  The emergence of COVID-19 offered a unique opportunity to study chronic pain
patients as they responded to sudden changes in social environments, increased
community stress, and reduced access to care. We report findings from n=70
Spinal Cord Stimulation (SCS) patients before and during initial pandemic
stages resulting from advances in home monitoring and artificial intelligence
that produced novel insights despite pandemic-related disruptions. From a
multi-dimensional array of frequently monitored signals-including mobility,
sleep, voice, and psychological assessments-we found that while the overall
patient cohort appeared unaffected by the pandemic onset, patients had
significantly different individual experiences. Three distinct patient
responses (sub-cohorts) were revealed, those with: worsened pain, reduced
activities, or improved quality of life. Remarkably, none of the specific
measures by themselves were significantly affected; instead, it was their
synergy that exposed the effects elicited by the pandemic onset. Partial
correlations illustrating linked dimensions by sub-cohort during the pandemic
and those associations were different for each sub-cohort before COVID-19,
suggesting that daily at-home tele-monitoring of chronic conditions may reveal
novel patient types. This work highlights the opportunities afforded by
applying modern analytic techniques to more holistic and longitudinal patient
outcomes, which might aid clinicians in making more informed treatment
decisions in the future.

Computational Engineering, Finance, and Science