Several journals have developed a tradition of publishing slightly different papers in their December issues. These papers are intended to either make a provocative statement, making us reflect upon unusual topics, or provide unusual examples of scientific topics. I like to call them Christmas Pearls. This year my favorite Christmas Pearls:

“Death is certain, the time is not”: mortality and survival in Game of Thrones

Kaplan-Meier survival analysis with Cox proportional hazard regression modeling was used to quantify survival times and probabilities to identify independent predictors of mortality among ‘important characters’ (n = 330) appearing in Seasons 1 to 7 of Game of Thrones.

Although the statistics are quite sound and the data extensive some remarks are mandatory.

First, resuscitation bias was not considered (e.g. John snow). Neither were white walkers. Not clear what justifies the exclusion of these non-less important characters. From a mixed-methods perspective, white walkers could have participated in a focus group discussion of the results, for example.

Secondly, the effectiveness of wall policies for security purposes is clearly understated.

Finally, the authors conclude:

There is great potential for preventing violent deaths in the world of Game of Thrones. Stable democratic governments, resilient institutions that deliver public goods, and implementation of evidence-based violence prevention policies can decrease the risk of violent deaths considerably“.

Given that winter is coming this is clearly an unrealistic and utopic worldview of Game of Thrones.


Is it time to start using the emoji in biomedical literature?


The lack of standardisation in emoji artwork that may cause ambiguity in interpretation is quite disturbing. Also, the emoji based alternatives to the denotation of statistical significance can’t really apprehend the need to consider the enunciation of the null hypothesis for adequate interpretation of P-values. The smiling-face-with-sunglasses_1f60e.png in a Kolmogorov-Smirnov to check distribution assumptions for parametric testing may be actually hiding


table 01