cEEG electrode-related pressure ulcers in acutely hospitalized patients

Abstract

Background: Pressure ulcers resulting from continuous EEG (cEEG) monitoring in hospitalized patients have gained attention as a preventable medical complication. We measured their incidence and risk factors. Methods: We performed an observational investigation of cEEG-electrode-related pressure ulcers (EERPU) among acutely ill patients over a 22-month period. Variables analyzed included age, sex, monitoring duration, hospital location, application methods, vasopressor usage, nutritional status, skin allergies, fever, and presence/severity of EERPU. We examined risk for pressure ulcers vs monitoring duration using Kaplan-Meyer survival analysis, and performed multivariate risk assessment using Cox proportional hazard model. Results:Among 1,519 patients, EERPU occurred in 118 (7.8%). Most (n 5 109, 92.3%) consisted of hyperemia only without skin breakdown. A major predictor was monitoring duration, with 3-, 5-, and 10-day risks of 16%, 32%, and 60%, respectively. Risk factors included older age (mean age 60.65 vs 50.3, p , 0.01), care in an intensive care unit (9.37% vs 5.32%, p , 0.01), lack of a head wrap (8.31% vs 27.3%, p 5 0.02), use of vasopressors (16.7% vs 9.64%, p , 0.01), enteral feeding (11.7% vs 5.45%, p 5 0.04), and fever (18.4% vs 9.3%, p , 0.01). Elderly patients (71-80 years) were at higher risk (hazard ratio 6.84 [1.95-24], p , 0.01), even after accounting for monitoring time and other pertinent variables in multivariate analysis. Conclusions: EERPU are uncommon and generally mild. Elderly patients and those with more severe illness have higher risk of developing EERPU, and the risk increases as a function of monitoring duration. Neurol Clin Pract 2017;7:15-25

Neonatal Electroencephalogram Electrode-Related Pressure Injury Prevention Quality Improvement Study

“…These results are similar to other published studies that targeted EERPI prevention as their main outcome 20 . However, because most of the published data targeted adult populations, with only a handful of studies including neonates, this study furthers the QI methodology work for EERPI in this high-risk, understudied population 21,22 …”

“…20 However, because most of the published data targeted adult populations, with only a handful of studies including neonates, this study furthers the QI methodology work for EERPI in this high-risk, understudied population. 21,22 Risk factors for HAPI development include exposure to various diagnostic and therapeutic medical devices, inactivity or immobility, friction and shear, hypoxia and poor skin perfusion, fluid retention, and nutrition deficiencies; critically ill neonates may be exposed to all of these factors. 23,24 Visscher and Taylor 25 found a 6.4% rate of medical device-related PIs in neonates.…”

Review of Noninvasive Neuromonitoring Modalities in Children II: EEG, qEEG

“…A limited array may also be used when a patient is anticipated to need cEEG monitoring for several days to reduce the number of sites at risk of skin breakdown. Risk factors for electrode-related skin injury include critical illness, longer duration of monitoring, age less than 1 year, fever, lack of headwrap, and need for vasoactive support [10][11][12]. The skin should be checked daily, and scalp rest should be provided if breakdown is identified.…”

Processed Electroencephalogram-Based Monitoring to Guide Sedation in Critically Ill Adult Patients: Recommendations from an International Expert Panel-Based Consensus

“…The use of the output index ranges suggested by the manufacturer for light and deep sedation might be an effective tool as a first approach to guide and individualize sedative drug dosing schemes integrated in a multimodal monitoring strategy in critically ill patients [23][24][25][26]. Some limitations of this technology are represented by the influence of EMG/artifacts, reduced signal quality (due to electrode detachment, sweating, or swelling of forehead), and patient conditions (e.g., brain damage) because they can alter the pEEG number [25,[27][28][29][30][31]. Therefore, the pEEG number should be verified by the concordance with the raw EEG rhythm [32,33].…”