Infections in the Intensive Care Unit

Editors

Yuetian Yu

Renji Hospital, School of Medicine, Shanghai Jiao Tong University

Zhongheng Zhang

Department of Emergency Medicine, Sir Run Run Shaw Hospital

George Dimopoulos

Head of 3rd University Department of Critical Care, EVGENIDIO Hospital National and Kapodistrian University of Athens

Impact

Sources of infection. Results were illustrated as circles represented the distribution in percentage (%) of the infection sites in the three subgroups (I: infection n = 1,103, outer circle; II: sepsis n = 133, middle circle; III: septic shock n = 42, inner circle).

Original Research

17 October 2022

Epidemiology, management, and outcome of infection, sepsis, and septic shock in a German emergency department (EpiSEP study)

Nicole Wolfertz

, 5 more and

Mark Michael

4,688 views

13 citations

Original Research

29 September 2022

Application of oXiris-continuous hemofiltration adsorption in patients with sepsis and septic shock: A single-centre experience in China

Yanyan Zhou

, 5 more and

Jinxiu Li

4,048 views

3 citations

Selection of risk factors of infectious diseases using LASSO regression algorithm. A vertical line was plotted at the given lambda, selected by 10-fold cross-validation with minimum classification error and minimum classification error plus one standard error. For the optimal lambda that gives minimum classification error, 8 features with a non-0 coefficient were selected. (A) LASSO coefficient profiles of the candidate variables. (B) The binomial deviance with 95% CI (y-axis) was plotted against log (lambda) (bottom x-axis), when the number of included variables were changed (upper x-axis). (C) The AUCs with 95% CI (y-axis) were plotted against log (lambda) (bottom x-axis), when the number of included variables were changed (upper x-axis). LASSO, the Least Absolute Shrinkage and Selection Operator; CI, confidence interval; AUC, areas under the curve.

Original Research

31 August 2022

A simple nomogram for predicting infectious diseases in adult kidney transplantation recipients

Ruo-Yang Chen

, 6 more and

Xiao-Dong Yuan

2,882 views

4 citations

Original Research

18 August 2022

Barriers to hand hygiene compliance in intensive care units during the COVID-19 pandemic: A qualitative study

Maryam Ahmadipour

, 4 more and

Zahra Ebrahimi Rigi

Background: The practice of hand washing is an effective way to prevent contamination and disease transmission. Following the COVID-19 pandemic, hand washing has become increasingly important. Therefore, this qualitative study aimed to understand barriers to hand hygiene compliance among healthcare workers during the COVID-19 pandemic.

Materials and methods: Twenty-five healthcare workers from intensive care units were sampled using purposive sampling in a qualitative content analysis study. Data were collected through a semi-structured interview and field notes. Based on the Lundman and Graneheim approach, the data were analyzed. COREQ checklist was used to report the research.

Results: According to the findings, there are three main categories of barriers to hand hygiene practice: barriers related to individuals (including two subcategories of lack of knowledge of healthcare workers and healthcare workers' improper attitude), barriers related to management (including two subcategories of wrong behavioral patterns and unsuitable training and planning), and barriers related to organizations (including four subcategories of heavy workloads, improperly designed wards, a lack of equipment, and lack of quality equipment).

Conclusions: This research indicates that hand washing practice increased during the COVID-19 pandemic. Nevertheless, some barriers persist, resulting in a decline in hand washing compliance among health care workers. This finding can help managers and policymakers remove barriers to hand washing compliance and improve healthcare workers' adherence to hand washing.

15,857 views

23 citations

Discrimation of pShock-CoV over prediction of 30-day mortality for patients with COVID in ICU and comparison with other severity models. (A) Perfomance of the pShock-CoV score in predicting 30-day mortality in the intensive care unit, and comparison with discrimination capacity for overall mortality. (B) Comparison pShock-CoV with CURB-65 and qSOFA for prediction of ICU 30-day mortality in COVID patients. Differences between AUC-ROCS were accessed by the DeLong test.

Brief Research Report

15 August 2022

Calibration and validation of the Pneumonia Shock Score in critically ill patients with SARS-CoV-2 infection, a multicenter prospective cohort study

Thomas A. Carmo

, 11 more and

Bruno B. Andrade

1,843 views

0 citations

Policy and Practice Reviews

10 August 2022

Expert consensus statement on therapeutic drug monitoring and individualization of linezolid

Bin Lin

, 35 more and

Haibin Dai

Linezolid is an oxazolidinone antibacterial drug, and its therapeutic drug monitoring and individualized treatment have been challenged since its approval. With the in-depth clinical research of linezolid, we have changed our attitude toward its therapeutic drug monitoring and our view of individualized treatment. On the basis of summarizing the existing clinical studies, and based on the practical experience of each expert in their respective professional fields, we have formed this expert consensus. Our team of specialists is a multidisciplinary team that includes pharmacotherapists, clinical pharmacology specialists, critical care medicine specialists, respiratory specialists, infectious disease specialists, emergency medicine specialists and more. We are committed to the safe and effective use of linezolid in patients in need, and the promotion of its therapeutic drug monitoring.

9,802 views

30 citations

Flow cytometry of T lymphocyte mitochondrial mass. (A) The analysis is started by examining the event count over time in order to exclude irregularities from the analysis. (B) Exclude the doublets from further analysis by investigating the PerCP/Cy5.5 signal for both the peak and the TOF characteristics compared to the integral attributes. (C) The remaining events are analyzed for their CD45 vs. SSC characteristics to define the lymphocyte after single-cell signal acquisition. Draw a gate around the cell population (all lymphocyte cells gate). (D–F) In the next step, the T cells (CD3+ T cells, CD3+CD4+ T cells, and CD3+CD8+ T cells) are determined due to the expression of CD3, CD4, and CD8, then set the corresponding gate, respectively. (G) Show these fluorescence characteristics of mitochondria by the half-offset histogram of the APC channel. The mitochondrial mass is detected by the MFI of APC. TOF, time of flight; APC, allophycocyanin; MFI, median fluorescence index.

Original Research

14 July 2022

The Diagnostic Value of Mitochondrial Mass of Peripheral T Lymphocytes in Early Sepsis

Ling-Xiao Pang

, 5 more and

Qian Li

2,214 views

12 citations

Phylogenomic tree was constructed based on the dapb1 gene.

Case Report

14 July 2022

Case Report: First Case of Endophthalmitis Caused by an Emerging Pathogen: Nocardia huaxiensis

Chang Liu

, 8 more and

Li Li

1,912 views

6 citations

Original Research

29 June 2022

Comparison of the Relationship Between SI and RASI Scores With the Outcome of Sepsis Patients

Amir Masoud Hashemian

, 6 more and

Mahdi Foroughian

1,305 views

2 citations

Original Research

27 June 2022

Bulk RNA Sequencing With Integrated Single-Cell RNA Sequencing Identifies BCL2A1 as a Potential Diagnostic and Prognostic Biomarker for Sepsis

Jun Li

, 8 more and

Liang-Jing Lu

4,437 views

10 citations

Time of the patients diagnosed with sepsis. (A) The occurrence time of sepsis after craniotomy. (B) The occurrence time of sepsis after intensive care unit (ICU) admission.

Original Research

17 May 2022

Incidence, Risk Factors and Outcomes of Sepsis in Critically Ill Post-craniotomy Patients: A Single-Center Prospective Cohort Study

Jianfang Zhou

, 8 more and

Linlin Zhang

2,595 views

4 citations

Original Research

13 May 2022

Salivary Alpha Amylase Bronchial Measure for Early Aspiration Pneumonia Diagnosis in Patients Treated With Therapeutic Hypothermia After Out-of-hospital Cardiac Arrest

Anis Moussali

, 9 more and

Jeremy Bourenne

1,787 views

4 citations

Case Report

10 May 2022

Case Report: Disseminated Nocardiosis Caused by Nocardia vulneris in a Patient With Macroglobulinemia

Fulan Qiu

, 4 more and

Hui Liu

1,752 views

8 citations

Forest plot depicting ICU mortality risk in septic patients with and without diabetes. Adjustment factors are the same as those in Model 3.

Original Research

29 April 2022

Association of Blood Glucose Level and Glycemic Variability With Mortality in Sepsis Patients During ICU Hospitalization

Zongqing Lu

, 10 more and

Min Yang

Background: There was considerable debate regarding the effect of mean blood glucose (MBG) and glycemic variability (GV) on the mortality of septic patients. This retrospective cohort study aimed to assess the association between MBG and GV with ICU mortality of sepsis patients and to explore the optimal MBG range.

Methods: Sepsis patients were enrolled from the Medical Information Mart for Intensive Care IV database (MIMIC-IV). MBG and glycemic coefficient of variation (Glu_CV) were, respectively, calculated to represent the overall glycemic status and GV during ICU stay. The associations between MBG, Glu_CV, and ICU mortality of the septic patients were assessed by using multivariate logistic regression in different subgroups and the severity of sepsis. Restricted cubic splines evaluated the optimal MBG target.

Results: A total of 7,104 adult sepsis patients were included. The multivariate logistic regression results showed that increased MBG and Glu_CV were significantly correlated with ICU mortality. The adjusted odds ratios were 1.14 (95% CI 1.09–1.20) and 1.05 (95% CI 1.00–1.12). However, there was no association between hyperglycemia and ICU mortality among diabetes, liver disease, immunosuppression, and hypoglycemia patients. And the impact of high Glu_CV on ICU mortality was not observed in those with diabetes, immunosuppression, liver disease, and non-septic shock. The ICU mortality risk of severe hyperglycemia (≧200 mg/dl) and high Glu_CV (>31.429%), respectively, elevated 2.30, 3.15, 3.06, and 2.37, 2.79, 3.14-folds in mild (SOFA ≦ 3), middle (SOFA 3–7), and severe group (SOFA ≧ 7). The MBG level was associated with the lowest risk of ICU mortality and hypoglycemia between 120 and 140 mg/dl in the subgroup without diabetes. For the diabetic subset, the incidence of hypoglycemia was significantly reduced when the MBG was 140–190 mg/dl, but a glycemic control target effectively reducing ICU mortality was not observed.

Conclusion: MBG and Glu_CV during the ICU stay were associated with all-cause ICU mortality in sepsis patients; however, their harms are not apparent in some particular subgroups. The impact of hyperglycemia and high GV on death increased with the severity of sepsis. The risk of ICU mortality and hypoglycemia in those with no pre-existing diabetes was lower when maintaining the MBG in the range of 120–140 mg/dl.

11,829 views

48 citations