Circadian rhythm in critically ill patients: Insights from the eICU Database

Chrononutrition in Critical Illness

Circadian rhythms in humans are biological rhythms that regulate various physiological processes within a 24-hour time frame. Critical illness can disrupt the circadian rhythm, as can environmental and clinical factors, including altered light exposure, organ replacement therapies, disrupted sleep-wake cycles, noise, continuous enteral feeding, immobility, and therapeutic interventions. Nonpharmacological interventions, controlling the ICU environment, and pharmacological treatments are among the treatment strategies for circadian disruption. Nutrition establishes biological rhythms in metabolically active peripheral tissues and organs through appropriate synchronization with endocrine signals. Therefore, adhering to a feeding schedule based on the biological clock, a concept known as "chrononutrition," appears to be vitally important for regulating peripheral clocks. Chrononutritional approaches, such as intermittent enteral feeding that includes overnight fasting and consideration of macronutrient composition in enteral solutions, could potentially restore circadian health by resetting peripheral clocks. However, due to the lack of evidence, further studies on the effect of chrononutrition on clinical outcomes in critical illness are needed. The purpose of this review was to discuss the role of chrononutrition in regulating biological rhythms in critical illness, and its impact on clinical outcomes.

Using routinely collected clinical data for circadian medicine: A review of opportunities and challenges

A wealth of data is available from electronic health records (EHR) that are collected as part of routine clinical care in hospitals worldwide. These rich, longitudinal data offer an attractive object of study for the field of circadian medicine, which aims to translate knowledge of circadian rhythms to improve patient health. This narrative review aims to discuss opportunities for EHR in studies of circadian medicine, highlight the methodological challenges, and provide recommendations for using these data to advance the field. In the existing literature, we find that data collected in real-world clinical settings have the potential to shed light on key questions in circadian medicine, including how 24-hour rhythms in clinical features are associated with-or even predictive of-health outcomes, whether the effect of medication or other clinical activities depend on time of day, and how circadian rhythms in physiology may influence clinical reference ranges or sampling protocols. However, optimal use of EHR to advance circadian medicine requires careful consideration of the limitations and sources of bias that are inherent to these data sources. In particular, time of day influences almost every interaction between a patient and the healthcare system, creating operational 24-hour patterns in the data that have little or nothing to do with biology. Addressing these challenges could help to expand the evidence base for the use of EHR in the field of circadian medicine.

Timing of diuretic administration effects on urine volume in hospitalized patients

Importance: Some medications have effects that depend on the time of day they are given. Current knowledge of the time-of-day effects of specific medications in hospitalized patients with cardiovascular disease is very limited. In hospitalized patients, increased medication efficiency might reduce dose (and associated side effects) and/or the length of time in the Intensive Care Unit (ICU) or hospital-potentially improving patient outcomes and patient and family quality of life and reducing financial costs. We studied whether the time of day or night patients in Cardiac or Intensive Care Units receive a diuretic affects urine volume. Methods: In this observational study, data were collected from 7,685 patients (63% male, 18 to 98 years old) admitted to one hospital's Acute Care Cardiac units, Cardiac ICUs, Cardiac Surgery ICUs, and/or Non-cardiac ICUs who received intravenous furosemide (a diuretic), had measurements of urine volume, were hospitalized for ≥3 days between January 2016 to July 2021 and were older than 18 years. The outcomes of interest were urine volume normalized by the most recent (not older than 24 h) weight or body mass index (BMI), (i) in the hour after the time of diuretic administration, and (ii) when no diuretics were administered for the previous 3 h. Results: We identified diuretic medication administration time 23:00-04:59 as a predictor of higher urine volume response. For patients without recent diuretic medication, higher urine volume was predicted 11:00-16:59 and 17:00-22:59. Other factors that affected urine volume response to the diuretic were sex, age, medication dose, creatinine concentration, diagnoses, and hospital unit. Discussion: Time-of-day of medication administration may be a factor associated with increased medication efficiency. Randomized controlled trials should be conducted to quantify the relative effect of modifiable factors, such as time of medication administration, that may affect short- and longer-term outcomes.

Association between circadian body temperature rhythm during the first 24 hours of ICU stay and 28-day mortality in elderly critically ill patients: A retrospective cohort study

Disrupted circadian temperature rhythm is commonly observed in elderly patients in the intensive care unit (ICU), but the association between circadian temperature rhythm and mortality in elderly patients is unclear. Adult patients with a relatively complete record of body temperature (BT) during the first 24 hours of ICU stay in the Multi-parameter Intelligent Monitoring in Intensive Care IV (MIMIC-IV) database were included in this retrospective cohort study. The circadian rhythm of body temperature was blunted as a ratio of the maximum BT between 12:00 and 24:00 divided by the minimum BT between 0:00 and 12:00, and we defined it as BT fluctuation ratio. The associations of BT fluctuation ratio with 28-day mortality were assessed separately using Cox proportional hazards model in elderly patients and non-elderly patients. The overall cohort comprised 12 767 patients. After adjusting for covariates, the analysis showed that the BT fluctuation ratio (%) was significantly associated with mortality at 28 days in total patients (hazard ratio: 1.044; 95% CI 1.001-1.088; P = 0.042), and still significantly in elderly patients (hazard ratio 1.055, 95% CI as 1.004-1.109, p = 0.035), but not significantly in non-elderly patients. The implementation of restricted cubic splines demonstrated a nonlinear correlation between the ratio of BT fluctuation and the hazard ratio of 28-day mortality, indicating that increased diurnal temperature fluctuations are linked to elevated risk of mortality. This study revealed that the augmented amplitude of the circadian rhythm of body temperature in the elderly patients constitutes a risk factor for the rise of 28-day mortality. Additionally, the circadian body temperature rhythm may facilitate the early detection of critically ill elderly patients.

Causes, Consequences, and Treatments of Sleep and Circadian Disruption in the ICU: An Official American Thoracic Society Research Statement

Background: Sleep and circadian disruption (SCD) is common and severe in the ICU. On the basis of rigorous evidence in non-ICU populations and emerging evidence in ICU populations, SCD is likely to have a profound negative impact on patient outcomes. Thus, it is urgent that we establish research priorities to advance understanding of ICU SCD. Methods: We convened a multidisciplinary group with relevant expertise to participate in an American Thoracic Society Workshop. Workshop objectives included identifying ICU SCD subtopics of interest, key knowledge gaps, and research priorities. Members attended remote sessions from March to November 2021. Recorded presentations were prepared and viewed by members before Workshop sessions. Workshop discussion focused on key gaps and related research priorities. The priorities listed herein were selected on the basis of rank as established by a series of anonymous surveys. Results: We identified the following research priorities: establish an ICU SCD definition, further develop rigorous and feasible ICU SCD measures, test associations between ICU SCD domains and outcomes, promote the inclusion of mechanistic and patient-centered outcomes within large clinical studies, leverage implementation science strategies to maximize intervention fidelity and sustainability, and collaborate among investigators to harmonize methods and promote multisite investigation. Conclusions: ICU SCD is a complex and compelling potential target for improving ICU outcomes. Given the influence on all other research priorities, further development of rigorous, feasible ICU SCD measurement is a key next step in advancing the field.

Circadian rhythms of vital signs are associated with in-hospital mortality in critically ill patients: A retrospective observational study

Vital signs have been widely used to assess the disease severity of patients, but there is still a lack of research on their circadian rhythms. The objective is to explore the circadian rhythms of vital signs in critically ill patients and establish an in-hospital mortality prediction model. Study patients from the recorded eICU Collaborative Research Database were included in the present analyses. The circadian rhythms of vital signs are analyzed in critically ill patients using the cosinor method. Logistic regression was used to screen independent predictors and establish a prediction model for in-hospital mortality by multivariate logistic regression analysis and to show in the nomogram. Internal validation is used to evaluate the prediction model by bootstrapping with 1000 resamples. A total of 29,448 patients were included in the current analyses. The Mesor, Amplitude, and Peak time of vital signs, such as heart rate (HR), temperature, respiration rate (RR), pulse oximetry-derived oxygen saturation (SpO2), and blood pressure (BP), were significant differences between survivors and non-survivors . Logistic regression analysis showed that Mesor, Amplitude, and Peak time of HR, RR, and SpO2 were independent predictors for in-hospital mortality in critically ill patients. The area under the curve (AUC) and c-index of the prediction model for the Medical intensive care unit (MICU) and Surgical intensive care unit (SICU) were 0.807 and 0.801, respectively. The Hosmer-Lemeshow test P-values were 0.076 and 0.085, respectively, demonstrating a good fit for the prediction model. The calibration curve and decision curve analysis (DCA) also demonstrated its accuracy and applicability. Internal validation assesses the consistency of the results. There were significant differences in the circadian rhythms of vital signs between survivors and non-survivors in critically ill patients. The prediction model established by the Mesor, Amplitude, and Peak time of HR, RR, and SpO2 combined with the Acute Physiology and Chronic Health Evaluation (APACHE) IV score has good predictive performance for in-hospital mortality and may eventually support clinical decision-making.Abbreviations: ICU: Intensive care unit; MICU: Medical intensive care unit; SICU: Surgical intensive care unit; HR: Heart rate; RR: Respiration rate; SpO2: Pulse oximetry-derived oxygen saturation; BP: Blood pressure; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; APACHE: Acute Physiology and Chronic Health Evaluation; bpm: beats per min; BMI: Body mass index; OR: Odd ratio; CI: Confidential interval; IQR: Interquartile range; SD: Standard deviation; ROC: Receiver operating characteristic; AUC: area under the curve; DCA: Decision curve analysis; IRB: Institutional review board.