESIS

A minimum of two independent reviewers used standardised methods to search, screen, critically appraise and synthesise included studies.

RESULTS

The results indicate a lack of economic evaluation specifically for perinatal anxiety, with most studies focusing on postnatal depression (PND). Interventions to prevent postnatal mental health problems are cost-effective. Modelling studies have also been conducted, which suggest that treating PND with counselling would be cost-effective.

CONCLUSION

The costs of not intervening in maternal mental health outweigh the costs of preventative interventions. Preventative measures such as screening and counselling for maternal mental health are shown to be cost-effective interventions to improve outcomes for women and children.

PROSPERO REGISTRATION NUMBER

CRD42022347859.

What is known about the health effects of non-steroidal anti-inflammatory drug (NSAID) use in marathon and ultraendurance running: a scoping review

This systematic scoping review aimed to understand the extent and scope of evidence on the health risks of non-steroidal anti-inflammatory drug (NSAID) use in marathon and ultraendurance running. NSAIDs are commonly consumed by runners to combat pain and inflammation; however, the health risks of consuming these drugs during marathon and ultrarunning events are currently not fully understood. Four databases (Cochrane Library, PubMed, MEDLINE and SPORTDiscus) were searched to identify articles focusing on running events of 26.2 miles or further, and they must have reported on the health risks of NSAID use. There was no restriction on the study design or the date of publication. Thirty studies were ultimately included: 4 randomised controlled trials, 1 cross-sectional study, 11 retrospective reviews, 4 case reports, 1 non-randomised control trial, and 9 prospective observational studies. The literature showed that potential health concerns of NSAID use could be split into five categories: electrolyte balance and hyponatraemia; acute kidney injury (AKI); gastrointestinal disturbances; oxidative stress, inflammation and muscle damage; other medical concerns. None of these sections had clear statistically significant links with NSAID use in ultraendurance running. However, potential links were shown, especially in AKI and electrolyte balance. This review suggests there is very limited evidence to show that NSAIDs have a negative impact on the health of ultrarunning athletes. Indications from a few non-randomised studies of a possible effect on kidney function need exploring with more high-quality research.

Strategies to Reduce the Impact of Trauma in Psychiatric Nurses: An Integrative Review of the Literature

BACKGROUND

Psychiatric nurses are at a higher risk for exposure to violence and aggression, leading to potential burnout, moral injury, post-traumatic stress, and turnover. There is little evidence of a preferred strategy to support nurses and decrease the impact of traumatic experiences on psychiatric nurses. The aim of this integrative review was to explore potential strategies to decrease the impact of traumatic experiences among nurses in psychiatric settings.

METHODS

Following a systematic search of PsycINFO/Ovid, CINAHL, and MEDLINE/Pubmed, Joanna Briggs Institute quality appraisal tools were used to analyze quality of the articles. Thirteen articles met the inclusion/exclusion criteria for this study. Data were analyzed and synthesized into three key themes and seven sub-themes.

RESULTS

Three themes were noted to be common to the included texts. 1. Interpersonal Supports (Formal Support, Peer/Supervisor Support, and Informal Family/Social Support). 2. Organizational Supports (Perception of Job Safety/Satisfaction, Promoting Personal Resilience, Supporting Team Resilience, and Organizational Commitment to Resilience). 3. Protection of Personal Resources.

CONCLUSIONS

Many common suggestions for decreasing the impact of exposure to violence and trauma were noted across the thirteen articles, however, there is little evidence of a preferred strategy, how strategies are developed and employed or the efficacy of any particular strategy. Further investigation is needed to identify and evaluate supportive interventions, their feasibility and efficacy.

Ten Steps to Conduct a Systematic Review

This article introduces a concise 10-step guide tailored for researchers engaged in systematic reviews within the field of medicine and health, aligning with the imperative for evidence-based healthcare. The guide underscores the importance of integrating research evidence, clinical proficiency, and patient preferences. It emphasizes the need for precision in formulating research questions, utilizing tools such as PICO(S)(Population Intervention Comparator Outcome), PEO (Population Exposure Outcome), SPICE (setting, perspective, intervention/exposure/interest, comparison, and evaluation), and SPIDER (expectation, client group, location, impact, professionals, service and evaluation), and advocates for the validation of research ideas through preliminary investigations. The guide prioritizes transparency by recommending the documentation and registration of protocols on various platforms. It highlights the significance of a well-organized literature search, encouraging the involvement of experts to ensure a high-quality search strategy. The critical stages of screening titles and abstracts are navigated using different tools, each characterized by its specific advantages. This diverse approach aims to enhance the effectiveness of the systematic review process. In conclusion, this 10-step guide provides a practical framework for the rigorous conduct of systematic reviews in the domain of medicine and health. It addresses the unique challenges inherent in this field, emphasizing the values of transparency, precision, and ongoing efforts to improve primary research practices. The guide aims to contribute to the establishment of a robust evidence base, facilitating informed decision-making in healthcare.

Application of Laser Treatment in Adhesive Bonding of Liners to Polymethyl Methacrylate Denture Resins: A Systematic Review and Meta-Analysis

Objective: This systematic review and meta-analysis aimed to assess the influence of laser treatment on adhesive bonding of liners to polymethyl methacrylate (PMMA) denture base resins. Methods: The focused question was: "Does the application of laser treatment (Intervention) influence the adhesive bonding strength (Outcome) of liners to PMMA denture base resins (Population) as compared with untreated or unconditioned surfaces (Control)?" In vitro and clinical reports as well as reports on influence of laser treatments on bonding strength of liners to PMMA denture resins in comparison with untreated surfaces were included. Reports without any control group[s], without any application of laser[s] for PMMA denture bases that did not utilize PMMA denture bases, and not evaluate bond strength of PMMA denture base resins were excluded. An electronic search was conducted on PubMed, Scopus, and Web of Science. Meta-analyses were performed for calculating the standard mean difference (SMD) with a 95% confidence interval (95% CI). Results: Nine of the 12 included studies found that laser irradiation treatment produced significant surface texture alterations of the PMMA denture base and improved the adhesion between the PMMA denture base and soft lining. According to the meta-analysis, tensile bond strength showed an SMD of -2.49% (95% CI: -3.89 to -1.08; p = 0.0005), suggesting a statistically significant difference between the control and test groups (i.e., favoring laser-treated samples than untreated samples). Regarding shear bond strength scores, the outcomes showed an SMD of -2.24% (95% CI: -3.79 to -0.69; p = 0.005), suggesting a statistically significant difference between the control and test groups (i.e., favoring laser-treated samples than untreated samples). Conclusions: Despite the high heterogeneity among the included studies, it can be concluded that laser treatment might improve the bonding strengths of liners to PMMA denture base resins as compared with untreated surfaces. To validate the aforementioned conclusions, further verification is required through the implementation of well-designed randomized controlled trials with large sample sizes.

Usability of exergames as a home-based balance training tool for older adults: protocol for a systematic review

INTRODUCTION

Exergames are used in the clinical practice of geriatric rehabilitation to increase physical activity levels and motivate players/patients. Their use in the home environment makes it possible to perform fun, engaging and interactive training with a large number of repetitions, thereby reducing the negative repercussions of postural imbalance in older adults. The aim of this systematic review is to collate and analyse evidence on the usability of exergames as a tool for home-based balance training for older adults.

METHODS AND ANALYSIS

We will include randomised controlled trials involving healthy older adults (aged 60 years or older) who are described as having impaired static or dynamic balance using any subjective or objective assessment criteria. We will search Web of Science, MEDLINE, Embase, Scopus, ScienceDirect and the Cochrane Library from database inception to December 2022.

CLINICALTRIALS

gov, the WHO International Clinical Trials Registry Platform and ReBEC will be searched for ongoing or unpublished trials. Two independent reviewers will screen the studies and extract the data. The findings will be presented in the text and tables, and if possible, relevant meta-analyses will be performed. The risk of bias and the quality of evidence will be assessed based on the recommendations of the Cochrane Handbook and Grading of Recommendations, Assessment, Development and Evaluation, respectively.

ETHICS AND DISSEMINATION

Ethical approval was not required because of the nature of this study. Findings will be disseminated through peer-reviewed publications, conference presentations and through clinical rehabilitation networks.

PROSPERO REGISTRATION NUMBER

CRD42022343290.

Systematic review of the effectiveness of non-pharmacological interventions used to treat adults with inducible laryngeal obstruction

Introduction

Inducible laryngeal obstruction (ILO) describes transient laryngeal closure during respiration and can cause significant morbidity. Non-pharmacological behavioural therapy is the commonly cited treatment but efficacy is largely unknown.

Aim

To synthesise the current evidence base on the effectiveness of non-pharmacological interventions used to treat adults with ILO.

Methods

Electronic databases (Medline/Embase/CINAHL/PsycINFO/AMED/CENTRAL) were systematically searched, informed by a population, intervention, comparison, outcome framework. Two reviewers independently screened a representative sample, with lead-author completion due to excellent inter-rater reliability. Data was extracted using a predefined piloted form. Methodological quality was appraised (blindly by two reviewers) using the Joanna Briggs Institute Critical Appraisal Tools. A narrative synthesis was performed due to heterogeneity of studies (PROSPERO registration number: CRD42020213187).

Results

Initial searching identified 3359 records. Full-text screening occurred in 92 records and 14 studies, comprising 527 participants, were deemed eligible. All studies were low-level evidence (observational by design, with four case reports), with a high risk of bias; none contained control arms for comparison. Intervention description was inconsistently and poorly described but direction of effect was positive in 76% of outcomes measured. The majority of studies showed a reduction in symptom scores and improved direct laryngeal imaging post intervention; there was an overall reduction, 59.5%, in healthcare utilisation.

Discussion

The literature is in an embryonic state and lacks robust data to truly inform on the effectiveness of non-pharmacological interventions used to treat adults with ILO. However, positive signals in the synthesis performed support non-pharmacological treatment approaches and further development is warranted.

Vision Abnormalities in Children and Young Adults With Cerebral Palsy; A Systematic Review

AIM

The current study was designed to provide detailed information on the prevalence of ocular abnormalities in patients with cerebral palsy (CP).

METHODS

Four international online scientific databases, including Web of Science, PubMed, Scopus, and Google Scholar were systemically searched. First, the titles of the articles were evaluated, and if relevant, their abstracts and full texts were reviewed. The quality of the studies was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist.

RESULTS

A total of 147 articles were found in the initial search. After applying the exclusion criteria, 65 articles were chosen for further review, from which 17 articles, comprising a total of 1734 patients with CP ranging in age from birth to 22 years, passed the STROBE quality check and were included in this review. The prevalence of ocular abnormalities in the CP patients reported in the evaluated studies ranged between 34% to 100%, with refractive error, strabismus, and nystagmus exhibiting the greatest overall prevalence at 52%, 48%, and 11%, respectively in this population.

CONCLUSION

Early ocular assessment of children with CP is essential for an accurate diagnosis, personalized rehabilitation and performing early interventions to improve their visual function.

Physician Experience Design (PXD): More Usable Machine Learning Prediction for Clinical Decision Making

Delirium is an acute neurocognitive disorder, which is difficult to identify and predict. Using GEMINI, Canada's largest hospital data and analytics study, we had a labeled sample of around 4,000 cases with approximately 25% of cases being labeled as having delirium. Based on this labeled data, we developed machine learning (ML) models and interacted with physicians to interpret the ML models and their predictions. We developed a preliminary Explainable Artificial Intelligence (XAI) framework for physician experience design (PXD) to improve the uptake of ML models by improving the transparency of model results, thereby increasing physician trust in models as well as the uptake of model results for clinical decision making. We developed our PXD approach first with Conceptual Investigation to collect and extract physicians' feedback on ML models and their evaluation requirements. We carried out a case study, working closely with the physicians in a participatory design process to develop a dashboard that presents ML delirium identification results interactively based on physician selections and inputs. In this approach a physician-preferred ML model for clinical decision making is selected through PXD evaluation.

The Role of Prostate-specific Membrane Antigen Positron Emission Tomography/Magnetic Resonance Imaging in Primary and Recurrent Prostate Cancer: A Systematic Review of the Literature

CONTEXT

Prostate-specific membrane antigen (PSMA) positron emission tomography/magnetic resonance imaging (PET/MRI) is a novel imaging technique with several potential applications in the prostate cancer (PCa) setting.

OBJECTIVE

To perform a systematic review of the current evidence regarding the diagnostic performance of PSMA PET/MRI in patients with primary and recurrent PCa.

EVIDENCE ACQUISITION

A comprehensive bibliographic search on the MEDLINE and Cochrane Library databases was performed in October 2020. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Studies were deemed eligible if they assessed patients with primary or recurrent PCa (P) undergoing PSMA PET/MRI (I) with or without comparison with other imaging techniques (C) in order to evaluate its diagnostic performance (O). Retrospective and prospective primary clinical studies were included. Results of previous meta-analyses were reported.

EVIDENCE SYNTHESIS

A total of 23 original articles and three meta-analyses were included. Limited evidence on PSMA PET/MRI is available, especially in the setting of partial gland ablation. PET/MRI can be an effective imaging modality for detecting primary PCa, showing higher accuracy than multiparametric MRI alone. It provides accurate local staging of primary PCa; however, there are contradictory results in this context when its performance is compared with other imaging techniques. PET/MRI also shows high performance for restaging and detecting tumor recurrence, even at low prostate-specific antigen levels.

CONCLUSIONS

PSMA PET/MRI could represent a valuable tool in the management of patients with primary and recurrent PCa. No specific recommendations can be provided.

PATIENT SUMMARY

Encouraging data regarding the benefits of prostate-specific membrane antigen positron emission tomography/magnetic resonance imaging in patients with prostate cancer are emerging from the literature.

The Association Between Effectiveness of Tinnitus Intervention and Cognitive Function-A Systematic Review

Tinnitus refers to the perception of sound in the absence of an external stimulus. This can be problematic and can lead to health problems in some sufferers, including effects on cognitive functions such as attention and memory. Although several studies have examined the effectiveness of tinnitus interventions, e.g., cognitive behavioral therapy and sound therapy, it is still unclear as to the overall quality and limitations of these studies and whether their results could be generalized. Clarification is also needed as to whether poor cognitive function will lead to a less favorable intervention outcome in tinnitus patients. The present systematic review was therefore designed to critically appraise and synthesize findings from randomized controlled trials (RCTs) of tinnitus intervention and its effects on cognition. The methodology followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Medline (PubMed), Embase, and PsycINFO were searched. Only RCTs that compared the effectiveness of a tinnitus intervention and a measure of cognitive function in adult participants with tinnitus were included. A total of 8 studies involving 610 participants tested using 11 cognitive function assessment tools (e.g., Stroop Color and Word Test and Visual Continuous Performance Task) and 5 tinnitus intervention outcome measurements (e.g., Tinnitus Handicap Inventory and Tinnitus Questionnaire) were included and analyzed. The outcomes of the review suggest that tinnitus intervention not only facilitates tinnitus management but also improves cognitive functions. It is likely that cognition and emotion play an important role in a patient's adjustment to tinnitus. Whether cognition can predict treatment outcomes is unclear due to insufficient evidence. Future research is needed using a standardized assessment protocol focusing on the effect of sound-based interventions on tinnitus severity and cognitive functions. Studies on whether cognitive function measurement can be used as a predictor for the effectiveness of tinnitus therapy are also needed.

Academic achievement and gender among adult critical care program directors

PURPOSE

Accreditation Council for Graduate Medical Education (ACGME) program director (PD) qualifications includes scholarly activity with demonstrated academic productivity and dissemination. Our hypothesis: academic productivity among adult critical care medicine (CCM) fellowship PDs is affected by gender with women having lower productivity.

MATERIALS AND METHODS

PDs in 39 institutions with CCM fellowships in anesthesiology, surgery, and pulmonary medicine were analyzed using data from ACGME website, PubMed, and NIH Research Portfolio Online Reporting Tools. Primary outcomes were total publications and h-index. Secondary outcomes included NIH funding and past five year publications. Independent variables and covariates included gender, academic rank, year appointed as program director, years certified in CCM, and specialty.

RESULTS

PDs who were women had fewer total publications (median: 13 vs: 20, p = 0.030), past 5 years publications (median: 6 vs median: 9; p = 0.025), and less NIH funding (12% vs 32%; p = 0.046) compared to men. In exploratory analyses stratified by rank, assistant professor ranked women had fewer total (p = 0.027) and recent publications (p = 0.031) compared to men.

CONCLUSIONS

Women who were PDs had fewer publications and less NIH funding compared to men with differences in publications more prominent in early career faculty.

Examining the Effectiveness of Restorative Justice in Reducing Victims’ Post-Traumatic Stress

Crime victimisation is a significant life event that can lead to the development of post-traumatic symptomology. Compared with the general population, victims of crime are significantly more likely to present with symptoms of post-traumatic stress disorder (PTSD). Restorative justice is an approach to criminal justice that considers the goal of the justice system to restore victims to their state pre-victimisation. The purpose of this review was to evaluate the effectiveness of restorative justice in reducing symptoms of post-traumatic stress that develop following victimisation. Relevant databases were searched to identify quantitative studies measuring post-traumatic symptoms in victims of crime who successfully completed either a restorative justice or customary justice intervention. A total of seven studies were identified examining one or more facet of post-traumatic symptomology. These studies provide modest support that restorative justice did produce a greater improvement on post-traumatic symptoms than customary justice procedures. However, this was only consistently evidenced for symptoms of avoidance and intrusion, whereas there were mixed findings with regard to the subscales of negative alterations in mood and cognition, and arousal and reactivity. Reasons for these inconsistencies are discussed and recommendation made for further empirical work on this subject.

Neuromuscular adverse events associated with anti-PD-1 monoclonal antibodies: Systematic review

Neuromuscular adverse events following cancer treatment with anti-programmed cell death protein 1 (PD-1) monoclonal antibodies are relatively rare, yet potentially fatal. We performed a systematic review to characterize the clinical presentation, diagnostic workup, and management of neuromuscular disorders (NMDs) in patients treated with nivolumab or pembrolizumab monotherapy or concurrent with other immunologic agents, such as ipilimumab. Sixty-one publications on 85 patients (mean age 66.9 years [range 34-86]; male/female 2.6:1; 59% metastatic melanoma) were identified from selected indexing databases until June 2018. Forty-eight patients had received nivolumab and 39 pembrolizumab. The mean number of PD-1 inhibitor treatment cycles prior to onset of symptoms was 3.6 (range 1-28). Symptoms included oculomotor (47%), respiratory (43%), bulbar (35%), and proximal weakness (35%), as well as muscle pain (28%). Diagnoses were categorized as myasthenia gravis (27%), neuropathy (23%), myopathy (34%), or a combination of these (16%). After a critical review of the data, however, evidence did not support the stated NMD diagnosis in 13% of cases, while up to 25% of patients had signs of additional NMDs. Cardiac complications occurred in more than 30% of patients diagnosed with myasthenia gravis or myositis. Mortality was high in these patients, despite adequate treatment strategies including corticosteroid, IV immunoglobulins, and plasma exchange. The clinical presentation of NMDs associated with PD-1 inhibitors is often atypical, with considerable overlap between myasthenia gravis and myopathy, and cardiac/respiratory complications are common.

The prescribable drugs with efficacy in experimental epilepsies (PDE3) database for drug repurposing research in epilepsy

OBJECTIVE

Current antiepileptic drugs (AEDs) have several shortcomings. For example, they fail to control seizures in 30% of patients. Hence, there is a need to identify new AEDs. Drug repurposing is the discovery of new indications for approved drugs. This drug "recycling" offers the potential of significant savings in the time and cost of drug development. Many drugs licensed for other indications exhibit antiepileptic efficacy in animal models. Our aim was to create a database of "prescribable" drugs, approved for other conditions, with published evidence of efficacy in animal models of epilepsy, and to collate data that would assist in choosing the most promising candidates for drug repurposing.

METHODS

The database was created by the following: (1) computational literature-mining using novel software that identifies Medline abstracts containing the name of a prescribable drug, a rodent model of epilepsy, and a phrase indicating seizure reduction; then (2) crowdsourced manual curation of the identified abstracts.

RESULTS

The final database includes 173 drugs and 500 abstracts. It is made freely available at www.liverpool.ac.uk/D3RE/PDE3. The database is reliable: 94% of the included drugs have corroborative evidence of efficacy in animal models (for example, evidence from multiple independent studies). The database includes many drugs that are appealing candidates for repurposing, as they are widely accepted by prescribers and patients-the database includes half of the 20 most commonly prescribed drugs in England-and they target many proteins involved in epilepsy but not targeted by current AEDs. It is important to note that the drugs are of potential relevance to human epilepsy-the database is highly enriched with drugs that target proteins of known causal human epilepsy genes (Fisher's exact test P-value < 3 × 10^-5 ). We present data to help prioritize the most promising candidates for repurposing from the database.

SIGNIFICANCE

The PDE3 database is an important new resource for drug repurposing research in epilepsy.

PubMed Labs: an experimental system for improving biomedical literature search

PubMed is a freely accessible system for searching the biomedical literature, with ∼2.5 million users worldwide on an average workday. In order to better meet our users’ needs in an era of information overload, we have recently developed PubMed Labs (www.pubmed.gov/labs), an experimental system for users to test new search features/tools (e.g. Best Match) and provide feedback, which enables us to make more informed decisions about potential changes to improve the search quality and overall usability of PubMed. In addition, PubMed Labs features a mobile-first and responsive layout that offers better support for accessing PubMed from increasingly popular mobiles and small-screen devices. In this paper, we detail PubMed Labs, its purpose, new features and best practices. We also encourage users to share their experience with us; based on which we are continuously improving PubMed Labs with more advanced features and better user experience.

Identifying new antiepileptic drugs through genomics-based drug repurposing

Currently available antiepileptic drugs (AEDs) fail to control seizures in 30% of patients. Genomics-based drug repurposing (GBR) offers the potential of savings in the time and cost of developing new AEDs. In the current study, we used published data and software to identify the transcriptomic signature of chornic temporal lobe epilepsy and the drugs that reverse it. After filtering out compounds based on exclusion criteria, such as toxicity, 36 drugs were retained. 11 of the 36 drugs identified (>30%) have published evidence of the antiepileptic efficacy (for example, curcumin) or antiepileptogenic affect (for example, atorvastatin) in recognised rodent models or patients. By objectively annotating all ∼20,000 compounds in the LINCS database as either having published evidence of antiepileptic efficacy or lacking such evidence, we demonstrated that our set of repurposable drugs is ∼6-fold more enriched with drugs having published evidence of antiepileptic efficacy in animal models than expected by chance (P-value <0.006). Further, we showed that another of our GBR-identified drugs, the commonly-used well-tolerated antihyperglycemic sitagliptin, produces a dose-dependent reduction in seizures in a mouse model of pharmacoresistant epilepsy. In conclusion, GBR successfully identifies compounds with antiepileptic efficacy in animal models and, hence, it is an appealing methodology for the discovery of potential AEDs.

Academic Productivity of Accreditation Council for Graduate Medical Education-Accredited Critical Care Fellowship Program Directors

OBJECTIVES

Academic productivity is an expectation for program directors of Accreditation Council for Graduate Medical Education-accredited subspecialty programs in critical care medicine. Within the adult critical care Accreditation Council for Graduate Medical Education-accredited programs, we hypothesized that program director length of time from subspecialty critical care certification would correlate positively with academic productivity, and primary field would impact academic productivity.

DESIGN

This study received Institutional Review Board exemption from the University of Florida. Data were obtained from public websites on program directors from all institutions that had surgery, anesthesiology, and pulmonary Accreditation Council for Graduate Medical Education-accredited subspecialty critical care training programs during calendar year 2012. Information gathered included year of board certification and appointment to program director, academic rank, National Institutes of Health funding history, and PubMed citations.

RESULTS

Specialty area was significantly associated with total (all types of publications) (p = 0.0002), recent (p < 0.0001), last author (p = 0.008), and original research publications (p < 0.0001), even after accounting for academic rank, years certified, and as a program director. These differences were most prominent in full professors, with surgery full professors having more total, recent, last author, and original research publications than full professors in the other critical care specialties.

CONCLUSIONS

This study demonstrates that one's specialty area in critical care is an independent predictor of academic productivity, with surgery having the highest productivity. For some metrics, such as total and last author publications, surgery had more publications than both anesthesiology and pulmonary, whereas there was no difference between the latter groups. This suggests that observed differences in academic productivity vary by specialty.

Integrating unified medical language system and association mining techniques into relevance feedback for biomedical literature search

Background

Finding highly relevant articles from biomedical databases is challenging not only because it is often difficult to accurately express a user’s underlying intention through keywords but also because a keyword-based query normally returns a long list of hits with many citations being unwanted by the user. This paper proposes a novel biomedical literature search system, called BiomedSearch, which supports complex queries and relevance feedback.

Methods

The system employed association mining techniques to build a k-profile representing a user’s relevance feedback. More specifically, we developed a weighted interest measure and an association mining algorithm to find the strength of association between a query and each concept in the article(s) selected by the user as feedback. The top concepts were utilized to form a k-profile used for the next-round search. BiomedSearch relies on Unified Medical Language System (UMLS) knowledge sources to map text files to standard biomedical concepts. It was designed to support queries with any levels of complexity.

Results

A prototype of BiomedSearch software was made and it was preliminarily evaluated using the Genomics data from TREC (Text Retrieval Conference) 2006 Genomics Track. Initial experiment results indicated that BiomedSearch increased the mean average precision (MAP) for a set of queries.

Conclusions

With UMLS and association mining techniques, BiomedSearch can effectively utilize users’ relevance feedback to improve the performance of biomedical literature search.

Text mining, a race against time? An attempt to quantify possible variations in text corpora of medical publications throughout the years

BACKGROUND

The continuous growth of medical sciences literature indicates the need for automated text analysis. Scientific writing which is neither unitary, transcending social situation nor defined by a timeless idea is subject to constant change as it develops in response to evolving knowledge, aims at different goals, and embodies different assumptions about nature and communication. The objective of this study was to evaluate whether publication dates should be considered when performing text mining.

METHODS

A search of PUBMED for combined references to chemokine identifiers and particular cancer related terms was conducted to detect changes over the past 36 years. Text analyses were performed using freeware available from the World Wide Web. TOEFL Scores of territories hosting institutional affiliations as well as various readability indices were investigated. Further assessment was conducted using Principal Component Analysis. Laboratory examination was performed to evaluate the quality of attempts to extract content from the examined linguistic features.

RESULTS

The PUBMED search yielded a total of 14,420 abstracts (3,190,219 words). The range of findings in laboratory experimentation were coherent with the variability of the results described in the analyzed body of literature. Increased concurrence of chemokine identifiers together with cancer related terms was found at the abstract and sentence level, whereas complexity of sentences remained fairly stable.

CONCLUSIONS

The findings of the present study indicate that concurrent references to chemokines and cancer increased over time whereas text complexity remained stable.

Biological information extraction and co-occurrence analysis

Nowadays, it is possible to identify terms corresponding to biological entities within passages in biomedical text corpora: critically, their potential relationships then need to be detected. These relationships are typically detected by co-occurrence analysis, revealing associations between bioentities through their coexistence in single sentences and/or entire abstracts. These associations implicitly define networks, whose nodes represent terms/bioentities/concepts being connected by relationship edges; edge weights might represent confidence for these semantic connections.This chapter provides a review of current methods for co-occurrence analysis, focusing on data storage, analysis, and representation. We highlight scenarios of these approaches implemented by useful tools for information extraction and knowledge inference in the field of systems biology. We illustrate the practical utility of two online resources providing services of this type-namely, STRING and BioTextQuest-concluding with a discussion of current challenges and future perspectives in the field.

Sequential detection of influenza epidemics by the Kolmogorov-Smirnov test

Background

Influenza is a well known and common human respiratory infection, causing significant morbidity and mortality every year. Despite Influenza variability, fast and reliable outbreak detection is required for health resource planning. Clinical health records, as published by the Diagnosticat database in Catalonia, host useful data for probabilistic detection of influenza outbreaks.

Methods

This paper proposes a statistical method to detect influenza epidemic activity. Non-epidemic incidence rates are modeled against the exponential distribution, and the maximum likelihood estimate for the decaying factor λ is calculated. The sequential detection algorithm updates the parameter as new data becomes available. Binary epidemic detection of weekly incidence rates is assessed by Kolmogorov-Smirnov test on the absolute difference between the empirical and the cumulative density function of the estimated exponential distribution with significance level 0 ≤ α ≤ 1.

Results

The main advantage with respect to other approaches is the adoption of a statistically meaningful test, which provides an indicator of epidemic activity with an associated probability. The detection algorithm was initiated with parameter λ₀ = 3.8617 estimated from the training sequence (corresponding to non-epidemic incidence rates of the 2008-2009 influenza season) and sequentially updated. Kolmogorov-Smirnov test detected the following weeks as epidemic for each influenza season: 50−10 (2008-2009 season), 38−50 (2009-2010 season), weeks 50−9 (2010-2011 season) and weeks 3 to 12 for the current 2011-2012 season.

Conclusions

Real medical data was used to assess the validity of the approach, as well as to construct a realistic statistical model of weekly influenza incidence rates in non-epidemic periods. For the tested data, the results confirmed the ability of the algorithm to detect the start and the end of epidemic periods. In general, the proposed test could be applied to other data sets to quickly detect influenza outbreaks. The sequential structure of the test makes it suitable for implementation in many platforms at a low computational cost without requiring to store large data sets.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

BACKGROUND

Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs.

RESULTS

We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination.

CONCLUSIONS

CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset of HL7-CDA documents, returning significantly fewer citations since queries are focused on characteristics identified within the EHR. For instance, compared with more than 200,000 citations retrieved by breast neoplasm, fewer than ten citations were retrieved when ten patient features were added using CDAPubMed. This is an open source tool that can be freely used for non-profit purposes and integrated with other existing systems.

Leveraging medical thesauri and physician feedback for improving medical literature retrieval for case queries

OBJECTIVE

This paper presents a study of methods for medical literature retrieval for case queries, in which the goal is to retrieve literature articles similar to a given patient case. In particular, it focuses on analyzing the performance of state-of-the-art general retrieval methods and improving them by the use of medical thesauri and physician feedback.

MATERIALS AND METHODS

The Kullback-Leibler divergence retrieval model with Dirichlet smoothing is used as the state-of-the-art general retrieval method. Pseudorelevance feedback and term weighing methods are proposed by leveraging MeSH and UMLS thesauri. Evaluation is performed on a test collection recently created for the ImageCLEF medical case retrieval challenge.

RESULTS

Experimental results show that a well-tuned state-of-the-art general retrieval model achieves a mean average precision of 0.2754, but the performance can be improved by over 40% to 0.3980, through the proposed methods.

DISCUSSION

The results over the ImageCLEF test collection, which is currently the best collection available for the task, are encouraging. There are, however, limitations due to small evaluation set size. The analysis shows that further refinement of the methods is necessary before they can be really useful in a clinical setting.

CONCLUSION

Medical case-based literature retrieval is a critical search application that presents a number of unique challenges. This analysis shows that the state-of-the-art general retrieval models are reasonably good for the task, but the performance can be significantly improved by developing new task-specific retrieval models that incorporate medical thesauri and physician feedback.

Recent progress in automatically extracting information from the pharmacogenomic literature

The biomedical literature holds our understanding of pharmacogenomics, but it is dispersed across many journals. In order to integrate our knowledge, connect important facts across publications and generate new hypotheses we must organize and encode the contents of the literature. By creating databases of structured pharmocogenomic knowledge, we can make the value of the literature much greater than the sum of the individual reports. We can, for example, generate candidate gene lists or interpret surprising hits in genome-wide association studies. Text mining automatically adds structure to the unstructured knowledge embedded in millions of publications, and recent years have seen a surge in work on biomedical text mining, some specific to pharmacogenomics literature. These methods enable extraction of specific types of information and can also provide answers to general, systemic queries. In this article, we describe the main tasks of text mining in the context of pharmacogenomics, summarize recent applications and anticipate the next phase of text mining applications.

MeSHy: Mining unanticipated PubMed information using frequencies of occurrences and concurrences of MeSH terms

MOTIVATION

PubMed is the most widely used database of biomedical literature. To the detriment of the user though, the ranking of the documents retrieved for a query is not content-based, and important semantic information in the form of assigned Medical Subject Headings (MeSH) terms is not readily presented or productively utilized. The motivation behind this work was the discovery of unanticipated information through the appropriate ranking of MeSH term pairs and, indirectly, documents. Such information can be useful in guiding novel research and following promising trends.

METHODS

A web-based tool, called MeSHy, was developed implementing a mainly statistical algorithm. The algorithm takes into account the frequencies of occurrences, concurrences, and the semantic similarities of MeSH terms in retrieved PubMed documents to create MeSH term pairs. These are then scored and ranked, focusing on their unexpectedly frequent or infrequent occurrences.

RESULTS

MeSHy presents results through an online interactive interface facilitating further manipulation through filtering and sorting. The results themselves include the MeSH term pairs, along with MeSH categories, the score, and document IDs, all of which are hyperlinked for convenience. To highlight the applicability of the tool, we report the findings of an expert in the pharmacology field on querying the molecularly-targeted drug imatinib and nutrition-related flavonoids. To the best of our knowledge, MeSHy is the first publicly available tool able to directly provide such a different perspective on the complex nature of published work.

IMPLEMENTATION AND AVAILABILITY

Implemented in Perl and served by Apache2 at http://bat.ina.certh.gr/tools/meshy/ with all major browsers supported.

Understanding the mobile internet to develop the next generation of online medical teaching tools

Healthcare providers (HCPs) use online medical information for self-directed learning and patient care. Recently, the mobile internet has emerged as a new platform for accessing medical information as it allows mobile devices to access online information in a manner compatible with their restricted storage. We investigated mobile internet usage parameters to direct the future development of mobile internet teaching websites. Nephrology On-Demand Mobile (NOD(M)) (http://www.nephrologyondemand.org) was made accessible to all mobile devices. From February 1 to December 31, 2010, HCP use of NOD(M) was tracked using code inserted into the root files. Nephrology On-Demand received 15,258 visits, of which approximately 10% were made to NOD(M), with the majority coming from the USA. Most access to NOD(M) was through the Apple iOS family of devices and cellular connections were the most frequently used. These findings provide a basis for the future development of mobile nephrology and medical teaching tools.

PubMed and beyond: a survey of web tools for searching biomedical literature

The past decade has witnessed the modern advances of high-throughput technology and rapid growth of research capacity in producing large-scale biological data, both of which were concomitant with an exponential growth of biomedical literature. This wealth of scholarly knowledge is of significant importance for researchers in making scientific discoveries and healthcare professionals in managing health-related matters. However, the acquisition of such information is becoming increasingly difficult due to its large volume and rapid growth. In response, the National Center for Biotechnology Information (NCBI) is continuously making changes to its PubMed Web service for improvement. Meanwhile, different entities have devoted themselves to developing Web tools for helping users quickly and efficiently search and retrieve relevant publications. These practices, together with maturity in the field of text mining, have led to an increase in the number and quality of various Web tools that provide comparable literature search service to PubMed. In this study, we review 28 such tools, highlight their respective innovations, compare them to the PubMed system and one another, and discuss directions for future development. Furthermore, we have built a website dedicated to tracking existing systems and future advances in the field of biomedical literature search. Taken together, our work serves information seekers in choosing tools for their needs and service providers and developers in keeping current in the field.

Database URL:http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/search

Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS

Background

Finding relevant articles from PubMed is challenging because it is hard to express the user's specific intention in the given query interface, and a keyword query typically retrieves a large number of results. Researchers have applied machine learning techniques to find relevant articles by ranking the articles according to the learned relevance function. However, the process of learning and ranking is usually done offline without integrated with the keyword queries, and the users have to provide a large amount of training documents to get a reasonable learning accuracy. This paper proposes a novel multi-level relevance feedback system for PubMed, called RefMed, which supports both ad-hoc keyword queries and a multi-level relevance feedback in real time on PubMed.

Results

RefMed supports a multi-level relevance feedback by using the RankSVM as the learning method, and thus it achieves higher accuracy with less feedback. RefMed "tightly" integrates the RankSVM into RDBMS to support both keyword queries and the multi-level relevance feedback in real time; the tight coupling of the RankSVM and DBMS substantially improves the processing time. An efficient parameter selection method for the RankSVM is also proposed, which tunes the RankSVM parameter without performing validation. Thereby, RefMed achieves a high learning accuracy in real time without performing a validation process. RefMed is accessible at http://dm.postech.ac.kr/refmed.

Conclusions

RefMed is the first multi-level relevance feedback system for PubMed, which achieves a high accuracy with less feedback. It effectively learns an accurate relevance function from the user’s feedback and efficiently processes the function to return relevant articles in real time.

Analysis of biological processes and diseases using text mining approaches

A number of biomedical text mining systems have been developed to extract biologically relevant information directly from the literature, complementing bioinformatics methods in the analysis of experimentally generated data. We provide a short overview of the general characteristics of natural language data, existing biomedical literature databases, and lexical resources relevant in the context of biomedical text mining. A selected number of practically useful systems are introduced together with the type of user queries supported and the results they generate. The extraction of biological relationships, such as protein-protein interactions as well as metabolic and signaling pathways using information extraction systems, will be discussed through example cases of cancer-relevant proteins. Basic strategies for detecting associations of genes to diseases together with literature mining of mutations, SNPs, and epigenetic information (methylation) are described. We provide an overview of disease-centric and gene-centric literature mining methods for linking genes to phenotypic and genotypic aspects. Moreover, we discuss recent efforts for finding biomarkers through text mining and for gene list analysis and prioritization. Some relevant issues for implementing a customized biomedical text mining system will be pointed out. To demonstrate the usefulness of literature mining for the molecular oncology domain, we implemented two cancer-related applications. The first tool consists of a literature mining system for retrieving human mutations together with supporting articles. Specific gene mutations are linked to a set of predefined cancer types. The second application consists of a text categorization system supporting breast cancer-specific literature search and document-based breast cancer gene ranking. Future trends in text mining emphasize the importance of community efforts such as the BioCreative challenge for the development and integration of multiple systems into a common platform provided by the BioCreative Metaserver.

MedlineRanker: flexible ranking of biomedical literature

The biomedical literature is represented by millions of abstracts available in the Medline database. These abstracts can be queried with the PubMed interface, which provides a keyword-based Boolean search engine. This approach shows limitations in the retrieval of abstracts related to very specific topics, as it is difficult for a non-expert user to find all of the most relevant keywords related to a biomedical topic. Additionally, when searching for more general topics, the same approach may return hundreds of unranked references. To address these issues, text mining tools have been developed to help scientists focus on relevant abstracts. We have implemented the MedlineRanker webserver, which allows a flexible ranking of Medline for a topic of interest without expert knowledge. Given some abstracts related to a topic, the program deduces automatically the most discriminative words in comparison to a random selection. These words are used to score other abstracts, including those from not yet annotated recent publications, which can be then ranked by relevance. We show that our tool can be highly accurate and that it is able to process millions of abstracts in a practical amount of time. MedlineRanker is free for use and is available at http://cbdm.mdc-berlin.de/tools/medlineranker.

Pharmspresso: a text mining tool for extraction of pharmacogenomic concepts and relationships from full text

Background

Pharmacogenomics studies the relationship between genetic variation and the variation in drug response phenotypes. The field is rapidly gaining importance: it promises drugs targeted to particular subpopulations based on genetic background. The pharmacogenomics literature has expanded rapidly, but is dispersed in many journals. It is challenging, therefore, to identify important associations between drugs and molecular entities – particularly genes and gene variants, and thus these critical connections are often lost. Text mining techniques can allow us to convert the free-style text to a computable, searchable format in which pharmacogenomic concepts (such as genes, drugs, polymorphisms, and diseases) are identified, and important links between these concepts are recorded. Availability of full text articles as input into text mining engines is key, as literature abstracts often do not contain sufficient information to identify these pharmacogenomic associations.

Results

Thus, building on a tool called Textpresso, we have created the Pharmspresso tool to assist in identifying important pharmacogenomic facts in full text articles. Pharmspresso parses text to find references to human genes, polymorphisms, drugs and diseases and their relationships. It presents these as a series of marked-up text fragments, in which key concepts are visually highlighted. To evaluate Pharmspresso, we used a gold standard of 45 human-curated articles. Pharmspresso identified 78%, 61%, and 74% of target gene, polymorphism, and drug concepts, respectively.

Conclusion

Pharmspresso is a text analysis tool that extracts pharmacogenomic concepts from the literature automatically and thus captures our current understanding of gene-drug interactions in a computable form. We have made Pharmspresso available at .

How to Interpret PubMed Queries and Why It Matters

A significant fraction of queries in PubMed^™ are multiterm queries without parsing instructions. Generally, search engines interpret such queries as collections of terms, and handle them as a Boolean conjunction of these terms. However, analysis of queries in PubMed^™ indicates that many such queries are meaningful phrases, rather than simple collections of terms. In this study, we examine whether or not it makes a difference, in terms of retrieval quality, if such queries are interpreted as a phrase or as a conjunction of query terms. And, if it does, what is the optimal way of searching with such queries. To address the question, we developed an automated retrieval evaluation method, based on machine learning techniques, that enables us to evaluate and compare various retrieval outcomes. We show that the class of records that contain all the search terms, but not the phrase, qualitatively differs from the class of records containing the phrase. We also show that the difference is systematic, depending on the proximity of query terms to each other within the record. Based on these results, one can establish the best retrieval order for the records. Our findings are consistent with studies in proximity searching.

Evaluating relevance ranking strategies for MEDLINE retrieval

This paper evaluates the retrieval effectiveness of relevance ranking strategies on a collection of 55 queries and about 160,000 MEDLINE((R)) citations used in the 2006 and 2007 Text Retrieval Conference (TREC) Genomics Tracks. The authors study two relevance ranking strategies: term frequency-inverse document frequency (TF-IDF) weighting and sentence-level co-occurrence, and examine their ability to rank retrieved MEDLINE documents given user queries. Furthermore, the authors use the reverse chronological order-PubMed's default display option-as a baseline for comparison. Retrieval effectiveness is assessed using both mean average precision and mean rank precision. Experimental results show that retrievals based on the two strategies had improved performance over the baseline performance, and that TF-IDF weighting is more effective in retrieving relevant documents based on the comparison between the two strategies.

Analysis of queries sent to PubMed at the point of care: observation of search behaviour in a medical teaching hospital

BACKGROUND

The use of PubMed to answer daily medical care questions is limited because it is challenging to retrieve a small set of relevant articles and time is restricted. Knowing what aspects of queries are likely to retrieve relevant articles can increase the effectiveness of PubMed searches. The objectives of our study were to identify queries that are likely to retrieve relevant articles by relating PubMed search techniques and tools to the number of articles retrieved and the selection of articles for further reading.

METHODS

This was a prospective observational study of queries regarding patient-related problems sent to PubMed by residents and internists in internal medicine working in an Academic Medical Centre. We analyzed queries, search results, query tools (Mesh, Limits, wildcards, operators), selection of abstract and full-text for further reading, using a portal that mimics PubMed.

RESULTS

PubMed was used to solve 1121 patient-related problems, resulting in 3205 distinct queries. Abstracts were viewed in 999 (31%) of these queries, and in 126 (39%) of 321 queries using query tools. The average term count per query was 2.5. Abstracts were selected in more than 40% of queries using four or five terms, increasing to 63% if the use of four or five terms yielded 2-161 articles.

CONCLUSION

Queries sent to PubMed by physicians at our hospital during daily medical care contain fewer than three terms. Queries using four to five terms, retrieving less than 161 article titles, are most likely to result in abstract viewing. PubMed search tools are used infrequently by our population and are less effective than the use of four or five terms. Methods to facilitate the formulation of precise queries, using more relevant terms, should be the focus of education and research.

Multi-database mining

Biomedical data useful for data mining are often distributed across multiple databases. These databases may be aggregated using several techniques to create single data sets that may be mined using standard approaches; however, separate databases may, in their design or data representation, capture information that is analytically useful and that is lost on integration. Recent techniques for mining multiple databases simultaneously but separately may preserve and leverage the unique perspectives within each database. This article presents an example, "dual mining," in which concurrent analysis of a target database with a related knowledge base can improve the identification of association patterns in the target most likely to be of interest for further analysis.

MScanner: a classifier for retrieving Medline citations

Background

Keyword searching through PubMed and other systems is the standard means of retrieving information from Medline. However, ad-hoc retrieval systems do not meet all of the needs of databases that curate information from literature, or of text miners developing a corpus on a topic that has many terms indicative of relevance. Several databases have developed supervised learning methods that operate on a filtered subset of Medline, to classify Medline records so that fewer articles have to be manually reviewed for relevance. A few studies have considered generalisation of Medline classification to operate on the entire Medline database in a non-domain-specific manner, but existing applications lack speed, available implementations, or a means to measure performance in new domains.

Results

MScanner is an implementation of a Bayesian classifier that provides a simple web interface for submitting a corpus of relevant training examples in the form of PubMed IDs and returning results ranked by decreasing probability of relevance. For maximum speed it uses the Medical Subject Headings (MeSH) and journal of publication as a concise document representation, and takes roughly 90 seconds to return results against the 16 million records in Medline. The web interface provides interactive exploration of the results, and cross validated performance evaluation on the relevant input against a random subset of Medline. We describe the classifier implementation, cross validate it on three domain-specific topics, and compare its performance to that of an expert PubMed query for a complex topic. In cross validation on the three sample topics against 100,000 random articles, the classifier achieved excellent separation of relevant and irrelevant article score distributions, ROC areas between 0.97 and 0.99, and averaged precision between 0.69 and 0.92.

Conclusion

MScanner is an effective non-domain-specific classifier that operates on the entire Medline database, and is suited to retrieving topics for which many features may indicate relevance. Its web interface simplifies the task of classifying Medline citations, compared to building a pre-filter and classifier specific to the topic. The data sets and open source code used to obtain the results in this paper are available on-line and as supplementary material, and the web interface may be accessed at .

Anne O'Tate: A tool to support user-driven summarization, drill-down and browsing of PubMed search results

BACKGROUND

PubMed is designed to provide rapid, comprehensive retrieval of papers that discuss a given topic. However, because PubMed does not organize the search output further, it is difficult for users to grasp an overview of the retrieved literature according to non-topical dimensions, to drill-down to find individual articles relevant to a particular individual's need, or to browse the collection.

RESULTS

In this paper, we present Anne O'Tate, a web-based tool that processes articles retrieved from PubMed and displays multiple aspects of the articles to the user, according to pre-defined categories such as the "most important" words found in titles or abstracts; topics; journals; authors; publication years; and affiliations. Clicking on a given item opens a new window that displays all papers that contain that item. One can navigate by drilling down through the categories progressively, e.g., one can first restrict the articles according to author name and then restrict that subset by affiliation. Alternatively, one can expand small sets of articles to display the most closely related articles. We also implemented a novel cluster-by-topic method that generates a concise set of topics covering most of the retrieved articles.

CONCLUSION

Anne O'Tate is an integrated, generic tool for summarization, drill-down and browsing of PubMed search results that accommodates a wide range of biomedical users and needs. It can be accessed at 4. Peer review and editorial matters for this article were handled by Aaron Cohen.