Investigation of homocysteine, D-dimer and platelet count levels as potential predictors of thrombosis risk in COVID-19 patients.

Thrombosis plays an important role in induction of Coronavirus disease 19 (COVID-19) complications including heart attack and stroke. Reliable biomarkers are needed to predict thrombosis risk for better management and improve patient outcomes. This study aimed to investigate the relationship between homocysteine, a thrombosis-related biomarker, and other thrombosis-related parameters, such as D-dimer and platelet count with disease outcome in COVID-19 patients. This case-control study including 50 intensive care unit hospitalized patients with Covid-19 with a positive RT-PCR test for SARS-CoV-2 infection and 50 healthy individuals as a control group was conducted. Both groups were matched for age and body mass index (BMI) and had no history of underlying diseases such as cardiovascular, liver, kidney or smoking. Blood samples were collected from both groups to measure serum homocysteine, platelet count and D-dimer levels. Data were analyzed using GraphPad Prism version 8.3 software. The study found no statistically significant difference in homocysteine levels between COVID-19 patients and the control group. However, D-dimer levels were significantly higher in the patient group. Platelet count analysis revealed a significant difference between patients who died and those who were discharged from the hospital (P < 0.05). Despite previous studies suggesting a link between homocysteine and thrombosis, this study found no significant difference in homocysteine levels between COVID-19 patients and the control group. The significantly elevated D-dimer levels in the death group patient suggest that D-dimer and thrombocytopenia may be more reliable predictors of thrombosis and worse outcome in COVID-19 patients without underlying diseases.

Artificial Intelligence-Based Models for Prediction of Mortality in ICU Patients: A Scoping Review.

BACKGROUND AND OBJECTIVE: Healthcare professionals may be able to anticipate more accurately a patient's timing of death and assess their possibility of recovery by implementing a real-time clinical decision support system. Using such a tool, the healthcare system can better understand a patient's condition and make more informed judgements about distributing limited resources. This scoping review aimed to analyze various death prediction AI (Artificial Intelligence) algorithms that have been used in ICU (Intensive Care Unit) patient populations. METHODS: The search strategy of this study involved keyword combinations of outcome and patient setting such as mortality, survival, ICU, terminal care. These terms were used to perform database searches in MEDLINE, Embase, and PubMed up to July 2022. The variables, characteristics, and performance of the identified predictive models were summarized. The accuracy of the models was compared using their Area Under the Curve (AUC) values. RESULTS: Databases search yielded an initial pool of 8271 articles. A two-step screening process was then applied: first, titles and abstracts were reviewed for relevance, reducing the pool to 429 articles. Next, a full-text review was conducted, further narrowing down the selection to 400 key studies. Out of 400 studies on different tools or models for prediction of mortality in ICUs, 16 papers focused on AI-based models which were ultimately included in this study that have deployed different AI-based and machine learning models to make a prediction about negative patient outcome. The accuracy and performance of the different models varied depending on the patient populations and medical conditions. It was found that AI models compared with traditional tools like SAP3 or APACHE IV score were more accurate in death prediction, with some models achieving an AUC of up to 92.9%. The overall mortality rate ranged from 5% to more than 60% in different studies. CONCLUSION: We found that AI-based models exhibit varying performance across different patient populations. To enhance the accuracy of mortality prediction, we recommend customizing models for specific patient groups and medical contexts. By doing so, healthcare professionals may more effectively assess mortality risk and tailor treatments accordingly. Additionally, incorporating additional variables-such as genetic information-into new models can further improve their accuracy.

Remaking critical care: Place, body work and the materialities of care in the COVID intensive care unit.

In this article, we take forward sociological ways of knowing care-in-practice, in particular work in critical care. To do so, we analyse the experiences of staff working in critical care during the first wave of the COVID-19 pandemic in the UK. This moment of exception throws into sharp relief the ways in which work and place were reconfigured during conditions of pandemic surge, and shows how critical care depends at all times on the co-constitution of place, practices and relations. Our analysis draws on sociological and anthropological work on the material culture of health care and its sensory instantiations. Pursuing this through a study of the experiences of 40 staff across four intensive care units (ICUs) in 2020, we provide an empirical and theoretical elaboration of how place, body work and care are mutually co-constitutive. We argue that the ICU does not exist independently of the constant embodied work of care and place-making which iteratively constitute critical care as a total system of relations.

Critical care response during the COVID-19 pandemic.

Since the coronavirus disease 2019 (COVID-19) pandemic, millions of people worldwide have passed away due to critical illness. Intensive care for severe COVID-19 infection remains one of the most important ways to save patients' lives. In Taiwan, the government-led critical care model and COVID-19 clinical rounds, grand rounds, and chief rounds by experts; critical care guidelines established by the Taiwan Centers for Disease Control and major professional societies; consensus and management recommendations among medical institutes; and research works in the field of critical care constitute the concrete basis of intensive care. This review article briefly summarizes the current achievements of critical care for COVID-19 in Taiwan and recommendations on future directions.

Design and Implementation of an Intensive Care Unit Command Center for Medical Data Fusion.

The rapid advancements in Artificial Intelligence of Things (AIoT) are pivotal for the healthcare sector, especially as the world approaches an aging society which will be reached by 2050. This paper presents an innovative AIoT-enabled data fusion system implemented at the CMUH Respiratory Intensive Care Unit (RICU) to address the high incidence of medical errors in ICUs, which are among the top three causes of mortality in healthcare facilities. ICU patients are particularly vulnerable to medical errors due to the complexity of their conditions and the critical nature of their care. We introduce a four-layer AIoT architecture designed to manage and deliver both real-time and non-real-time medical data within the CMUH-RICU. Our system demonstrates the capability to handle 22 TB of medical data annually with an average delay of 1.72 ms and a bandwidth of 65.66 Mbps. Additionally, we ensure the uninterrupted operation of the CMUH-RICU with a three-node streaming cluster (called Kafka), provided a failed node is repaired within 9 h, assuming a one-year node lifespan. A case study is presented where the AI application of acute respiratory distress syndrome (ARDS), leveraging our AIoT data fusion approach, significantly improved the medical diagnosis rate from 52.2% to 93.3% and reduced mortality from 56.5% to 39.5%. The results underscore the potential of AIoT in enhancing patient outcomes and operational efficiency in the ICU setting.

Unveiling the performance of the prehospital Rapid Emergency Medicine Score (pREMS): How the predictive score impacts in-hospital outcomes in traumatic brain injury (TBI): A retrospective observational cohort study.

INTRODUCTION: This study aimed to evaluate the predictive accuracy of the prehospital rapid emergency medicine score (pREMS) for predicting the outcomes of hospitalized patients with traumatic brain injury (TBI) who died, were discharged, were admitted to the intensive care unit (ICU), or were admitted to the operating room (OR) within 72 h. METHODS: A retrospective cohort analysis was performed on a sample of 513 TBI patients admitted to the emergency department (ED) of Besat Hospital in 2023. Only patients of both sexes aged 18 years or older who were not pregnant and had adequate documentation of vital signs were included in the analysis. Patients who died during transport and patients who were transferred from other hospitals were excluded. The predictive power of the pREMS for each outcome was assessed by calculating the sensitivity and specificity curves and by analyzing the area under the receiver operating characteristic curve (AUROC). RESULTS: The mean pREMS scores for hospital discharge, death, ICU admission and OR admission were 11.97 ± 3.84, 6.32 ± 3.15, 8.24 ± 5.17 and 9.88 ± 2.02, respectively. pREMS accurately predicted hospital discharge and death (AOR = 1.62, P < 0.001) but was not a good predictor of ICU or OR admission (AOR = 1.085, P = 0.603). The AUROCs for the ability of the pREMS to predict outcomes in hospitalized TBI patients were 0.618 (optimal cutoff point = 7) for ICU admission and OR and 0.877 (optimal cutoff point = 9.5) for hospital discharge and death at 72 h. CONCLUSION: The results indicate that the pREMS, a new preclinical trauma score for traumatic brain injury, is a useful tool for prehospital risk stratification (RST) in TBI patients. The pREMS showed good discriminatory power for predicting in-hospital mortality within 72 h in patients with traumatic brain injury.

Proactive debriefing to promote wellbeing in intensive care nurses: A protocol.

BACKGROUND: The dynamic, rewarding, yet challenging environment of the intensive care unit is experienced in extremes by intensive care nurses. To ensure intensive care nurses can continue to fulfil their professional roles and responsibilities, careful consideration and promotion of collective and individual wellbeing is required. Regular proactive debriefing provides an opportunity to commune, connect, and reflect on the challenging nature of clinical work and is a potential intervention to aid in the promotion of wellbeing. AIM/OBJECTIVE: This study aims to collaboratively develop, implement, and evaluate a proactive debriefing intervention, which will target the promotion of nurses' wellbeing. STUDY PLAN: This hybrid effectiveness-implementation study will use a pretest/post-test design to test a codesigned proactive debriefing intervention on the wellbeing of nurses working in a large quaternary intensive care unit. This research will be conducted in two phases. Phase one will consist of focus groups and a codesign workshop. Phase two surrounds the implementation and analysis of the codesigned intervention.

An online delirium detection tool: Cross-cultural adaptation of a Chinese version of the Family Confusion Assessment Method.

BACKGROUND: Intensive care unit (ICU) delirium is a common complication in older critically ill patients that has a significant impact. The Family Confusion Assessment Method (FAM-CAM) is a vital tool for assisting family members in identifying delirium; however, no study has yet been reported on the Chinese version of the scale. OBJECTIVES: The objective of this study was to translate the FAM-CAM into a Chinese version and to verify its effectiveness for delirium detection in an online patient visit setting. METHODS: This was a cross-sectional study. The FAM-CAM was translated to Chinese according to the International Society for Pharmacoeconomics and Outcomes Research guidelines. Patients and family members were recruited to participate in delirium assessments in three ICUs of one hospital. Family members then used the Chinese version of the FAM-CAM to assess for delirium via online visitation, and ICU nurses assessed patients for delirium using the Intensive Care Delirium Screening Checklist (ICDSC). Results were then compared between family members' and nurses' assessments. RESULTS: Overall, 190 critically ill patients and 190 family members were included, of whom 117 (61.6%) were assessed for delirium using the Intensive Care Delirium Screening Checklist. The Cohen's kappa coefficient between the Intensive Care Delirium Screening Checklist and FAM-CAM was 0.759 (P < 0.01). The sensitivity of the Chinese version of the FAM-CAM was 0.880, specificity was 0.890, positive predictive value was 0.928, negative predictive value was 0.823, and area under the receiver operating characteristic curve was 0.881 (95% confidence interval: 0.872-0.935, P < 0.01). CONCLUSION: The Chinese version of the FAM-CAM was shown to effectively help families detect delirium and was suggested as a crucial tool for assisting ICU nurses in the early identification of delirium. This tool may effectively be used to assess delirium during online visits.

Characteristics of and Outcomes After Dialysis-Treated Acute Kidney Injury, 2009-2018: A Taiwanese Multicenter Study.

RATIONALE & OBJECTIVE: Dialysis-treated acute kidney injury (AKI) is increasingly common in intensive care units (ICUs) and is associated with poor outcomes. Few studies have explored the temporal trends in severity of acute illness at dialysis initiation, indications for dialysis, and their association with patient outcomes. STUDY DESIGN: Multicenter retrospective cohort study. SETTING & PARTICIPANTS: 9,535 adult patients admitted to the ICU who received their first dialysis treatment from Chang Gung Memorial Hospital system in Taiwan from 2009 through 2018. EXPOSURE: Calendar year. OUTCOMES: ICU mortality and dialysis treatment at discharge among hospital survivors. ANALYTICAL APPROACH: The temporal trends during the study period were investigated using test statistics suited for continuous or categorical data. The association between the study year and the risk of mortality was analyzed using multivariable Cox regression with adjustment for relevant clinical variables, including the severity of acute illness, defined by Sequential Organ Failure Assessment (SOFA) score. RESULTS: The mean SOFA score at dialysis initiation decreased slightly from 14.0 in 2009 to 13.6 in 2018. There was no significant trend in the number of indications for dialysis initiation that were fulfilled over time. Observed ICU mortality decreased over time, and the curve appeared to be reverse J-shaped, with a substantial decrease from 56.1% in 2009 to 46.3% in 2015 and a slight increase afterward. The risk of mortality was significantly reduced from 2013 to 2018 compared with 2009 in adjusted models. The decreasing trend in ICU mortality over time remained significant. There was an increase in dialysis treatment at discharge among survivors, mainly in patients with estimated glomerular filtration rate<60mL/min/1.73m2, from 36.8% in 2009 to 43.9% in 2018. LIMITATIONS: Residual confounding from unmeasured factors over time such as severity of comorbidities, detailed medication interventions, and delivered dialysis dose. CONCLUSIONS: We observed reductions in mortality among ICU patients with dialysis-treated acute kidney injury between 2009 and 2018, even after adjusting for dialysis indication and severity of illness at dialysis initiation. However, dialysis treatment at discharge among survivors has increased over time, mainly in patients with preexisting kidney disease. PLAIN-LANGUAGE SUMMARY: The current medical management of severe acute kidney injury (AKI) is primarily limited to supportive care and kidney replacement therapy if indicated, leading to perceptions that outcomes among intensive care unit (ICU) patients with dialysis-treated AKI have not improved. In this multicenter retrospective study of ICU patients with dialysis-treated AKI between 2009 and 2018 in Taiwan, patient mortality decreased over time despite increasing comorbidities. Moreover, the decreasing linear trends remained significant even when considering severity of acute illness at dialysis initiation, which was based on physiologic and laboratory measurements seldom evaluated in previous studies. Further research should explore the basis for these improvements.

Prediction of Mortality and Major Adverse Kidney Events in Critically Ill Patients With Acute Kidney Injury.

RATIONALE & OBJECTIVE: Risk prediction tools for assisting acute kidney injury (AKI) management have focused on AKI onset but have infrequently addressed kidney recovery. We developed clinical models for risk stratification of mortality and major adverse kidney events (MAKE) in critically ill patients with incident AKI. STUDY DESIGN: Multicenter cohort study. SETTING & PARTICIPANTS: 9,587 adult patients admitted to heterogeneous intensive care units (ICUs; March 2009 to February 2017) who experienced AKI within the first 3 days of their ICU stays. PREDICTORS: Multimodal clinical data consisting of 71 features collected in the first 3 days of ICU stay. OUTCOMES: (1) Hospital mortality and (2) MAKE, defined as the composite of death during hospitalization or within 120 days of discharge, receipt of kidney replacement therapy in the last 48 hours of hospital stay, initiation of maintenance kidney replacement therapy within 120 days, or a ≥50% decrease in estimated glomerular filtration rate from baseline to 120 days from hospital discharge. ANALYTICAL APPROACH: Four machine-learning algorithms (logistic regression, random forest, support vector machine, and extreme gradient boosting) and the SHAP (Shapley Additive Explanations) framework were used for feature selection and interpretation. Model performance was evaluated by 10-fold cross-validation and external validation. RESULTS: One developed model including 15 features outperformed the SOFA (Sequential Organ Failure Assessment) score for the prediction of hospital mortality, with areas under the curve of 0.79 (95% CI, 0.79-0.80) and 0.71 (95% CI, 0.71-0.71) in the development cohort and 0.74 (95% CI, 0.73-0.74) and 0.71 (95% CI, 0.71-0.71) in the validation cohort (P < 0.001 for both). A second developed model including 14 features outperformed KDIGO (Kidney Disease: Improving Global Outcomes) AKI severity staging for the prediction of MAKE: 0.78 (95% CI, 0.78-0.78) versus 0.66 (95% CI, 0.66-0.66) in the development cohort and 0.73 (95% CI, 0.72-0.74) versus 0.67 (95% CI, 0.67-0.67) in the validation cohort (P < 0.001 for both). LIMITATIONS: The models are applicable only to critically ill adult patients with incident AKI within the first 3 days of an ICU stay. CONCLUSIONS: The reported clinical models exhibited better performance for mortality and kidney recovery prediction than standard scoring tools commonly used in critically ill patients with AKI in the ICU. Additional validation is needed to support the utility and implementation of these models. PLAIN-LANGUAGE SUMMARY: Acute kidney injury (AKI) occurs commonly in critically ill patients admitted to the intensive care unit (ICU) and is associated with high morbidity and mortality rates. Prediction of mortality and recovery after an episode of AKI may assist bedside decision making. In this report, we describe the development and validation of a clinical model using data from the first 3 days of an ICU stay to predict hospital mortality and major adverse kidney events occurring as long as 120 days after hospital discharge among critically ill adult patients who experienced AKI within the first 3 days of an ICU stay. The proposed clinical models exhibited good performance for outcome prediction and, if further validated, could enable risk stratification for timely interventions that promote kidney recovery.

Intensive Care Unit-Acquired Weakness in Patients With Acute Kidney Injury: A Contemporary Review.

Acute kidney injury (AKI) and intensive care unit-acquired weakness (ICU-AW) are 2 frequent complications of critical illness that, until recently, have been considered unrelated processes. The adverse impact of AKI on ICU mortality is clear, but its relationship with muscle weakness-a major source of ICU morbidity-has not been fully elucidated. Furthermore, improving ICU survival rates have refocused the field of intensive care toward improving long-term functional outcomes of ICU survivors. We begin our review with the epidemiology of AKI in the ICU and of ICU-AW, highlighting emerging data suggesting that AKI and AKI treated with kidney replacement therapy (AKI-KRT) may independently contribute to the development of ICU-AW. We then delve into human and animal data exploring the pathophysiologic mechanisms linking AKI and acute KRT to muscle wasting, including altered amino acid and protein metabolism, inflammatory signaling, and deleterious removal of micronutrients by KRT. We next discuss the currently available interventions that may mitigate the risk of ICU-AW in patients with AKI and AKI-KRT. We conclude that additional studies are needed to better characterize the epidemiologic and pathophysiologic relationship between AKI, AKI-KRT, and ICU-AW and to prospectively test interventions to improve the long-term functional status and quality of life of AKI survivors.

Unintended impact of COVID-19 pandemic on the rate of catheter related nosocomial infections and incidence of multiple drug resistance pathogens in three intensive care units not allocated to COVID-19 patients in a large teaching hospital.

BACKGROUND: The prevalence of resistant hospital infections in the intensive care unit (ICU) increases mortality and antibiotic resistance. COVID-19 pandemic may have unintended impact on nosocomial infections (NI) and the prevalence of resistant microorganism. METHODOLOGY: The present non-interventional study was performed by a pre and a post survey each lasting 8 months before (March-October 2019) and after (March-October 2020) the onset of COVID-19 pandemic in three ICU's, not allocated to COVID-19 patients, in Nemazee Hospital, Shiraz, Iran. The rates of the following nosocomial infections were compared at pre- and post-pandemic period: ventilator associated pneumonia (VAP), central line associated blood stream infection (CLABSI), catheter-associated urinary tract infections (CAUTI) and incidence of multiple drug resistance (MDR) pathogens. RESULTS: Pre-pandemic and pandemic incidence of VAP was 23.5 and 17.2 cases per 1000 device-days, respectively; an absolute decrease of 27%. The main reason for the decrease in the rate of VAP during the pandemic was a significant decrease in the rate of VAP caused by Acinetobacter baumannii; from 39 to 17% in total VAP episodes. The rate of VAP associated with other microorganisms remained relatively unchanged from 14.2 cases in pre-pandemic period to 14.3 cases per 1000 MV-days during the pandemic (P = 0.801). Pre-pandemic incidence of CLABSI was 7.3 cases and, in pandemic period, was 6.5 cases per 1000 device-days (IRR = 0.88, 95% CI 0.43-1.73, P = 0.703). Pre-pandemic incidence of CAUTI was 2 and in pandemic period, was 1.4 cases per 1000 device-days (IRR = 0.70, 95% CI 0.22-1.98, P = 0.469). CONCLUSION: The results of the present study showed a decrease in the incidence of VAP in critically ill non-COVID-19 patients during the pandemic compared to before the pandemic, especially regarding Acinetobacter baumannii.

Outcomes in critically Ill HIV-infected patients between 1997 and 2020: analysis of the OUTCOMEREA multicenter cohort.

PURPOSE: Despite antiviral therapy (ART), 800,000 deaths still occur yearly and globally due to HIV infection. In parallel with the good virological control and the aging of this population, multiple comorbidities [HIV-associated-non-AIDS (HANA) conditions] may now be observed. METHODS: HIV adult patients hospitalized in intensive care unit (ICU) from all the French region from university and non-university hospital who participate to the OutcomeRea™ database on a voluntary basis over a 24-year period. RESULTS: Of the 24,298 stays registered, 630 (2.6%) were a first ICU stay for HIV patients. Over time, the mean age and number of comorbidities (diabetes, renal and respiratory history, solid neoplasia) of patients increased. The proportion of HIV diagnosed on ICU admission decreased significantly, while the median duration of HIV disease as well as the percentage of ART-treated patients increased. The distribution of main reasons for admission remained stable over time (acute respiratory distress > shock > coma). We observed a significant drop in the rate of active opportunistic infection on admission, while the rate of active hemopathy (newly diagnosed or relapsed within the last 6 months prior to admission to ICU) qualifying for AIDS increased-nonsignificantly-with a significant increase in the anticancer chemotherapy administration in ICU. Admissions for HANA or non-HIV reasons were stable over time. In multivariate analysis, predictors of 60-day mortality were advanced age, chronic liver disease, past chemotherapy, sepsis-related organ failure assessment score > 4 at admission, hospitalization duration before ICU admission > 24 h, AIDS status, but not the period of admission. CONCLUSION: Whereas the profile of ICU-admitted HIV patients has evolved over time (HIV better controlled but more associated comorbidities), mortality risk factors remain stable, including AIDS status.

Easing Suffering for ICU Patients and Their Families: Evidence and Opportunities for Primary and Specialty Palliative Care in the ICU.

Intensive care unit (ICU) admissions are often accompanied by many physical and existential pressure points that can be extraordinarily wearing on patients and their families and surrogate decision makers (SDMs). Multidisciplinary palliative support, including physicians, advanced practice nurses, nutritionists, chaplains and other team members, may alleviate many of these sources of potential suffering. However, the palliative needs of ICU patients undoubtedly exceed the bandwidth of current consultative specialty palliative medicine teams. Informed by standard-of-care palliative medicine domains, we review common ICU symptoms (pain, dyspnea and thirst) and their prevalence, sources and their treatment. We then identify palliative needs and impacts in the domains of communication, SDM support and transitions of care for patients and their families through their journey in the ICU, from discharge and recovery at home to chronic critical illness, post-ICU disability or death. Finally, we examine the evidence for strategies to incorporate specialty palliative medicine and palliative principles into ICU care for the improvement of patient- and family-centered care. While randomized controlled studies have failed to demonstrate measurable improvement in pre-determined outcomes for patient- and family-relevant outcomes, embracing the principles of palliative medicine and assuring their delivery in the ICU is likely to translate to overall improvement in humanistic, person-centered care that supports patients and their SDMs during and following critical illness.

Secondary bacterial infections & extensively drug-resistant bacteria among COVID-19 hospitalized patients at the University Hospital in Kraków.

INTRODUCTION: Healthcare-associated infections (HAI) and bacterial antimicrobial resistance posed a therapeutic risk during the coronavirus disease 2019 (COVID-19) pandemic. The aim of this study was to analyze the HAIs in COVID-19 patients in the Intensive Care Unit (ICU) and non-ICU at the University Hospital in Krakow (UHK) with an emphasis on the susceptibility of the most frequently isolated pathogens and the prevalence of extensively drug resistant (XDR) microorganisms. METHODS: This laboratory-based study was carried out at the University Hospital in Krakow in the ICU and non-ICUs dedicated to COVID-19 patients between May 2021 and January 2022. All isolates of Klebsiella pneumoniae were analyzed using PFGE protocol. RESULTS: 292 independent HAI cases were identified, with the predominance of urinary tract infections (UTI), especially in the non-ICU setting. The most common ICU syndrome was pneumonia (PNA). The prevalence of XDR organisms was 22.6% in the ICU and 14.8% in non-ICUs among all isolates. The incidence of carbapenem-resistant Enterobacteriaceae infection was 24.8 cases per 10,000 hospitalizations and the carbapenem-resistant A. baumannii infection incidence was 208.8 cases per 10,000 hospitalizations. The prevalence of XDR strains was highest in Acinetobacter spp, in PNA cases. The PFGE typing demonstrated that almost all XDR strains varied widely from each other. CONCLUSIONS: In this study, there was a high incidence of HAI in COVID-19 patients, especially when compared to Western Europe and the United States. Similarly, the prevalence of XDR microorganisms, especially XDR-A.baumannii, was also high. PFGE did not confirm the horizontal spread of any organism strains.

Short-term exposure to ambient fine particulate pollution aggravates ventilator-associated pneumonia in pediatric intensive care patients undergoing cardiovascular surgeries.

BACKGROUND: Ambient air pollutants can be hazardous to human health, especially for vulnerable children. The impact of ambient air pollutant exposure before and during intensive care unit (ICU) stays on the development of ventilator-associated pneumonia (VAP) in critically ill children has not been established. We aimed to determine the correlations between short-term exposures to ambient fine particulate matter (PM2.5) and VAP in pediatric cardiac surgery patients in the ICU, and explore the effect of delayed exposure. METHODS: The medical record of 1755 child patients requiring artificial ventilation in the ICU between December 2013 to December 2020, were analyzed. The daily average concentrations of particulate matters (PM2.5 and PM10), sulfur dioxide (SO2), and ozone (O3) were calculated from public data. Interactions between these pollutants and VAP were simulated with the distributed lag non-linear model. RESULTS: Three hundred forty-eight cases (19.829%) of VAP were identified in this study, while the average concentrations of PM2.5, PM10, O3 and SO2 were 58, 118, 98 and 26 µg/m3, respectively. Exposure to increased levels of PM2.5 two days prior (lag 2-day) to VAP diagnosis is significantly correlated with an enhanced risk for VAP development. Even a slight increase of 10 µg/m3 in PM2.5 can translate to a 5.4% increase in VAP incidence (95% CI: 1.4%-9.5%) while the VAP incidence increased to 11.1% (95%CI: 4.5-19.5%) when PM2.5 concentration is well below the National Ambient Air Quality standard (NAAQS) of 50 µg/m3. The association was more pronounced in those aged below 3-months, with low body mass index or suffered from pulmonary arterial hypertension. CONCLUSION: Short-term PM2.5 exposure is a significant risk for development of VAP in pediatric patients. This risk is present even with PM2.5 levels below the NAAQS. Ambient PM2.5 may represent a previously unrecognized risk factor for pneumonia and the current environmental pollution standards need to be reevaluated to consider susceptible populations. TRIAL REGISTRATION: The trial was registered with the National Clinical Trial Center: The correlation between ambient air pollution and the complications in ICU underwent cardiac surgery. TRIAL REGISTRATION NUMBER: ChiCTR2000030507. Date of registration: March 5, 2020. URL of trial registry record: http://www.chictr.org.cn/index.aspx .

Mid-Regional Pro-Adrenomedullin Can Predict Organ Failure and Prognosis in Sepsis?

Sepsis causes immune dysregulation and endotheliitis, with an increase in mid-regional pro-adrenomedullin (MR-proADM). The aim of the study is to determine an MR-proADM value that, in addition to clinical diagnosis, can identify patients with localized infection or those with sepsis/septic shock, with specific organ damage or with the need for intensive care unit (ICU) transfer and prognosis. The secondary aim is to correlate the MR-proADM value with the length of stay (LOS). In total, 301 subjects with sepsis (124/301 with septic shock) and 126 with localized infection were retrospectively included. In sepsis, MR-proADM ≥ 3.39 ng/mL identified acute kidney injury (AKI); ≥2.99 ng/mL acute respiratory distress syndrome (ARDS); ≥2.28 ng/mL acute heart failure (AHF); ≥2.55 ng/mL Glascow Coma Scale (GCS) < 15; ≥3.38 multi-organ involvement; ≥3.33 need for ICU transfer; ≥2.0 Sequential Organ Failure Assessment (SOFA) score ≥ 2; and ≥3.15 ng/mL non-survivors. The multivariate analysis showed that MR-proADM ≥ 2 ng/mL correlates with AKI, anemia and SOFA score ≥ 2, and MR-proADM ≥ 3 ng/mL correlates with AKI, GCS < 15 and SOFA score ≥ 2. A correlation between mortality and AKI, GCS < 15, ICU transfer and cathecolamine administration was found. In localized infection, MR-proADM at admission ≥ 1.44 ng/mL identified patients with AKI; ≥1.0 ng/mL with AHF; and ≥1.44 ng/mL with anemia and SOFA score ≥ 2. In the multivariate analysis, MR-proADM ≥ 1.44 ng/mL correlated with AKI, anemia, SOFA score ≥ 2 and AHF. MR-proADM is a marker of oxidative stress due to an infection, reflecting severity proportionally to organ damage.

Identifying the unique behaviors embedded in the process of interprofessional collaboration in the ICU.

Interprofessional collaboration (IPC) is an important aspect of high-quality care in intensive care units (ICUs). The practice of IPC, however, is complex and the components that constitute IPC are not well defined. We sought to identify distinct behaviors embedded in clinician workflow that indicate engagement in the IPC process. We conducted a clinical ethnography in two ICUs in southeastern Michigan. From March 2017 to March 2019, we collected 31 hours of observations and completed 12 separate clinician shadowings and 12 interviews with ICU nurses, physicians, and respiratory therapists. We applied an iterative analytical approach to identify two types of IPC behaviors which we a priori labeled as "enablers" (i.e. the ways clinicians transition into or facilitate collaboration) and "collaborative activities" (i.e. behaviors clinicians use to directly collaborate with other professionals). 18 IPC behaviors were identified - ten "enablers" and eight "collaborative activities." Specifically, the enablers include: active listening, approach, coordinating work, intraprofessional consultation, invitation, nonverbal accessibility, reflexive questioning, sending pages/call, validation, and verbal accessibility. The collaborative activities are: correction, fill in the gap, information exchange, negotiation, providing help, socializing, teaching/training, and troubleshooting. By identifying IPC behaviors embedded in clinician workflow, our results may support more focused assessments of IPC in practice and guide clinicians toward behaviors they can use to engage in the IPC process.

The relationship between alarm fatigue and burnout among critical care nurses: A cross-sectional study.

BACKGROUND: Alarm fatigue has significant negative impacts on nurses and patient safety. However, the relationship between alarm fatigue and burnout is still unclear. AIMS: This study aimed to explore the relationship between alarm fatigue and burnout among critical care nurses. STUDY DESIGN: A descriptive-analytical cross-sectional study design was used. Data were collected from five hospitals in mainland China between January 2022 and March 2022. A general information questionnaire, the Chinese version of the Intensive Care Unit Nurse Alarm Fatigue Questionnaire, and the Chinese version of the Maslach Burnout Inventory were used. RESULTS: A total of 236 critical care nurses were enrolled in this study. The mean score of alarm fatigue among critical care nurses was 21.11 ± 6.83. The results showed that critical care nurses experienced moderate alarm fatigue levels, and most nurses had moderate to high levels of burnout. The multiple linear regression analyses showed that alarm fatigue was independently associated with emotional exhaustion, depersonalization dimensions, and reduced personal accomplishment dimension. CONCLUSIONS: Alarm fatigue was associated with burnout among critical care nurses. Reducing critical care nurses' alarm fatigue may help to alleviate burnout. RELEVANCE TO CLINICAL PRACTICE: Managers should provide comprehensive training for nurses and promote the application of artificial intelligence technology in alarm management to reduce alarm fatigue and improve burnout among critical care nurses.

Emotional intelligence and coping strategies among intensive care unit nurses.

BACKGROUND: Stress is an integral part of daily work for nurses, especially those who work in intensive care units (ICUs). However, chronic stress can affect nurses' mental and physical well-being, increasing their risk of burnout and decreasing the quality of care. A higher emotional intelligence (EI) level may be correlated with greater use of effective coping strategies, leading to a reduction of the adverse effects of stress. AIM: This study aimed to examine the relationship between EI and coping strategies among adult ICU nurses in Poland. STUDY DESIGN: A cross-sectional survey design was used. Current adult ICU nurses in nine Polish hospitals were invited to participate. The survey instruments used were: the Polish version of the Schutte Self-Report Emotional Intelligence Test, the Inventory to Measure Coping Strategies with Stress (Brief-COPE), and a self-constructed questionnaire. RESULTS: 114/543 (21%) nurses completed the survey. ICU nurses showed an average level of EI (70.2%). The main stress coping strategies were active coping and planning, the rarest being substance use, behavioural disengagement, and denial. For nurses with a higher EI level, the most frequently used strategies included positive reframing (R = 0.43; p < .001), active coping (R = 0.38; p < .001), planning (R = 0.37; p < .001) and religion (R = 0.25; p = .006). Nurses were less likely to utilize strategies of behavioural disengagement (R = -0.32; p = .001) and self-blame (R = -0.40; p < .001). CONCLUSIONS: EI may have an impact on coping strategies, as a higher EI level was correlated with the greater use of effective coping strategies in ICU nurses. RELEVANCE TO CLINICAL PRACTICE: Training in coping with stress and increasing EI may have a positive impact on reducing the risk of burnout in nurses and thus improving the quality of care delivered.