Microsoft word - research project.doc
Karolina Kucerova Charles University in Prague Evidence-Based Medicine Course The University of North Carolina at Chapel Hill Spring 2004
This work intends to concentrate on comparison of two sources of medical
information included in the Medline database, PubMed and OVID. Its first part should
consist of some “academic information” about these resources, their history and
contents. The other part would give some examples of searches in both of these
sources, compare their strategy and outcomes. It should be user-oriented, given the
point of view of a person that is not meeting these resources in everyday practice.
Medline (Medical Literature, Analysis and Retrieval System Online) is the largest
bibliographic database of journal articles in the field of medicine, nursing, dentistry,
veterinary medicine, the health care system, and some other related sciences. It
contains over 12 million records in retrospective from year 1966. Over 4600 journals
in 30 languages are treated. Vast majority of cited articles is in English.
Medline’s provider is U.S. National Library of Medicine, who also makes the
database available via internet free of charge (some database centers – e.g. Dialog,
DataStar, STN International, OVID – offer Medline as well, charged of course). NLM
also allows searching in documents older than 1966 (NLM Gateway), offers
document delivery service for articles cited in Medline, and publishes a
consumer-oriented MedlinePlus service which is also free.
NLM uses and handles the widespread classification system Medical Subject
PubMed is a special service of U.S. National Library of Medicine and National Center
for Biotechnology Information (NCBI). It is part of an Entrez system that offers also
databases of Nucleotide and Protein Sequences, Protein Structures, Complete
PubMed offers not only Medline records but also links to full-text articles where
available; number of journals offering this service is growing.
PubMed contains also many additional services: you may use Journal database,
refine search terms in MeSH, search for particular article, use clinical queries – filters
for more efficient searching, and personalize PubMed and save searches and
Medline via PubMed was launched in 1997.
OVID Technologies is a database center, founded in 1988 in New York. In 1994 it
bought BRS Online, a large database center oriented on medicine and other life
sciences, and until now OVID belongs to leaders in medical information services. In
2001 OVID acquired another large database provider, the SilverPlatter.
OVID contains not only different bibliographic databases but also e-books, full-text
journals and several SilverPlatter databases (e.g. Health & Safety Publishing).
Medical specialist could well use the Clinical Decision Support section of OVID
content. Its Tools are aimed at helping clinicians in their daily work and Contents
involve resources including EBM reviews.
The use of PubMed and OVID
Even before performing any search I can state some differences between the
PubMed and OVID. They either result from the “theory,” or they can be experienced
during the use of tutorials (PubMed and OVID).
1. PubMed is free, and so it is more accessible for all possible users.
2. Concerning the interface, most OVID features are concentrated on one page,
they can be displayed at the same time, or they are referred in a simple way;
PubMed offers more utilities on new pages, many of whom are automatically
combined with the main search (but some are not).
3. Because of this I appreciate the possibility of saving the PubMed search as an
URL; if I got lost in the search, I can find the most relevant page in my
4. On the other hand, PubMed integrates more features for searching. These
include not only MeSH search etc., but also clinical queries filters or
availability of other Entrez resources (protein, genome information etc.)
5. OVID integrates another groups of resources – other databases, and also
special resources for EBM (Cochrane databases etc.) and clinical decisions
6. PubMed uses automatic explosion and automatic mapping which both can
help a lot in formulating strategy: man does not have to be so careful in
Of course there could be many more qualities found but I consider these the most
important ones that could be noticed without profound knowledge of the systems.
Other characteristics would appear in the searches.
Search No. 1
In the first search I am solving a problem of a 50-year-old woman coming to her
clinician with urinary incontinence. She wants to know whether she could benefit from
advertised medicines tolterodine or oxybutynin.
PICO question: In middle-aged women with urinary incontinence, are tolterodine or
oxybutynin an effective treatment? This question obviously focuses on therapy, and
so we will be looking for randomized controlled study.
The first thing I do is look for terms in MeSH. The drugs are not MeSH terms, urinary
incontinence is. Putting these terms in PubMed Search ((tolterodine OR oxybutynin) AND
urinary incontinence), I receive the expanded query ((("tolterodine"[Substance Name] OR
tolterodine[Text Word]) OR oxybutynine[All Fields]) AND ("urinary incontinence"[MeSH Terms] OR
urinary incontinence[Text Word])) and 84 results. Filtering it for middle-aged women, humans,
RCT’s and English language, I get 16 results.
Another possibility is to search the three main terms in Clinical queries. It gives a
very long query with 76 results. Imposing the same filter, 16 results appear again.
Looking at the results, it is obvious that many of them are very relevant, often head-
to-head studies. But maybe even more useful would be searching for systematic
The main query ((tolterodine OR oxybutynin) AND urinary incontinence) gives me 5 citations,
three or four of them seem to be highly relevant.
Their titles: Is tolterodine (Detrol) or oxybutynin (Ditropan) the best for treatment of
urge urinary incontinence?; Anticholinergic drugs versus placebo for overactive
bladder syndrome in adults (this one is from Cochrane Database of Systematic
Reviews); Tolterodine versus oxybutynin in the treatment of urge urinary
incontinence: a meta-analysis. and Tolterodine use for symptoms of overactive
Entering OVID, in this and the other search I choose only the Medline 1966-2004
database. Although I could earn more from the EBM publications, this project
In OVID I have to follow many steps. I search urinary incontinence as a MeSH term
(exploded), combine it with textwords tolterodine and oxybutynin. I have 242 results at
the moment. Limiting the search to systematic reviews and humans, I retrieve 10
citations. The ones retrieved via PubMed are among them.
Trying to get closer to my patient, I limit the search on English and middle-aged females:
2 results remain. Their titles are Is tolterodine (Detrol) or oxybutynin (Ditropan) the
best for treatment of urge urinary incontinence? and Behavioral vs. drug treatment for
urge urinary incontinence in older women: a randomized controlled trial. We can see
that even this refined search brought one citation PubMed did not notice.
Search No. 2
In this case a woman comes and wants to know whether her newborn child has
higher risk of allergy when sharing a flat with a pet cat.
PICO question: In infants, does intense cat exposure augment the risk of developing
allergies? This is a question of etiology/harm, I will be looking especially for cohort
In PubMed, I search for the terms in MeSH. I find the term Cats (not cat) and
hypersensitivity (not allergy). Knowing this, with the use of etiology/harm strategy I
formulate the query (cat OR cats) AND (allergy OR hypersensitivity) AND ("Case-control
studies"[MeSH] OR cohort), it gives me 156 relevant citations. Filtered for humans, infants
and English, 57 of them are left. The same query in clinical queries/harm gives 116
citations, 51 of them stay after the limit is imposed. Adding the word review to the
query, 7 citations are left. Their titles appear to be relevant: Early exposure to
allergen: is this the cat's meow, or are we barking up the wrong tree?; Early pet
exposure: friend or foe?; The development of childhood asthma: lessons from the
German Multicentre Allergy Study (MAS); The atopic child and the environment. If
they were not relevant, the larger set of citations can be sought.
Using the experience from PubMed I search terms cat and cats, hypersensitivity and
allergy, in Mesh and text, exploded where possible. Combining them results in 1902
citations. Adding the limit for case-control studies (MeSH term) and text word cohort, 135
matches remain. Of them 52 are in English, relate to humans under 2 years of age.
These appear to be the ones found by PubMed.
Limiting to systematic reviews is not useful as only 2 results remain. Trying to repeat
the PubMed strategy, I search for the term review. OVID automatically searches for
publication type and answers 0. Search for review as text word in combination with the
52 documents gives only one result. The only useful limit could possibly be the
publication year – 2000 through 2004 there are 34 articles matched.
Apart from the differences mentioned above, both the Medline providers offer
Searching via OVID might be more synoptic as every step is clearly visible in the
table. You can – or you even must – clearly define very step of your search. It
means, for example, that especially searching synonyms or similar terms is
exceedingly time-consuming; while paying for connect time this could be extremely
unpleasant. And what really annoys me? It is the interaction with the web browser:
the “Forward” and “Back” buttons do not work here, and I as I am using them
automatically all the time I often have to perform the search more than once.
PubMed can very easily make you lost. Either you forget to send the term from
MeSH to the search field, or you forget to delete the last search’s limits, or you
search for clinical query instead of systematic review… But otherwise the PubMed
tries to do as much work as possible for you, which is a great help especially for a
non-professional bibliographic researcher.
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