Dataset Information

Are men difficult to find? Identifying male-specific studies in MEDLINE and Embase.

ABSTRACT: BACKGROUND:Systematic reviews often investigate the effectiveness of interventions for one sex. However, identifying interventions with data presented according to the sex of study participants can be challenging due to suboptimal indexing in bibliographic databases and poor reporting in titles and abstracts. The purposes of this study were to develop a highly sensitive search filter to identify literature relevant to men's health and to assess the performance of a range of sex-specific search terms used individually and in various combinations. METHODS:Comprehensive electronic searches were undertaken across a range of databases to inform a series of systematic reviews investigating obesity management for men. The included studies formed a reference standard set. A set of sex-specific search terms, identified from database-specific controlled vocabularies and from natural language used in the titles and abstracts of relevant papers, was investigated in MEDLINE and Embase. Sensitivity, precision, number needed to read (NNR) and percent reduction in results compared to searching without sex-specific terms were calculated. RESULTS:The reference standard set comprised 57 papers in MEDLINE and 63 in Embase. Seven sex-specific search terms were identified. Searching without sex-specific terms returned 31,897 results in MEDLINE and 37,351 in Embase and identified 84% (MEDLINE) and 83% (Embase) of the reference standard sets. The best performing individual sex-specific term achieved 100%/98% sensitivity (MEDLINE/Embase), NNR 544/609 (MEDLINE/Embase) and reduced the number of results by 18%/17% (MEDLINE/Embase), relative to searching without sex-specific terms. The best performing filter, compromising different combinations of controlled vocabulary terms and natural language, achieved higher sensitivity (MEDLINE and Embase 100%), greater reduction in number of results (MEDLINE/Embase 24%/20%) and greater reduction in NNR (MEDLINE/Embase 506/578) than the best performing individual sex-specific term. CONCLUSIONS:The proposed MEDLINE and Embase filters achieved high sensitivity and a reduction in the number of search results and NNR, indicating that they are useful tools for efficient, comprehensive literature searching but their performance is partially dependent on the appropriate use of database controlled vocabularies and index terms.

SUBMITTER: Stewart F

PROVIDER: S-EPMC4120011 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Are men difficult to find? Identifying male-specific studies in MEDLINE and Embase.

Stewart Fiona F Fraser Cynthia C Robertson Clare C Avenell Alison A Archibald Daryll D Douglas Flora F Hoddinott Pat P van Teijlingen Edwin E Boyers Dwayne D

Systematic reviews 20140718

<h4>Background</h4>Systematic reviews often investigate the effectiveness of interventions for one sex. However, identifying interventions with data presented according to the sex of study participants can be challenging due to suboptimal indexing in bibliographic databases and poor reporting in titles and abstracts. The purposes of this study were to develop a highly sensitive search filter to identify literature relevant to men's health and to assess the performance of a range of sex-specific ...[more]

PMID: 25033713

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Project description:BackgroundCluster randomized trials (CRTs) are becoming an increasingly important design. However, authors of CRTs do not always adhere to requirements to explicitly identify the design as cluster randomized in titles and abstracts, making retrieval from bibliographic databases difficult. Machine learning algorithms may improve their identification and retrieval. Therefore, we aimed to develop machine learning algorithms that accurately determine whether a bibliographic citation is a CRT report.MethodsWe trained, internally validated, and externally validated two convolutional neural networks and one support vector machine (SVM) algorithm to predict whether a citation is a CRT report or not. We exclusively used the information in an article citation, including the title, abstract, keywords, and subject headings. The algorithms' output was a probability from 0 to 1. We assessed algorithm performance using the area under the receiver operating characteristic (AUC) curves. Each algorithm's performance was evaluated individually and together as an ensemble. We randomly selected 5000 from 87,633 citations to train and internally validate our algorithms. Of the 5000 selected citations, 589 (12%) were confirmed CRT reports. We then externally validated our algorithms on an independent set of 1916 randomized trial citations, with 665 (35%) confirmed CRT reports.ResultsIn internal validation, the ensemble algorithm discriminated best for identifying CRT reports with an AUC of 98.6% (95% confidence interval: 97.8%, 99.4%), sensitivity of 97.7% (94.3%, 100%), and specificity of 85.0% (81.8%, 88.1%). In external validation, the ensemble algorithm had an AUC of 97.8% (97.0%, 98.5%), sensitivity of 97.6% (96.4%, 98.6%), and specificity of 78.2% (75.9%, 80.4%)). All three individual algorithms performed well, but less so than the ensemble.ConclusionsWe successfully developed high-performance algorithms that identified whether a citation was a CRT report with high sensitivity and moderately high specificity. We provide open-source software to facilitate the use of our algorithms in practice.

Project description:BackgroundFinding duplicates is an important phase of systematic review. However, no consensus regarding the methods to find duplicates has been provided. This study aims to describe a pragmatic strategy of combining auto- and hand-searching duplicates in systematic review and to evaluate the prevalence and characteristics of duplicates.Methods and findingsLiteratures regarding portal vein thrombosis (PVT) and Budd-Chiari syndrome (BCS) were searched by the PubMed, EMBASE, and Cochrane library databases. Duplicates included one index paper and one or more redundant papers. They were divided into type-I (duplicates among different databases) and type-II (duplicate publications in different journals/issues) duplicates. For type-I duplicates, reference items were further compared between index and redundant papers. Of 10936 papers regarding PVT, 2399 and 1307 were identified as auto- and hand-searched duplicates, respectively. The prevalence of auto- and hand-searched redundant papers was 11.0% (1201/10936) and 6.1% (665/10936), respectively. They included 3431 type-I and 275 type-II duplicates. Of 11403 papers regarding BCS, 3275 and 2064 were identified as auto- and hand-searched duplicates, respectively. The prevalence of auto- and hand-searched redundant papers was 14.4% (1640/11403) and 9.1% (1039/11403), respectively. They included 5053 type-I and 286 type-II duplicates. Most of type-I duplicates were identified by auto-searching method (69.5%, 2385/3431 in PVT literatures; 64.6%, 3263/5053 in BCS literatures). Nearly all type-II duplicates were identified by hand-searching method (94.9%, 261/275 in PVT literatures; 95.8%, 274/286 in BCS literatures). Compared with those identified by auto-searching method, type-I duplicates identified by hand-searching method had a significantly higher prevalence of wrong items (47/2385 versus 498/1046, p<0.0001 in PVT literatures; 30/3263 versus 778/1790, p<0.0001 in BCS literatures). Most of wrong items originated from EMBASE database.ConclusionGiven the inadequacy of a single strategy of auto-searching method, a combined strategy of auto- and hand-searching methods should be employed to find duplicates in systematic review.

Project description:BackgroundResearchers performing systematic reviews (SRs) must carefully consider the relevance of thousands of citations retrieved from bibliographic database searches, the majority of which will be excluded later on close inspection. Well-developed bibliographic searches are generally created with thesaurus or index terms in combination with keywords found in the title and/or abstract fields of citation records. Records in the bibliographic database Embase contain many more thesaurus terms than MEDLINE. Here, we aim to examine how limiting searches to major thesaurus terms (in MEDLINE called focus terms) in Embase and MEDLINE as well as limiting to words in the title and abstract fields of those databases affects the overall recall of SR searches.MethodsTo examine the impact of using search techniques aimed at higher precision, we analyzed previously completed SRs and focused our original searches to major thesaurus terms or terms in title and/or abstract only in Embase.com or in Embase.com and MEDLINE (Ovid) combined. We examined the total number of search results in both Embase and MEDLINE and checked whether included references were retrieved by these more focused approaches.ResultsFor 73 SRs, we limited Embase searches to major terms only while keeping the search in MEDLINE and other databases such as Web of Science as they were. The overall search yield (or total number of search results) was reduced by 8%. Six reviews (9%) lost more than 5% of the relevant references. Limiting Embase and MEDLINE to major thesaurus terms, the number of references was 13% lower. For 15% of the reviews, the loss of relevant references was more than 5%. Searching Embase for title and abstract caused a loss of more than 5% in 16 reviews (22%), while limiting Embase and MEDLINE that way this happened in 24 reviews (33%).ConclusionsOf the four search options, two options substantially reduced the overall search yield. However, this also resulted in a greater chance of losing relevant references, even though many references were still found in other databases such as Web of Science.

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Are men difficult to find? Identifying male-specific studies in MEDLINE and Embase.

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Are men difficult to find? Identifying male-specific studies in MEDLINE and Embase.

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