Early Postoperative Actigraphy Poorly Predicts Hypoactive Delirium

Abstract

Study Objectives: Delirium is a postoperative complication accompanied by disturbances in attention, cognition, arousal, and psychomotor activity. Wrist actigraphy has been advocated to study inactivity and inferred sleep patterns during delirium. We hypothesized that altered patterns of motor activity or immobility, reflective of disordered sleep and wakefulness patterns, would serve as predictive markers of hypoactive postoperative delirium. Methods: Eighty-four elderly surgical patients were classified into three groups based on the timing of hypoactive delirium following surgery: intact with no delirium throughout postoperative days (POD) 0-5 (n = 51), delirium during POD 0-1 (n = 24), and delirium during POD 2-5 (n = 13). Delirium was detected on daily Confusion Assessment Method evaluations and chart review. Actigraphy measures were calculated from accelerometry signals acquired on the first postoperative day (POD 0, 16:00-23:00) and night (POD 0, 23:00-POD 1, 06:00). Results: Actigraphy metrics showed substantial interpatient variability. Among the three patient groups, only those without delirium showed greater movement during the day compared to night and also fewer minutes of night immobility (P = .03 and P = .02, Wilcoxon rank-sum tests). These patients were poorly discriminated from those with delirium during either POD 0-1 or POD 2-5, using differences in day and night activity (C-statistic, 95% confidence interval [CI]: 0.66 [0.53-0.79] and C-statistic, 95% CI: 0.71 [0.55-0.87], respectively). Inclusion of low-frequency signals improved performance of immobility measures without affecting those based on activity. Cognitively intact patients during POD 0-5 were distinguished from those with delirium during POD 0-1, based on differences in the number of day and night immobile minutes (C-statistic 0.65, 95% CI: [0.53-0.78]). Actigraphy metrics with the strongest association to delirium incidence were not reliably correlated with an increased risk during POD 0-5, when accounting for patient age, sex, intensive care unit admission, and Charlson Comorbidity Index (adjusted odds ratio of 1.7, 95% CI: [1.0-3.0], P = .09, likelihood ratio test). Conclusions: Early postoperative wrist actigraphy metrics that serve as markers of sleep and wakefulness offer limited capacity as sole predictors or markers of hypoactive delirium.

The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review

“…Participants came from 11 study populations ( Appendix A ; Table A1 and Table A2 ): older adults (n = 17: PA n = 16, SCR n = 2) [ 3 , 4 , 10 , 45 , 46 , 59 , 60 , 61 , 62 , 63 , 101 , 106 , 107 , 113 , 114 , 115 , 116 ], mixed admissions (delirium and dementia) (n = 12: PA n = 8, SCR n = 7) [ 33 , 38 , 42 , 43 , 65 , 66 , 67 , 68 , 93 , 94 , 95 , 119 ], orthopaedic surgery/fractures (n = 12: PA n = 11, SCR n = 2) [ 41 , 52 , 69 , 70 , 71 , 72 , 73 , 96 , 97 , 98 , 99 , 102 ], cardiac medical/surgical patients (n = 10: PA n = 7, SCR n = 4) [ 39 , 50 , 53 , 74 , 75 , 100 , 103 ,…”

Objectively measured sleep fragmentation is associated with incident delirium in older hospitalized patients: Analysis of data collected from an randomized controlled trial

“…Additionally, our inability to predict delirium from sleep fragmentation data prior to disease onset beyond other risk factors using our mixed model suggests the interplay between these factors is complex. A recent study by Maybrier et al suggested that actigraphy metrics poorly predicted hypoactive delirium in the post‐operative setting (Maybrier et al., 2019). While these are important findings, we note that our study differs in several key ways.…”

“…However, there are few reliable methods to predict delirium beyond basic risk factors such as age, existing cognitive impairment or illness severity. Accordingly, there have been recent investigations into improving the ability to predict delirium using objective, non‐invasive measures of rest/activity cycles (Maybrier et al., 2019; van Uitert et al., 2011).…”

Actigraphy-based sleep and activity measurements in intensive care unit patients randomized to ramelteon or placebo for delirium prevention

“…This suggests that actigraphy, and other tools that use similar technology, may become useful in assessing and treating delirium in the hospital by evaluating individuals' sleep, activity, and circadian patterns in the acute care setting. Others have also used day vs. night activity patterns to discriminate delirium from no delirium 40 .…”