HomeHealthcareDelivering optimal health: A road map for the future of clinical care

Delivering optimal health: A road map for the future of clinical care

Remember the hassles and pitfalls of driving before GPS? No way to predict a traffic jam or detour, no way to know if you were on the best route. Now our satellite apps guide us, warning of hazards, finding the fastest way to our destination.

Imagine a similar guidance system for navigating patient care. A system to warn you of impending illness, even before symptoms present, and guide you in making optimal therapeutic decisions. Rather than striving to find the most effective treatment for existing disease, we’d be proactively anticipating and preventing it. That’s a radical, but overdue and necessary, shift.

I believe we’ve developed just such a system. The “Physiological Fitness Landscape” (PFL) model for clinicians is a revolutionary framework for delivering ideal health care. Its widescale application could shift clinical practice from an imprecise and imperfect, post-hoc, treatment-based approach, to one that harnesses applied bioinformatics to create patient-specific, highly individualized, precision guidelines for maintaining good health.

Fitness Landscapes are well known conceptual models within and beyond the field of evolutionary biology. We have applied the main tenets of species-level fitness modeling to a scaffold of physics and, using the predictive power of computer algorithms, propose a data-driven bioinformatics approach to clinical practice that can revolutionize healthcare.

Energy metabolism and wellness are intrinsically linked. Mitochondrial energy production and metabolic efficiency begin to wane around age 30. But its normally slow decline, and the disease vulnerability that comes with it, is accelerated, and exacerbated by chronic physical and emotional stress.

In the PFL model, as in those on which it’s based, fitness is visualized as existing within a three-dimensional landscape of hills and valleys. From the Stability Zone of the valley floor, representing baseline homeostasis and good health, we are continually pushed higher by internal and external stressors. What matters is how quickly and easily we can return to baseline.

Poor diet, excessive alcohol, lack of exercise, disrupted microbiota, smoking, work and family pressures. They all serve to send us to a precarious peak from which we could plunge, without warning, at the slightest additional provocation. For the young and fit, life’s stressors equate to gentle hills in the PFL model. But for the old and the unhealthy, any additional stress could be the last push toward diabetes, heart attack, stroke, Alzheimer’s disease, cancer or premature death.

The toxic effects of stress are cumulative. Without stress resilience, each new stressor can land us on a new baseline – a higher plateau, well above the valley Safety Zone. This Instability Zone is where inflammatory and metabolic syndromes set in. From there, unchecked stressors lead us inevitably upward to the next plateau until eventually, we reach the Threshold of Criticality. Here, at the mountain peak, we can easily be pushed to the Threshold of Reversibility – tumbling us off the mountain top to a state of ill health where no intervention is likely to help.

We propose using comprehensive metabolic panels at regular intervals to establish a wellness baseline for each patient. The accumulated data will allow us to readily discern even minute, symptomless changes in metabolic efficiency in the individual, and, by anonymously collecting and combining this powerful bioinformatics, create algorithm-based standards of preventive health care that will transform our field.

The PFL model can serve clinicians as a conceptual and clinical tool for the development of therapeutic interventions aimed at changing the accepted trajectory of aging and chronic disease. By applying its tenets to the care of individual patients, healthcare providers will be able to harness the power of data. And rather than treating existing diseases, they’ll be able to see the warning signs of impending illness and stop it before it starts.

Photo: metamorworks, Getty Images



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