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Development and validation of QMortality risk prediction algorithm to estimate short term risk of death and assess frailty: cohort study

BMJ 2017; 358 doi: https://doi.org/10.1136/bmj.j4208 (Published 20 September 2017) Cite this as: BMJ 2017;358:j4208

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Re: Predicting risk of death. The importance of BMI and Heart Rate.

Julia Hippisley-Cox and Carol Coupland (BMJ 20 September 2017) did an outstanding job in the Development and validation of QMortality risk prediction algorithm to estimate short term risk of death.

Over the years I have investigated the importance of the BMI and Resting Heart Rate (RHR) as risk factors in the form of the Pulse Mass Index, which correlates with the cardiovascular risk.

Assuming a relation of 3 to 1 between RHR and BMI, I tested a theoretical index as follows:

BMIxBMIx3/1730.

When I apply this formula compared to the empirical results of several observational very extensive studies over Body-Mass Index and Mortality, the concordance of the results is very similar, with over 90 percent precision, up to over 99 percent.

That means that this index can predict, right at the first consultation, with over 90 percent certainty, what can be the relative risk of mortality for these patients.

It would be very interesting to compare and apply this formula to the raw data from Julia Hippisley-Cox and Carol Coupland.

Prof. Enrique Sánchez Delgado MD

Internal Medicine-Clinical Pharmacology and Therapeutics
Hospital Vivian Pellas, Managua

Competing interests: No competing interests

06 October 2017
Prof. Enrique J. Sanchez Delgado, MD
Internal Medicine-Clinical Pharmacology and Therapeutics
Hospital Vivian Pellas
Hospital Vivian Pellas, Managua, Nicaragua
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