Intensive Care Unit Environment Research Articles

Longitudinal genomics reveals carbapenem-resistant Acinetobacter baumannii population changes with emergence of highly resistant ST164 clone

Carbapenem-resistant Acinetobacter baumannii (CRAB) is a persistent nosocomial pathogen that poses a significant threat to global public health, particularly in intensive care units (ICUs). Here we report a three-month longitudinal genomic surveillance study conducted in a Hangzhou ICU in 2021. This followed a three-month study conducted in the same ICU in 2019, and infection prevention and control (IPC) interventions targeting patients, staff and the ICU environment. Most A. baumannii isolated in this ICU in 2021 were CRAB (80.9%; 419/518) with higher-level resistance to carbapenems. This was accompanied by the proportion of global clone 2 (GC2) isolates falling from 99.5% in 2019 to 50.8% (213/419) in 2021. The phylogenetic diversity of GC2 increased, apparently driven by regular introductions of distinct clusters in association with patients. The remaining CRAB (40.2%; 206/419) were a highly clonal population of ST164. Isolates of ST164 carried blaNDM-1 and blaOXA-23 carbapenemase genes, and exhibited higher carbapenem MIC50/MIC90 values than GC2. Comparative analysis of publicly available genomes from 26 countries (five continents) revealed that ST164 has evolved towards carbapenem resistance on multiple independent occasions. Its success in this ICU and global capacity for acquiring resistance determinants indicate that ST164 CRAB is an emerging high-risk lineage of global concern.

Cardiorespiratory and circadian clock markers in intensive care unit patients.

Biological synchronized rhythmicity is a critical physiological process. The lack of synchronized rhythms, mainly those showing a circadian basis, like sleep, the heart rate (HR) and arterial blood pressure (BP), often leads to several organic challenges, usually associated with adverse outcomes. The aim of the study was to investigate whether the intensive care unit (ICU) environment favors clock genes and cardiorespiratory changes. A total of 22 critically ill patients (16 males; 72.73%) with a mean age of 60.82 ±20.07 years and well-established cardiovascular conditions were selected from ICU. Blood samples were obtained, and total RNA was isolated and reverse-transcribed into complementary DNA (cDNA). A quantitative polymerase chain reaction (qPCR) was performed to assess the target gene expression levels. The urinary concentration levels of melatonin (MEL) were assessed. The heart rate, BP (systolic - SBP, diastolic - DBP and mean - MBP) and the oxygen saturation (SpO2) levels were assessed as continuous variables. The urinary MEL and Brain and muscle Arnt-like protein-1 (BMAL1) levels were shown to have a non-linear relationship with HR (coefficient (coef): 2.318, p = 0.032; coef: 2.722, p = 0.006, respectively) and SBP (coef: 1.000, p = 0.008; coef: 2.000, p = 0.037, respectively), with an explanatory power of up to 50.3% and 39.7% of the HR and SBP variability, respectively. Melatonin, but not BMAL1, was also shown to have a non-linear relationship with MBP (coef: 1.000, p = 0.007), with an explanatory power of up to 31.3% regarding the MBP variability. The HR and SBP oscillatory dynamics was shown to be related to changes in the genetic expression of BMAL1 and the urinary MEL concentrations. To a lower degree, MEL also impacted the variation of MBP. Our results suggest that not only are circadian functional matrices crucial for the dynamics of vital parameters in critically ill patients, but also that routinely assessed cardiovascular parameters like HR and BP may constitute important markers for the circadian timing system function. These parameters are easy to assess and have a relevant prognostic value regarding recovery outcomes, as well as the morbidity and mortality rates in ICU.

The relationship between teamwork and moral distress among NICU nurses

BackgroundIn the demanding environment of the neonatal intensive care unit (NICU), quality nursing care hinges on effective teamwork and communication among nurses. However, this requirement for close cooperation can expose nurses to significant levels of moral distress. This study aims to explore the connection between the quality of teamwork and the experience of moral distress among NICU nurses.MethodsEmploying a cross-sectional, multicenter descriptive correlational design, this study surveyed female NICU nurses across the cities of Khorramabad and Semnan. Census sampling was utilized over five months, from July to November 2023, resulting in the participation of 190 nurses. Tools for data collection included demographic questionnaires, the Team-STEPPS Teamwork Perception Questionnaire (T-TPQ), and the Moral Distress Scale-Revised (MDS-R) for nurses.ResultsThe findings revealed an average teamwork score of 3.73 ± 0.78, denoting an acceptable level, and an average moral distress score of 91.2 ± 56.7, indicating a low level. In multiple linear regression, marital status showed a direct positive correlation (β = 38.5, SE (β) = 9.3, p < 0.001), while the number of children (β = -14.6, SE (β) = 4.9, p = 0.003) and the teamwork score (β = -1.1, SE (β) = 0.12, p < 0.001) were inversely correlated with moral distress.ConclusionThe study’s results suggest that stronger teamwork among nurses correlates with reduced moral distress. Enhancing teamwork within NICUs could lead to policy development focused on the safety and quality of newborn care, also potentially alleviating moral distress experienced by nurses.

Neonatal multimorbidity and the phenotype of premature aging in preterm infants.

Multimorbidity is the co-occurrence of multiple chronic health problems, associated with aging, frailty, and poor functioning. Children born preterm experience more multimorbid conditions in early life compared to term-born peers. Though neonatal multimorbidity is linked to poor health-related quality of life, functional outcomes, and peer group participation, gaps in our theoretical understanding and conceptualization remain. Drawing from life course epidemiology and the Developmental Origins of Heath and Disease models, we offer a framework that neonatal multimorbidity reflects maturational vulnerability posed by preterm birth. The impact of such vulnerability on health and development may be further amplified by adverse exposures and interventions within the environment of the neonatal intensive care unit. This can be exacerbated by disadvantaged home or community contexts after discharge. Uncovering the physiologic and social antecedents of multiple morbid conditions in the neonatal period and their biological underpinnings will allow for more accurate risk-prediction, counseling, and care planning for preterm infants and their families. According to this framework, the maturational vulnerability to multimorbidity imparted by preterm birth and its negative effects on health and development are not predetermined or static. Elucidating pathways of early biologic and physical aging will lead to improvements in care and outcomes. IMPACT: Multimorbidity is associated with significant frailty and dysfunction among older adults and is indicative of early physiologic aging. Preterm infants commonly experience multimorbidities in the newborn period, an underrecognized threat to long-term health and development. We offer a novel framework incorporating multimorbidity, early cellular aging, and life course health development to innovate risk-prediction, care-planning, and therapeutics.

End-stage heart failure patients in ICU: the importance of advance planning and effective communication.

During the disease trajectory, patients with advanced heart failure are often hospitalised with a high probability of admission to the intensive care setting. Using a case study, this article explores the care given to a patient with decompensated heart failure in an intensive care unit (ICU). It will discuss the significance of holistic assessment and effective symptom management, in particular the research related to breathlessness management. The importance of effective communication within the ICU multidisciplinary team, including with the patient/family will be explored, as the ICU environment can often lead to communication breakdown, patients being unable to voice their wishes and over-medicalisation. The effectiveness of early involvement of the palliative care team in ICU will be examined, including the use of tools such advance care planning and a treatment escalation plan and whether use of these can enable a better patient and family experience at the end of life. The role of palliative care champions will be discussed.

Clinician and Visitor Activity Patterns in an Intensive Care Unit Room: A Study to Examine How Ambient Monitoring Can Inform the Measurement of Delirium Severity and Escalation of Care.

The early detection of the acute deterioration of escalating illness severity is crucial for effective patient management and can significantly impact patient outcomes. Ambient sensing technology, such as computer vision, may provide real-time information that could impact early recognition and response. This study aimed to develop a computer vision model to quantify the number and type (clinician vs. visitor) of people in an intensive care unit (ICU) room, study the trajectory of their movement, and preliminarily explore its relationship with delirium as a marker of illness severity. To quantify the number of people present, we implemented a counting-by-detection supervised strategy using images from ICU rooms. This was accomplished through developing three methods: single-frame, multi-frame, and tracking-to-count. We then explored how the type of person and distribution in the room corresponded to the presence of delirium. Our designed pipeline was tested with a different set of detection models. We report model performance statistics and preliminary insights into the relationship between the number and type of persons in the ICU room and delirium. We evaluated our method and compared it with other approaches, including density estimation, counting by detection, regression methods, and their adaptability to ICU environments.

RECURRENT RESUSCITATION PROCEDURES IN PEDIATRIC PATIENTS

The present study refers to a real case report, in which a bioethical analysis is developed, from the perspective of principlism, in the environment of a pediatric intensive care unit, with the objective of discussing the dysthanasia practiced in the medical setting and the decision-making of those involved in this case. A search was performed in the Scientific Electronic Library Online (SciELO) and PubMed databases for literature review. Dysthanasia consists of a treatment that only prolongs the pain, making any investment in healing an aggression against the dignity of the human person. When the patient is a child close to death, the difficulty for professionals becomes even greater. Therefore, it is necessary to pay greater attention to the curriculum, raising discussions and reflections on the subject, in order to train professionals to deal with finitude and play their role of offering support and comfort, as well as helping families to identify what quality of life means to them and how it is possible to achieve it.

The effect of environmental stressors perceived by surgical intensive care unit patients on hopelessness level

The aim of the research was to determine the effects of environmental stressors perceived by patients hospitalized in the surgical intensive care unit on hopelessness level. This descriptive research was performed between September 2023 and February 2024. The population of the study included all adult patients hospitalized in the Surgical Intensive Care Clinic of a City Hospital in Eastern Türkiye. The sample of the study includes 230 patients selected by random sampling method from this population. We used Personal Information Form, Intensive Care Unit Environmental Stressors Scale (ICUESS) and Beck Hopelessness Scale (BHS) to collect the data. Descriptive statistics, t-test, ANOVA, and correlation analysis tests were used to evaluate the data. The ICUESS mean score of the patients participated in the study was found to be at a high level with 102.13±15.95. Beck hopelessness scale score mean was found to be at a mild level with 6.36±5.78. It was found that the patients' gender, age, educational status, chronic disease status and previous intensive care experience affected the level of hopelessness. The relationship between ICUESS and BHS scores of the patients included in the study was examined and it was found that there was a low level of positive significant relationship between them (r: 0.162, p: 0.014). The hopelessness level of patients in surgical intensive care units was found to increase as the level of exposure to environmental stressors increased. It may be recommended to identify environmental stressors affecting the hopelessness level of patients and to implement interventions to reduce them.

The Effect of Implementation of Skin Care Guidelines on Nurses’ Knowledge Regarding Skin Care and Incidence of Skin Injuries Among Neonates at a Private Tertiary Care Hospital

Background: Skin care of sick newborns is important because skin acts as a barrier to prevent neonates from infections which may lead to neonatal morbidity and mortality. The highly technological environment of the neonatal intensive care unit (NICU) makes them vulnerable to loss of skin integrity. In acute care setting maintenance of skin integrity is considered as an established quality indicator representing nursing care. Aim of Study: The study aimed to determine the effect of skin care guidelines on nurses’ knowledge related to skincare and the incidence of skin injuries among neonates. Methodology: Pre-post quasi-experimental study was conducted in the NICU of a private tertiary care hospital. A consecutive sampling technique was used. The intervention comprised educational sessions and demonstrations of skin care practices from AWHONN skin care guidelines. The data on the nurses’ knowledge were collected through self-developed and self-administered questionnaires. Skin injuries were recorded on a checklist through observation for 1 month before and after the intervention. A paired sample t-test was used for comparing knowledge and continuous demographical variables. While the incidence density ratio was calculated for skin injuries. Results: There was a statistically significant improvement in the nurses’ knowledge of skin care from pre (mean 15.06 ± 5.16) to post (mean19.40 ± 5.17) measurement P-value .001. Incidence density rate of skin injuries reduced from 19% to 3% after the implementation of skin care guidelines. Conclusion: Through the implementation guidelines nurses’ knowledge and practices regarding skin care improved while skin injuries among neonates were reduced.

Using Machine Learning and Electronic Health Records to Identify Neuropsychiatric Risk Scores for Delirium in ICU and General Hospital Settings.

Delirium is a common and acute neuropsychiatric syndrome that requires timely intervention to prevent its associated morbidity and mortality. Yet, its diagnosis and symptoms are often overlooked due to its variable clinical presentation and fluctuating nature. Thus, in this study, we address the barriers to delirium diagnosis by utilizing a machine learning-based predictive algorithm for incident delirium that relies on archived electronic health records (EHRs) data. We used the Medical Information Mart for Intensive Care (MIMIC) database to create a detailed dataset for identifying delirium in intensive care unit (ICU) patients. Our approach involved training machine learning models on this dataset to pinpoint critical clinical features for delirium detection. These features were then refined and applied to non-ICU patients using EHRs from the American University of Beirut Medical Center (AUBMC). Our study assessed machine learning models like Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Classification and Regression Trees (CART), Random Forest (RF), Neural Oblivious Decision Ensembles (NODE), and Logistic Regression (LR), highlighting superior delirium detection in diverse clinical settings. The CatBoost model excelled in ICU environments with an F1 Score of 89.2%, while XGBoost performed best in general hospital settings with a 75.4% F1 Score. Interpretations using Tabular Local Interpretable Model-agnostic Explanations (LIME) revealed critical indicators such as prothrombin time and hematocrit levels, enhancing model transparency and clinical applicability. These clinical insights help differentiate the delirium predictors between ICU patients, who are often sensitive to various factors. The proposed predictive algorithm improves delirium detection rates and streamlines efficiency in hospital electronic systems, thereby enabling prompt interventions to prevent delirium progression and associated complications. The clinical indicators for delirium that we identified in general hospital settings and ICU can greatly help healthcare professionals identify potential causes of delirium and reduce misdiagnosis.

Challenges of preterm families: parenthood and participation in the Neonatal Intensive Care Unit in Northern Italy

ABSTRACT Prematurity can disrupt the psychological transition to parenthood, with the unfamiliar environment of the Neonatal Intensive Care Unit (NICU) often exacerbating parental concerns about their baby’s health and survival. This study explores factors influencing parental coping mechanisms during their NICU stay, focusing on gender differences and parental perceptions of staff support. Sixteen Italian parents of preterm infants (born before 37 weeks of gestation and hospitalized for at least 10 days) participated in remote narrative interviews. Thematic analysis revealed key differences in the emotional experiences and care participation between mothers and fathers, shaped by traditional Italian gender norms and further impacted by COVID-19 restrictions limiting fathers’ access to the NICU. Additionally, parents who were more involved in their infant’s recovery through interactions with doctors reported higher levels of personal well-being. These findings highlight the importance of fostering parent-staff communication and support, particularly during times of crisis, to promote positive outcomes in the parent-infant relationship and enhance parental well-being. Recommendations include tailored interventions to ensure mothers and fathers are actively engaged in their infant’s care.

Enhancing ICU care with nurse-written diaries.

Patient diaries are a supportive intervention aiding intensive care unit (ICU) survivors and their families post-critical illness. Despite their growing acceptance, ICU diary usage varies across settings. This study explored themes in nurse-written ICU diaries and their impact on nursing work and communication. This qualitative study employed an interpretative narrative methodology to explore the experiences of ICU nurses. The narrative approach enabled the synthesis of diverse events and impressions into coherent stories, facilitating a deeper understanding of participants' perspectives. Data collection involved thematic analysis of diaries following Braun and Clarke's methodology. The analysis included familiarization, coding, theme identification and validation by the research team. The findings were reviewed by participants and translated into English using the WHO's cultural adaptation guidelines, ensuring reliability and credibility in the study's outcomes. The sample consisted of 28 ICU nurses, each with professional experience ranging from 1 to 23 years. The hospitalized subjects for whom our sample wrote the diary consist of 13 participants aged 23-79 years. Two main themes emerged from the analysis: (1) simplifying the intensive care situation with specific minimization strategies and (2) attention to nonverbal communication. This study highlights the role of nurse-written ICU diaries in making the ICU environment more understandable and less intimidating for patients. Nurse-written ICU diaries contribute to improved communication and emotional support within the ICU environment. Further research is needed to explore these effects more fully and to assess the broader implications of ICU diaries on patient outcomes. Nurse-written intensive care unit (ICU) diaries have a significant impact on both patient care and nursing practice in ICUs. ICU diaries serve as a crucial tool for enhancing communication, emotional support and empathetic care within these high-stress environments. By simplifying complex medical information and focusing on nonverbal communication, nurses can make the ICU experience more comprehensible and less intimidating for patients. This approach reduces patient anxiety and psychological stress while fostering a stronger nurse-patient relationship, ultimately improving care quality.

Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study.

Cardiac arrest (CA) is one of the leading causes of death among patients in the intensive care unit (ICU). Although many CA prediction models with high sensitivity have been developed to anticipate CA, their practical application has been challenging due to a lack of generalization and validation. Additionally, the heterogeneity among patients in different ICU subtypes has not been adequately addressed. This study aims to propose a clinically interpretable ensemble approach for the timely and accurate prediction of CA within 24 hours, regardless of patient heterogeneity, including variations across different populations and ICU subtypes. Additionally, we conducted patient-independent evaluations to emphasize the model's generalization performance and analyzed interpretable results that can be readily adopted by clinicians in real-time. Patients were retrospectively analyzed using data from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) and the eICU-Collaborative Research Database (eICU-CRD). To address the problem of underperformance, we constructed our framework using feature sets based on vital signs, multiresolution statistical analysis, and the Gini index, with a 12-hour window to capture the unique characteristics of CA. We extracted 3 types of features from each database to compare the performance of CA prediction between high-risk patient groups from MIMIC-IV and patients without CA from eICU-CRD. After feature extraction, we developed a tabular network (TabNet) model using feature screening with cost-sensitive learning. To assess real-time CA prediction performance, we used 10-fold leave-one-patient-out cross-validation and a cross-data set method. We evaluated MIMIC-IV and eICU-CRD across different cohort populations and subtypes of ICU within each database. Finally, external validation using the eICU-CRD and MIMIC-IV databases was conducted to assess the model's generalization ability. The decision mask of the proposed method was used to capture the interpretability of the model. The proposed method outperformed conventional approaches across different cohort populations in both MIMIC-IV and eICU-CRD. Additionally, it achieved higher accuracy than baseline models for various ICU subtypes within both databases. The interpretable prediction results can enhance clinicians' understanding of CA prediction by serving as a statistical comparison between non-CA and CA groups. Next, we tested the eICU-CRD and MIMIC-IV data sets using models trained on MIMIC-IV and eICU-CRD, respectively, to evaluate generalization ability. The results demonstrated superior performance compared with baseline models. Our novel framework for learning unique features provides stable predictive power across different ICU environments. Most of the interpretable global information reveals statistical differences between CA and non-CA groups, demonstrating its utility as an indicator for clinical decisions. Consequently, the proposed CA prediction system is a clinically validated algorithm that enables clinicians to intervene early based on CA prediction information and can be applied to clinical trials in digital health.

Caregivers’ experiences on preterm infants’ management in a tertiary care facility in Ghana: a qualitative exploratory study

BackgroundPreterm birth is a process that fundamentally alters parental or caregiver roles, particularly in the early weeks of childbirth. Caregiver experiences can be distressing due to struggles with an unfamiliar and potentially threatening environment of the Neonatal Intensive Care Unit (NICU). These experiences can affect the development of parenting or caregiving roles to a greater extent. Supporting caregivers of preterm infants through education and information sharing can significantly improve neonatal outcomes. This study sought to explore the experiences of caregivers with hospitalized preterm infants regarding the education and information they received from healthcare workers on the care of preterm infants.MethodAn exploratory descriptive qualitative study that explored caregivers’ experiences with the management of preterm infants hospitalized at the Level III Neonatal Intensive Care Unit (NICU) of a tertiary level facility with an annual delivery of almost 7500 and a bed capacity of 26. The study utilized a deductive approach and a purposive sampling technique to recruit 16 caregivers who participated in an in-depth interview using a piloted semi-structured interview guide. The interviews were audio-recorded, transcribed, and analyzed using thematic analysis.FindingsThe study identified three major themes, which were (1) preterm infant feeding and keeping infants warm, (2) routine procedures and activities at the NICU, and (3) preparation towards homecare after discharge. Seven (7) sub-themes were generated. Caregivers were satisfied with the education and information they received on infant feeding and keeping the infant ward. They also had adequate education that prepared them for home care of the preterm infant. Caregivers did not receive timely information and education on the health status of their infants and the care processes of the NICU. They felt they were left out as they were not involved in decision-making. Regarding the care of the preterm infant. The inadequate flow of information and use of medical terminologies were a great source of worry and frustration for participants. The study showed that although the NICU staff were willing to offer health education to caregivers, information giving and education were not structured and hence did not address all the needs of the caregivers.ConclusionHealthcare providers caring for preterm infants include caregiver education in their routine NICU activities and procedures. These processes start from the period of admission till discharge. Their education sessions primarily focus on breastfeeding, keeping the infant warm and adequate preparation of caregivers for preterm infant home care. This notwithstanding there are gaps in caregiver education and information on routine procedures in the NICU as well as information on the health needs of the infant. Participants are not fully involved in the decision-making processes and the use of medical terminologies compound caregivers’ frustrations and anxieties. It is important to develop structured educational programs tailored to address the information needs faced by caregivers to ensure optimal health outcomes for their preterm infants.

Continuous Electroencephalographic Monitoring in Adult ICU Challenges and Potential Solutions: A Scoping Review

Background: Continuous electroencephalographic (cEEG) monitoring is continuous monitoring of brain activity that is often used in the intensive care unit (ICU). Recently, the usage of cEEG has grown in many institutions as it detects non-convulsive seizures better than routine EEG (rEEG). However, due to the aggressive environment of ICU, the application and the prolonged recording is challenging. The objectives of this scoping review are to evaluate the common challenges faced during cEEG in adult ICU and proper solutions for optimal implementation. Methods: A scoping review was conducted using Arksey and O’Malley framework. The included articles contain “continuous EEG in ICU settings” in their titles, written in English, and published between 2010 and 2022. That was by searching the databases: PubMed, Google Scholar, and Summon. Results: 14 articles were included as they meet the criteria of this review. (28.57 %) of the included studies mentioned the challenges regarding staff, (42.85 %) addressed the challenges of electrode application and the alternative techniques in ICU, and (42.85%) discussed the difficulties in interpretation and duration of the recording. Conclusion: Continuous EEG is increasingly recognized as valuable mean of monitoring cerebral function, but it is faced with numerous challenges: the difficult environment of ICU and the type of critical patient admitted requiring the optimal electrode application and maintenance, minimizing artifacts and adequate duration of recording to detect abnormalities, and sufficiently trained personnel including ICU staff, technologist and neurophysiologist to provide the optimal patient care as it is the main goal.

The Approach to Altered Mental Status in the Intensive Care Unit.

Altered mental status (AMS) is a syndrome posing substantial burden to patients in the intensive care unit (ICU) in both prevalence and intensity. Unfortunately, ICU patients are often diagnosed merely with syndromic labels, particularly the duo of toxic-metabolic encephalopathy (TME) and delirium. Before applying a nonspecific diagnostic label, every patient with AMS should be evaluated for specific, treatable diseases affecting the central nervous system. This review offers a structured approach to increase the probability of identifying specific causal etiologies of AMS in the critically ill. We provide tips for bedside assessment in the challenging ICU environment and review the role and yield of common neurodiagnostic procedures, including specialized bedside modalities of diagnostic utility in unstable patients. We briefly review two common etiologies of TME (uremic and septic encephalopathies), and then review a selection of high-yield toxicologic, neurologic, and infectious causes of AMS in the ICU, with an emphasis on those that require deliberate consideration as they elude routine screening. The final section lays out an approach to the various etiologies of AMS in the critically ill.

Assessing the safety and efficacy of probiotics in improving the gut microbiome of premature infants

Introduction and PurposeThe gut microbiome is crucial to infant health and development. For premature infants, microbiome development differs from full-term babies, posing long-term health risks. Factors such as delivery method, feeding, antibiotic treatment, and neonatal intensive care unit (NICU) environment significantly influence the microbiome of premature infants. Probiotics, especially Bifidobacterium strains, show promise in enhancing health and reducing risks of necrotizing enterocolitis (NEC) and late-onset sepsis (LOS).Material and MethodsThis review is based on articles from the PubMed database, covering the years 2004-2023, using keywords: gut microbiome, premature infants, probiotic, microbiome development, and neonatal intensive care unit.ResultsCurrent research indicates probiotics, particularly Bifidobacterium strains, positively impact the gut microbiome of premature infants, improving immunity and metabolism, and providing protection against NEC and LOS. Multi-strain probiotic preparations combining Bifidobacterium and Lactobacilaceae strains appear promising, but further research is needed to fully understand their effects. Addressing food intolerance (FI) in premature infants is another potential application of microbiome-focused therapies.ConclusionsWhile probiotics show promise in improving the microbiome of preterm infants, comprehensive research on single and multi-strain probiotics and their specific mechanisms of action is needed. Controversies persist regarding the safety, FDA regulation, and selection of specific probiotics and formulations. There is no consensus on the optimal timing for introducing probiotics. Further research is required to optimize probiotic selection and determine the best benefits. Enhanced standardization and oversight are essential to ensure safe and effective use of probiotics in neonatal healthcare.

Frequently Touched Sites in the Intensive Care Unit Environment Returning 100 Colony-Forming Units per Surface Area Sampled Are Associated With Increased Risk of Major Bacterial Pathogen Detection.

A threshold for surface hygiene has not been defined for the healthcare arena. We aimed to identify the magnitude of bacterial contamination offrequently touched sites in the intensive care unit (ICU) environment that could be used to guide quality improvement initiatives. Nineteen patients in a mixed ICU environment (providing care for medical and surgical patients) were followed from admission for 72 hoursin 2010. Baseline cultures of frequently touched environmental sites were obtained at time zero following active decontamination and at 12, 24, 48, and 72 hours without further disinfection. We tested for an association of environmental reservoirs returning ≥ 100 colony-forming units (CFU) per surface area sampledwith major bacterial pathogen detection. There were 446 ICU room, day, and reservoir combinations sampled from 19 patients. There were pathogens detected in 40% (79/199) of samples with ≥ 100 CFU vs. 14% (35/247) of samples returning < 100 CFU. The relative risk was 2.80 (95% CI: 1.97-3.98, P <0.0001). The odds ratio adjusted for time in hours was 3.11 (95% CI: 1.84-5.34, P < 0.0001). Frequently touched ICU environmental sites returning ≥ 100 CFU are associated with major bacterial pathogen detection. This threshold for surface hygiene can be used to ensure compliance with ICU environmental cleaning protocols and toguide quality improvement initiatives.

The Impact of Information Relevancy and Interactivity on Intensivists' Trust in a Machine Learning-Based Bacteremia Prediction System: Simulation Study.

The exponential growth in computing power and the increasing digitization of information have substantially advanced the machine learning (ML) research field. However, ML algorithms are often considered "black boxes," and this fosters distrust. In medical domains, in which mistakes can result in fatal outcomes, practitioners may be especially reluctant to trust ML algorithms. The aim of this study is to explore the effect of user-interface design features on intensivists' trust in an ML-based clinical decision support system. A total of 47 physicians from critical care specialties were presented with 3 patient cases of bacteremia in the setting of an ML-based simulation system. Three conditions of the simulation were tested according to combinations of information relevancy and interactivity. Participants' trust in the system was assessed by their agreement with the system's prediction and a postexperiment questionnaire. Linear regression models were applied to measure the effects. Participants' agreement with the system's prediction did not differ according to the experimental conditions. However, in the postexperiment questionnaire, higher information relevancy ratings and interactivity ratings were associated with higher perceived trust in the system (P<.001 for both). The explicit visual presentation of the features of the ML algorithm on the user interface resulted in lower trust among the participants (P=.05). Information relevancy and interactivity features should be considered in the design of the user interface of ML-based clinical decision support systems to enhance intensivists' trust. This study sheds light on the connection between information relevancy, interactivity, and trust in human-ML interaction, specifically in the intensive care unit environment.

Role of artificial intelligence in critical care nutrition support and research.

Nutrition plays a key role in the comprehensive care of critically ill patients. Determining optimal nutrition strategy, however, remains a subject of intense debate. Artificial intelligence (AI) applications are becoming increasingly common in medicine, and specifically in critical care, driven by the data-rich environment of intensive care units. In this review, we will examine the evidence regarding the application of AI in critical care nutrition. As of now, the use of AI in critical care nutrition is relatively limited, with its primary emphasis on malnutrition screening and tolerance of enteral nutrition. Despite the current scarcity of evidence, the potential for AI for more personalized nutrition management for critically ill patients is substantial. This stems from the ability of AI to integrate multiple data streams reflecting patients' changing needs while addressing inherent heterogeneity. The application of AI in critical care nutrition holds promise for optimizing patient outcomes through tailored and adaptive nutrition interventions. A successful implementation of AI, however, necessitates a multidisciplinary approach, coupled with careful consideration of challenges related to data management, financial aspects, and patient privacy.