Tag: BioMech Health

Can Doctors Objectively Quantify and Measure Pain? The Future of Pain Management 

Frank Fornari

By Dr. Frank Fornari, chairman and founder, BioMech Health.

Millions of Americans live with acute and chronic pain that affects every aspect of their lives. Pain by itself is an important marker of how a patient is feeling and indicates what kind of medical intervention might be necessary.

The healthcare industry needs a clinically acceptable way to objectively measure pain and since pain is a very complex mixture of biochemistry and genetics and it’s unlikely that a laboratory test that directly quantifies pain will be developed.  

Doctors have been using questionnaires and subjective responses including, the answer to the popular question, ‘What is your pain on a scale of 0 to 10?’ Unfortunately, each person’s pain tolerance and perception is different. Responses can be exaggerated or underplayed, pain can vary in how it is experienced or the conditions it is caused by…not to mention, adults and children can experience pain differently. It’s ultimately up to the clinician to determine the level of pain. To further complicate the pathology, clinicians may treat pain differently when it is a symptom versus when it becomes the primary pathology. One clinically actionable solution is to indirectly quantify the effects of pain using motion as a functional biomarker.

There is no question that a multidiagnostic strategy is always the best when applied to any disease. Healthcare professionals have now found that assessing a patient’s functional movements including balance, gait, and range of motion are more important than a subjective pain-based response alone. New tools have made it possible to use motion as a functional biomarker and endpoint for many treatments where pain is involved. The ability to assess sudden or gradual changes in movement can be a vital factor in the early diagnosis, treatment, and management of a wide number of painful health issues. 

Can pain be quantified? A new clinical trial showcases landmark progress in objective pain measurement. 

Diagnostic and therapeutic challenges overly rely on self-reporting and the paucity of biologically-based objective methodologies. Non-addiction medicine rehabilitation specialists are likely to adjust medications based upon patients’ complaints and justify increasing dosages, secondary to inadequate pain control, attributing such scenarios to the development of tolerance or progression of the disease.  Without objective signs of non-adherence, the clinician may increase dosage accordingly by the absence of aberrant behavior. This does not rule out the presence of tolerance, physical dependence, addiction or drug diversion.  Patient behavioral variability renders subjective analyses unreliable, and well-informed addicted patients can avoid these indirect indicators until the addiction severity overpowers self-control.

There are many treatments for pain and the ability to quantify the patient’s functional status can aid the clinician in the determination and management of their pain. A recent clinical study led by medical director Gladstone C. McDowell II, M.D., of Integrated Pain Solutions is being conducted to understand the link between functional motion and incapacitating back and leg pain in patients being treated with Nevro Corp. HFX Spinal Cord Stimulation. Dr. McDowell’s work was chosen as the Best Spinal Cord Stimulation Abstract winner at the 2022 American Society of Pain and Neuroscience (ASPN) annual Conference. 

The year-long study involved 25 adult patients who were implanted with the Nevro Senza® Spinal Cord Stimulator (“SCS”). Patients’ functional status were assessed using the Oswestry Disability Index (“ODI”), a standard patient self-reporting instrument. A clinical sensor-based motion system was also employed to systematically measure functional motion and cognition in patients to warrant the use of a permanent stimulation device. Strategically placed sensors allow for the noninvasive capture of normal and pathological motion data to identify, assess, and adequately transform patient motion patterns including ambulation, balance, symmetry, range of motion, and cognition. 

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