Misunderstanding and Misuse of Basic Clinical Decision Principles among Child Abuse Pediatricians

The previous post about Dr. Cox, ensnared in a CPT (Child Protection Team) witch hunt in Wisconsin, has led me to evaluate several more research reports on child abuse, including SBS (shaken baby syndrome), AHT (abusive head trauma), and sentinel injuries.  These reports are rife with critical assumptions, severe limitations, and gross errors which greatly limit the resulting conclusions in most studies I have reviewed.  However, one study that was pointed out to me today  takes the cake.  I don't know what the prevalence of this degree of misunderstanding is, but CPTs and child abuse pediatricians need make sure they have a proper understanding of sensitivity, specificity, positive and negative predictive value, base rates, etc.  And they should not be testifying about the probability of child abuse at all if they don't have this stuff down cold. And I think this means that some proportion of them needs to go back to school or stop testifying.

The article and associated correspondence at issue is entitled The Positive Predictive Value of Rib Fractures as an Indicator of Nonaccidental Trauma in Children published in 2004.  The authors looked at a series of rib fractures in children at a single Trauma Center in Colorado during a six year period and identified all patients with a rib fracture.  They then restricted their analysis to children less than 3 years of age.  There were 316 rib fractures among just 62 children in the series; the average number of rib fractures per child is ~5.  The proper unit of analysis for a study looking at positive predictive value is children, sorted into those with and without abuse, and with and without rib fracture(s) as seen in the 2x2 tables below.

Move Over Feckless Extubation, Make Room For Reckless Extubation

Following the theme of some recent posts on Status Iatrogenicus (here and here) about testing and treatment thresholds, one of our stellar fellows Meghan Cirulis MD and I wrote a letter to the editor of JAMA about the recent article by Subira et al comparing shorter duration Pressure Support Ventilation to longer duration T-piece trials.  Despite adhering to my well hewn formula for letters to the editor, it was not accepted, so as is my custom, I will publish it here.

Spoiler alert - when the patients you enroll in your weaning trial have a base rate of extubation success of 93%, you should not be doing an SBT - you should be extubating them all, and figuring out why your enrollment criteria are too stringent and how many extubatable patients your enrollment criteria are missing because of low sensitivity and high specificity.

Don't Get Soaked: The Practical Utility of Predicting Fluid Responsiveness

In this article in the September 27th issue of JAMA, the authors discuss the rationale and evidence for predicting fluid responsiveness in hemodynamically unstable patients.  While this is a popular academic topic, its practical importance is not as clear.  Some things, such as predicting performance on a SBT with a Yang-Tobin f/Vt,  don't make much sense - just do the SBT if that's the result you're really interested in.  The prediction of whether it will rain today is not very important if the difference in what I do is as small as tucking an umbrella into my bag or not.  Neither the inconvenience of getting a little wet walking from the parking garage nor that of carrying the umbrella is very great.  Similarly, a prediction of whether or not it will rain two months from now when I'm planning a trip to Cancun is not very valuable to me because the confidence intervals about the estimate are too wide to rely upon.  Better to just stick with the base rates:  how much rainfall is there in March in the Caribbean on an average year?

Our letter to the editor was not published in JAMA, so I will post it here:

To the Editor:  A couple of issues relating to the article about predicting responsiveness to fluid bolus¹ deserve attention.  First, the authors made a mathematical error that may cause confusion among readers attempting to duplicate the Bayesian calculations described in article.  The negative predictive value (NPV) of a test is the proportion of patients with a negative test who do not have the condition – the true negative rate.²  In each of the instances in which NPV is mentioned in the article, the authors mistakenly report the proportion of patients with a negative test who do have the condition.  This value, 1-NPV, is the false negative rate - the posterior probability of the condition in those with a negative test.

Second, in the examples that discuss NPV, the authors use a prior probability of fluid responsiveness of 50%.  A clinician who appropriately uses a threshold approach to decision making³ must determine a probability threshold above which treatment is warranted, considering the net utility of all possible outcomes with and without treatment given that treatment’s risks and benefits⁴.  Because the risk of fluid administration in judicious quantities is low⁵, the threshold for fluid administration is correspondingly low and fluid bolus may be warranted based on prior probability alone, thus obviating additional testing.  Even if additional testing is negative and suggests a posterior probability of fluid responsiveness of only 10% (with an upper 95% confidence limit of 18%), many clinicians would still judge a trial of fluids to be justified because fluids are considered to be largely benign and untreated hypovolemia is not⁴.  (The upper confidence limit will be higher still if the prior probability was underestimated.)  Finally, the posterior probabilities hinge critically on the estimates of prior probabilities, which are notoriously nebulous and subjective.  Clinicians are likely intuitively aware of these quandaries, which may explain why empiric fluid bolus is favored over passive leg raise testing outside of academic treatises⁶.

1.            Bentzer P, Griesdale DE, Boyd J, MacLean K, Sirounis D, Ayas NT. WIll this hemodynamically unstable patient respond to a bolus of intravenous fluids? JAMA. 2016;316(12):1298-1309.

2.            Fischer JE, Bachmann LM, Jaeschke R. A readers' guide to the interpretation of diagnostic test properties: clinical example of sepsis. Intensive Care Med. 2003;29(7):1043-1051.

3.            Pauker SG, Kassirer JP. The threshold approach to clinical decision making. N Engl J Med. 1980;302(20):1109-1117.

4.            Tsalatsanis A, Hozo I, Kumar A, Djulbegovic B. Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing. PLoS One. 2015;10(8):e0134800.

5.            Investigators TP. A Randomized Trial of Protocol-Based Care for Early Septic Shock. N Engl J Med. 2014;370(18):1683-1693.

6.            Marik PE, Monnet X, Teboul J-L. Hemodynamic parameters to guide fluid therapy. Annals of Intensive Care. 2011;1:1-1.

Scott K Aberegg, MD, MPH

Andrew M Hersh, MD

The University of Utah School of Medicine

Salt Lake City, Utah

Billions and Billions of People on Statins? Damn the Torpedos and Full Speed Ahead

Absolutely Relative
Risk is in the Mind of the Taker

Among the many editorials providing background and backlash about the new cholesterol guidelines is this one:  More Than a Billion People Taking Statins? by John Ioannidis, which echoes the worries of others that the result of the guidelines (which changed the 10-year risk threshold for treatment from 10% to 7.5%) may be that many more people (billions and billions?) will be prescribed statins.  But the title is a curious one - if statins are beneficial, should we lament their widespread prescription and adoption or is it just unfortunate that heart disease is so prevalent? Whose side are we on, the cure or the disease?

Are the premises of the guidelines flawed leading to flawed extrapolations, or are the premises correct and we just don't like the implications?  Let's look at the premises - because if they're flawed, we may find that other premises we have accepted are flawed.