Are We Always Right? Evaluation of the Performance and Knowledge of the Passive Leg Raise Test in Detecting Volume Responsiveness in Critical Care Patients: A National German Survey.

Background: In hemodynamically unstable patients, the passive leg raise (PLR) test is recommended for use as a self-fluid challenge for predicting preload responsiveness. However, to interpret the hemodynamic effects and reliability of the PLR, the method of performing it is of the utmost importance. Our aim was to determine the current practice of the correct application and interpretation of the PLR in intensive care patients. Methods: After ethical approval, we designed a cross-sectional online survey with a short user-friendly online questionnaire. Using a random sample of 1903 hospitals in Germany, 182 hospitals with different levels of care were invited via an email containing a link to the questionnaire. The online survey was conducted between December 2021 and January 2022. All critical care physicians from different medical disciplines were surveyed. We evaluated the correct points of concern for the PLR, including indication, contraindication, choice of initial position, how to interpret and apply the changes in cardiac output, and the limitations of the PLR. Results: A total of 292 respondents participated in the online survey, and 283/292 (97%) of the respondents completed the full survey. In addition, 132/283 (47%) were consultants and 119/283 (42%) worked at a university medical center. The question about the performance of the PLR was answered correctly by 72/283 (25%) of the participants. The limitations of the PLR, such as intra-abdominal hypertension, were correctly selected by 150/283 (53%) of the participants. The correct effect size (increase in stroke volume ≥ 10%) was correctly identified by 217/283 (77%) of the participants. Conclusions: Our results suggest a considerable disparity between the contemporary practice of the correct application and interpretation of the PLR and the practice recommendations from recently published data at German ICUs.

Author Response.

How to cite this article: Vijayakumar M, Selvam V, Renuka MK, Rajagopalan RE. Author Response. Indian J Crit Care Med 2024;28(5):515.

Modified NUTRIC Score as a Predictor of All-cause Mortality in Critically Ill Patients: A Systematic Review and Meta-analysis.

Purpose: The purpose of our meta-analysis was to look at the impact of modified nutrition risk in the critically ill (mNUTRIC) on mortality in patients with critical illness. Materials and methods: Literature relevant to this meta-analysis was searched in PubMed, Web of Science, and Cochrane Library till 26 August 2023. Prospective or retrospective studies, patients >18 years of age, studies that reported on mortality and mNUTRIC (mNUTRIC cut-off score) were included. The QUIPS tool was used to evaluate the risk for bias in prognostic factors. Results: A total of 31 studies on mNUTRIC score, involving 13,271 patients were included. The summary area under the curve (sAUC) of 0.80 (95% CI: 0.76-0.83) illustrates the mNUTRIC score's strong discrimination. The pooled sensitivity was 0.79 (95% CI: 0.74-0.84) and pooled specificity was 0.68 (95% CI: 0.63-0.73). We found no discernible variation in the mNUTRIC's prediction accuracy among cut-off values of <5 and >5 in our subgroup analysis and sAUC values were 0.82 (95% CI: 0.78-0.85) and 0.78 (95% CI: 0.74-0.81), respectively. Conclusion: We observed that mNUTRIC can discriminate between critically ill individuals and predict their mortality. Prospero: CRD42023460292. How to cite this article: Prakash J, Verma S, Shrivastava P, Saran K, Kumari A, Raj K, et al. Modified NUTRIC Score as a Predictor of All-cause Mortality in Critically Ill Patients: A Systematic Review and Meta-analysis. Indian J Crit Care Med 2024;28(5):495-503.

Effect of Admission Day and Time on Patient Outcome: An Observational Study in Intensive Care Units of a Tertiary Care Hospital in India.

Background: The current study aimed to assess any association between intensive care unit (ICU) and hospital outcomes with ICU admission timings of critically ill patients. Methods: Retrospective observational single-center study involving all adult admissions. Each patient admission was categorized in "after-hours" (08:00 p.m.-07:59 a.m.), or "normal-hours" (08:00 a.m.-07:59 p.m.), "Weekday" (Monday-Saturday), or "Weekend" (Sunday), "Same day" (admission directly to ICU) or "other day admission" (admission to ICU after a hospital stay of ≥24 hours). Intensive care unit and hospital mortality, length of stay (LOS), and ICU readmission were assessed for any association with different admission timings. Results: Among 3,029 patients, 54.2% (1,668) were male, with mean age 66.49 (SD ± 15.69) years, mean acute physiology and chronic health evaluation-IV (APACHE-IV) score 55.5 (SD ± 26.3). Around 86.1% of admission occurred during weekdays, 13.9% on weekends, 57.4% normal-hours, 42.6% after-hours, 66.3% same day and 33.7% other day admission. Intensive care unit and hospital mortality were 10.8 and 14.2% respectively. Neither ICU nor hospital mortality were significantly different among patients admitted normal vs after-hours (p = 0.32, 0.23), and weekdays vs weekends (p = 0.09, 0.93), nor was ICU LOS (p = 0.21, 0.74). Intensive care unit and hospital mortality (p = 0.001), DORB (p = 0.001), hospital LOS (p = 0.001), and readmission to ICU (p = 0.001) were significantly higher in the other day admission group compared to same-day admission. In a multivariate regression analysis age, APACHE IV score along with other day admission to ICU did have a significant effect on both ICU and hospital mortality. Conclusion: Intensive care unit and hospital mortality and LOS did not differ significantly with hours or days of ICU admission though they were significantly higher in other day admission groups. How to cite this article: Bhattacharyya M, Todi SK. Effect of Admission Day and Time on Patient Outcome: An Observational Study in Intensive Care Units of a Tertiary Care Hospital in India. Indian J Crit Care Med 2024;28(5):436-441.

Mobilizing Progress: A Comprehensive Review of the Efficacy of Early Mobilization Therapy in the Intensive Care Unit.

Early mobilization therapy has emerged as a crucial aspect of intensive care unit (ICU) management, aiming to counteract the detrimental effects of prolonged immobility in critically ill patients. This comprehensive review examines the efficacy of early mobilization therapy in the ICU setting, synthesizing evidence from clinical trials, meta-analyses, and guidelines. Key findings indicate that early mobilization is associated with numerous benefits, including reduced muscle weakness, a shorter duration of mechanical ventilation, decreased ICU and hospital length of stay, and improved functional outcomes. However, safety concerns, staffing limitations, and patient-specific considerations pose significant barriers to widespread adoption. Despite these challenges, early mobilization is important for improving ICU patient outcomes. This review underscores the critical need for continued research and implementation efforts to optimize early mobilization protocols, address remaining challenges, and expand access to this beneficial therapy. By working collaboratively to overcome barriers and prioritize early mobilization, healthcare providers can enhance the quality of care and improve outcomes for critically ill patients in the ICU.

Efficiency of therapeutic plasma exchange in critically ill systemic rheumatologic diseases: A single-center 9-year experience.

INTRODUCTION: Therapeutic plasma exchange (TPE), an effective method to eliminate harmful soluble mediators associated with tissue injury, serves as a crucial intervention for systemic rheumatologic diseases (SRDs). However, its value in critically ill SRDs remains uncertain. This retrospective study aims to evaluate the efficacy of TPE in SRDs. METHODS: Critically ill SRD patients admitted to the department of intensive care unit of a large tertiary hospital receiving TPE from January 2011 to December 2019 were included. RESULTS: A total of 91 critically ill SRD patients received TPE were enrolled. Their mean age was 47.67 ± 16.35 years with a female predominance (n = 68). Significant decrease in SOFA score post-TPE treatment was observed (p < 0.05). There were no TPE-related fatalities. Improvement was observed in 64 (70.32%) patients. CONCLUSION: This study shows favorable clinical outcomes. TPE may be an acceptable treatment option for critically ill SRD patients.

Development and external validation of a prediction model for the premature circuit clotting of continuous renal replacement therapy in critically ill patients.

OBJECTIVE: This study aimed to develop and validate a prediction model for premature circuit clotting of continuous renal replacement therapy (CRRT) in critically ill patients. DESIGN: A retrospective cohort study was conducted on ICU patients undergoing CRRT. The Medical Information Mart for Intensive Care-III Clinical Database CareVue subset and Medical Information Mart for Intensive Care-IV were utilized for model development, while the eICU Collaborative Research Database was employed for external validation. Predictive factors were selected through Least Absolute Shrinkage and Selection Operator Regression and univariate logistic regression. A prediction model was then developed using binary logistic regression. Internal and external validations assessed the model's discrimination, calibration, and clinical net benefit. RESULTS: This study encompassed 2531 patients overall, with a premature circuit clotting rate of 31.88 %. The prediction model comprises five variables: body temperature, anticoagulation, mean arterial pressure, maximum transmembrane pressure change within two hours, and vasopressor. The model demonstrated robust predictive performance, achieving an area under the receiver operating characteristic curve of 0.897 (95 % CI: 0.879-0.915) in the training set and 0.877 (95 % CI: 0.852-0.902) in the external validation set. Internal validation yielded a Brier score of 0.087, while external validation showed a Brier score of 0.120. Calibration curves indicated good model calibration for both validations. The decision curve analysis indicates that the model yields a clinical net benefit across a wide range of decision thresholds. CONCLUSION: The model demonstrates robust discrimination, calibration, and clinical net benefit, with readily available variables indicating substantial potential for valuable clinical applications. IMPLICATIONS FOR CLINICAL PRACTICE: Healthcare providers in the ICU can leverage the model to evaluate the risk of premature circuit clotting in critically ill patients undergoing continuous renal replacement therapy, facilitating timely intervention to mitigate its incidence.

AKIMLpred: An interpretable machine learning model for predicting acute kidney injury within seven days in critically ill patients based on a prospective cohort study.

BACKGROUND: Early recognition and timely intervention for AKI in critically ill patients were crucial to reduce morbidity and mortality. This study aimed to use biomarkers to construct a optimal machine learning model for early prediction of AKI in critically ill patients within seven days. METHODS: The prospective cohort study enrolled 929 patients altogether who were admitted in ICU including 680 patients in training set (Jiefang Campus) and 249 patients in external testing set (Binjiang Campus). After performing strict inclusion and exclusion criteria, 421 patients were selected in training set for constructing predictive model and 167 patients were selected in external testing for evaluating the predictive performance of resulting model. Urine and blood samples were collected for kidney injury associated biomarkers detection. Baseline clinical information and laboratory data of the study participants were collected. We determined the average prediction efficiency of six machine learning models through 10-fold cross validation. RESULTS: In total, 78 variables were collected when admission in ICU and 43 variables were statistically significant between AKI and non-AKI cohort. Then, 35 variables were selected as independent features for AKI by univariate logistic regression. Spearman correlation analysis was used to remove two highly correlated variables. Three ranking methods were used to explore the influence of 33 variables for further determining the best combination of variables. The gini importance ranking method was found to be applicable for variables filtering. The predictive performance of AKIMLpred which constructed by the XGBoost algorithm was the best among six machine learning models. When the AKIMLpred included the nine features (NGAL, IGFBP7, sCysC, CAF22, KIM-1, NT-proBNP, IL-6, IL-18 and L-FABP) with the highest influence ranking, its model had the best prediction performance, with an AUC of 0.881 and an accuracy of 0.815 in training set, similarly, with an AUC of 0.889 and an accuracy of 0.846 in validation set. Moreover, the performace was slightly outperformed in testing set with an AUC of 0.902 and an accuracy of 0.846. The SHAP algorithm was used to interpret the prediction results of AKIMLpred. The web-calculator of AKIMLpred was shown for predicting AKI with more convenient(https://www.xsmartanalysis.com/model/list/predict/model/html?mid=8065&symbol=11gk693982SU6AE1ms21). AKIMLpred was better than the optimal model built with only routine tests for predicting AKI in critically ill patients within 7 days. CONCLUSION: The model AKIMLpred constructed by the XGBoost algorithm with selecting the nine most influential biomarkers in the gini importance ranking method had the best performance in predicting AKI in critically ill patients within 7 days. This data-driven predictive model will help clinicians to make quick and accurate diagnosis.

Machine Learning for Predicting Risk and Prognosis of Acute Kidney Disease in Critically Ill Elderly Patients During Hospitalization: Internet-Based and Interpretable Model Study.

BACKGROUND: Acute kidney disease (AKD) affects more than half of critically ill elderly patients with acute kidney injury (AKI), which leads to worse short-term outcomes. OBJECTIVE: We aimed to establish 2 machine learning models to predict the risk and prognosis of AKD in the elderly and to deploy the models as online apps. METHODS: Data on elderly patients with AKI (n=3542) and AKD (n=2661) from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were used to develop 2 models for predicting the AKD risk and in-hospital mortality, respectively. Data collected from Xiangya Hospital of Central South University were for external validation. A bootstrap method was used for internal validation to obtain relatively stable results. We extracted the indicators within 24 hours of the first diagnosis of AKI and the fluctuation range of some indicators, namely delta (day 3 after AKI minus day 1), as features. Six machine learning algorithms were used for modeling; the area under the receiver operating characteristic curve (AUROC), decision curve analysis, and calibration curve for evaluating; Shapley additive explanation (SHAP) analysis for visually interpreting; and the Heroku platform for deploying the best-performing models as web-based apps. RESULTS: For the model of predicting the risk of AKD in elderly patients with AKI during hospitalization, the Light Gradient Boosting Machine (LightGBM) showed the best overall performance in the training (AUROC=0.844, 95% CI 0.831-0.857), internal validation (AUROC=0.853, 95% CI 0.841-0.865), and external (AUROC=0.755, 95% CI 0.699-0.811) cohorts. In addition, LightGBM performed well for the AKD prognostic prediction in the training (AUROC=0.861, 95% CI 0.843-0.878), internal validation (AUROC=0.868, 95% CI 0.851-0.885), and external (AUROC=0.746, 95% CI 0.673-0.820) cohorts. The models deployed as online prediction apps allowed users to predict and provide feedback to submit new data for model iteration. In the importance ranking and correlation visualization of the model's top 10 influencing factors conducted based on the SHAP value, partial dependence plots revealed the optimal cutoff of some interventionable indicators. The top 5 factors predicting the risk of AKD were creatinine on day 3, sepsis, delta blood urea nitrogen (BUN), diastolic blood pressure (DBP), and heart rate, while the top 5 factors determining in-hospital mortality were age, BUN on day 1, vasopressor use, BUN on day 3, and partial pressure of carbon dioxide (PaCO2). CONCLUSIONS: We developed and validated 2 online apps for predicting the risk of AKD and its prognostic mortality in elderly patients, respectively. The top 10 factors that influenced the AKD risk and mortality during hospitalization were identified and explained visually, which might provide useful applications for intelligent management and suggestions for future prospective research.

The Interplay between Antibiotics and the Host Immune Response in Sepsis: From Basic Mechanisms to Clinical Considerations: A Comprehensive Narrative Review.

Sepsis poses a significant global health challenge due to immune system dysregulation. This narrative review explores the complex relationship between antibiotics and the immune system, aiming to clarify the involved mechanisms and their clinical impacts. From pre-clinical studies, antibiotics exhibit various immunomodulatory effects, including the regulation of pro-inflammatory cytokine production, interaction with Toll-Like Receptors, modulation of the P38/Pmk-1 Pathway, inhibition of Matrix Metalloproteinases, blockade of nitric oxide synthase, and regulation of caspase-induced apoptosis. Additionally, antibiotic-induced alterations to the microbiome are associated with changes in systemic immunity, affecting cellular and humoral responses. The adjunctive use of antibiotics in sepsis patients, particularly macrolides, has attracted attention due to their immune-regulatory effects. However, there are limited data comparing different types of macrolides. More robust evidence comes from studies on community-acquired pneumonia, especially in severe cases with a hyper-inflammatory response. While studies on septic shock have shown mixed results regarding mortality rates and immune response modulation, conflicting findings are also observed with macrolides in acute respiratory distress syndrome. In conclusion, there is a pressing need to tailor antibiotic therapy based on the patient's immune profile to optimize outcomes in sepsis management.

A Comprehensive Review on Serum Ferritin as a Prognostic Marker in Intensive Care Units: Insights Into Ischemic Heart Disease.

Serum ferritin has garnered considerable attention as a prognostic marker in intensive care units (ICUs), offering valuable insights into patient outcomes and clinical management strategies. This comprehensive review examines the role of serum ferritin in predicting outcomes among critically ill patients, with a particular focus on its implications for ischemic heart disease (IHD). Elevated serum ferritin levels have consistently been associated with adverse outcomes in ICU settings, including increased mortality, prolonged hospital stays, and higher morbidity rates. Furthermore, the relationship between serum ferritin levels and IHD underscores its potential as a biomarker for cardiovascular risk assessment in critically ill populations. The review synthesizes existing literature to highlight the predictive value of serum ferritin in assessing illness severity and guiding clinical decision-making in the ICUs. It also explores potential mechanisms linking serum ferritin to adverse outcomes and discusses implications for clinical practice. Integrating serum ferritin measurements into routine assessments could enhance prognostication and risk stratification in ICU patients, while further research is needed to elucidate optimal management strategies and therapeutic targets. Collaborative efforts between clinicians and researchers are essential to advance our understanding of serum ferritin's prognostic value in the ICUs and translate this knowledge into improved patient care and outcomes.

Population pharmacokinetics of intravenous daptomycin in critically ill patients: implications for selection of dosage regimens.

Daptomycin is gaining prominence for the treatment of methicillin-resistant Staphylococcus aureus infections. However, the dosage selection for daptomycin in critically ill patients remains uncertain, especially in Chinese patients. This study aimed to establish the population pharmacokinetics of daptomycin in critically ill patients, optimize clinical administration plans, and recommend appropriate dosage for critically ill patients in China. The study included 64 critically ill patients. Blood samples were collected at the designated times. The blood daptomycin concentration was determined using validated liquid chromatography-tandem mass spectrometry. A nonlinear mixed-effects model was applied for the population pharmacokinetic analysis and Monte Carlo simulations of daptomycin. The results showed a two-compartment population pharmacokinetic model of daptomycin in critically ill adult Han Chinese patients. Monte Carlo simulations revealed that a daily dose of 400 mg of daptomycin was insufficient for the majority of critically ill adult patients to achieve the anti-infective target. For critically ill adult patients with normal renal function (creatinine clearance rate >90 mL/min), the probability of achieving the target only reached 90% when the daily dose was increased to 700 mg. For patients undergoing continuous renal replacement therapy (CRRT), 24 h administration of 500 mg met the pharmacodynamic goals and did not exceed the safety threshold in most patients. Therefore, considering its efficacy and safety, intravenous daptomycin doses are best scaled according to creatinine clearance, and an increased dose is recommended for critically ill patients with hyperrenalism. For patients receiving CRRT, medication is recommended at 24 h intervals.

The complexity of glucose time series is associated with short- and long-term mortality in critically ill adults: a multi-center, prospective, observational study.

BACKGROUND: The wealth of data taken from continuous glucose monitoring (CGM) remains to be fully used. We aimed to evaluate the relationship between a promising new CGM metric, complexity of glucose time series index (CGI), and mortality in critically ill patients. METHODS: A total of 293 patients admitted to mixed medical/surgical intensive care units from 5 medical centers in Shanghai were prospectively included between May 2020 and November 2021. CGI was assessed using intermittently scanned CGM, with a median monitoring period of 12.0 days. Outcome measures included short- and long-term mortality. RESULTS: During a median follow-up period of 1.7 years, a total of 139 (47.4%) deaths were identified, of which 73 (24.9%) occurred within the first 30 days after ICU admission, and 103 (35.2%) within 90 days. The multivariable-adjusted HRs for 30-day mortality across ascending tertiles of CGI were 1.00 (reference), 0.68 (95% CI 0.38-1.22) and 0.36 (95% CI 0.19-0.70), respectively. For per 1-SD increase in CGI, the risk of 30-day mortality was decreased by 51% (HR 0.49, 95% CI 0.35-0.69). Further adjustment for HbA1c, mean glucose during hospitalization and glucose variability partially attenuated these associations, although the link between CGI and 30-day mortality remained significant (per 1-SD increase: HR 0.57, 95% CI 0.40-0.83). Similar results were observed when 90-day mortality was considered as the outcome. Furthermore, CGI was also significantly and independently associated with long-term mortality (per 1-SD increase: HR 0.77, 95% CI 0.61-0.97). CONCLUSIONS: In critically ill patients, CGI is significantly associated with short- and long-term mortality.

Impact of attaining aggressive vs. conservative PK/PD target on the clinical efficacy of beta-lactams for the treatment of Gram-negative infections in the critically ill patients: a systematic review and meta-analysis.

BACKGROUND: To perform a systematic review with meta-analysis with the dual intent of assessing the impact of attaining aggressive vs. conservative beta-lactams PK/PD target on the clinical efficacy for treating Gram-negative infections in critical patients, and of identifying predictive factors of failure in attaining aggressive PK/PD targets. METHODS: Two authors independently searched PubMed-MEDLINE and Scopus database from inception to 23rd December 2023, to retrieve studies comparing the impact of attaining aggressive vs. conservative PK/PD targets on clinical efficacy of beta-lactams. Independent predictive factors of failure in attaining aggressive PK/PD targets were also assessed. Aggressive PK/PD target was considered a100%fT>4xMIC, and clinical cure rate was selected as primary outcome. Meta-analysis was performed by pooling odds ratios (ORs) extrapolated from studies providing adjustment for confounders using a random-effects model with inverse variance method. RESULTS: A total of 20,364 articles were screened, and 21 observational studies were included in the meta-analysis (N = 4833; 2193 aggressive vs. 2640 conservative PK/PD target). Attaining aggressive PK/PD target was significantly associated with higher clinical cure rate (OR 1.69; 95% CI 1.15-2.49) and lower risk of beta-lactam resistance development (OR 0.06; 95% CI 0.01-0.29). Male gender, body mass index > 30 kg/m2, augmented renal clearance and MIC above the clinical breakpoint emerged as significant independent predictors of failure in attaining aggressive PK/PD targets, whereas prolonged/continuous infusion administration of beta-lactams resulted as protective factor. The risk of bias was moderate in 19 studies and severe in the other 2. CONCLUSIONS: Attaining aggressive beta-lactams PK/PD targets provided significant clinical benefits in critical patients. Our analysis could be useful to stratify patients at high-risk of failure in attaining aggressive PK/PD targets.

An Observational Study of Nutritional Assessment, Prescription, Practices, and Its Outcome among Critically Ill Patients Admitted to an Intensive Care Unit.

Aim and background: Optimal feeding strategy for critically ill patients of intensive care unit (ICU) is often a matter of debate as patients admitted to ICU are highly catabolic and reduction in muscle mass is very common. We aimed at early achievement of nutritional goals in preventing skeletal muscle breakdown and improving clinical outcomes among critically ill patients with high risk of malnutrition. Materials and methods: Nutrition risk in the critically ill (mNUTRIC) Score was used to identify the risk of malnutrition within 24 hours of admission. Quadriceps muscle mass index was measured within 24 hours of admission to ICU and repeated on 7th day. Enteral feeding was monitored by the nutrition expert as part of routine patient care and clinical outcomes were monitored. Results: A total of 287 patients admitted in ICU were screened for malnutrition and 60 (20.9%) of them had high score (>5). There was no statistically significant reduction in the quadriceps muscle mass index (p < 0.05) (t = 0.601) measured within 24 hours of admission and on the 7th day of ICU stay, signifying that the nutritional prescription and monitoring may be useful in preserving the muscle mass. This study did not find statistically significant association between the high mNUTRIC score on admission and the clinical outcomes, such as 28 days mortality, incidence of pressure ulcers, length of ICU stay, and hospital-acquired infection (p > 0.05). Conclusion: Early initiation and maintenance of enteral nutrition is essential for meeting target calories and protein requirements. It may help to preserve muscle mass in critically ill patients who are otherwise at high risk of malnutrition. How to cite this article: Sharon T, Nayak SG, Shanbhag V, Hebbar S. An Observational Study of Nutritional Assessment, Prescription, Practices, and Its Outcome among Critically Ill Patients Admitted to an Intensive Care Unit. Indian J Crit Care Med 2024;28(4):364-368.

A Comprehensive Review of Chloride Management in Critically Ill Patients.

Chloride, often overshadowed in electrolyte management, emerges as a crucial player in the physiological intricacies of critically ill patients. This comprehensive review explores the multifaceted aspects of chloride, ranging from its significance in cellular homeostasis to the consequences of dysregulation in critically ill patients. The pathophysiology of hyperchloremia and hypochloremia is dissected, highlighting their intricate impact on acid-base balance, renal function, and cardiovascular stability. Clinical assessment strategies, including laboratory measurements and integration with other electrolytes, lay the foundation for targeted interventions. Consequences of dysregulated chloride levels underscore the need for meticulous management, leading to an exploration of emerging therapies and interventions. Fluid resuscitation protocols, the choice between crystalloids and colloids, the role of balanced solutions, and individualized patient approaches comprise the core strategies in chloride management. Practical considerations, such as monitoring and surveillance, overcoming implementation challenges, and embracing a multidisciplinary approach, are pivotal in translating theoretical knowledge into effective clinical practice. As we envision the future, potential impacts on critical care guidelines prompt reflections on integrating novel therapies, individualized approaches, and continuous monitoring practices. In conclusion, this review synthesizes current knowledge, addresses practical considerations, and envisions future directions in chloride management for critically ill patients. By embracing a holistic understanding, clinicians can navigate the complexities of chloride balance, optimize patient outcomes, and contribute to the evolving landscape of critical care medicine.

Reliability and validity assessment of the Chinese version of the Intrahospital Transport Safety Scale (IHTSS) in intensive care units.

BACKGROUND: Intrahospital transport of critically ill patients is a common practice in intensive care units (ICUs), where patients' safety is constantly challenged in high-intensity and dynamic environments. While Intrahospital Transport Safety Scale (IHTSS) is widely used internationally to evaluate the intrahospital transport safety, it has not been introduced in China. OBJECTIVES: This study aimed to assess the reliability and validity of the Chinese version of the IHTSS scale among critical care nurses in China. METHODS: A cross-sectional study was conducted using a cluster sampling method. A total of 544 critical care nurses from 25 ICUs in 10 tertiary hospitals were recruited. We employed exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to examine the questionnaire's underlying factor structure, ensuring construct validity. Additionally, internal consistency was assessed using Cronbach's alpha coefficient, test-retest reliability, and corrected item-total correlation. RESULTS: The Chinese version of the scale displayed robust psychometric properties, with a Cronbach's α coefficient of 0.976, a split-half reliability of 0.906, and a test-retest reliability of 0.856. EFA revealed a robust four-factor model that accounted for 75.970% of the variance, with the factor loadings of the items ranging from 0.433 to 0.951. CFA indicated a strong model fit, with a chi-square to degrees of freedom ratio (CMIN/DF) of 2.765, comparative fit index (CFI) of 0.943, incremental fit index (IFI) of 0.943, and goodness-of-fit index (GFI) of 0.845, supporting the efficacy of the four-factor model in assessing intrahospital transport safety for critically ill patients. CONCLUSION: The Chinese version of the IHTSS demonstrated favourable reliability and validity among critical care nurses in China, making it a suitable tool for measuring the level of intrahospital transport safety for critically ill patients.

Threshold of hyperglycaemia associated with mortality in critically ill patients: a multicentre, prospective, observational study using continuous glucose monitoring.

AIMS/HYPOTHESIS: Continuous glucose monitoring (CGM) provides comprehensive information on the exposure to dysglycaemia. This study aimed to investigate the threshold of hyperglycaemia related to mortality risk in critically ill patients using CGM technology. METHODS: A total of 293 adult critically ill patients admitted to intensive care units of five medical centres were prospectively included between May 2020 and November 2021. Participants wore intermittently scanned CGM for a median of 12.0 days. The relationships between different predefined time above ranges (TARs), with the thresholds of hyperglycaemia ranging from 7.8 to 13.9 mmol/l (140-250 mg/dl), and in-hospital mortality risk were assessed by multivariate Cox proportional regression analysis. Time in ranges (TIRs) of 3.9 mmol/l (70 mg/dl) to the predefined hyperglycaemic thresholds were also assessed. RESULTS: Overall, 66 (22.5%) in-hospital deaths were identified. Only TARs with a threshold of 10.5 mmol/l (190 mg/dl) or above were significantly associated with the risk of in-hospital mortality, after adjustment for covariates. Furthermore, as the thresholds for TAR increased from 10.5 mmol/l to 13.9 mmol/l (190 mg/dl to 250 mg/dl), the hazards of in-hospital mortality increased incrementally with every 10% increase in TARs. Similar results were observed concerning the associations between TIRs with various upper thresholds and in-hospital mortality risk. For per absolute 10% decrease in TIR 3.9-10.5 mmol/l (70-190 mg/dl), the risk of in-hospital mortality was increased by 12.1% (HR 1.121 [95% CI 1.003, 1.253]). CONCLUSIONS/INTERPRETATION: A glucose level exceeding 10.5 mmol/l (190 mg/dl) was significantly associated with higher risk of in-hospital mortality in critically ill patients.

Oxidative stress, defective proteostasis and immunometabolic complications in critically ill patients.

Oxidative stress (OS) develops in critically ill patients as a metabolic consequence of the immunoinflammatory and degenerative processes of the tissues. These induce increased and/or dysregulated fluxes of reactive species enhancing their pro-oxidant activity and toxicity. At the same time, OS sustains its own inflammatory and immunometabolic pathogenesis, leading to a pervasive and vitious cycle of events that contribute to defective immunity, organ dysfunction and poor prognosis. Protein damage is a key player of these OS effects; it generates increased levels of protein oxidation products and misfolded proteins in both the cellular and extracellular environment, and contributes to forms DAMPs and other proteinaceous material to be removed by endocytosis and proteostasis processes of different cell types, as endothelial cells, tissue resident monocytes-macrophages and peripheral immune cells. An excess of OS and protein damage in critical illness can overwhelm such cellular processes ultimately interfering with systemic proteostasis, and consequently with innate immunity and cell death pathways of the tissues thus sustaining organ dysfunction mechanisms. Extracorporeal therapies based on biocompatible/bioactive membranes and new adsorption techniques may hold some potential in reducing the impact of OS on the defective proteostasis of patients with critical illness. These can help neutralizing reactive and toxic species, also removing solutes in a wide spectrum of molecular weights thus improving proteostasis and its immunometabolic corelates. Pharmacological therapy is also moving steps forward which could help to enhance the efficacy of extracorporeal treatments. This narrative review article explores the aspects behind the origin and pathogenic role of OS in intensive care and critically ill patients, with a focus on protein damage as a cause of impaired systemic proteostasis and immune dysfunction in critical illness.

Early predictors of intensive care unit admission among COVID-19 patients in Qatar.

Background: COVID-19 is associated with significant morbidity and mortality. This study aimed to explore the early predictors of intensive care unit (ICU) admission among patients with COVID-19. Methods: This was a case-control study of adult patients with confirmed COVID-19. Cases were defined as patients admitted to ICU during the period February 29-May 29, 2020. For each case enrolled, one control was matched by age and gender. Results: A total of 1,560 patients with confirmed COVID-19 were included. Each group included 780 patients with a predominant male gender (89.7%) and a median age of 49 years (interquartile range = 18). Predictors independently associated with ICU admission were cardiovascular disease (adjusted odds ratio (aOR) = 1.64, 95% confidence interval (CI): 1.16-2.32, p = 0.005), diabetes (aOR = 1.52, 95% CI: 1.08-2.13, p = 0.016), obesity (aOR = 1.46, 95% CI: 1.03-2.08, p = 0.034), lymphopenia (aOR = 2.69, 95% CI: 1.80-4.02, p < 0.001), high AST (aOR = 2.59, 95% CI: 1.53-4.36, p < 0.001), high ferritin (aOR = 1.96, 95% CI: 1.40-2.74, p < 0.001), high CRP (aOR = 4.09, 95% CI: 2.81-5.96, p < 0.001), and dyspnea (aOR = 2.50, 95% CI: 1.77-3.54, p < 0.001). Conclusion: Having cardiovascular disease, diabetes, obesity, lymphopenia, dyspnea, and increased AST, ferritin, and CRP were independent predictors for ICU admission in patients with COVID-19.