HRV in Active-Duty Special Forces and Public Order Military Personnel

Heart rate variability (HRV) is a simple, non-invasive, real-time analyzable, and highly reproducible measurement that captures incidences for assessing a person’s health and physical condition. Public security jobs are characterized by major exposure to risk factors known to influence the cardiovascular response to stimuli, e.g., night shifts, highly physically demanding activity, and acute stress activity. This study aimed to evaluate the HRV parameters in a population of 112 male personnel of the special forces and public order of the Carabinieri, aged 25–59, when engaged in several duty tasks, such as paratroopers, night shift police station officers, night shift patrol, dynamic precision shooting evaluative team, dynamic precision shooting non-evaluative team, and office clerks (used as control group). During the specific task of each participant, the HRV parameters were collected with wearable devices and processed. The HRV parameters in the time and frequency domains collected were average heart rate, standard deviation of all normal RR intervals, root mean square of successive differences in adjacent normal-to-normal (NN) intervals, very-low-frequency power, low-frequency power, high-frequency power, stress index, parasympathetic nervous system activity index, and sympathetic nervous system activity index. Parametric tests for independent series to compare the HRV parameters by subgroups within the study subjects were used. A multivariate linear regression analysis was conducted to evaluate the association between the HRV parameters and some personal and organizational factors. The comparison between different subgroups showed that activities with a high demand for concentration and precision, as is the case with paratroopers and dynamic precision shooters, differ significantly from activities that can be defined as routine, such as office work. Other activities, such as patrolling or remote management from operations centers, although including critical elements, did not deviate significantly from the control group. The study of HRV parameters is therefore a useful tool for occupational physicians, both for addressing work suitability assessments and for better targeting health promotion campaigns, to be considered as being aimed at monitoring the subject’s physiological parameters, and not at the diagnosis of any pathological condition, which should always be carried out by the medical specialist.

A Generalized Evolutionary Classifier (EC) for Evolutionarily Guided Precision Medicine (EGPM)

Precision medicine (PM) matches patients to therapies, utilizing traditional biomarker classifiers. Dynamic precision medicine (DPM) is an evolutionarily directed approach which adapts every six weeks, plans ahead for future resistance development, incorporates multiple therapeutic agents, and may improve survival (simulated hazard ratio DPM:PM, HR-DPM/PM, 0.52). We developed an evolutionary classifier (EC) to select patients who benefit from DPM. Subclonal prevalence and growth, mutation, and drug sensitivity parameters determine each DPM recommended adaptation (move). In simulations, if the first two moves are identical for DPM and PM, patients will not benefit (90% negative predictive value). The first two moves provide nearly the benefit of 40 moves. Patients benefiting equally between 2 and 40 moves have extraordinary predicted benefit (HR-DPM/PM 0.04). This EC development paradigm may apply to other dynamic cancer models despite different underlying assumptions. It may reduce the duration and frequency of required monitoring, and also enable "window" clinical trials.