Background: Individualized positive end-expiratory pressure (PEEP) by electrical impedance tomography (EIT) has potential interest in the optimization of ventilation distribution in acute respiratory distress syndrome (ARDS). The aim of the study was to determine whether early individualized titration of PEEP with EIT improved outcomes in patients with ARDS. Methods: A total of 117 ARDS patients receiving mechanical ventilation were randomly assigned to EIT group (n = 61, PEEP adjusted based on ventilation distribution) or control group (n = 56, low PEEP/FiO₂ table). The primary outcome was 28-day mortality. Secondary and exploratory outcomes were ventilator-free days, length of ICU stay, incidence of pneumothorax and barotrauma, and difference in Sequential Organ Failure Assessment (SOFA) score at day 1 (ΔD1-SOFA) and day 2 (ΔD2-SOFA) compared with baseline. Measurements and main results: There was no statistical difference in the value of PEEP between the EIT group and control group, but the combination of PEEP and FiO₂ was different between groups. In the control group, a significantly positive correlation was found between the PEEP value and the corresponding FiO₂ (r = 0.47, p < 0.00001) since a given matched table was used for PEEP settings. Diverse combinations of PEEP and FiO₂ were found in the EIT group (r = 0.05, p = 0.68). There was no significant difference in mortality rate (21% vs. 27%, EIT vs. control, p = 0.63), ICU length of stay (13.0 (7.0, 25.0) vs 10.0 (7.0, 14.8), median (25th–75th percentile); p = 0.17), and ventilator-free days at day 28 (14.0 (2.0, 23.0) vs 19.0 (0.0, 24.0), p = 0.55) between the two groups. The incidence of new barotrauma was zero. Compared with control group, significantly lower ΔD1-SOFA and ΔD2-SOFA were found in the EIT group (p < 0.001) in a post hoc comparison. Moreover, the EIT group exhibited a significant decrease of SOFA at day 2 compared with baseline (paired t-test, difference by − 1 (− 3.5, 0), p = 0.001). However, the control group did show a similar decrease (difference by 1 (− 2, 2), p = 0.131). Conclusion: Our study showed a 6% absolute decrease in mortality in the EIT group: a statistically non-significant, but clinically non-negligible result. This result along with the showed improvement in organ function might justify further reserach to validate the beneficial effect of individualized EIT-guided PEEP setting on clinical outcomes of patients with ARDS. Trial registration: ClinicalTrials, NCT02361398. Registered 11 February 2015—prospectively registered, https://clinicaltrials.gov/show/NCT02361398.

Introduction: The peripheral perfusion index (PI) is a noninvasive numerical value of peripheral perfusion, and the transcutaneous oxygen challenge test (OCT) is defined as the degree of transcutaneous partial pressure of oxygen (PtcO₂) response to 1.0 FiO_2. The value of noninvasive monitoring peripheral perfusion to predict outcome remains to be established in septic patients after resuscitation. Moreover, the prognostic value of PI has not been investigated in septic patients. Methods: Forty-six septic patients, who were receiving PiCCO-Plus cardiac output monitoring, were included in the study group. Twenty stable postoperative patients were studied as a control group. All the patients inspired 1.0 of FiO₂ for 10 minutes during the OCT. Global hemodynamic variables, traditional metabolic variables, PI and OCT related-variables were measured simultaneously at 24 hours after PiCCO catheter insertion. We obtained the 10min-OCT ((PtcO₂ after 10 minutes on inspired 1.0 oxygen) - (baseline PtcO₂)), and the oxygen challenge index ((10min-OCT)/(PaO₂ on inspired 1.0 oxygen - baseline PaO₂)) during the OCT. Results: The PI was significantly correlated with baseline PtcO₂, 10min-OCT and oxygen challenge index (OCI) in all the patients. The control group had a higher baseline PtcO₂, 10min-OCT and PI than the septic shock group. In the sepsis group, the macro hemodynamic parameters and ScvO₂ showed no differences between survivors and nonsurvivors. The nonsurvivors had a significantly lower PI, 10min-OCT and OCI, and higher arterial lactate level. The PI, 10min-OCT and OCI predicted the ICU mortality with an accuracy that was similar to arterial lactate level. A PI <0.2 and a 10min-OCT <66mmHg were related to poor outcome after resuscitation. Conclusions: The PI and OCT are predictive of mortality for septic patients after resuscitation. Further investigations are required to determine whether the correction of an impaired level of peripheral perfusion may improve the outcome of septic shock patients.

Background: Early prediction of the clinical outcome of patients with sepsis is of great significance and can guide treatment and reduce the mortality of patients. However, it is clinically difficult for clinicians.Methods: A total of 2,224 patients with sepsis were involved over a 3-year period (2016–2018) in the intensive care unit (ICU) of Peking Union Medical College Hospital. With all the key medical data from the first 6 h in the ICU, three machine learning models, logistic regression, random forest, and XGBoost, were used to predict mortality, severity (sepsis/septic shock), and length of ICU stay (LOS) (>6 days, ≤ 6 days). Missing data imputation and oversampling were completed on the dataset before introduction into the models.Results: Compared to the mortality and LOS predictions, the severity prediction achieved the best classification results, based on the area under the operating receiver characteristics (AUC), with the random forest classifier (sensitivity = 0.65, specificity = 0.73, F1 score = 0.72, AUC = 0.79). The random forest model also showed the best overall performance (mortality prediction: sensitivity = 0.50, specificity = 0.84, F1 score = 0.66, AUC = 0.74; LOS prediction: sensitivity = 0.79, specificity = 0.66, F1 score = 0.69, AUC = 0.76) among the three models. The predictive ability of the SOFA score itself was inferior to that of the above three models.Conclusions: Using the random forest classifier in the first 6 h of ICU admission can provide a comprehensive early warning of sepsis, which will contribute to the formulation and management of clinical decisions and the allocation and management of resources.

Objectives: Several studies have investigated the prognostic value of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) in patients with infection. However, the result was controversial. Thus, the purpose of the present meta-analysis was to determine the prognostic value of the sTREM-1 level in predicting mortality at the initial stage of infection.Methods: The literature was searched in the PubMed, EMBASE, Web of Knowledge and Cochrane databases. A 2×2 contingency table was constructed on the basis of mortality and sTREM-1 levels in patients with infection. 2 authors independently judged study eligibility and extracted data. The prognostic value of sTREM-1 in predicting mortality was determined using a bivariate meta-analysis model. Q-test and I²index were used to test heterogeneity.Results: 9 studies were selected from 803 studies. An elevated sTREM-1 level was associated with a higher risk of death in infection, with pooled risk ratio (RR) was 2.54 (95% CI 1.77 to 3.65) using a random-effects model (I²=53.8%). With the bivariate random-effects regression model, the pooled sensitivity and specificity of sTREM-1 to predict mortality in infection were 0.75 (95% CI 0.61 to 0.86) and 0.66 (95% CI 0.54 to 0.75), respectively. The diagnostic OR was 6 (95% CI 3 to 10). The overall area under the summary receiver operator characteristic (SROC) curve was 0.76 (95% CI 0.72 to 0.79). When we calculated the sepsis subgroup, the pooled RR was 2.98 (95% CI 2.19 to 4.40). The pooled sensitivity and specificity were 0.74 (95% CI 0.58 to 0.85) and 0.72 (95% CI 0.62 to 0.80), respectively. The overall area under the SROC curve was 0.78 (95% CI 0.74 to 0.81).Conclusions: Elevated sTREM-1 concentrations had a moderate prognostic significance in assessing the mortality of infection in adult patients. However, sTREM-1 alone is insufficient to predict mortality as a biomarker.

The gut microbiota of intensive care unit (ICU) patients displays extreme dysbiosis associated with increased susceptibility to organ failure, sepsis, and septic shock. However, such dysbiosis is difficult to characterize owing to the high dimensional complexity of the gut microbiota. We tested whether the concept of enterotype can be applied to the gut microbiota of ICU patients to describe the dysbiosis. We collected 131 fecal samples from 64 ICU patients diagnosed with sepsis or septic shock and performed 16S rRNA gene sequencing to dissect their gut microbiota compositions. During the development of sepsis or septic shock and during various medical treatments, the ICU patients always exhibited two dysbiotic microbiota patterns, or ICU-enterotypes, which could not be explained by host properties such as age, sex, and body mass index, or external stressors such as infection site and antibiotic use. ICU-enterotype I (ICU E1) comprised predominantly Bacteroides and an unclassified genus of Enterobacteriaceae, while ICU-enterotype II (ICU E2) comprised predominantly Enterococcus. Among more critically ill patients with Acute Physiology and Chronic Health Evaluation II (APACHE II) scores > 18, septic shock was more likely to occur with ICU E1 (P = 0.041). Additionally, ICU E1 was correlated with high serum lactate levels (P = 0.007). Therefore, different patterns of dysbiosis were correlated with different clinical outcomes, suggesting that ICU-enterotypes should be diagnosed as independent clinical indices. Thus, the microbial-based human index classifier we propose is precise and effective for timely monitoring of ICU-enterotypes of individual patients. This work is a first step toward precision medicine for septic patients based on their gut microbiota profiles.

Introduction: We investigated whether combining the peripheral perfusion index (PI) and central venous oxygen saturation(ScvO₂) would identify subsets of patients for assessing the tissue perfusion and predicting outcome during the resuscitation in critically ill patients. Methods: A total of 202 patients with central venous catheters for resuscitation were enrolled in this prospective observational study. The arterial, central venous blood gas and the PI were measured simultaneously at the enrollment (T0) and 8 h (T8) after early resuscitation. Based on the distribution of the PI in healthy population, a cutoff of PI ≥1.4 was defined as a normal PI. Moreover, the critical value of PI was defined as the best cutoff value related to the mortality in the study population. The PI impairment stratification is defined as follows: a normal PI(≥1.4), mild PI impairment (critical value < PI < 1.4) and critical PI impairment (PI ≤ critical value). Results: The PI at T8 was with the greatest AUC for prediction the 30-day mortality and PI is an independent risk factor for 30-day mortality. Moreover, a cutoff of PI < 0.6 is related to poor outcomes following resuscitation. So, based on cutoffs of ScvO₂ (70 %) and critical PI (0.6) at T8, we assigned the patients to four categories: group 1 (PI ≤ 0.6 on ScvO₂ < 70 %), group 2 (PI ≤ 0.6 on ScvO₂ ≥ 70 %), group 3 (PI > 0.6 on ScvO₂ < 70 %), and group 4 (PI > 0.6 on ScvO₂ ≥ 70 %). The combination of low ScvO₂(<70 %) and PI(≤0.6) was associated with the lowest survival rates at 30 days [log rank (Mantel–Cox) = 87.518, p < 0.0001]. The sub-group patients who had high ScvO₂(>80 %) at T8 were with low mortality and high PI. Moreover, the normal PI (≥1.4) did not show a better outcome than mild impaired PI (0.6-1.4) patients who had a normalized ScvO₂(>70 %) after resuscitation. The PI was correlated with the lactate, P(v-a)CO₂, and ScvO₂ in all the measurements (n = 404). These relationships are strengthened with abnormal PI (PI < 1.4) but not with normal PI (PI ≥ 1.4). Conclusion: Complementing ScvO₂ assessment with PI can better identify endpoints of resuscitation and adverse outcomes. Pursuing a normalized PI (≥1.4) may not result in better outcomes for a mild impaired PI after ScvO₂ is normalized.