Research

Kudos

The Plain Language Movement & Law

The plain language movement started in both sides of the Atlantic in the 1970s to make law easy to understand. The legal documents were plagued by legalese and were thus inaccessible to the commoner. This problem can be traced back to almost a 1000 years when William, the Duke of Normandy defeated the Anglo-Saxon King Harold in the Battle of Hastings in 1066. As William and his followers spoke a dialect of French, English became the language of the common and lowly folk.
The courts and lawyers soon followed suit. Within a few decades the Legal system had became inscrutable to the common man. With the ascendancy of English came the urge to rid the system of the French and Latin terms and replace them with crisp Anglo Saxon words. The push to make common sense in common language fashionable had a reasonable amount of success.
The legal system and the people benefited a lot from making things simple. Unfortunately, the Plain Language movement only focused on the law, not medicine.

Saving Medicine From Medicalese

Flip(or click) through the pages of any medical journal and you will see how hard our language has become for anyone outside our profession to make sense of. Even among doctors, each discipline has its own jargon and stylistic idiosyncrasies making it harder for others to understand. We live in a time when obfuscation is celebrated as a skill and straight talk is scoffed at.
To give an example, I was reading a top endocrinology journal yesterday and was dismayed to find that the pages have been hijacked by genes, genes and more genes or molecules,molecules and more molecules. It felt like the journal had written in 100 size font in invisible ink – look, this is for the experts. No one else is welcome.
I am not arguing that the top journals should dumb down their content or ask authors to keep click baity titles. However I’m certain that the scientific community will be better served by a Cochrane style plain language summary for every scientific article. In fact developing a written version of the elevator pitch is likely to narrow our focus on what matters. However, most journals don’t have the space/ inclination for such summaries. We need a plain language movement for medicine.

What can we do in the meantime?

kudos-greater-research-impact
Kudos. It is a free online service to explain about your research in plain English. Each paper gets these four pieces of information – Title, What is about, Why is it important and the Perspectives of the author. Kudos also provides shareable links and can automatically post to Facebook, Twitter and LinkedIn. It can even track the response your article is generating! (It’s like having your own Altmetric dashboard)
Here’s a plain language summary of one of our papers – Tumor(s) Induced Osteomalacia- A curious case of double Trouble
If you are an academic, check out Kudos. It’s free and the experience can help you focus on what matters.

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The Insulin plant

Yeah..you read that right. There’s actually a plant called insulin plant and it’s supposed to reduce blood glucose levels(no surprise there).You have probably heard of several natural remedies for diabetes and are rolling your eyes now.. The diabetes armamentarium is brimming with antidiabetic agents which are effective and proven. Some like GLP1 analogues and SGLT2 inhibitors have even proven to have cardiovascular benefits.

So why bother about a plant?

For a couple of reasons

  • Research : There are many plants which have potential antidiabetic diabetic activity – infact there are at least 111 plants which are known to reduce blood glucose. (1). However the Indian patent laws do not allow patenting plants and more importantly medicines derived from natural products. I have always had trouble understanding the second clause – even if you do some fancy chemical extraction and make a useful substance that was essentially hidden underground for millennia, you wouldn’t get a patent in India. Consequently the incentive to exploit the “natural remedies” for commercial gain is very limited. Thus,most of these plants/plant based substances may never reach the market as a tablet. Does that mean we can’t study them or learn from them? Not really – one can essentially mimic a natural substance, tweak it, call it bioinspiration and pretend that the molecular structure was an epiphany during a coffee break ! Or at least apply for an AYUSH grant to do some research – I’m a novice here, but I guess there can’t a better time to apply for AYUSH grants than now. Even if we aren’t involved in the business of making drugs, if the natural form is safe enough, we can consume them. Even if the effect is modest.
  • Clinical: Apart from the research aspect, there is a huge public craze for cost effective natural remedies or drugs derived from plants. The runaway success of products like BGR34 is a testimony to this.

Now you might wonder, if this plant stuff is good, it should have a good scientific backing. Indeed there’s a good body of research behind this. But let’s be frank – research is often locked behind paywalls. Even when it is ‘accessible’ it isn’t truly accessible to those outside the profession – most people are turned off by graphs,tables and statistics. The idea of this post is to simply strip the complexity off the published scientific literature and bring the reader upto speed on this quirky plant.

Here’s a brief bio of the insulin plant in Q&A format

What exactly is the insulin plant?

This plant belongs to the Costaceae family – two species are common , the Costus igneus and the Costus pictus. The leaves of this plant are sometimes taken as supplements for reducing blood sugar. Known as the Spiral flag( insulin chedi in Tamil and Malayalam), the plant can grow upto 2 feet and has colorful flowers.

costus-igneus

What does the plant contain?

It contains triterpenoids such as α and β amyrin,lupeol, stigmatsterol.,Diosgenin etc. That’s a lot of active principles- but mostly we are yet to understand how these substances interact with one another and whether isolating them is more useful than the natural mixture in which they are found.

How do I get this plant?

The insulin plant can be obtained from a nursery or someone who is already using it. Care should be taken to avoid mistaking some other plant for this. For the purposes of research, the identity of the plant needs to be confirmed by the Botanical Survey of India,Coimbatore. They give an authentication certificate with a number and date.

Is it safe for human consumption?

Published Toxicity studies in animals show no major toxic effects in the short term (2). Anecdotal human evidence seems to support this. However one should remember that with plants/plant products, there are a lot of variables one must account for – subspecies,soil,part of the plant, extract or whole leaves, growth in shade vs sunlight etc. Since there are no published long term human studies, we are essentially on our own when consuming this. Consequently, those at risk of hypoglycemia (elderly, recurrent hypos, comorbid illness, kidney diseases) and pregnant women should strictly avoid experimenting on themselves.

Is it effective in reducing blood sugar?

Much of the published research on this plant is from animal studies. These animal studies generally show a reduction in blood glucose. You can get a gist of the published research in the form of table by clicking here

Homogeneity is hard to obtain in these studies. Only limited human data is available. The absence of data doesn’t mean absence of useful effect though.

Does it have any other uses?

These days plenty of drugs reduce glucose. It is only natural to expect more !. Plant products tend to have pleiotropic effects and may well have off target effects which we don’t want. There are some of the effects of the insulin plant.

  1. Hypolipidemic effect
  2. Antioxidant effect
  3. Diuretic effect
  4. Anticancer effect
  5. Reduces TSH (3)

What does the current research mean?

Very little is known about the insulin plant – especially the human use of it. However, with the public clamor for natural remedies, there may be a future for this plant/its products. Because of its pleiotropic effects, it might have a role in conditions such as prediabetes,subclinical hypothyroidism apart from diabetes.

To conclude, the insulin plant is a potential plant therapy for diabetes. However at present we don’t know much about its human use and thus must proceed with caution.It opens up several research areas. If found useful in raw form, it may become one of the cheapest ways of treating diabetes.

Further Reading

1. Eddouks M, Bidi A, El Bouhali B, Hajji L, Zeggwagh NA. Antidiabetic plants improving insulin sensitivity. J Pharm Pharmacol. 2014 Sep;66(9):1197–214.

2. Hegde PK, Rao HA, Rao PN. A review on Insulin plant (Costus igneus Nak). Pharmacogn Rev. 2014 Jan;8(15):67–72.

3. Ashwini S, Bobby Z, Sridhar MG, Cleetus CC. Insulin Plant (Costus pictus) Extract Restores Thyroid Hormone Levels in Experimental Hypothyroidism. Pharmacognosy Res. 2017 Mar;9(1):51–9.

Getting started with case reports

A case report is the perfect starting point for a resident new to scholarly publishing. It is easy to write, requires little creativity (after all it is just a documentation of a patient that came to meet the doctor) and though has limited impact, has good educational value. More than anything else, it lowers the barrier to scientific writing.


There is a catch though – case reports are the low hanging fruits. Accordingly there is quite a bit of competition there – lot of people want to write, very few publishers want to publish. This has created a vacuum which has been fulfilled by speciality case report journals. These journals publish only case reports and therefore have a much higher acceptance rate – somewhere in the range of 30 to 70 %. The increased demand also causes a situation where publishers may resort to questionable practices. In fact, almost half the journals are found to be dubious.



How to identify the genuine journals?


The trick is to find those case report journals which are PubMed Indexed. Only one PubMed Indexed journal(published by Baishideng group) is known to indulge in questionable practices[Refer to the Excel file linked at the end of the article]. So a case report journal that is PubMed Indexed is highly likely to be genuine. For example, my first publication was a case report in BMJ case reports.  BMJ case reports has a decent acceptance rate, but in order to submit one of the authors or the institution must have subscription. Individual subscription costs around 185 GBP (around Rs.15000), but just one subscription in a department is more than enough. Be sure to check if your institution has subscription – in which case, you can contact the librarian to get the submission access code. BMJ case reports doesn’t have an impact factor as such (many case report only journals don’t.). However you can use the scimagojr 2 year citations per article as a reasonable proxy.


Of course, case reports are also published by journals that publish other stuff like reviews and original articles. However the acceptance rate is likely to be lower in these journals. If you are confident of your material, it is best to try in a general journal first before trying a case reports only journal. When in doubt, ask an expert.



A master list of case reports only journals can be accessed in Excel format here. Sadly I couldn’t get a master list of submission fees – if you have details on that, do let me know. If you found this post useful, please share with your friends.


Further reading


New journals for publishing medical case reports

Online workflow for writing articles

It has become increasingly common for people to collaborate on writing projects. The tools that enable such collaboration have improved over the years too and currently allow for a completely online workflow. Unfortunately many residents and early career researchers don’t take advantage of the recent developments. In this post, I will outline a completely online workflow for writing articles
This way, you could work with any number of people on the same project and all of you could have access to the same digital library from which you can cite. You might wonder that the functionality of team library has been available for quite some now in popular reference management software like Zotero. However , without going through a few hoops, you can’t get Zotero to work seamlessly with Google docs.
Of late, I am increasingly using Google docs for my document preparation needs. Sure it isn’t MS Word, but few people need the full power of MS Word for their routine documents. The ‘portability’ of a Google docs document is particularly attractive to me since I have computers running different operating systems.
Here’s my completely online workflow. Every component of the workflow is free.(as in free beer).

workflow

The advantages of this online workflow includes

  • No need to install any software
  • You always get the latest and greatest version
  • OS/device independent
  • Collaboration is easy and seamless

The F1000 workspace also has a desktop client and  and you can start working even if you already have a pdf collection. It also has  a word add in, if you prefer to write in MS Word.Try it out for your next article. You will be pleasantly surprised.

Decoding sensitivity and specificity

Last week, like most other weeks of the year, I had encountered the terms – sensitivity and specificity three times! These terms have somehow become the first class citizens in a physician’s lingo. They are so commonly bandied about that many of us don’t even stop to think about what they really  mean. 

Consider this scenario . One of my well meaning friends told me before  exams  that the sensitivity and specificity of different tests used to diagnose Cushing’s syndrome is a very important question and should be memorized. And I duly proceeded to do the same. To my utter chagrin most of these tests had very similar sensitivity and specificity.

Here is a table  showing different sensitivity and specificity of the tests.

sensitivity

Before proceeding further, let’s refresh what sensitivity and specificity means

In plain English,

Sensitivity = probability of the test being positive if you have a disease

Specificity = probability of testing negative if you don’t have a disease

It can be rewritten as

Sensitivity =  P(PositiveTest | Disease)

Specificity =P(NegativeTest | NoDisease)

The above notation for sensitivity is read as Probability of positive test, GIVEN a patient is diseased. Similarly for specificity.

Here in lies the problem – both sensitivity and specificity are Conditional Probabilities. In the best of days, probability can be a little difficult to grasp and conditional probabilities tend to confuse people even more.

Natural frequencies are an easier way to communicate the same information and understanding them better. Most clinicians aren’t really interested in the ‘sensivitiy’ and ‘specificity’ alone. What we want is actually positive and negative predictive values. If a test is positive, what is the probability of having the disease?

To know this we need to know the prevalence of the disease. A positive test is more likely to be true positive if the prevalence of the disease is high. A positive test is more likely to be a false alarm if the prevalence of the disease is low.

prevalence_graph

Effect of prevalence on test result

Let us for the sake of discussion, consider the prevalence of Cushing’s syndrome  is 1 % .

How do we decode this sensitivity and specificity into natural frequencies?

Let’s use an example from the picture given above. LDDST with 98 % sensitivity. False positivity rate, can be calculated as 1 – specificity. That is Around 3 % for LDDST.  So the three ingredients we need for transforming conditional probabilities to natural frequencies are

  1. Prevalence
  2. Sensitivity
  3. Specificity

Ten out of every 1000 (1% prevalence) people are expected to have Cushing’s syndrome. Of these ten people almost all test positive (98% sensitivity – rounded off). Of the 990 without disease, 3% (30 people) still test positive.

Let’s draw a tree to make this clearer. May be I am different, but a tree seems easier for me than a 2 x2 table.

senstree

 

So of all positive tests, that is 40, only 10 are expected to be true positive. In other words just 25 % !

Now repeat the same thing with other tests in the table. You will find that there is only a tiny sliver of difference between the tests. There is only so much information you can extract from a given test, which is why we need a combination of tests.

Over a period of time, drawing a tree like this will become second nature to  you if you mentally practice with approximations. Soon you will realize that natural frequencies are much easier for us to understand and think about than conditional probabilities. It sort of empowers both the doctor and the patient and helps in better communication of risks.

If you are a Bayesian at heart, you will cringe at the thought of prevalence having such a huge say in the outcome. What about your clinical acumen? Someone with a set of ‘strong’ signs and another with a set of ‘weak signs’ can’t have the same ‘arbitrary’ number influencing the interpretation of a blood test right?

Perhaps you will then agree that the model below represents the way we should think about blood tests better

final

In such a situation, we are better off educating PGs (even interns) about the uncertainty involved, instead of asking them to recite some numbers. As for me, I continue to draw trees 😉 

If you find this useful, feel free to share with your students/friends.

The One Eyed Surgeon

Yesterday I attended an annual internal oration on the cancer scenario in India and the challenges that lay ahead. With abject poverty, woefully inadequate infrastructure and acute shortage of oncologists in several parts of our country, the stats predicted a bleak future.It appeared as if we were going to a nuclear war armed with sticks and stones.In this hopeless scenario, I was reminded of one of my heroes, a man who fought against impossible odds and scripted one of medicine’s most glorious victories.

The year was 1957. A middle aged surgeon was working  in Uganda, in the Mulago hospital in Kampala.He was a devout Christian and considered himself a missionary. By his own admission, he wasn’t a great surgeon.What he lacked in surgical genius, he made up for in tenacity. One day a boy named Africa who walked into his clinic. The malnourished boy had a large swelling in his jaw-making him look grotesque. In a few days, the boy died of his tumor. A couple of weeks later another boy walked into his clinic, with the same kind of swelling and met the same end eventually. The surgeon was intrigued – by the striking similarity of the cases and the ferocity of the tumor. He decided to investigate.

He had a handicap though – a stray bouncer had damaged one of his eyes permanently during an adoloscent cricket match. He was aging and was working in Sub Saharan Africa -far from where the limelight usually shone in medicine. He had no funds or even great expertise to draw upon. The people he treated were poor and wanted some solace for their pain, not fancy research.

Nevertheless with characteristic zeal, he asked around if doctors had seen similar cases. They said yes – so he pored over the records and to his astonishment found several similar cases, all of them ending in death. No one had connected the dots till then. He then looked at the literature – sure enough, there was an article about a similar tumor in 1901 in an obscure tropical medicine journal. The tumor he had seen wasn’t new. The pathologists had reported each of these tumors as sarcoma.

He quickly wrote a manuscript titled “A sarcoma involving the jaws in African Children” and posted it to the British Journal of Surgery. The reply never came.

By sheer accident, he met a physician called Oettle in South Africa. Oettle was younger and his star was on the ascent. By now the surgeon had collected grim photos of his patients. He showed Oettle and asked about similar cases in South Africa. Oettle waved his hand and said these cases didn’t exist in South Africa.

With no formal training in epidemiology, the surgeon decided to send out questionnaires with the photos to doctors across the country. The pace was excruciatingly slow – it took around 4 years for 400 responses. Armed with the information, he represented each case with a pin on a map. Since he couldn’t afford colored pins, he painted the pins with his daughter’s paint himself. A pattern was emerging. The tumor seemed to have a geographical distribution.

He presented his finding in Middlesex. Little did he know that his presentation would trigger a multinational effort against a common enemy.Among the audience was a man named Tony Epstein, a British pathologist. The idea of an infectious agent causing the tumor began to emerge. There were skeptics – unlike other infections, there are no cancer epidemics. Nor did the brothers and sisters of these unfortunate children get the disease. What kind of infectious agent behaved like this?

The surgeon decided to do a ‘geographical biopsy’. He applied for funds and got a 15 pound grant from the British government. With that and the help of his friend, he took an old four wheeler, repaired it and started on a long Safari. In sweltering heat, he would travel to Johannesburg and then back to Kampala, covering a total of 12 countries! In each place, he collected data (even before that term became entrenched in medical literature). On a hunch,he got external review of the old  slides. The results surprised him. The tumors were neither sarcomas nor carcinomas. The originated from lymphoid tissue- a lymphoma. Under the magnification of a microscope, these small round cells resembled a starry sky.

Tony quickly enlisted the help of his friend Yvonne Barr. Since they coudn’t isolate the infectious agent – it was too small – they decided to try a different approach. They looked for antibodies to the small infectious agent – presumably a virus. Sure enough almost all the cases had antibodies directed against this agent and it even stained the tumor cells. At long last, they had discovered the first human cancer caused by virus, one that bears their name – the Epstein Barr Virus.

Meanwhile the surgeon’s name became popular in medical circles and he received an offer to try methotrexate in these children from Sloan Kettering. To his amazement the tumor melted in these children. It returned in some. So he begged for another cyclophosphamide from an American manufacturer, which managed to hold the emperor of all maladies at bay even if for a short while.

This is the story of how within a decade a cancer was discovered, its morphological fingerprint identified, its geography dilineated, its causative agent discovered and its  treatment started.It is  the story of how an one eyed Irish surgeon, saw what all others had missed. It is a story of discovery that spans several continents in the face of impossible odds. It is a story that shows than even the ordinary can achieve great things with perseverance.

So when you feel  overwhelmed that you are in some remote no man’s land fighting a lone battle, remember this surgeon.

Burkitt

The name is Burkitt. Denis Parsons Burkitt.

Aaplot: Easy way to draw annotated scatterplot in Stata

The standard way to draw scatter plot with a linear fit in Stata is quite simple. Even then you will have to use the built in graph editor for polishing it or making it publication ready.

Let me illustrate that with the auto dataset that ships with Stata. We will draw a scatter plot of mpg(miles per gallon) and the price of the cars. We will also draw a line of best fit and a confidence interval.

sysuse auto
twoway scatter mpg price || liftci mpg price

Now this is the unedited resulting graph.

default_lfit

As you can see, it needs labelling of the axis, line equation etc. Its not a lot of work, but still there is a way to make this easier.

Aaplot is a user written ado file, contributed by Nicholas Cox.

Install it like this

ssc install aaplot

Now you can draw the same thing with additional details with a single command.

aaplot mpg price,addplot(lfitci mpg price)

aaplot

(Unlike R, you don’t need to load the addons separately in Stata! How cool is that :-))