Sound and light levels in intensive care units in a large urban hospital in the United States

Intensive care units (ICUs) may disrupt sleep. Quantitative ICU studies of concurrent and continuous sound and light levels and timings remain sparse in part due to the lack of ICU equipment that monitors sound and light. Here, we describe sound and light levels across three adult ICUs in a large urban United States tertiary care hospital using a novel sensor. The novel sound and light sensor is composed of a Gravity Sound Level Meter for sound level measurements and an Adafruit TSL2561 digital luminosity sensor for light levels. Sound and light levels were continuously monitored in the room of 136 patients (mean age = 67.0 (8.7) years, 44.9% female) enrolled in the Investigation of Sleep in the Intensive Care Unit study (ICU-SLEEP; Clinicaltrials.gov: #NCT03355053), at the Massachusetts General Hospital. The hours of available sound and light data ranged from 24.0 to 72.2 hours. Average sound and light levels oscillated throughout the day and night. On average, the loudest hour was 17:00 and the quietest hour was 02:00. Average light levels were brightest at 09:00 and dimmest at 04:00. For all participants, average nightly sound levels exceeded the WHO guideline of < 35 decibels. Similarly, mean nightly light levels varied across participants (minimum: 1.00 lux, maximum: 577.05 lux). Sound and light events were more frequent between 08:00 and 20:00 than between 20:00 and 08:00 and were largely similar on weekdays and weekend days. Peaks in distinct alarm frequencies (Alarm 1) occurred at 01:00, 06:00, and at 20:00. Alarms at other frequencies (Alarm 2) were relatively consistent throughout the day and night, with a small peak at 20:00. In conclusion, we present a sound and light data collection method and results from a cohort of critically ill patients, demonstrating excess sound and light levels across multiple ICUs in a large tertiary care hospital in the United States. ClinicalTrials.gov, #NCT03355053. Registered 28 November 2017, https://clinicaltrials.gov/ct2/show/NCT03355053.

Effects of Ketamine Infusion on Breathing and Encephalography in Spontaneously Breathing ICU Patients

BACKGROUND

Preclinical studies suggest that ketamine stimulates breathing. We investigated whether adding a ketamine infusion at low and high doses to propofol sedation improves inspiratory flow and enhances sedation in spontaneously breathing critically ill patients.

METHODS

In this prospective interventional study, twelve intubated, spontaneously breathing patients received ketamine infusions at 5 mcg/kg/min, followed by 10 mcg/kg/min for 1 h each. Airway flow, pressure, and esophageal pressure were recorded during a spontaneous breathing trial (SBT) at baseline, and during the SBT conducted at the end of each ketamine infusion regimen. SBT consisted of one-minute breathing with zero end-expiratory pressure and no pressure support. Changes in inspiratory flow at the pre-specified time points were assessed as the primary outcome. Ketamine-induced change in beta-gamma electroencephalogram power was the key secondary endpoint. We also analyzed changes in other ventilatory parameters respiratory timing, and resistive and elastic inspiratory work of breathing.

RESULTS

Ketamine infusion of 5 and 10 mcg/kg/min increased inspiratory flow (median, IQR) from 0.36 (0.29-0.46) L/s at baseline to 0.47 (0.32-0.57) L/s and 0.44 (0.33-0.58) L/s, respectively (p = .013). Resistive work of breathing decreased from 0.4 (0.1-0.6) J/l at baseline to 0.2 (0.1-0.3) J/l after ketamine 10 mcg/kg/min (p = .042), while elastic work of breathing remained unchanged. Electroencephalogram beta-gamma power (19-44 Hz) increased compared to baseline (p < .01).

CONCLUSIONS

In intubated, spontaneously breathing patients receiving a constant rate of propofol, ketamine increased inspiratory flow, reduced inspiratory work of breathing, and was associated with an "activated" electroencephalographic pattern. These characteristics might facilitate weaning from mechanical ventilation.

1159 Sleep Traits And Incident Delirium During A Decade Of Follow-up In 173,000 Participants

Introduction

Delirium is an acute decline in attention and cognition that is with associated long-term cognitive dysfunction in elderly patients. Accumulating evidence points to strong associations between sleep health and disorders of the brain. We tested whether baseline sleep duration, chronotype, daytime dozing, insomnia or sleep apnea predict incident delirium during hospitalization.

Methods

We studied participants from the UK Biobank who have been followed for up to 10 years until 2017. We included 173,221 participants (mean age 60±5; range 50-71 at baseline) who had at least one episode of hospitalization/surgery and were free from prior episodes of delirium. Delirium diagnosis, hospitalization and surgical events were derived using ICD-10 coding. Multivariate logistic regression models were performed to examine the associations of self-reported baseline sleep duration (&lt;6hrs/6-9h/&gt;9h), daytime dozing (often/rarely), insomnia (often/rarely) and presence of sleep apnea (ICD-10 and self-report) with incident delirium during follow-up. Models were adjusted for demographics, education, Townsend deprivation index, and major confounders (number of hospitalizations/surgical procedures, BMI, diabetes, major cardiovascular diseases and risk factors, major neurological diseases, major respiratory diseases, cancer, alcohol, depression/anxiety, sedatives/sleep aides, antipsychotics, steroids and opioids).

Results

In total, 1,023 (5.7 per 1,000 subjects) developed delirium. A prior diagnosis of sleep apnea (n=1,294) saw almost a two-fold increased odds (OR 1.96, 95% CI: 1.30-2.30 p=0.001) while those who often had daytime dozing were also at increased risk (OR 1.35, 95% CI: 1.02-1.80, p=0.025). Both these effects were independent of each other. No independent effects on incident delirium were observed from sleep duration, insomnia, or chronotype.

Conclusion

Certain sleep disturbances, in particular sleep apnea and daytime dozing, are independently associated with an increased risk for developing delirium. Further work is warranted to examine underlying mechanisms and to test whether optimizing sleep health can reduce the risk of developing delirium.

Support

This work was supported by NIH grants T32GM007592, RF1AG064312, and RF1AG059867.

0259 Shiftworkers are at Increased Risk of Developing Chronic Pain and Opioid Use Disorders: A Study of 116,000 UK Biobank Participants Over a Decade

Introduction

In the current epidemic of opioid-related deaths, and widespread use of opioids to treat chronic pain, there is a pressing need to understand the underlying risk factors that contribute to such devastating conditions. Shiftwork has been associated with adverse health outcomes. We tested whether shiftwork during middle age is linked to the development of chronic pain and opioid misuse.

Methods

We studied 116,474 participants in active employment between 2006–2010 (mean age 57±8; range 37–71) from the UK Biobank, who have been followed for up to 10 years until 2017. We included participants who were free from all forms of self-reported pain, and were not taking opioid medications at baseline. Chronic pain and opioid use disorder diagnoses were determined using hospitalization records and diagnostic coding from ICD-10. Multivariate logistic regression models were performed to examine the associations of shiftwork status (yes/no) and nightshift frequency (none/occasional/permanent) and with incident chronic pain and/or opioid use disorder during follow-up. Models were adjusted for demographics, education, Townsend deprivation index, major confounders (BMI, diabetes, bone fractures/injuries, operations, peripheral vascular disease, joint/inflammatory diseases, cancer, standing/manual labor at work) and covariates (smoking, alcohol, high cholesterol, depression/anxiety, and cardiovascular diseases).

Results

In total, 190 (1.6/1,000) developed chronic pain or opioid use disorders. Shiftworkers (n=17,673) saw a 1.5-fold increased risk (OR 1.56, 95% CI: 1.08–2.24, p=0.01) relative to day workers. Within shiftworkers, those who reported occasional nightshift work (n=3,966) were most vulnerable (OR 1.57, 95% CI: 1.06–2.34, p=0.02). Results remained similar after adjusting for baseline sleep duration, chronotype and insomnia.

Conclusion

Shiftwork, and in particular rotating nightshift work is associated with increased risk for developing chronic pain and opioid use disorders. Replication is required to confirm the findings and to examine underlying mechanisms.

Support

This work was supported by NIH grants T32GM007592, RF1AG064312, and RF1AG059867.