Correspondence  |   October 2016
In Reply
Author Notes
  • McMaster University and the Perioperative Research Group, Population Health Research Institute, Hamilton, Ontario, Canada (Y.L.M.). yannick.lemanach@phri.ca
  • (Accepted for publication June 16, 2016.)
    (Accepted for publication June 16, 2016.)×
Article Information
Correspondence
Correspondence   |   October 2016
In Reply
Anesthesiology 10 2016, Vol.125, 816-817. doi:10.1097/ALN.0000000000001270
Anesthesiology 10 2016, Vol.125, 816-817. doi:10.1097/ALN.0000000000001270
We thank Kappen et al. for their interest in our article describing the development of the Preoperative Score to Predict Postoperative Mortality (POSPOM).1  The inconsistencies are consequences of an unfortunate error in the text (in the validation cohort, a POSPOM score equal to 30 was associated to a predicted in-hospital mortality of 7.40%, and not 5.65%). All tables and figures have been verified and corrected. An erratum has been issued and appears in this issue.2 
In our validation cohort of 2,789,932 patients, only 22,136 (0.79%) had a predicted risk of in-hospital mortality greater than 10%. As a consequence, we intentionally presented a truncated calibration plot focusing on the probability range that includes more than 99% of patients. The reporting of calibration for prediction models remains difficult, as underlined by the comment by Kappen et al. Graphical analysis of the calibration plot remains the preferred approach.3,4  However, most patients were at very low risk of in-hospital mortality. This resulted in a heavily left-skewed distribution, making the histogram of predicted probabilities uninformative. Because the calibration plot included more than 99% of patients, we believe that it is correct to state that in the validation cohort, POSPOM “has good calibration with only a small underestimation of in-hospital mortality in the validation cohort for predicted probabilities ranging from 1 to 10%.” However, we agree with the authors that a closer inspection of those patients with high probabilities of in-hospital mortality is required.
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