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Hartung D.M.,Oregon State University | Hartung D.M.,Oregon Health And Science University | Zarin D.A.,National Library of Medicine | Guise J.-M.,Oregon Health And Science University | And 3 more authors.
Annals of Internal Medicine | Year: 2014

Background: ClinicalTrials.gov requires reporting of result summaries for many drug and device trials. Purpose: To evaluate the consistency of reporting of trials that are registered in the ClinicalTrials.gov results database and published in the literature. Data Sources: ClinicalTrials.gov results database and matched publications identified through ClinicalTrials.gov and a manual search of 2 electronic databases. Study Selection: 10% random sample of phase 3 or 4 trials with results in the ClinicalTrials.gov results database, completed before 1 January 2009, with 2 or more groups. Data Extraction: One reviewer extracted data about trial design and results from the results database and matching publications. A subsample was independently verified. Data Synthesis: Of 110 trials with results, most were industrysponsored, parallel-design drug studies. The most common inconsistency was the number of secondary outcome measures reported (80%). Sixteen trials (15%) reported the primary outcome description inconsistently, and 22 (20%) reported the primary outcome value inconsistently. Thirty-eight trials inconsistently reported the number of individuals with a serious adverse event (SAE); of these, 33 (87%) reported more SAEs in ClinicalTrials.gov. Among the 84 trials that reported SAEs in ClinicalTrials.gov, 11 publications did not mention SAEs, 5 reported them as zero or not occurring, and 21 reported a different number of SAEs. Among 29 trials that reported deaths in ClinicalTrials.gov, 28% differed from the matched publication. Limitation: Small sample that included earliest results posted to the database. Conclusion: Reporting discrepancies between the ClinicalTrials.gov results database and matching publications are common. Which source contains the more accurate account of results is unclear, although ClinicalTrials.gov may provide a more comprehensive description of adverse events than the publication. © 2014 American College of Physicians. Source

Jimeno-Yepes A.,National Library of Medicine
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium | Year: 2011

MEDLINE indexing performed by the US National Library of Medicine staff describes the essence of a biomedical publication in about 14 Medical Subject Headings (MeSH). Since 2002, this task is assisted by the Medical Text Indexer (MTI) program. We present a bottom-up approach to MEDLINE indexing in which the abstract is searched for indicators for a specific MeSH recommendation in a two-step process. Supervised machine learning combined with triage rules improves sensitivity of recommendations while keeping the number of recommended terms relatively small. Improvement in recommendations observed in this work warrants further exploration of this approach to MTI recommendations on a larger set of MeSH headings. Source

Fung K.W.,National Library of Medicine
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium | Year: 2012

Two mapping projects are currently underway, creating maps from SNOMED CT to ICD-10 and ICD-10-CM respectively. Even though the two projects belong to different organizations, there has been a lot of synergism between them. The ICD-10-CM map project heavily re-used the mapping methodology, tools and map data developed in the ICD-10 map project. An algorithm was derived to generate candidate ICD-10-CM map records from the ICD-10 map. We evaluated the algorithm in 5,264 SNOMED CT concepts common to both maps. 4,317 ICD-10-CM candidate maps could be generated from the ICD-10 map and 3,341 (77%) of the generated maps agreed with the published map. By priming the mapping process with candidate maps generated from the other map project, significant saving in time and effort in future phases of the two projects can be anticipated. The reasons for the discordance between the generated map and published map were also analyzed. Source

Adamusiak T.,National Library of Medicine
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium | Year: 2012

To assess whether errors can be found in LOINC by changing its representation to OWL DL and comparing its classification to that of SNOMED CT. We created Description Logic definitions for LOINC concepts in OWL and merged the ontology with SNOMED CT to enrich the relatively flat hierarchy of LOINC parts. LOINC - SNOMED CT mappings were acquired through UMLS. The resulting ontology was classified with the ConDOR reasoner. Transformation into DL helped to identify 427 sets of logically equivalent LOINC codes, 676 sets of logically equivalent LOINC parts, and 239 inconsistencies in LOINC multiaxial hierarchy. Automatic classification of LOINC and SNOMED CT combined increased the connectivity within LOINC hierarchy and increased its coverage by an additional 9,006 LOINC codes. LOINC is a well-maintained terminology. While only a relatively small number of logical inconsistencies were found, we identified a number of areas where LOINC could benefit from the application of Description Logic. Source

Bentolila S.,Cornell University | Stefanov S.,National Library of Medicine
Plant Physiology | Year: 2012

Plant mitochondrial genomes have features that distinguish them radically from their animal counterparts: a high rate of rearrangement, of uptake and loss of DNA sequences, and an extremely low point mutation rate. Perhaps the most unique structural feature of plant mitochondrial DNAs is the presence of large repeated sequences involved in intramolecular and intermolecular recombination. In addition, rare recombination events can occur across shorter repeats, creating rearrangements that result in aberrant phenotypes, including pollen abortion, which is known as cytoplasmic male sterility (CMS). Using nextgeneration sequencing, we pyrosequenced two rice (Oryza sativa) mitochondrial genomes that belong to the indica subspecies. One genome is normal, while the other carries the wild abortive-CMS. We find that numerous rearrangements in the rice mitochondrial genome occur even between close cytotypes during rice evolution. Unlike maize (Zea mays), a closely related species also belonging to the grass family, integration of plastid sequences did not play a role in the sequence divergence between rice cytotypes. This study also uncovered an excellent candidate for the wild abortive-CMS-encoding gene; like most of the CMS-associated open reading frames that are known in other species, this candidate was created via a rearrangement, is chimeric in structure, possesses predicted transmembrane domains, and coopted the promoter of a genuine mitochondrial gene. Our data give new insights into rice mitochondrial evolution, correcting previous reports. © 2011 American Society of Plant Biologists. Source

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