Imagine you went to buy an expensive piece of clothing. Rather than measuring your size, the store owner simply said “well, on average most folks require a medium, so let’s try that on, we can always re-size it later.” Continue reading “PulmCrit Wee: MDCalc for the perfect tape-measure intubation”
A 70-year-old woman with peptic ulcer disease comes to the ED with sudden severe abdominal pain. She also has a history of diabetes and hypertension, both well controlled with oral medication. Her vitals at triage show low-grade tachycardia but are otherwise within normal limits. She is peritoneal on exam and an upright chest x-ray reveals free air. While labs are pending, she is made NPO and started on IV fluid resuscitation.
You are the general surgeon called to see the patient, and your history and Continue reading ““Doc, do I really need this operation? What are the TRUE risks?” Improving the conversation around surgical risk using evidence-based medicine”
Paradoxical embolism via patent foramen ovale (PFO) is a rare cause of stroke, but it’s not uncommon to find PFOs in patients without traditional stroke risk factors (about 1 in 4 people in the general population have a PFO). How should patients with no other convincing cause of stroke be counseled, especially if invasive PFO closure is being considered? We talked to Dr. David Thaler, creator of the Risk of Paradoxical Embolism (RoPE) Score, about his research and experience with taking care of patients with cryptogenic stroke.
Why did you develop the RoPE Score? Was there a clinical experience that inspired you to create this tool for clinicians?
PFOs have interested and frustrated me for years. They’re so common in the general population, and we find them all the time in stroke patients, old ones and young ones. And paradoxical embolism is definitely a thing—there’s no question that it happens—but because the prevalence is so high in the general population, there’s also no question that a lot of the PFOs that we find are incidental. That’s where this started from in my mind: Continue reading “Deciphering Cryptogenic Stroke with Dr. David Thaler, Creator of the RoPE Score”
Did you know that FH is very treatable but missed in 90% of cases, and leads to early cardiac death? We’ve added some calculators to try to address it:
Unless you’re an endocrinologist, FH is one of those diseases you probably memorized in medical school, brought up on rounds when the Continue reading “Don’t Forget the Zebras: Familial Hypercholesterolemia”
With the launch of the ASCVD Calculator and the ASCVD algorithm we recently added to MDCalc (The difference? I’ll explain further down) we thought it might be nice to review the 2013 guideline. Let’s start at the beginning.
Before the ASCVD
A long time ago, in a galaxy far, far away, (2002) there were the ATP-III Guidelines — short for the “Adult Treatment Panel,” a group of cholesterol and lipid experts that attempted to figure out what the heck to do with patients with lipid issues. It really focused on LDL cholesterol and addressed trying to aggressively reduce it. Find high risk people with high LDL, and get that LDL down! Continue reading “About the ASCVD and ACC/AHA 2013 Calculators”
She sat down with us to give our users a some expert advice on the difficulties of vaccinations and some tips to use with patients.
MDCalc: What are some of the challenges you face when trying to vaccinate patients? How do you overcome these challenges?
Suzanne Rosefeld: The vast majority of my patients understand the importance of childhood vaccines. Before vaccinating each child I explain what the vaccine I am recommending is for. In the cases where there is hesitancy I make sure I answer every one of their questions. I listen to their concerns and address, using hard scientific evidence in terms of risk/benefit, each issue.
MDC: What are some of the most common cases in which you do not vaccinate patients?
SR: I do not vaccinate a child if they are at the beginning of an illness, even if its “just a cold”. Vaccines do not “make one sick” (with the exception of the live virus vaccines) but can “distract” the immune system. I am privileged by having a very responsible parent body and find that they 1) appreciate my considerations and, more importantly, 2) return at the recommended time to get the deferred vaccines. Continue reading “Dr. Suzanne Rosenfeld on the Dos and Don’ts of Vaccines”
She was kind enough to sit down for an interview to provide some insight into the practice and treatment of hepatitis patients, considering May is Hepatitis Awareness Month.
MDCalc: It has been an exciting couple years in your field, with the discovery of a Hepatitis C cure, an area of your research (PMID: 27047770). What should docs know about these cures?
Gina Choi: The new treatments for hepatitis C are very safe and effective with minimal side effects. Treatment duration is also short, ranging from 8-24 weeks, depending on the type of hepatitis C, or genotype, and the presence of cirrhosis.
MDC: Who should doctors screen and refer for Hepatitis C? What’s the best way for them to do so?
He took some time out of his busy schedule to provide some insight into the practice and treatment of alcoholic patients, considering April is Alcohol Awareness Month.
MDCalc: What are some of the challenges in working with alcoholic patients? Are there any rules you live by when evaluating patients?
David Oslin: Trust but verify. It’s important that patients understand that being honest with their provider will have the best results but I also realize that part of their illness makes honesty and openness difficult.
Challenges are like many chronic debilitating illness. Addiction is life-threatening and not all patients do well with treatment. Like any other illness, we aren’t always successful in helping patients.
Another rule that I keep in mind is to be open to patients who want to try no matter how often they have set backs.
MD: What are the most promising aspects of recent and past alcoholic research? Are there any areas you would like to see more advancement in?
DO: There is a growing understanding of the neuroscience of addiction, and this is beginning to pay off with new medications that are effective in treatment. We also seem to be finally turning the corner in having providers realize that one treatment doesn’t fit all patients and that multiple treatment options are often warranted. This is also where I would like to see more progress.
MD: What advice would you offer busy clinicians on the best way they can (a) screen for alcohol abuse, and (b) help patients who may suffer from alcoholism?
DO: Use self reported but structured assessments such as the AUDIT-C which is only 3 questions. It is very useful in primary care practices or general psychiatry practices.
MD: Other comments? Any words of wisdom when seeing alcoholic or intoxicated patients? What research are you doing currently and what is next in the pipeline for you?
DO: Treatment works!
To view Dr. Oslin’s publications, visit PubMed.
We come across a lot of academic papers and research at MDCalc when figuring out what to add to the site next. There’s a huge range of information that we’ll add to MDCalc, including scores, algorithms, “decision rules,” referenced lists of accepted information (like exclusion criteria for TPA), and actual math equations. (We end up referring to these all as “calculators,” just so that it’s easy to know what we’re referring to.)
But not all “calculators” are created equal, of course. Some are better than others, for a number of reasons.
- How strong is its evidence? Probably first and most importantly, does the calculator appear to do what it’s supposed to do? If the paper states its job is to figure out who has right ear pain vs who has left ear pain, did it do that according to the results? And, taking it an important step further – and that we typically require on MDCalc – did it get validated?
- Is it solving or helping in a clinical conundrum? You could imagine someone coming up with a clinical decision instrument for ear pain:
- Which ear does the patient have pain in?
- Does that ear look red?
- Is that ear tender?
But obviously no one needs a score for this, because that’s just what you do as a clinician. It’s obvious. It’s one of the criticisms people have of some of our calculators, including the HEART Score for Major Cardiac Events, specifically the elevated troponin. We all known that patients with chest pain with an elevated troponin are much more likely to have a poor outcome, so obviously those patients require admission to the hospital – no one needs a rule or instrument for that.
- Are terms well-defined? It often takes detective work to figure out where a particular criteria is defined in the paper; often terms are not clear at all, and we end up contacting authors to figure out exactly what they meant by “Heart Rate > 100,” or “Recent Surgery.” Heart Rate > 100 initially, or ever? How recent is recent?
- Is it reasonably easy to perform? While hopefully MDCalc makes it much easier to use any decision instrument and takes away your mnemonics and rote memorization, it’s really important that a user can move through the score with relative ease. For example, the APACHE II Score is widely criticized for being incredibly complex, long, and requiring a huge number of data points. And if you’re missing one of them, you then have to potentially order additional laboratory tests to calculate it. When possible, scores should be straightforward and easy to perform with as few pieces of clinical data as possible.
Those are some of the criteria that help us determine if a piece of research should join the MDCalc reference list. We’ll dive deeper into some of these categories, as well as talk more about poor clinical decision instruments next.
Long before there were lab tests and x-rays and CT scans, doctors were diagnosing disease. Diseases were described – as they still are today – as a collection of signs and symptoms. (A syndrome is technically any collection of signs of symptoms, with the term disease suggesting “disorder” or derangement from normal.) At some point, doctors started cutting the dead open to see what was actually happening to these patients on the inside, and then describing those findings as well. Medical school is still taught this way. You study a disease’s pathology at length, including what it looks like and what’s happening at a cellular level.
And since the beginning of time, patients have always come with only their signs and symptoms; patients don’t carry around a placard telling you what their disease is. So doctors started wondering, “There must be some way to figure out which of these patients with vomiting and abdominal pain have appendicitis, without having to do surgery on them.” And as testing began, so did the idea of a gold standard: the best, most absolute proof that a patient has a certain disease. If you have the gold standard, you’ve got the disease. In the case of appendicitis, it’s an inflamed, infected appendix when the surgeon cuts you open, with signs of appendicitis when the pathologist looks under the microscope after surgery.
But there’s often a few problems with the gold standard concept when you apply it to us humans:
- First, the gold standard isn’t always so physically apparent as a swollen appendix. To take the most abstract example, how do you come up with a gold standard for say, depression, or alcoholism? (They exist, but they’re obviously not based on what depression looks like under a microscope.)
- Second, the gold standard test is very often very invasive, so you don’t always want to use the gold standard to diagnose every single disease. Imagine if we just had to cut everyone open who have vomiting and abdominal pain? Or if we cut into every person’s brain with a headache to see which ones have a brain tumor?
- Next, even the gold standard test can be imperfect. Gout’s gold standard is joint fluid showing monosodium urate crystals, but experts even admit that this test isn’t 100% reliable. Maybe the fluid you get just happens to not have any crystals in it by pure luck. Or maybe there’s too few crystals to find.
- Not only can the gold standard be invasive, but it can be really resource intensive. Take for example the gold standard for knowing if a patient has bacteria growing in their blood. It can sometimes take 3-5 days (and almost always at least 24 hours) for these tests to give results. Who can wait five days for a test when the disease might leave the patient dead in two?
- Finally, depending on the disease, sometimes we don’t even need to use the gold standard. The disease is so mild and temporary that the gold standard is just a waste. Take the common cold: while there’s certainly tests we can do to confirm that a patient with a runny nose has a cold… who cares? It’s a cold!
And thus, other testing was born. Lab tests, CT scans, MRIs, EKGs, and even scores and calculators like we have on MDCalc. These were great, but it’s taken decades (and this work is on-going) to figure out how good these tests are compared to that “gold standard.” And to do this work, we have to do both tests and get the gold standard and then see how good the test was. For example, a CT scan is a test we often order for patients we think have appendicitis. And while CT is an excellent test to see which patients will have a gold standard appendicitis, even CT isn’t perfect. (It’s probably about 95-98%, which is pretty incredible, but still not perfect).
The scores on MDCalc are used just like lab tests or CT scans: how good are they at predicting which diseases or outcomes a patient has compared to the gold standard?