Serum lactate levels have been widely studied as a prognostic marker in critically ill patients, particularly those in the intensive care unit. However, it remains unknown whether the serum lactate levels affect the mortality rate of critically ill patients admitted to hospital. To investigate this hypothesis, the vital signs and blood gas analysis data of 1,393 critically ill patients who visited the Emergency Department of Affiliated Kunshan Hospital of Jiangsu University (Kunshan, China) between January and December 2021 were collected. Patients were divided into two groups, 30-day survival group and a 30-day death group, and logistic regression analysis was used to investigate the association between vital signs, laboratory results and mortality rates of critically ill patients. A total of 1,393 critically ill patients was enrolled in the present study, with a male-to-female ratio of 1.17:1.00, a mean age of 67.72±19.29 years and a mortality rate of 11.6%. The multivariate logistic regression analysis revealed that increased serum lactate levels were an independent risk factor for mortality rate of critically ill patients [Odds ratio (OR)=1.50, 95% confidence interval (95% CI): 1.40-1.62]. The critical cut-off value for the serum lactate levels was identified as 2.35 mmol/l. In addition, OR values of age, heart rate, systolic blood pressure, transcutaneous oxygen saturation (SpO2) and hemoglobin were 1.02, 1.01, 0.99, 0.96 and 0.99, respectively (95% CI: 1.01-1.04, 1.00-1.02, 0.98-0.99, 0.94-0.98 and 0.98-1.00, respectively). The logistic regression model was found to be of value in terms of identifying the mortality rate of patients and the area under the receiver operating characteristic curve was 0.894 (95% CI: 0.863-0.925; P<0.001). In conclusion, the present study showed that high serum lactate levels in critically ill patients upon admission to hospital are associated with higher 30-day mortality rate.

The relationship between relative hyperglycemia and ventricular arrhythmia (VA) in critically ill patients admitted to intensive care units (ICU) remains unclear. This study aims to investigate the association between stress hyperglycemia ratio (SHR) and VA in this population.
This retrospective and observational study analyzed data from 4324 critically ill patients admitted to the ICU, obtained from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The SHR was calculated as the highest blood glucose level during the first 24 h of ICU admission divided by the admission blood glucose level. Based on the optimal cut-off values under the receiver operating characteristic curve, patients were stratified into high SHR (≥ 1.31) and low SHR (< 1.31) group. To investigate the impact of diabetes mellitus (DM) on the outcome, patients were stratified as low SHR/DM; low SHR/non-DM; high SHR/DM, and high SHR/non-DM. Restricted cubic spline (RCS) and logistic regression analysis were performed to analyze the relationship between SHR and VA.
A total of 4,324 critically ill patients were included in this retrospective and observational study. The incidence of VA was higher in the high SHR group. Multiple-adjusted RCS revealed a \"J-shaped\" correlation between SHR and VA morbidity. The logistic regression model demonstrated that high SHR was associated with VA. The high SHR/non-DM group had a higher risk of VA than other groups stratified based on SHR and DM. Subgroup analysis showed that high SHR was associated with an increased risk of VA in patients with coronary artery disease.
High SHR is an independent risk factor and has potential as a biomarker of higher VT/VF risk in ICU-admitted patients.

Several biomarkers have been proposed to predict the occurrence of acute kidney injury (AKI); however, their efficacy varies between different trials. The aim of this study was to compare the predictive performance of different candidate biomarkers for AKI.
In this systematic review, we searched PubMed, Medline, Embase, and the Cochrane Library for papers published up to August 15, 2022. We selected all studies of adults (> 18 years) that reported the predictive performance of damage biomarkers (neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid-binding protein (L-FABP)), inflammatory biomarker (interleukin-18 (IL-18)), and stress biomarker (tissue inhibitor of metalloproteinases-2 × insulin-like growth factor-binding protein-7 (TIMP-2 × IGFBP-7)) for the occurrence of AKI. We performed pairwise meta-analyses to calculate odds ratios (ORs) and 95% confidence intervals (CIs) individually. Hierarchical summary receiver operating characteristic curves (HSROCs) were used to summarize the pooled test performance, and the Grading of Recommendations, Assessment, Development and Evaluations criteria were used to appraise the quality of evidence.
We identified 242 published relevant studies from 1,803 screened abstracts, of which 110 studies with 38,725 patients were included in this meta-analysis. Urinary NGAL/creatinine (diagnostic odds ratio [DOR] 16.2, 95% CI 10.1-25.9), urinary NGAL (DOR 13.8, 95% CI 10.2-18.8), and serum NGAL (DOR 12.6, 95% CI 9.3-17.3) had the best diagnostic accuracy for the risk of AKI. In subgroup analyses, urinary NGAL, urinary NGAL/creatinine, and serum NGAL had better diagnostic accuracy for AKI than urinary IL-18 in non-critically ill patients. However, all of the biomarkers had similar diagnostic accuracy in critically ill patients. In the setting of medical and non-sepsis patients, urinary NGAL had better predictive performance than urinary IL-18, urinary L-FABP, and urinary TIMP-2 × IGFBP-7: 0.3. In the surgical patients, urinary NGAL/creatinine and urinary KIM-1 had the best diagnostic accuracy. The HSROC values of urinary NGAL/creatinine, urinary NGAL, and serum NGAL were 91.4%, 85.2%, and 84.7%, respectively.
Biomarkers containing NGAL had the best predictive accuracy for the occurrence of AKI, regardless of whether or not the values were adjusted by urinary creatinine, and especially in medically treated patients. However, the predictive performance of urinary NGAL was limited in surgical patients, and urinary NGAL/creatinine seemed to be the most accurate biomarkers in these patients. All of the biomarkers had similar predictive performance in critically ill patients. Trial registration CRD42020207883 , October 06, 2020.

UNASSIGNED: Immunosuppression is a risk factor for poor prognosis of critically ill patients, but current monitoring of the immune status in clinical practice is still inadequate. Absolute lymphocyte count (ALC) is not only a convenient biomarker for immune status monitoring but is also suitable for clinical application. In this study, we aimed to explore different trajectories of ALC, and evaluate their relationship with prognosis in critically ill patients.
UNASSIGNED: We retrospectively enrolled 10,619 critically ill patients admitted to a general intensive care unit (ICU) with 56 beds from February 2016 to May 2020. Dynamic ALC was defined as continuous ALC from before ICU admission to 5 days after ICU admission. Initial ALC was defined as the minimum ALC within 48 h after ICU admission. Group-based trajectory modeling (GBTM) was used to group critically ill patients according to dynamic ALC. Multivariate cox regression model was used to determine the independent association of trajectory endotypes with death and persistent inflammation, immunosuppression, catabolism syndrome (PICS).
UNASSIGNED: A total of 2022 critically ill patients were unsupervisedly divided into four endotypes based on dynamic ALC, including persistent lymphopenia endotype (n = 1,211; 58.5%), slowly rising endotype (n = 443; 22.6%), rapidly decreasing endotype (n = 281; 14.5%) and normal fluctuation endotype (n = 87; 4.4%). Among the four trajectory endotypes, the persistent lymphopenia endotype had the highest incidence of PICS (24.9%), hospital mortality (14.5%) and 28-day mortality (10.8%). In multivariate cox regression model, persistent lymphopenia was associated with increased risk of 28-day mortality (HR: 1.54; 95% CI: 1.06-2.23), hospital mortality (HR: 1.66; 95% CI: 1.20-2.29) and PICS (HR: 1.79; 95% CI: 1.09-2.94), respectively. Sensitivity analysis further confirmed that the ALC trajectory model of non-infected patients and non-elderly patients can accurately distinguished 91 and 90% of critically ill patients into the same endotypes as the original model, respectively.
UNASSIGNED: The ALC trajectory model is helpful for grouping critically ill patients, and early persistent lymphopenia is associated with poor prognosis. Notably, persistent lymphopenia may be a robust signal of immunosuppression in critically ill patients.

The pharmacokinetics (PK) of several drugs including antimicrobials might be highly altered during extracorporeal membrane oxygenation (ECMO) therapy. We present the change of voriconazole (VRC) PK during ECMO in a critically ill patient who received intravenous VRC at a maintenance dose of 200 mg every 12 h for empirical antifungal therapy. Two PK profiles were drawn before and after the initiation of ECMO therapy. Though the trough levels (both C0 and C12) with ECMO were slightly lower than that without ECMO (12.58 and 12.84 vs. 14.02 μg/mL), the peak levels and the area under the concentration-time curve from 0 h to 6 h (AUC0-6) were comparable (16.36 vs. 16.06 μg/mL and 90.78 vs. 91.45 μg·h/mL, respectively), indicating that VRC plasma exposure during ECMO therapy did not greatly decrease in our patient. The circuit factors including the type of membrane should be taken into account to further identify the effects of ECMO on the PK of VRC.

To investigate if a Family-Clinician Shared Decision-Making (FCSDM) intervention benefits patients, families and intensive care units (ICUs) clinicians.
Six ICUs in China were allocated to intervention or usual care. 548 patients with critical illness, 548 family members and 387 ICU clinicians were included into the study. Structured FCSDM family meetings were held in the intervention group. Scales of SSDM, HADS, QoL2 and CSACD were used to assess families\' satisfaction and distress, patients\' quality of life, and clinicians\' collaboration respectively.
Comparing the intervention group with the control group at post-intervention, there were significant differences in the families\' satisfaction (P = 0.0001), depression level (P = 0.005), and patients\' quality of life (P = 0.0007). The clinicians\' mean CSCAD score was more positive in the intervention group than controls (P < 0.05). There was no significant between-group differences on ICU daily medical cost, but the intervention group demonstrated shorter number of days\' stay in ICU (P = 0.0004).
The FCSDM intervention improved families\' satisfaction and depression, shortened patients\' duration of ICU stay, and enhanced ICU clinicians\' collaboration.
Further improvement and promotion of the FCSDM model are needed to provide more evidence to this field in China.

BACKGROUND: This study explored the differences, correlation, and consistency between blood glucose levels measured using an arterial blood gas analyzer and a rapid blood glucose meter in critically ill patients.
METHODS: A total of 73 critically ill patients admitted to the Department of Critical Care Medicine, from October to December 2016 were enrolled in this study. The patient\'s arterial blood glucose was measured by arterial blood gas analyzer, while peripheral blood glucose was measured by a rapid blood glucose meter (via the non-infusion limb). The correlation between indicators was analyzed using the linear regression model. Bland-Altman was performed to evaluate the agreement of the two methods for measuring blood glucose. P<0.05 was considered statistically significant.
RESULTS: The blood glucose values measured using the arterial blood gas analyzer was significantly different from the values obtained using the rapid blood glucose meter (P=0.000). Regression analysis showed that R2 was 0.857 and β was 0.324 (P=0.000). Bland-Altman plot analysis showed that arterial blood glucose values obtained using the arterial blood gas analyzer were higher than the peripheral blood glucose values obtained using the rapid blood glucose meter on the non-infused limb, with 2.74% of dots lying outside the 95% limit of agreement and the maximum absolute value (2.30 mmol/L) of blood glucose difference within the limit of agreement. The blood glucose levels measured using the two different methods showed good agreement.
CONCLUSIONS: The difference in blood glucose values measured using the two different measurement methods was statistically significant, but the maximum absolute value (2.30 mmol/L) of blood glucose difference within the limit of agreement, which is acceptable in the clinical setting. In clinical care, it is not necessary to repeat a measure of the patient\'s capillary blood glucose (CBG) using the rapid blood glucose meter after the blood glucose levels have been measured with the arterial blood gas analyzer, thereby reducing the associated pain and inconvenience for the patients.

This study aimed to investigate the frequency and characteristics of respiratory co-infections in COVID-19 patients in the intensive care unit (ICU). In this retrospective observational study, pathogens responsible for potential co-infections were detected by the bacterial culture, real-time polymerase chain reaction (RT-PCR), or serological fungal antigen tests. Demographic and clinical characteristics, as well as microbial results, were analyzed. Bacterial culture identified 56 (58.3%) positive samples for respiratory pathogens, with the most common bacteria being Burkholderia cepacia (18, 18.8%). RT-PCR detected 38 (76.0%) and 58 (87.9%) positive results in the severe and critical groups, respectively. Most common pathogens detected were Stenotrophomonas maltophilia (28.0%) and Pseudomonas aeruginosa (28.0%) in the severe group and S. maltophilia (45.5%) in the critical group. P. aeruginosa was detected more during the early stage after ICU admission. Acinetobacter baumannii and Staphylococcus aureus were more frequently identified during late ICU admission. Fungal serum antigens were more frequently positive in the critical group than in the severe group, and the positive rate of fungal serum antigens frequency increased with prolonged ICU stay. A high frequency of respiratory co-infections presented in ICU COVID-19 patients. Careful examinations and necessary tests should be performed to exclude these co-infections.

UNASSIGNED: To investigate the association between the change of acute gastrointestinal injury (AGI) grade and the outcome in critically ill patients.
UNASSIGNED: This was a prospectively observational study. All patients admitted in the ICU from October 2013 to June 2015, with the duration of ICU > 72 h and age >18 years, were enrolled in this study. The AGI grade and gastrointestinal symptoms were evaluated during ICU stay following the 2012 ESICM recommendation. The ICU mortality, duration of ICU stay, mechanical ventilation (MV) use, vasoactive drug use, and continuous renal replacement therapy of patients were recorded accordingly.
UNASSIGNED: A total of 320 patients were included, and 265 of them were diagnosed with AGI. The overall ICU mortality was 11.88%, while it was 13.58% in patients with AGI. In logistic regression analyses, the decreasing trend of AGI grade was identified as a protective factor for ICU death (odds ratio (OR), 0.484; 95% confidence interval (CI), 0.26-0.90), while the max AGI grade was a risk factor (OR, 3.464; 95% CI, 2.71-8.47) for ICU death.
UNASSIGNED: The changes of AGI grades in critically ill patients were associated with their clinical outcomes. The ICU-acquired AGI patients associated with longer ICU stay days.

Background: Clinical trialists and clinicians have used a number of sleep quality measures to determine the outcomes of interventions to improve sleep and ameliorate the neurobehavioral consequences of sleep deprivation in critically ill patients, but findings have not always been consistent. To elucidate the source of these consistencies, an important consideration is responsiveness of existing sleep measures. The purpose of an evaluative measure is to describe a construct of interest in a specific population, and to measure the extent of change in the construct over time. This systematic literature review identified measures of sleep quality in critically ill adults hospitalized in the Intensive Care Unit (ICU), and assessed their measurement properties, strengths and weaknesses, clinical usefulness, and responsiveness. We also recommended modifications, including new technology, that may improve clinical usefulness and responsiveness of the measures in research and practice. Methods: CINAHAL, PubMed/Medline, and Cochrane Library were searched from January 1, 2000 to February 1, 2020 to identify studies that evaluated sleep quality in critically ill patients. Results: Sixty-two studies using polysomnography (PSG) and other electroencephalogram-based methods, actigraphy, clinician observation, or patient perception using questionnaires were identified and evaluated. Key recommendations are: standard criteria are needed for scoring PSG in ICU patients who often have atypical brain waves; studies are too few, samples sizes too small, and study duration too short for recommendations on electroencephalogram-based measures and actigraphy; use the Sleep Observation Tool for clinician observation of sleep; and use the Richards Campbell Sleep Questionnaire to measure patient perception of sleep. Conclusions: Measuring the impact of interventions to prevent sleep deprivation requires reliable and valid sleep measures, and investigators have made good progress developing, testing, and applying these measures in the ICU. We recommend future large, multi-site intervention studies that measure multiple dimensions of sleep, and provide additional evidence on instrument reliability, validity, feasibility and responsiveness. We also encourage testing new technologies to augment existing measures to improve their feasibility and accuracy.