Like a hypermarket

New Pubmed’s interface

There is one thing that happens on a recurring basis and that is a real slap in the face for me. It turns out that I like to go shopping for food once a week, so I usually go to the hypermarket every Friday. I am a creature of habit that always eats the same things and almost the same days, so I go swift and fast through the aisles of the hyper throwing things in the shopping cart so I have the matter settled in the twinkling of an eye. The problem is that in hypermarkets they have the bad habit of periodically changing foods sites, so you go crazy until you learn its new location again. To cap it all, the first few days foods have been changed, but not yet its information panels, so I have to go around a thousand turns until I find the cans of squid in their ink that, as we all know, are one of our main staple foods.

You will wonder why I tell you all this stuff. As it turns out, the National Library of Medicine (NML) has done a similar thing: now that I had finally managed to learn how the its search engine worked, they go and change it completely.

Of course, it must be said in honor of the truth that NML’s people have not limited themselves to changing the aspects of windows and boxes, but have implemented a radical change with an interface that they define as cleaner and simpler, as well as better adapted to mobile devices, which are increasingly used to do bibliographic searches. But that doesn’t end there: there are a lot of improvements in the algorithms to find the more than 30 million citations that Pubmed includes and, in addition, the platform is hosted in the cloud, promising to be more stable and efficient.

New Pubmed’s interface

The NLM announced the new Pubmed in October 2019 and it will be the default option at the beginning of the year 2020 so, although the legacy version will be available a few more months, we have no choice but to learn how to handle the new version. Let’s take a look.

Although all the functionalities that we know of the legacy version are also present in the new one, the aspect is radically different from the home page, which I show you in the first figure.The most important element is the new search box, where we have to enter the text to click on the “Search” button. If the NLM does not deceive us, this will be the only resource that we will have to use the vast majority of the time, although we still have a link at our disposal to enter the advanced search mode.

Below we have four sections, including the one that contains help to learn how to use the new version, and that include tools that we already knew, such as “Clinical Queries”, “Single Citation Matcher” or “MeSH Database”. At the time of writing this post, these links direct you to the old versions of the tools, but this will change when the new interface is accessed by default.

Finally, a new component called “Trending Articles” has been added at the bottom. Here are articles of interest, which do not have to be the most recent ones, but those that have aroused interest lately and have been viralized in one way or another. Next to this we have the “Latest Literature” section, where recent articles from high impact journals are shown.

Now let’s see a little how searches are done using the new Pubmed. One of the keys to this update is the simple search box, which has become much smarter by incorporating a series of new sensors that, according to the NLM, try to detect exactly what we want to look for from the text we have inserted.

For example, if we enter information about the author, the abbreviation of the journal and the year of publication, the citation sensor will detect that we have entered basic citation information and will try to find the article we are looking for. For example, if I type ” campoy jpgn 2019″, I will get the results you see in second figure, where Pubmed shows the two articles found published by this doctor in this Journal in 2019. It would be something like what before we obtained using the “Single Citation Matcher”.

We can also do the search in a more traditional way. For example, if we want to search by author, it is best to write the last name followed by the initial of the name, all in lower case, without labels or punctuation marks. For example, if we want to look for articles by Yvan Vandenplas, we will write “vandenplas y”, with which we will obtain the papers that I show you in the third figure. Of course, we can also search by subject. If I type “parkinson” in the search box, Pubmed will make a series of suggestions on similar search terms. If I press “Search”, I get the results of the fourth figure which, as you can see , includes all the results with the related terms.

Let us now turn to the results page, which is also full of surprises. You can see a detail in the fifth figure. Under the search box we have two links: “Advanced”, to access the advanced search, and “Create alert”, so that Pubmed notifies us every time a new related article is incorporated (you already know that for this to be possible we have to create an account in NCBI and enter by pressing the “Login” button at the top; this account is free and saves all our activity in Pubmed for later use).

Below these links there are three buttons which allow you to save the search ( “Save”), send it by e-mail (“Email”) and, clicking the three points button, send it to the clipboard or to our bibliography or collections, if we have an NCBI account.

On the right we have the buttons to sort the results. The “Best Match” is one of the new priorities of the NLM, which tries to show us in the first positions the most relevant articles. Anyway, we can sort them in chronological order (“Most recent”), as well as change the way of presenting them by clicking on the gearwheel on the right (in “Summary” or “Abstract” format).

We are going to focus now into the left of the results page. The first thing we see is a graph with the results indexed by year. This graph can be enlarged, which allows us to see the evolution of the number of papers on the subject indexed over time. In addition, we can modify the time interval and restrict the search to what is published in a given period. In the sixth figure I show you how to limit the search to the results of the last 10 years.Under each result we have two new links: “Cite” and “Share”. The first allows us to write the work citation in several different formats. The second, share it on social networks.

Finally, to the left of the results screen we have the list of filters that we can apply. These can be added or removed in a similar way to how it was done with the legacy version of Pubmed and its operation is very intuitive, so we will not spend more time on them.

If we click on one of the items in the list of results we will access the screen with the text of the paper (seventh figure). This screen is similar to that of the legacy version of Pubmed, although new buttons such as “Cite” and those for accessing social networks are included, as well as additional information on related articles and articles in which the one we have selected is cited. Also, as a novelty, we have some navigation arrows on the left and right ends of the screen to change to the text of the previous and subsequent articles, respectively.

Advanced search

To finish this post, let’s take a look at the new advanced search, which can be accessed by clicking on the “Advanced” link, which will take us to the screen you see in the eighth figure.

Its operation is very similar to the legacy version. We can add terms with Boolean operators, combine searches, etc. I encourage you to play with the advanced search, the possibilities are endless. The newest part of this tool is the section with the history and the search details (“History and Search Details”) at the bottom. This allows you to keep previous searches and return to them, taking into account that all this is lost when you leave Pubmed, unless you have an NCBI account.

I call your attention to the “Search Details” tab, which you can open as shown in the ninth figure. The search becomes more transparent, since it shows how Pubmed interpreted it based on an automatic system of choice of terms (“Automatic Term Mapping”). Although we do not know very well how to narrow the search to specific terms of Parkinson’s disease, Pubmed does know what we are looking for and includes all the terms in the search, in addition to the initial text that we introduced, of course.

We’re leaving…

And here we end for today. You have seen that these people of the NLM have outdone themselves, putting at our disposal a new tool easier to use, but at the same time, much more powerful and intelligent. Google must be shaking with fear, but don’t worry, it is sure it will invent something to try to prevail.

You can go forgetting about the legacy version, do not wait for it to disappear to start enjoying the new one. We will have to talk about these issues again when new versions of the rest of the tools are established, such as Clinical Queries, but that is another story …

The jargon of the search engine

Searching  Pubmed using MeSH terms

We saw in a previous post how to do a Pubmed search using the simplest system, which is to enter natural language text in the simple search box and press the “Search” button. This method is quite easy and even works quite well when we are looking for something about very rare diseases but, in general, it will give us a very sensitive and unspecific results list, which in this context means that we will get a large number of articles, but many of them will have little to do with what we are looking for.

In these cases we will have to use some tool to make the result more specific: fewer articles and more related to the problem that originates the search. One of the ways is to perform an advanced search instead of a simple search, but for this we will have to use the browser’s own jargon, the so-called thematic descriptors of controlled language.

Some previous definitions

A descriptor is a term used to construct indexes, also called thesauri. Instead of using the words of the natural language, they are selected or grouped under specific terms, which are to serve as a key in the index of the search engine database.

The thesaurus, formed by the set of descriptors, is specific to each search engine, although many terms may be common. In the case of Pubmed the descriptors are known as MeSH terms, which are the initials of Medical Subject Headings.

This thesaurus or list of terms with controlled vocabulary has also been developed by the National Library of Medicine and constitutes another database with more than 30,000 terms that are updated annually. Within the National Library there are a number of people whose mission is to analyze the new articles that are incorporated into the Medline database and assign them the descriptors that best fit their content. Thus, when we search using a particular descriptor, we will find the articles that are indexed with this descriptor.

Searching Pubmed using MeSH terms

But the thing of the descriptors is a little more complicated than it may seem, since they are grouped in hierarchies (MeSH Tree Structures), being able to a same descriptor to belong to several hierarchies, in addition to having subheadings, of such form that we can search using the general MeSH term or further narrow the search using one of its subheaders. The truth is that reading all this makes us want to forget the search using the thesaurus, but we cannot afford that luxury: the search using the MeSH database is the most effective and accurate, since the language has been controlled to eliminate inaccuracies and synonyms of natural language.

Also, the thing is not so complicated when we get to work with it. Let’s see it with the example we use to display the simple search. We want to compare the efficacy of amoxicillin and cefaclor on the duration of otitis media in infants. After elaborating the structured clinical question we obtain our five terms of search, in natural language: otitis, infants, amoxicillin, cefaclor and prognosis.

Now we can go to the Pubmed home page (remember the shortcut: type pubmed in the browser bar and press control-enter). Below the simple search window we saw that there are three columns. We look at the one on the right, “More Resources” and click on the first option, “MeSH Database”, which gives us access to the homepage of the database descriptors (as seen in the first figure).If we write otitis in the search window we see that Pubmed lends us a hand by displaying a list of terms that look like what we are writing. One of them is otitis media, which is what we are interested in, so we select it and Pubmed takes us to the next page where there are several options to choose from. At the moment I do the search there are three options: “Otitis Media”, “Otitis Media, Suppurative” and “Otitis Media with Effusion”. Notice that Pubmed defines each term, so that we understand well what it means with each term. These are the three MeSH terms that fit what we asked for, but we have to choose one.

The simplest thing we can do from this window is to check the selection box to the left of the term that interests us and click the button on the right side of the screen that says “add to search builder”. If we do this, Pubmed begins to construct the search string starting with the chosen term. If we do this with the first term in the list you will see that the text “Otitis Media” [Mesh] appears in the text box “Pubmed Search Builder” , on the top right of the screen (as you can see in the attached figure).But remember that we have said that the MeSH terms have subheaders. To get them, instead of marking the selection box of the term “Otitis Media”, we click on the term, opening the window with the subheadings, as you can see in the second figure.

The hierarchical tree of MeSH terms

Each of the terms with their selection box on the left corresponds to a subheading of the descriptor “Otitis Media”. For example, if we were interested in doing a search directed to the cost of the treatment, we could mark the subheading “economics” and then press the button to add to the search. The text that would appear in the text box of the search string would be “Otitis Media / economics” [Mesh] and the search result would be a bit more specific.

Before leaving the MeSH term window let’s look at a few details. In addition to the subheadings, which can be more or less numerous, the bottom of the page shows the hierarchy of the descriptor (MeSH Tree Structure). Our descriptor is in bold, so we can see which terms it depends on and which ones depend on it. In some cases we may be more interested in using a higher term for the search, so we will have to click on it to go to its own window. If we do this, in general, the search will be more sensitive and less specific (more empty vessels).

We can also click on a term that is below the hierarchy, making the search more specific and decreasing the number of results.

And it does not end here. If we select a MeSH term for the search, it includes the terms that are below in the hierarchy. For example, if we select the descriptor “Otitis Media”, Pubmed will include in the search all that hang from it (mastoidits, otitis with effusion, suppurative otitis and petrositis, which may not interest us at all). This can be avoided by checking the box that says “Do not include MeSH terms found under this term in the MeSH hierarchy”.

An example to finish

Well, I think we’re going to end up with this example, if there is still someone who is still reading at this point. Let’s say we chose the simplest way: let’s go to “Otitis Media” and add it to the search. Next we write the second search term in the search window of the database: infants. We get 14 possibilities, select the first (“Infant”) and add it to the search. We do the same with “Amoxicillin”, “Cefaclor” and “Prognosis”. When we have added all of them to the search string (note that the default boolean operator is AND, but we can change it), the search string is as follows: (“(Otitis Media [Mesh]) AND” Infant ” Mesh]) AND “Amoxicillin” [Mesh]) AND “Cefaclor” [Mesh]) AND “Prognosis” [Mesh].

Finally, click the “Search PubMed” button and get the search result, which in this case is a bit more restricted than we obtained with natural language (this is usually the case).

If we wanted to remove the articles about the treatment with clavulanic acid, as we did in the example with the simple search, we could add the term clavulanate as we add the other terms, but changing the boolean operator AND by the NOT operator. But there is another way that is even simpler. If you notice, when Pubmed gives us the list of results, in the search window of Pubmed is written the search string that has been used and we can add or remove terms from this string, using MeSH or natural language terms, which we prefer. So, in our example, to the text string we would add NOT clavulanate in the search box and we would click on the “Search” button again.

We’re leaving…

And here we are going to leave it for today. Just saying that there are other ways to use MeSH terms, using the advanced search form, and we can further narrow the results using some resources, like the Clinical Queries or using limits. But that is another story…

The oyster with the thousand pearls

Simple search using Pubmed

We saw in a previous post that our ignorance as doctors is huge, which forces us to ask ourselves questions about what to do with our patients on numerous occasions.

At this point, we will be interested in seeking and finding the best available evidence on the subject that occupies us, for which we will have to do a good bibliographical search. Although the bibliographic search is defined as the set of manual, automatic and intellectual procedures aimed at locating, selecting and retrieving references or works that respond to our question, the vast majority of the time we simplify the process and we just do a digital search.

What is Pubmed?

In these cases we will have to resort to one of the many biomedical databases available to find the pearl that clarifies our doubt and help remedy our ignorance. Of all these databases, there is no doubt that the most widely used is Medline, the database of the National Library of Medicine. The problem is that Medline is a very large database, with about 16 million articles from more than 4800 scientific journals. So, as is easy to assume, finding what you are looking for may not be a simple task on many occasions.

In fact, when we use Medline what we use is a tool that is known as Pubmed. This is a project developed by the National Center for Biotechnology Information (NCBI for friends), which allows access to three National Library of Medicine databases: Medline, PreMedline and AIDS. These databases are not filtered, so we will need critical reading skills to evaluate the results (there are other resources that give the information already filtered), since the searcher provides nothing more (and nothing less) than the article reference and, in many cases, a brief summary. Best of all, it’s free, which is not the case with all the search tools available.

Pubmed’s interface

So, if we want to explore this oyster with thousands of pearls, we will have to learn how to use Pubmed to find the pearls we are looking for. You can enter Pubmed by clicking on this link, although a shortcut is to type pubmed in the address bar of the browser and press control-enter. The browser will know where we want to go and will redirect us to the Pubmed home page. Let’s take a look at starting to use it (see the first attached figure) (Pubmed look changes from time to time, so something may have changed since I wrote this post, probably to improve).

The first thing we see is the simple search box, where we can type the search terms to get the results by clicking the “Search” button. You see that under this box there is a link that says “Advanced”, with which we will access the advanced search screen, which we will talk about of another day. Today we will focus on the simple search.

Below are three columns. The first one says “Using PubMed.” Here you can find help on the use of this tool, including tutorials on the different search modalities and tools that includes Pubmed. I advise you to dive in this section to discover many more possibilities of this search engine than the few that I will tell you in this post.

The second column is the “PubMed Tools”. Here are two of special interest, the “Single Citation Matcher”, to find the reference in PubMed of a specific article knowing some aspects of its bibliographic citation, and “Clinical Queries”, that allow us to filter the results of the searches according to the type of studies or their characteristics.

The third column shows search engine’s resources, such as the MeSH database, which is nothing more than the search term thesaurus that includes Pubmed.

First, a structured clinical question

Well, let’s get something to practice. Let us think, for example, that I want to know if it is better to use amoxicillin or cefaclor for the treatment of otitis in infants so that the evolution of the disease is less prolonged. Logically, I can not write this as it is. First I have to build my structured clinical question and then use the components of the question as search terms.

My question would be: in (P) infants with otitis, (I) treatment with cefaclor (C) compared to treatment with amoxicillin, (0) reduces the duration of disease ?. So, with this example, we could use five search terms: otitis, infants, amoxicillin, cefaclor and duration.

Simple search using Pubmed

In the simple search we will simply enter the words in the search box (natural language) and click on the “Search” box.

The search box supports boolean operators, which are “y”, “o” and “not” (they are often capitalized: AND, OR and NOT). When we put several words in a row without any boolean operators, Pubmed understands that the words are separated by AND. Thus, if we have a term consisting of two words and we want it to be considered as one, we will have to write it in quotation marks. For example, if we write acute appendicitis and we want it to count as a single term, we will have to introduce “acute appendicitis”.

Another useful operator is the truncation, which is to place an asterisk (a wild mark) at the end of the root of the word to search for all words that begin with that root. For example, infan * will search for infant, infancy…

Let’s go with our example. We write otitis AND infants AND amoxicillin AND cefaclor AND course and click on “Search” (see the second attached figure). We were lucky enough; we get only 11 results (you can get a different number if you do the search at another time).

We take a look and see that the works are more or less adjusted to what we are looking for. The only drawback is that it includes articles that study the effect of amoxicillin-clavulanate, which we are not interested in. Well, we’re going to take them off. To the text of search we add NOT clavulanate, and we get an even more limited search.

We only have to select or click on the works that interest us to get the summary (if available) and, in some cases, even get access to the full text, although this will depend on whether the text is freely accessible or on the permissions or subscriptions of the institution from which we access to Pubmed.

We’re leaving…

So far we have seen the simplest way to search with Pubmed: simple search with free text. The problem is that using this form of search is not always going to get such a specific result, it will be much more frequent that we get thousands of results, most of them without any interest for us. In these cases we will have to resort to other resources such as advanced search, the use of MeSH terms or the use of Pubmed Clinical Queries. But that is another story…