Hours Of Intensive Care Unit Admission Research Articles

Impact of daily cyclic enteral nutrition versus standard continuous enteral nutrition in critically ill patients: a study protocol for a randomised controlled trial in three intensive care units in France (DC-SCENIC)

IntroductionCurrent guidelines on clinical nutrition of ventilated patients in the intensive care unit (ICU) recommend initiating continuous enteral nutrition within 48 hours of ICU admission when feasible. However, discontinuous feeding...

Determining Predictive Power of Base Excess in Comparison with SOFA Score for Predicting Mortality in ICU Patients.

Acid-base disturbances are frequently found in intensive care unit (ICU) patients. Base excess (BE) is commonly used to quantify the degree of metabolic impairment. We aimed to compare the predictive value of BE and Sequential Organ Failure Assessment (SOFA) score for mortality in ICU patients. This prospective and observational investigation was performed on 87 ICU patients who underwent mechanical ventilation. SOFA score and acid-base variables at 6 hours of ICU admission were analyzed and compared between survivors and non-survivors. Receiver-operating characteristic (ROC) curve was applied to analyze the predictive value of BE and SOFA for mortality. Mean age of patients was 63.91±5.03 years, and 60 (69%) were male. The non-survived patients had significantly higher SOFA (P = 0.001) and APACHE II scores (P = 0.001). The non-survived patients had a lower bicarbonate (P = 0.002), PO2 (P = 0.001), pH (P = 0.0021), and a higher PCO2 (P = 0.001) compared with survivors, and most patients who died (80%) had a low BE value (< -2) (P = 0.002). The estimated AUC of SOFA and BE was 0.83 (95% CI, 0.73 - 0.92) and 0.71 (95% CI, 0.57 - 0.85), respectively. BE is, to some extent capable of predicting mortality in ICU patients. However, the SOFA score is a more accurate and reliable parameter in comparison to BE for prediction.

PROGNOSTIC PERFORMANCE OF SERIAL DETERMINATION OF THE SOCIETY FOR CARDIOVASCULAR ANGIOGRAPHY AND INTERVENTIONS SHOCK CLASSIFICATION IN ADULTS WITH CRITICAL ILLNESS.

Purpose: The aim of the study is to evaluate whether serial assessment of shock severity can improve prognostication in intensive care unit (ICU) patients. Materials and Methods: This is a retrospective cohort of 21,461 ICU patient admissions from 2014 to 2018. We assigned the Society for Cardiovascular Angiography and Interventions (SCAI) Shock Stage in each 4-h block during the first 24 h of ICU admission; shock was defined as SCAI Shock stage C, D, or E. In-hospital mortality was evaluated using logistic regression. Results: The admission SCAI Shock stages were as follows: A, 39.0%; B, 27.0%; C, 28.9%; D, 2.6%; and E, 2.5%. The SCAI Shock stage subsequently increased in 30.6%, and late-onset shock developed in 30.4%. In-hospital mortality was higher in patients who had shock on admission (11.9%) or late-onset shock (7.3%) versus no shock (4.3%). Persistence of shock predicted higher mortality (adjusted OR = 1.09; 95% CI = 1.06-1.13, for each ICU block with shock). The mean SCAI Shock stage had higher discrimination for in-hospital mortality than the admission or maximum SCAI Shock stage. Dynamic modeling of the SCAI Shock classification improved discrimination for in-hospital mortality (C-statistic = 0.64-0.71). Conclusions: Serial application of the SCAI Shock classification provides improved mortality risk stratification compared with a single assessment on admission, facilitating dynamic prognostication.

810. Predictors of 30-Day Mortality Among Critically Ill Patients with Candidemia Identified by T2Candida Panel

Abstract Background Candidemia is associated with mortality rates exceeding 40%. However, prior studies indicate mortality may be reduced when antifungal therapy is initiated within 12 hours. The T2Candida Panel is a diagnostic assay that detects Candida species directly from a whole blood specimen within 3-5 hours (T2 Biosystems, Lexington, MA). The objective of this study is to identify predictors of 30-day mortality in patients with candidemia identified by T2Candida Panel. Methods This is a retrospective, multicenter study of critically ill patients with candidemia identified by T2Candida Panel from January 2016 - December 2022. Critically ill patients were defined as those who developed candidemia during an intensive care unit (ICU) stay or within 72 hours of ICU admission or discharge. T2Candida sites were chosen across the United States based on T2Candida utilization. Exclusion criteria were patients &amp;lt; 18 years of age, those with prophylactic indications for antifungal therapy, prisoners and pregnant patients. Multivariate logistic regression was conducted to identify factors associated with 30-day mortality measured from the T2Candida draw time. Results There were 171 ICU patients from seven institutions with candidemia identified by T2Candida panel. The mean (standard deviation [SD]) age was 59.7 (14.8) years and 52.1% were male. Mean (SD) APACHE II and Charlson Comorbidity Index scores were 20.6 (7.1) and 4.9 (2.8), respectively. Empiric antifungal therapy was administered to 36.8% of patients and the majority received infectious diseases (ID) consult (92.4%). Echinocandins were the most common agents used for empiric (72.7%) and definitive therapy (62.6%). Overall, 30-day mortality occurred in 36.0% and was not associated with antifungal de-escalation. Administration of empiric therapy (aOR 0.457, 95% CI 0.199-1.054) and ID consult (aOR 0.225, 95% CI 0.056-0.913) were associated with reduced odds of 30-day mortality. Conclusion Empiric antifungal administration and ID consult were independently associated with reduced odds of 30-day mortality in patients with candidemia identified by T2Candida Panel. Future studies are needed to evaluate the impact of the T2Candida panel on antifungal stewardship. Disclosures Ryan K. Shields, PharmD, MS, Allergan: Advisor/Consultant|Cidara: Advisor/Consultant|Entasis: Advisor/Consultant|GSK: Advisor/Consultant|Melinta: Advisor/Consultant|Melinta: Grant/Research Support|Menarini: Advisor/Consultant|Merck: Advisor/Consultant|Merck: Grant/Research Support|Pfizer: Advisor/Consultant|Roche: Grant/Research Support|Shionogi: Advisor/Consultant|Shionogi: Grant/Research Support|Utility: Advisor/Consultant|Venatorx: Advisor/Consultant|Venatorx: Grant/Research Support Michael J. Rybak, PharmD, PhD, MPH, Abbvie, Merck, Paratek, Shionogi, Entasis, La Jolla, T2 Biosystems: Advisor/Consultant

Abstract 12030: Predicting Atrial Fibrillation in Critically Ill Patients: A Machine Learning Approach

Introduction: Atrial fibrillation (AF) is the most prevalent arrhythmia in critically ill patients, with significant implications for morbidity and mortality. Early prediction of AF risk is crucial for proactive management. This study aims to develop and validate a machine learning-based risk prediction model for AF in intensive care unit (ICU) patients. Methods: Using the Medical Information Mart for Intensive Care (MIMIC-IV) database, we conducted a retrospective cohort study that included adult ICU patients and collected 47 clinical and laboratory variables. The primary outcome variable was the development of AF within the first 48 hours of ICU admission. Various machine learning models were evaluated for their performance in predicting AF, and the best-performing model was further optimized using hyperparameter tuning. A compact model, incorporating only 15 variables and two novel features, was also developed to facilitate potential clinical implementation. The first new feature, ‘ older septic ’ indicated patients aged 70 or older with sepsis, capturing the combined effect of age and sepsis as a risk factor for AF. The second new feature, ‘ cardiac risk score ’ was a composite score considering patient’s pre-existing cardiac risk factors. Model interpretability was assessed using Shapley Additive exPlanations (SHAP) analysis. Results: The cohort comprised 46,266 ICU patients, with 4.6% developing AF within 48 hours of admission. The CatBoost Classifier model demonstrated superior performance, achieving an area under the receiver operating characteristic curve (AUC) of 0.850 (95% CI: 0.811-0.889) on the test set. The compact model with new features yielded an AUC of 0.820 (95% CI: 0.782-0.858), which is a comparable performance using a fraction of the variables. SHAP analysis highlighted the importance of the newly created features as key predictors, indicating the significance of age, sepsis, and cardiac risk factors in AF development. Conclusions: This study underscores the potential of machine learning models in predicting AF development in ICU patients. The compact model, with a satisfactory AUC, can be a valuable tool for identifying high-risk patients, enabling timely interventions to mitigate the adverse outcomes associated with AF.

Study on critical illness and bone turnover

Purpose: Critical illness has been recognized to acutely influence bone metabolism and, consequently, bone mineral density. The main purpose of this study was to describe bone metabolism changes in adult survivors of critical illness in an attempt to correlate them with severity scores. Methods: An open, prospective, observational, monocentric study in patients admitted to the intensive care unit (ICU) was conducted, evaluating bone metabolism at baseline (within 72 hours of ICU admission), 6 months, and 12 months. Results: Fifty-nine patients admitted to the ICU (63% males), mean age 58 ± 16 years, were enrolled. Of these, 20 patients (34%) completed the one-year follow up. At baseline, bone resorption showed an increase, which was maintained at 6 months, and followed by normalization at 12 months. Patients showed, in the majority of cases, hypovitaminosis D with hyperparathyroidism at baseline with subsequent normalization. A trend towards a correlation was described between severity scores and serum 25(OH) vitamin D and bone turnover marker levels. Conclusions: These results help to confirm a positive association between critical illness requiring ICU admission and bone metabolism changes. This study lays the foundations for further studies evaluating bone health in ICU patients. KEY WORDS: Critical illness, osteoporosis, bone turnover, bone metabolism, treatment.

Shock Severity Classification and Mortality in Adults With Cardiac, Medical, Surgical, and Neurological Critical Illness

ObjectiveTo evaluate whether the Society for Cardiovascular Angiography and Interventions (SCAI) Shock Classification could perform risk stratification in a mixed cohort of intensive care unit (ICU) patients, similar to its validation in patients with acute cardiac disease. MethodsWe included 21,461 adult Mayo Clinic ICU patient admissions from December 1, 2014, to February 28, 2018, including cardiac ICU (16.7%), medical ICU (37.4%), neurosciences ICU (27.7%), and surgical ICU (18.2%). The SCAI Shock Classification (a 5-stage classification from no shock [A] to refractory shock [E]) was assigned in each 4-hour period during the first 24 hours of ICU admission. ResultsThe median age was 65 years, and 43.2% were female. In-hospital mortality occurred in 1611 (7.5%) patients, with a stepwise increase in in-hospital mortality in each higher maximum SCAI Shock stage overall: A, 4.0%; B, 4.6%; C, 7.0%; D, 13.9%; and E, 40.2%. The SCAI Shock Classification provided incremental mortality risk stratification in each ICU, with the best performance in the cardiac ICU and the worse performance in the neurosciences ICU. The SCAI Shock Classification was associated with higher adjusted in-hospital mortality (adjusted odds ratio, 1.32 per each stage; 95% CI, 1.24 to 1.41; P<.001); this association was not observed in the neurosciences ICU when considered separately. ConclusionThe SCAI Shock Classification provided incremental mortality risk stratification beyond established prognostic markers across the spectrum of medical and surgical critical illness, proving utility outside its original intent.

Relationships Between Personality Traits and Perceived Stress in Surrogate Decision-Makers of Intensive Care Unit Patients.

Personality traits, specifically neuroticism, are related to stress in surrogate decision-makers (SDMs) in outpatient settings. We hypothesized that intrinsic traits are related to SDM stress in the intensive care unit (ICU) to determine if personality considerations should be included in interventions to support SDMs. Eligible participants (adult SDMs of non-capacitated ICU patients) completed validated questionnaires including stress (Impact of Events Scale-Revised, IES-R) and personality (Big Five Inventory, BFI) within 72 hours of ICU admission and again at 3 months post-ICU discharge (in addition to a qualitative interview). Bivariate Pearson correlations explored the relationship between BFI and IES-R at each time point (95% CI) and t-tests explored the relationship between stress and COVID-19. Mixed-methods analysis integrated qualitative and quantitative data. Of 32 SDMs, 71.9% were female, 93.8% white, and 97.0% were family members. Neuroticism was not significantly correlated to IES-R at 72 hours (r = 0.09; p = 0.64), but r increased 3 months post-discharge (r = 0.32; p = 0.07). Other BFI traits did not show similar patterns. Total stress was greater in surrogates of COVID-19-positive patients (COVID-19-positive: 60.6; COVID-19-negative: 49.8; p = 0.025). Mixed-methods analysis demonstrated that participants with high neuroticism scores had poorer emotional regulation than those with low neuroticism scores. This study supports that personality, particularly neuroticism, influences the stress of SDMs in the ICU. Further study of personality traits may identify surrogates who are at higher risk of stress-related disorders, which can guide future interventions.

Analysis of Predictors and Outcomes of COVID-19 Patients Requiring ICU Admission from COVID-19 Registry, India.

Patients admitted to intensive care units (ICUs) with severe coronavirus disease (COVID-19) are associated with high mortality. The present retrospective, multicenter study describes the predictors and outcomes of COVID-19 patients requiring ICU admission from COVID-19 Registry of Indian Council of Medical Research (ICMR), India. Prospectively collected data from participating institutions were entered into the electronic National Clinical Registry of COVID-19. We enrolled patients aged >18 years with COVID-19 pneumonia requiring ICU admission between March 2020 and August 2021. Exclusion criteria were negative in RT-PCR report, death within 24 hours of ICU admission, or incomplete data. Their demographic and laboratory variables, ICU severity indices, treatment strategies, and outcomes were analyzed. A total of 5,865 patients were enrolled. Overall mortality was 43.2%. Non-survivors were older (58.2 ± 15.4 vs 53.6 ± 14.7 years; p = 0.001), had multiple comorbidities (33.2% vs 29.5%, p = 0.001), had higher median D-dimer (1.56 vs 1.37, p = 0.015), higher CT severity index (16.8 ± 5.2 vs 13.5 ± 5.47, p = 0.001) and longer median hospital stay (10 vs 8 days, p = 0.001) and ICU stay (5 vs 4 days, p = 0.001), compared with survivors.On multivariate analysis, high CRP (HR 1.008, 95% CI: 1.006-1.010, p = 0.001) and high D-dimer (HR 1.089, 95% CI: 1.065-1.113, p < 0.001) were associated with invasive mechanical ventilation while older age (HR 1.19, CI: 1.001-1.038, p = 0.039) and high D-dimer (HR-1.121, CI: 1.072-1.172, p = 0.001) were independently associated with mortality and while the use of prophylactic low molecular weight heparin (LMWH) (HR 0.647, CI: 0.527-0.794, p = 0.001) lowered mortality. Among 5,865 COVID-19 patients admitted to ICU, mortality was 43.5%. High CRP and D-dimers were independently associated with the need for invasive mechanical ventilation while older age and high D-dimer were associated with higher mortality. The use of prophylactic LMWH independently reduced mortality. Kajal K, Singla K, Puri GD, Bhalla A, Mukherjee A, Kumar G, et al. Analysis of Predictors and Outcomes of COVID-19 Patients Requiring ICU Admission from COVID-19 Registry, India. Indian J Crit Care Med 2023;27(8):552-562.

Continuous and early prediction of future moderate and severe Acute Kidney Injury in critically ill patients: Development and multi-centric, multi-national external validation of a machine-learning model.

Acute Kidney Injury (AKI) is a major complication in patients admitted to Intensive Care Units (ICU), causing both clinical and economic burden on the healthcare system. This study develops a novel machine-learning (ML) model to predict, with several hours in advance, the AKI episodes of stage 2 and 3 (according to KDIGO definition) acquired in ICU. A total of 16'760 ICU adult patients from 145 different ICU centers and 3 different countries (US, Netherland, Italy) are retrospectively enrolled for the study. Every hour the model continuously analyzes the routinely-collected clinical data to generate a new probability of developing AKI stage 2 and 3, according to KDIGO definition, during the ICU stay. The predictive model obtains an auROC of 0.884 for AKI (stage 2/3 KDIGO) prediction, when evaluated on the internal test set composed by 1'749 ICU stays from US and EU centers. When externally tested on a multi-centric US dataset of 6'985 ICU stays and multi-centric Italian dataset of 1'025 ICU stays, the model achieves an auROC of 0.877 and of 0.911, respectively. In all datasets, the time between model prediction and AKI (stage 2/3 KDIGO) onset is at least of 14 hours after the first day of ICU hospitalization. In this study, a novel ML model for continuous and early AKI (stage 2/3 KDIGO) prediction is successfully developed, leveraging only routinely-available data. It continuously predicts AKI episodes during ICU stay, at least 14 hours in advance when the AKI episode happens after the first 24 hours of ICU admission. Its performances are validated in an extensive, multi-national and multi-centric cohort of ICU adult patients. This ML model overcomes the main limitations of currently available predictive models. The benefits of its real-world implementation enable an early proactive clinical management and the prevention of AKI episodes in ICU patients. Furthermore, the software could be directly integrated with IT system of the ICU.

Association between furosemide administration and clinical outcomes in patients with sepsis-associated acute kidney injury receiving renal replacement therapy: a retrospective observational cohort study based on MIMIC-IV database

ObjectiveTo investigate the association between furosemide administration and clinical outcomes in patients with sepsis-associated acute kidney injury (SAKI) receiving renal replacement therapy (RRT).DesignA retrospective observational cohort study.SettingThe data were collected...

The effect of oseltamivir use in critically ill patients with COVID-19: A multicenter propensity score-matched study

BackgroundOseltamivir has been used as adjunctive therapy in the management of patients with COVID-19. However, the evidence about using oseltamivir in critically ill patients with severe COVID-19 remains scarce. This study aims to evaluate the effectiveness and safety of oseltamivir in critically ill patients with COVID-19. MethodsThis multicenter, retrospective cohort study includes critically ill adult patients with COVID-19 admitted to the intensive care unit (ICU). Patients were categorized into two groups based on oseltamivir use within 48 hours of ICU admission (Oseltamivir vs. Control). The primary endpoint was viral load clearance. ResultsA total of 226 patients were matched into two groups based on their propensity score. The time to COVID-19 viral load clearance was shorter in patients who received oseltamivir (11 vs. 16 days, p = 0.042; beta coefficient: −0.84, 95%CI: (−1.33, 0.34), p = 0.0009). Mechanical ventilation (MV) duration was also shorter in patients who received oseltamivir (6.5 vs. 8.5 days, p = 0.02; beta coefficient: −0.27, 95% CI: [−0.55,0.02], P = 0.06). In addition, patients who received oseltamivir had lower odds of hospital/ventilator-acquired pneumonia (OR:0.49, 95% CI:(0.283,0.861), p = 0.01). On the other hand, there were no significant differences between the groups in the 30-day and in-hospital mortality. ConclusionOseltamivir was associated with faster viral clearance and shorter MV duration without safety concerns in critically ill COVID-19 patients.

Posttraumatic Stress Symptom Trajectories in Family Caregivers of Patients With Acute Cardiorespiratory Failure

Overall, 1 in 3 family caregivers of patients who require intensive care unit (ICU) admission will experience significant posttraumatic stress symptoms (PTSSs), but little is known about how PTSSs evolve over time. Measuring PTSS trajectories could facilitate the development of targeted interventions to improve mental health outcomes for family caregivers of critically ill patients. To measure 6-month PTSS trajectories among caregivers of patients with acute cardiorespiratory failure. This prospective cohort study was conducted in the medical ICU of a large academic medical center among adult patients requiring (1) vasopressors for shock, (2) high-flow nasal cannula, (3) noninvasive positive pressure ventilation, or (4) invasive mechanical ventilation. Each patient was enrolled along with their primary caregiver, ie, the unpaid individual who provided the most physical, emotional, or financial support prior to ICU admission. Family caregiver PTSSs were assessed using the Impact of Events Scale-Revised within 48 hours of ICU admission, following ICU discharge, and 3 and 6 months after enrollment. Latent class growth analysis was used to measure PTSS trajectories. Preselected patient and caregiver characteristics measured at ICU admission were analyzed for association with trajectory membership. Six-month patient and caregiver outcomes were analyzed by caregiver trajectory. Overall, 95 family caregivers were enrolled and provided baseline data; mean (SD) age was 54.2 (13.6) years, 72 (76%) were women, 22 (23%) were Black individuals, and 70 (74%) were White individuals. Three trajectories were identified: persistently low (51 caregivers [54%]), resolving (29 [31%]), and chronic (15 [16%]). Low caregiver resilience, prior caregiver trauma, high patient severity of illness, and good patient premorbid functional status were associated with the chronic trajectory. Caregivers with the chronic PTSS trajectory had worse 6-month health-related quality of life (mean [SD] total 36-item Short Form Survey score, persistently low trajectory: 104.7 [11.3]; resolving trajectory: 101.7 [10.4]; chronic trajectory: 84.0 [14.4]; P < .001) and reduced effectiveness at work (mean [SD] perceived effectiveness at work score, persistently low trajectory: 86.0 [24.2]; resolving trajectory: 59.1 [32.7]; chronic trajectory: 72.3 [18.4]; P = .009). In this study, 3 distinct PTSS trajectories among ICU family caregivers were observed, with 16% of caregivers experiencing chronic PTSSs over the subsequent 6 months. Family caregivers with persistent PTSS had lower resilience, prior trauma, higher patient severity of illness, and higher baseline patient functional status compared with family caregivers with persistently low PTSS, with adverse effects on quality of life and work. Identifying these caregivers is an essential first step to develop interventions tailored to those with the greatest need for support.

Rectus abdominis and rectus femoris muscle thickness in determining nutritional risk in critically ill patients: a prospective cohort study in Turkey

ObjectivesMalnutrition is a clinical condition that is frequently seen in critically ill patients in the intensive care unit (ICU). Although there are many scoring systems and tools used to determine...

Early sodium bicarbonate therapy for critically ill patients with septic shock and acute moderate metabolic acidosis

To the editor: In recent decades, septic shock has continued to be a life-threatening health problem around the world.[1] Meanwhile, metabolic acidosis (MA) is also well known in critically ill patients, and even moderate metabolic acidosis (MMA) is associated with higher mortality than sepsis.[2] Although the administration of sodium bicarbonate (SB) is widely used in sepsis shock with MA in the intensive care unit (ICU), its clinical efficacy is not well established. In the 2021 update of the Surviving Sepsis Campaign guidelines, Evans et al. recommend the administration of SB in adults with septic shock, severe metabolic acidemia (pH ≤7.2), and acute kidney injury (AKI, AKIN score 2 or 3).[3,4] However, clinical evidence for the efficacy of the administration of SB in critically ill patients with septic shock and acute MMA is still limited. We retrospectively investigated a large ICU database (MIMIC-IV, https://www.physionet.org/) from 2008 to 2019 in 6 ICUs at a single-center hospital (Beth Israel Deaconess Medical Centre; Boston, MA). All adults with septic shock and acute MMA (7.2 < pH < 7.3, bicarbonate concentration <20 mmol/L, and PaCO2 <50 mmHg) within the first 48 hours after ICU admission were included in this study. Propensity score analysis[5] (PSA) was performed to account for differences in the probability of receiving or not receiving SB. For the PSA, we matched patients 1 to 1. The marginal structural Cox model[5] (MSCM) was developed to adjust for both baseline and time-varying confounding variables. The primary outcome was ICU and in-hospital mortality. Variables, including sex, age, body mass index, comorbidities on ICU admission, mechanical ventilation, vasopressors, and renal replacement therapy, were extracted from the MIMIC-IV database for the first 24 hours of ICU admission. Serum creatinine within the first 48 hours of an ICU stay was used to identify AKI stages. Administration of lactate solution for the first 24 hours was also included in the study. To account for the possible influence of clinical practice in previous years, the year of admission was used as a random factor in a mixed-effects model. Laboratory variables (PaO2, PaCO2, pH, and bicarbonate concentration) were recorded throughout the ICU period. For patients who underwent multiple tests, the highest values of lactate and PaCO2 and the lowest values of PaO2, bicarbonate concentration, and pH on each day were used for analysis. The above variables included in the PSA and MSCM are listed in Supplemental Table 1 (https://links.lww.com/ECCM/A58). A total of 577 patients with septic shock and MMA were identified, of whom 194 were included in the SB and 383 in the non-SB groups (Supplemental Table 2, https://links.lww.com/ECCM/A58). In the PSA group, early SB infusion was associated with both lower ICU mortality (hazards ratio [HR]: 0.61; 95% confidence interval [CI]: 0.40–0.93; P < 0.05) and lower in-hospital mortality (HR: 0.69; 95% CI: 0.50–0.97; P < 0.05; Fig. 1). In MSCM, our study also found a statistically significant positive effect of early SB infusion on ICU mortality (HR: 0.31; 95% CI: 0.13–0.72; P < 0.01) and hospital mortality (HR: 0.55; 95% CI: 0.31–0.97; P < 0.05) in patients with septic shock and MMA (Supplementary Figure 1, https://links.lww.com/ECCM/A59).Figure 1: Forest plot showing the effect of early sodium bicarbonate infusion on ICU and hospital mortality in the PSA for critically ill patients with septic shock and acute moderate metabolic acidosis. The hazard ratios were estimated using the PSA. After propensity score matching, 194 patients from the non-SB group were matched to SB group (n = 194) to balance the baseline differences in the probability to receive SB or not. The x-axis tick marks follow a logarithmic scale. ICU, intensive care unit; PSA, propensity score analysis; SB, sodium bicarbonate.Our observational study suggests that early infusion of SB in critically ill adult patients with septic shock and MMA within the first 48 hours after ICU admission has a significant beneficial effect on both ICU and hospital mortality. Further large, randomized, controlled clinical trials are needed to provide high-quality evidence to improve the Surviving Sepsis Campaign guidelines.

Evaluation of Early Tocilizumab Effect on Multiorgan Dysfunction in Critically Ill Patients With COVID-19: A Propensity Score-Matched Study.

Background: Tocilizumab (TCZ) has been proposed as potential rescue therapy for severe COVID-19. No previous study has primarily assessed the role of TCZ in preventing severe COVID-19-related multiorgan dysfunction. Hence, this multicenter cohort study aimed to evaluate the effectiveness of TCZ early use versus standard of care in preventing severe COVID-19-related multiorgan dysfunction in COVID-19 critically ill patients during intensive care unit (ICU) stay. Methods: A multicenter, retrospective cohort study includes critically ill adult patients with COVID-19 admitted to the ICUs. Patients were categorized into two groups, the treatment group includes patients who received early TCZ therapy within 24 hours of ICU admission and the control group includes patients who received standard of care. The primary outcome was the multiorgan dysfunction on day three of the ICU admission. The secondary outcomes were 30-day, and in-hospital mortality, ventilator-free days, hospital length of stay (LOS), ICU LOS, and ICU-related complications. Results: After propensity score matching, 300 patients were included in the analysis based on predefined criteria with a ratio of 1:2. Patients who received TCZ had lower multiorgan dysfunction score on day three of ICU admission compared to the control group (beta coefficient: -0.13, 95% CI: -0.26, -0.01, P-value = 0.04). Moreover, respiratory failure requiring MV was statistically significantly lower in patients who received early TCZ compared to the control group (OR 0.52; 95% CI 0.31, 0.91, P-value = 0.02). The 30-day and in-hospital mortality were significantly lower in patients who received TCZ than those who did not (HR 0.56; 95% CI 0.37, 0.85, P-value = 0 .006 and HR 0.54; 95% CI 0.36, 0.82, P-value = 0.003, respectively). Conclusion: In addition to the mortality benefits associated with early TCZ use within 24 hours of ICU admission, the use of TCZ was associated with a significantly lower multiorgan dysfunction score on day three of ICU admission in critically ill patients with COVID-19.

Nomogram Prediction Model of Hypernatremia on Mortality in Critically Ill Patients

To investigate the value of hypernatremia in the intensive care unit (ICU) for the risk prediction of mortality in severe patients. Clinical data of critically ill patients admitted to the ICU of Beijing Friendship Hospital, were collected for retrospective analysis. Univariate and multivariate logistic regression analyses were employed to analyze the influencing factors. Nomograms predicting the mortality were constructed with R software and validated with repeated sampling. A total of 442 cases were eligible for this study. Hypernatremia within 48 hours of ICU admission, change in sodium concentration (CNa+) within 48 hours, septic shock, APACHE II score, hyperlactatemia within 48 hours, use of continuous renal replacement therapy (CRRT) within 48 hours, and the use of mechanical ventilation (MV) within 48 hours of ICU admission were all identified as independent risk factors for death within 28 days of ICU admission. These predictors were included in a nomogram of 28-day mortality in severe patients, which was constructed using R software. The nomogram could predict the individualized risk of 28-day mortality based on the above factors. The model has better discrimination and accuracy and has high clinical application value.

Factors associated with mortality in acute respiratory failure patients without acute respiratory distress syndrome.

Excess tidal volume and driving pressure were associated with increased mortality in patients with acute respiratory distress syndrome (ARDS). Still, the appropriate mechanical ventilation strategy for patients who do not have ARDS needs to be understood. This study aimed to identify risk factors for mortality in acute respiratory failure patients without ARDS. We included all mechanically ventilated patients who did not meet the criteria for ARDS and were admitted to the medical intensive care unit (ICU) from October 2017 to September 2018. Patients who had tracheostomy before admission, were intubated for more than 24 hours before transfer to ICU, or underwent extracorporeal membrane oxygenation within 24 hours of ICU admission were excluded. Clinical and physiologic data were recorded and compared between survived and non-survived patients. Of 289 patients with acute respiratory failure, 134 patients without ARDS were included; 69 (51%) died within 28 days. Demographics, principal diagnosis, and lung injury score on the first day of admission were not significantly different between survived and non-survived patients. In multivariate analysis, higher peak inspiratory pressure (PIP) during the first 3 days of admission [odds ratio (OR) 1.11, 95% confidence interval (CI): 1.01-1.22, P=0.04], higher sequential organ failure assessment score (OR 1.15, 95% CI: 1.04-1.28, P=0.008) and underlying cerebrovascular diseases (OR 7.09, 95% CI: 1.78-28.28, P=0.006) were independently associated with mortality in these patients, whereas dynamic lung compliance (Cdyn) and respiratory rate were not associated with mortality in the multivariate model. Mortality was high in mechanically ventilated patients without ARDS. Higher PIP is a potentially modifiable risk factor for mortality in these patients, independent of the baseline Cdyn. Underlying cerebrovascular diseases and increased disease severity are also independent factors associated with 28-day mortality.

How Necessary Is Empirical Antibiotic Therapy in COVID-19 Patients before ICU infections develop? An Observational Study

Introduction: There have been few studies reporting empirical antibiotic use in Covid-19 patients, particularly in those admitted to the intensive care unit (ICU). This study evaluated empirical antibiotic use in patients admitted to the ICU with Covid-19&#x0D; Methods: This two-center retrospective study included 79 consecutive patients who were admitted to the ICU due to Covid-19 infection between October 1 and December 31, 2020, and received empirical antibiotics. The patients were classified into two groups: those who developed ICU infections after 48 hours of ICU admission despite empirical antibiotic therapy (Group 1), and those who received empirical antibiotic therapy during the ICU stay, but were free of ICU infections (Group 2).&#x0D; Results: In Group 1, 37 patients (46.8%) developed ICU infections after a median of 12 days (IQR 5.5-15.5) of ICU stay. The cumulative antibiotic use until the detection ICU infections was 395 antibiotic days corresponding to 1070 DOTs/1000 hospital days. The median antibiotic use was 9 days (IQR 4-15.5). In Group 2, 42 patients (53.2%) received empirical antibiotic therapy for a median of 5 ICU days (IQR 3-8.3) and for a total of 256 antibiotic days (1051 DOTs/1000 hospital days). Twenty–three patients received empirical antibiotic therapy during the entire ICU stay. The median ICU stay was 6.5 days (IQR 4-10) and the median antibiotic use was 5 days (IQR 3-8.2).&#x0D; Discussion and Conclusion: Our findings are alarming and raise doubt about the potential role of antibiotics in the initial therapy of Covid-19 patients at the time of ICU admission and suggest the need to narrow or tailor antibiotic use based on clear laboratory and radiologic indications.

How Necessary Is Empirical Antibiotic Therapy in COVID-19 Patients before ICU infections develop? An Observational Study

Introduction: There have been few studies reporting empirical antibiotic use in Covid-19 patients, particularly in those admitted to the intensive care unit (ICU). This study evaluated empirical antibiotic use in patients admitted to the ICU with Covid-19 Methods: This two-center retrospective study included 79 consecutive patients who were admitted to the ICU due to Covid-19 infection between October 1 and December 31, 2020, and received empirical antibiotics. The patients were classified into two groups: those who developed ICU infections after 48 hours of ICU admission despite empirical antibiotic therapy (Group 1), and those who received empirical antibiotic therapy during the ICU stay, but were free of ICU infections (Group 2). Results: In Group 1, 37 patients (46.8%) developed ICU infections after a median of 12 days (IQR 5.5-15.5) of ICU stay. The cumulative antibiotic use until the detection ICU infections was 395 antibiotic days corresponding to 1070 DOTs/1000 hospital days. The median antibiotic use was 9 days (IQR 4-15.5). In Group 2, 42 patients (53.2%) received empirical antibiotic therapy for a median of 5 ICU days (IQR 3-8.3) and for a total of 256 antibiotic days (1051 DOTs/1000 hospital days). Twenty–three patients received empirical antibiotic therapy during the entire ICU stay. The median ICU stay was 6.5 days (IQR 4-10) and the median antibiotic use was 5 days (IQR 3-8.2). Discussion and Conclusion: Our findings are alarming and raise doubt about the potential role of antibiotics in the initial therapy of Covid-19 patients at the time of ICU admission and suggest the need to narrow or tailor antibiotic use based on clear laboratory and radiologic indications.