Circadian rhythm is a universal, built-in timing system that lasts nearly 24 hours and can be assessed through chronobiologic analysis of the time series of melatonin, cortisol and temperature [11]. This system was developed by the changes the human body respond to the external environment, specifically, the periodic changes in light and darkness caused by the Earth's revolution around the sun. Prior research generally confirms that circadian rhythms are controlled by a master clock in the suprachiasmatic nucleus (SCN) of the hypothalamus and regulated by the nerve hormone including the hypothalamo-pituitary-adrenal (HPA) axis and melatonin in the pineal gland [1, 12]. Patients hospitalized in the ICU are subject to changes in various zeitgebers due to light/dark cycles, social interactions, dietary patterns, medication, etc., which may cause changes in circadian rhythms such as core body temperature, leading to further adverse consequences [13, 14]. Our study explores the role of diurnal temperature trend in ICU patients in predicting illness and prognosis, and for the first time uses temperature models to distinguish the clinical trends of different groups.
Traditionally, temperature has been considered a dichotomous variable and patients are classified as febrile or nonfebrile based on absolute value. However, evidence suggests that temperature pattern analysis can convey meaningful clinical information whether or not patients meet the criteria for fever [15–17]. Varela et al. investigated the role of temperature change analysis in predicting survival in critically ill patients and found that temperature analysis was similar in its ability to predict mortality as the sequential organ failure assessment score [18]. Some scholars have reported that typical changes in temperature patterns include changes in amplitude, increases in frequency, or increases or decreases in baseline variability [19]. Therefore, it provides support for patients in intensive care units to explore effective diurnal temperature trend prediction models.
Published studies have reported the relationship between BT and biological rhythm or progression of disease or all-cause mortality in hospitalized, and ICU patients. Benjamin et al performed a cohort of severe trauma patients in France and reported that early exacerbation of the temperature rhythmicity is associated with the development of sepsis [20]. In another cohort of 6759 neurologic ICU patients from a 20-bed neurology ICU in the USA, elevated body temperature was found to predict higher mortality rate and worse outcome [21]. BT is one of the vital signs that can be used to evaluate APCHE III and mortality in critically ill patients [18]. However, no studies have reported circadian BT variation and its prognostic value in the ICU. In our study, we extracted complete BT records of patients’ first 24 hours in the ICU from a public database and investigated the circadian characteristics of BT to determine how to identify patients with a higher risk of mortality early in the hospital. We found that NBTR served as an important protective factor for higher survival in the 28-d mortality (HR: 0.923; 95% CI, 0.888–0.960) after adjusting for a series of covariates. To the best of our knowledge, this study is the first in which the relationship between the circadian rhythm of BT and ICU mortality has been evaluated.
Wu's study showed that the prognosis for sepsis patients in ICU became worse with decreased temperature minimum (T min), as well as increased T max and T max–min [22]. Further analysis indicated that A36.5–37°C (A: the area under the temperature curve) was associated with a positive prognosis. Meanwhile, A38–38.5°C, A38.5–39°C, and A39–39.5°C could result in a poor prognosis. From that perspective, stratified comparison can better distinguish the survival conditions of different risk ratios. Therefore, it is necessary to scientifically distinguish the risk levels of different groups for accurate prediction of clinical outcomes of diseases. To exclude the effect of clinical indicators included in the analysis on the relationship between BTCRR and survival outcomes, we divided the participants into 5 groups according to various BTCRR proportion and then conducted interaction and subgroup analysis. Findings suggested that the higher the proportion, the higher the survival. The association between BTCRR and mortality remained significant in various subgroups. We have demonstrated a non-linear, significant association between the percent BTCRR and mortality by 28-d. The results suggest that increasing the BTCRR to approximately 100 % was associated with decreased mortality, while increases above that point were associated with increasing mortality. From the perspective of biorhythm, moderate elevation of body temperature at night in ICU patients may be a positive embodiment of immune protection. This is consistent with the normal body temperature regulation, indicating that the patient has better immune regulation function [23–27]. Therefore, BTCRR could be used as a reliable risk factor for ICU mortality.
An abnormal circadian status of BT is mainly caused by dysfunction of the thermoregulation center and day/night differences in physical activities [28]. Patients in the ICU usually experience tremendous acute stressors like infections, trauma, multiple organ dysfunctions, artificial light, noise, mechanical ventilation, enteral nutrition, and medications. These factors further lead to abnormal thermoregulation [29–31]. Previous studies showed that abnormal body temperature is determined by the outcome of energy metabolism [32]. In addition, abnormal BT variation observed in patients is associated with autonomic nervous system dysfunction and poor sleep quality, which is also common in ICU patients, unless they are sedated or unconscious [33, 34]. Nevertheless, there is still no definitive study of the mechanism behind the circadian changes in body temperature, which provides a train of thought for further exploration.
However, there are some limitations to our analysis. Firstly, MIMIC-III is a single-center database, and thus obvious selection bias cannot be ignored. On the positive side, the recruited patients were enrolled from various ICUs, in other words, their data may reflect real-world situations encountered by clinicians. Secondly, given the retrospective design, the data were previously collected. Therefore, some of the information is incomplete such as the frequency of BT monitoring, noise level, patient/nurse ratio. Although we have adjusted for as many covariates as possible and conducted a series of sensitivity analysis, a multicenter prospective study with adequate covariates is needed to further confirm the association between BTCRR and prognostic outcomes in critically ill patients. Thirdly, our study is only an association between BTCRR and mortality, not a cause-and-effect relationship. Subsequently, a high-quality prospective research is urgently needed to evaluate causality between BTCRR and mortality.