Fever, hypothermia, and mortality in sepsis: Comment on: Rumbus Z, Matics R, Hegyi P, Zsiboras C, Szabo I, Illes A, Petervari E, Balasko M, Marta K, Miko A, Parniczky A, Tenk J, Rostas I, Solymar M, Garami A. Fever is associated with reduced, hypothermia with increased mortality in septic patients: a meta-analysis of clinical trials. PLoS One. 2017;12(1):e0170152. DOI: 10.1371/journal.pone.0170152

Lanthanide luminescence nanothermometer with working wavelength beyond 1500 nm for cerebrovascular temperature imaging in vivo

Nanothermometers enable the detection of temperature changes at the microscopic scale, which is crucial for elucidating biological mechanisms and guiding treatment strategies. However, temperature monitoring of micron-scale structures in vivo using luminescent nanothermometers remains challenging, primarily due to the severe scattering effect of biological tissue that compromises the imaging resolution. Herein, a lanthanide luminescence nanothermometer with a working wavelength beyond 1500 nm is developed to achieve high-resolution temperature imaging in vivo. The energy transfer between lanthanide ions (Er3+ and Yb3+) and H2O molecules, called the environment quenching assisted downshifting process, is utilized to establish temperature-sensitive emissions at 1550 and 980 nm. Using an optimized thin active shell doped with Yb3+ ions, the nanothermometer's thermal sensitivity and the 1550 nm emission intensity are enhanced by modulating the environment quenching assisted downshifting process. Consequently, minimally invasive temperature imaging of the cerebrovascular system in mice with an imaging resolution of nearly 200 μm is achieved using the nanothermometer. This work points to a method for high-resolution temperature imaging of micron-level structures in vivo, potentially giving insights into research in temperature sensing, disease diagnosis, and treatment development.

Hypothermia: Beyond the Narrative Review-The Point of View of Emergency Physicians and Medico-Legal Considerations

Hypothermia is a widespread condition all over the world, with a high risk of mortality in pre-hospital and in-hospital settings when it is not promptly and adequately treated. In this review, we aim to describe the main specificities of the diagnosis and treatment of hypothermia through consideration of the physiological changes that occur in hypothermic patients. Hypothermia can occur due to unfavorable environmental conditions as well as internal causes, such as pathological states that result in reduced heat production, increased heat loss or ineffectiveness of the thermal regulation system. The consequences of hypothermia affect several systems in the body-the cardiovascular system, the central and peripheral nervous systems, the respiratory system, the endocrine system and the gastrointestinal system-but also kidney function, electrolyte balance and coagulation. Once hypothermia is recognized, prompt treatment, focused on restoring body temperature and supporting vital functions, is fundamental in order to avert preventable death. It is important to also denote the fact that CPR has specificities related to the unique profile of hypothermic patients.

Two-stage prediction model for in-hospital mortality of patients with influenza infection

BACKGROUND

Infleunza is a challenging issue in public health. The mortality and morbidity associated with epidemic and pandemic influenza puts a heavy burden on health care system. Most patients with influenza can be treated on an outpatient basis but some required critical care. It is crucial for frontline physicians to stratify influenza patients by level of risk. Therefore, this study aimed to create a prediction model for critical care and in-hospital mortality.

METHODS

This retrospective cohort study extracted data from the Chang Gung Research Database. This study included the patients who were diagnosed with influenza between 2010 and 2016. The primary outcome of this study was critical illness. The secondary analysis was to predict in-hospital mortality. A two-stage-modeling method was developed to predict hospital mortality. We constructed a multiple logistic regression model to predict the outcome of critical illness in the first stage, then S1 score were calculated. In the second stage, we used the S1 score and other data to construct a backward multiple logistic regression model. The area under the receiver operating curve was used to assess the predictive value of the model.

RESULTS

In the present study, 1680 patients met the inclusion criteria. The overall ICU admission and in-hospital mortality was 10.36% (174 patients) and 4.29% (72 patients), respectively. In stage I analysis, hypothermia (OR = 1.92), tachypnea (OR = 4.94), lower systolic blood pressure (OR = 2.35), diabetes mellitus (OR = 1.87), leukocytosis (OR = 2.22), leukopenia (OR = 2.70), and a high percentage of segmented neutrophils (OR = 2.10) were associated with ICU admission. Bandemia had the highest odds ratio in the Stage I model (OR = 5.43). In stage II analysis, C-reactive protein (OR = 1.01), blood urea nitrogen (OR = 1.02) and stage I model's S1 score were assocaited with in-hospital mortality. The area under the curve for the stage I and II model was 0.889 and 0.766, respectively.

CONCLUSIONS

The two-stage model is a efficient risk-stratification tool for predicting critical illness and mortailty. The model may be an optional tool other than qSOFA and SIRS criteria.

Hypothermia is Associated With Poor Prognosis in Hospitalized Patients With Severe COVID-19 Symptoms

Rationale Hypothermia forms a part of the diagnostic criteria for Systemic Inflammatory Response Syndrome (SIRS), National Early Warning Score (NEWS) and has repeatedly been shown to be associated with worse outcomes when compared to normothermic and hyperthermic patients with sepsis. We evaluate whether this is the case in COVID-19 patients. Objective To determine whether there is an association between hypothermia and worse prognosis in COVID-19 patients in the intensive care unit. Methods Retrospective study of a cohort of patients (n = 57) admitted to the intensive care unit of a community hospital with a positive test for COVID-19. Measurements Data relating to mortality, comorbidities and length of stay was recorded from electronic medical records for each patient. Hypothermia was defined as ≥2 recorded body temperatures of less than 96.5℉ (35.83℃) at the time of admission. Main results Of the 57 patients enrolled in the study, 21 developed hypothermia during their stay and 36 did not. Our results show that patients who have hypothermia at the time of admission spend a longer time intubated (p < 0.01) and go through longer ICU stays (p < 0.01). These patients are also 2.18 times more likely to suffer a fatal outcome compared to patients that did not develop hypothermia while in the intensive care unit (Chi-squared = 8.6209, p < 0.01, RR = 2.18). Conclusions Hypothermia in patients with severe COVID-19 at the time of admission to the ICU is associated with poorer outcomes for patients. This manifests as a longer period of intubation, longer ICU stay, and increased risk of mortality.