Association of Sarcopenia, as Defined Based on the Skeletal Muscle Index, With Mortality and Morbidity After Cardiac Surgery: A Retrospective Cohort Study.

OBJECTIVE: To investigate whether "sarcopenia," defined based on the preoperative skeletal muscle index (SMI), can predict major postoperative morbidity and all-cause mortality. DESIGN: A retrospective observational cohort study. SETTING: At the authors' Department of Critical Care Medicine. PARTICIPANTS: A total of 986 adult Chinese patients underwent cardiac surgery (coronary artery bypass graft, valve surgery, combined surgery, or aortic surgery) between January 2019 and August 2022. MEASUREMENTS AND MAIN RESULTS: The skeletal muscle area at the third lumbar level (L3) was measured via preoperative computed tomography (up to 3 months from the date of imaging to the date of surgery) and normalized to patient height (skeletal muscle index). Sarcopenia was determined based on the skeletal muscle index being in the lowest sex-specific quartile. The primary outcome was all-cause mortality. The secondary outcome was major morbidity. A total of 968 patients were followed for a median of 2.00 years, ranging from 1.06 to 2.90 years. After the follow-up, 76 patients died during the follow-up period. Multivariate Cox proportional analysis showed a relationship between sarcopenia (adjusted hazard ratio 1.80, 95% CI 1.04-3.11; p = 0.034) and all-cause mortality. Kaplan-Meier curves revealed a significantly lower survival rate in the sarcopenia group than in the nonsarcopenia group. Overall, 199 (20.6%) patients had major morbidity. Multivariate analysis showed a significant relationship between sarcopenia (adjusted odds ratio = 2.21, 95% CI 1.52∼3.22, p < 0.001) and major morbidity. CONCLUSIONS: Sarcopenia, defined by the skeletal muscle index, is associated with all-cause mortality and major morbidity after cardiac surgery, thereby suggesting the need for perioperative sarcopenia risk assessment for patients undergoing cardiac surgery to guide the prevention and management of adverse outcomes.

Lung morphology impacts the association between ventilatory variables and mortality in patients with acute respiratory distress syndrome.

BACKGROUND: Acute respiratory distress syndrome (ARDS) patients with different lung morphology have distinct pulmonary mechanical dysfunction and outcomes. Whether lung morphology impacts the association between ventilatory variables and mortality remains unclear. Moreover, the impact of a novel combined ventilator variable [(4×DP) + RR] on morality in ARDS patients needs external validation. METHODS: We obtained data from the Chinese Database in Intensive Care (CDIC), which included adult ARDS patients who received invasive mechanical ventilation for at least 24 h. Patients were further classified into two groups based on lung morphology (focal and non-focal). Ventilatory variables were collected longitudinally within the first four days of ventilation. The primary outcome was 28-day mortality. Extended Cox regression models were employed to explore the interaction between lung morphology and longitudinal ventilatory variables on mortality. FINDINGS: We included 396 ARDS patients with different lung morphology (64.1% non-focal). The overall 28-day mortality was 34.4%. Patients with non-focal lung morphology have more severe and persistent pulmonary mechanical dysfunction and higher mortality than those with focal lung morphology. Time-varying driving pressure (DP) was more significantly associated with 28-day mortality in patients with non-focal lung morphology compared to focal lung morphology patients (P for interaction = 0.0039). The impact of DP on mortality was more significant than that of respiratory rate (RR) only in patients with non-focal lung morphology. The hazard ratio (HR) of mortality for [(4×DP) + RR] was significant in patients with non-focal lung morphology (HR 1.036, 95% CI 1.027-1.045), not in patients with focal lung morphology (HR 1.019, 95% CI 0.999-1.039). INTERPRETATION: The association between ventilator variables and mortality varied among patients with different lung morphology. [(4×DP) + RR] was only associated with mortality in patients with non-focal lung morphology. Further validation is needed.

Effects of early versus delayed application of prone position on ventilation-perfusion mismatch in patients with acute respiratory distress syndrome: a prospective observational study.

BACKGROUND: Prone position has been shown to improve oxygenation and survival in patients with early acute respiratory distress syndrome (ARDS). These beneficial effects are partly mediated by improved ventilation/perfusion (V/Q) distribution. Few studies have investigated the impact of early versus delayed proning on V/Q distribution in patients with ARDS. The aim of this study was to assess the regional ventilation and perfusion distribution in early versus persistent ARDS after prone position. METHODS: This is a prospective, observational study from June 30, 2021, to October 1, 2022 at the medical ICU in Zhongda Hospital, Southeast University. Fifty-seven consecutive adult patients with moderate-to-severe ARDS ventilated in supine and prone position. Electrical impedance tomography was used to study V/Q distribution in the supine position and 12 h after a prone session. RESULTS: Of the 57 patients, 33 were early ARDS (≤ 7 days) and 24 were persistent ARDS (> 7 days). Oxygenation significantly improved after proning in early ARDS (157 [121, 191] vs. 190 [164, 245] mm Hg, p < 0.001), whereas no significant change was found in persistent ARDS patients (168 [136, 232] vs.177 [155, 232] mm Hg, p = 0.10). Compared to supine position, prone reduced V/Q mismatch in early ARDS (28.7 [24.6, 35.4] vs. 22.8 [20.0, 26.8] %, p < 0.001), but increased V/Q mismatch in persistent ARDS (23.8 [19.8, 28.6] vs. 30.3 [24.5, 33.3] %, p = 0.006). In early ARDS, proning significantly reduced shunt in the dorsal region and dead space in the ventral region. In persistent ARDS, proning increased global shunt. A significant correlation was found between duration of ARDS onset to proning and the change in V/Q distribution (r = 0.54, p < 0.001). CONCLUSIONS: Prone position significantly reduced V/Q mismatch in patients with early ARDS, while it increased V/Q mismatch in persistent ARDS patients. Trial registration ClinicalTrials.gov (NCT05207267, principal investigator Ling Liu, date of registration 2021.08.20).

Combined Serum NGAL and Fetuin A to Predict 28-Day Mortality in Patients with Sepsis and Risk Prediction Model Construction.

It was to investigate the predictive value of NGAL and Fetuin-A for 28-day mortality in patients with sepsis, and to construct a mortality risk prediction model. 120 patients admitted to The Affiliated Hospital of Xuzhou Medical University Hospital were grouped. Serum biochemical parameters were measured and scale scores were performed. The patient data were divided into a training set and test set in a ratio of 7:3, and the logistic regression model and random forest model were included to evaluate the 28-day mortality prediction efficacy of each index and model. The results showed that WBC, PLT, RBCV, and PLR decreased, SCr, Lac, PCT, D-dimer, NPR, NGAL, and Fetuin-A increased, APACHE II scale, SOFA scale, and OASIS scale scores increased in the death group (P < 0.05). SCr ≥ 408 µmol/L, Lac ≥ 2.3 mmol/L, PCT ≥ 30 ng/mL, D-dimer ≥ 2.33 mg/L, PLR ≥ 190, APACHE II ≥ 18 points, SOFA ≥ 2, OASIS ≥ 30, NGAL ≥ 352 mg/L, and Fetuin-A ≥ 0.32 g/L were found to be risk factors for 28-day death, while WBC ≥ 12 × 109/L, PLT ≥ 172 × 103/µL, and RBCV ≥ 30% were found to be protective factors for 28-day mortality. The predicted AUCs of APACHE II, SOFA, OASIS, NGAL, Fetuin-A, NGAL & Fetuin-A, logistic regression model, and random forest model were 0.80, 0.71, 0.77, 0.69, 0.86, 0.92, 0.83, and 0.81. NGAL combined with Fetuin-A has good prediction efficacy in 28-day mortality in septic patients.

Predictive Value of Arterial Blood Lactic Acid Concentration on the Risk of in-Hospital All-Cause Death in Patients with Acute Heart Failure.

The study aims to examine the predictive value of arterial blood lactic acid concentration for in-hospital all-cause mortality in the intensive care unit (ICU) for patients with acute heart failure (AHF). We retrospectively analyzed the clinical data of 7558 AHF patients in the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The exposure variable of the present study was arterial blood lactic acid concentration and the outcome variable was in-hospital all-cause death. The patients were divided into those who survived (n = 6792) and those who died (n = 766). The multivariate logistic regression model, restricted cubic spline (RCS) plot, and subgroup analysis were used to evaluate the association between lactic acid and in-hospital all-cause mortality. In addition, receiver operating curve (ROC) analysis also was performed. Finally, we further explore the association between NT-proBNP and lactic acid and in-hospital all-cause mortality. Compared with the lowest quartiles, the odds ratios with 95% confidence intervals for in-hospital all-cause mortality across the quartiles were 1.46 (1.07-2.00), 1.48 (1.09-2.00), and 2.36 (1.73-3.22) for lactic acid, and in-hospital all-cause mortality was gradually increased with lactic acid levels increasing (P for trend <0.05). The RCS plot revealed a positive and linear connection between lactic acid and in-hospital all-cause mortality. A combination of lactic acid concentration and the Simplified Acute Physiology Score (SAPS) II may improve the predictive value of in-hospital all-cause mortality in patients with AHF (AUC = 0.696). Among subgroups, respiratory failure interacted with an association between lactic acid and in-hospital all-cause mortality (P for interaction <0.05). The correlation heatmap revealed that NT-proBNP was positively correlated with lactic acid (r = 0.07) and positively correlated with in-hospital all-cause mortality (r = 0.18). There was an inverse L-shaped curve relationship between NT-proBNP and in-hospital all-cause mortality, respectively. Mediation analysis suggested that a positive relationship between lactic acid and in-hospital all-cause death was mediated by NT-proBNP. For AHF patients in the ICU, the arterial blood lactic acid concentration during hospitalization was a significant independent predictor of in-hospital all-cause mortality. The combination of lactic acid and SAPS II can improve the predictive value of the risk of in-hospital all-cause mortality in patients with AHF.

Neurally adjusted ventilatory assist as a weaning mode for adults with invasive mechanical ventilation: a systematic review and meta-analysis.

BACKGROUND: Prolonged ventilatory support is associated with poor clinical outcomes. Partial support modes, especially pressure support ventilation, are frequently used in clinical practice but are associated with patient-ventilation asynchrony and deliver fixed levels of assist. Neurally adjusted ventilatory assist (NAVA), a mode of partial ventilatory assist that reduces patient-ventilator asynchrony, may be an alternative for weaning. However, the effects of NAVA on weaning outcomes in clinical practice are unclear. METHODS: We searched PubMed, Embase, Medline, and Cochrane Library from 2007 to December 2020. Randomized controlled trials and crossover trials that compared NAVA and other modes were identified in this study. The primary outcome was weaning success which was defined as the absence of ventilatory support for more than 48 h. Summary estimates of effect using odds ratio (OR) for dichotomous outcomes and mean difference (MD) for continuous outcomes with accompanying 95% confidence interval (CI) were expressed. RESULTS: Seven studies (n = 693 patients) were included. Regarding the primary outcome, patients weaned with NAVA had a higher success rate compared with other partial support modes (OR = 1.93; 95% CI 1.12 to 3.32; P = 0.02). For the secondary outcomes, NAVA may reduce duration of mechanical ventilation (MD = - 2.63; 95% CI - 4.22 to - 1.03; P = 0.001) and hospital mortality (OR = 0.58; 95% CI 0.40 to 0.84; P = 0.004) and prolongs ventilator-free days (MD = 3.48; 95% CI 0.97 to 6.00; P = 0.007) when compared with other modes. CONCLUSIONS: Our study suggests that the NAVA mode may improve the rate of weaning success compared with other partial support modes for difficult to wean patients.

Machine learning prediction of the failure of high-flow nasal oxygen therapy in patients with acute respiratory failure.

Acute respiratory failure (ARF) is a prevalent and serious condition in intensive care unit (ICU), often associated with high mortality rates. High-flow nasal oxygen (HFNO) therapy has gained popularity for treating ARF in recent years. However, there is a limited understanding of the factors that predict HFNO failure in ARF patients. This study aimed to explore early indicators of HFNO failure in ARF patients, utilizing machine learning (ML) algorithms to more accurately pinpoint individuals at elevated risk of HFNO failure. Utilizing ML algorithms, we developed seven predictive models. Their performance was evaluated using various metrics, including the area under the receiver operating characteristic curve, calibration curve, and precision recall curve. The study enrolled 700 patients, with 490 in the training group and 210 in the validation group. The overall HFNO failure rate was 14.1% among the 700 patients. The ML algorithms demonstrated robust performance in our study. This research underscores the potential of ML techniques in creating clinically relevant models for predicting HFNO outcomes in ARF patients. These models could play a pivotal role in enhancing the risk management of HFNO, leading to more patient-centered and personalized care approaches.

DEVELOPMENT OF A MACHINE LEARNING MODEL FOR PREDICTING 28-DAY MORTALITY OF SEPTIC PATIENTS WITH ATRIAL FIBRILLATION.

ABSTRACT: Introduction: Septic patients with atrial fibrillation (AF) are common in the intensive care unit accompanied by high mortality. The early prediction of prognosis of these patients is critical for clinical intervention. This study aimed to develop a model by using machine learning (ML) algorithms to predict the risk of 28-day mortality in septic patients with AF. Methods: In this retrospective cohort study, we extracted septic patients with AF from the Medical Information Mart for Intensive Care III (MIMIC-III) and IV database. Afterward, only MIMIC-IV cohort was randomly divided into training or internal validation set. External validation set was mainly extracted from MIMIC-III database. Propensity score matching was used to reduce the imbalance between the external validation and internal validation data sets. The predictive factors for 28-day mortality were determined by using multivariate logistic regression. Then, we constructed models by using ML algorithms. Multiple metrics were used for evaluation of performance of the models, including the area under the receiver operating characteristic curve, sensitivity, specificity, recall, and accuracy. Results: A total of 5,317 septic patients with AF were enrolled, with 3,845 in the training set, 960 in the internal testing set, and 512 in the external testing set, respectively. Then, we established four prediction models by using ML algorithms. AdaBoost showed moderate performance and had a higher accuracy than the other three models. Compared with other severity scores, the AdaBoost obtained more net benefit. Conclusion: We established the first ML model for predicting the 28-day mortality of septic patients with AF. Compared with conventional scoring systems, the AdaBoost model performed moderately. The model established will have the potential to improve the level of clinical practice.

Effect of EIT-guided PEEP titration on prognosis of patients with moderate to severe ARDS: study protocol for a multicenter randomized controlled trial.

BACKGROUND: Acute respiratory syndrome distress (ARDS) is a clinical common syndrome with high mortality. Electrical impedance tomography (EIT)-guided positive end-expiratory pressure (PEEP) titration can achieve the compromise between lung overdistension and collapse which may minimize ventilator-induced lung injury in these patients. However, the effect of EIT-guided PEEP titration on the clinical outcomes remains unknown. The objective of this trial is to investigate the effects of EIT-guided PEEP titration on the clinical outcomes for moderate or severe ARDS, compared to the low fraction of inspired oxygen (FiO2)-PEEP table. METHODS: This is a prospective, multicenter, single-blind, parallel-group, adaptive designed, randomized controlled trial (RCT) with intention-to-treat analysis. Adult patients with moderate to severe ARDS less than 72 h after diagnosis will be included in this study. Participants in the intervention group will receive PEEP titrated by EIT with a stepwise decrease PEEP trial, whereas participants in the control group will select PEEP based on the low FiO2-PEEP table. Other ventilator parameters will be set according to the ARDSNet strategy. Participants will be followed up until 28 days after enrollment. Three hundred seventy-six participants will be recruited based on a 15% decrease of 28-day mortality in the intervention group, with an interim analysis for sample size re-estimation and futility assessment being undertaken once 188 participants have been recruited. The primary outcome is 28-day mortality. The secondary outcomes include ventilator-free days and shock-free days at day 28, length of ICU and hospital stay, the rate of successful weaning, proportion requiring rescue therapies, compilations, respiratory variables, and Sequential Organ Failure Assessment (SOFA). DISCUSSION: As a heterogeneous syndrome, ARDS has different responses to treatment and further results in different clinical outcomes. PEEP selection will depend on the properties of patients and can be individually achieved by EIT. This study will be the largest randomized trial to investigate thoroughly the effect of individual PEEP titrated by EIT in moderate to severe ARDS patients to date. TRIAL REGISTRATION: ClinicalTrial.gov NCT05207202. First published on January 26, 2022.

Impact of Time-Varying Intensity of Mechanical Ventilation on 28-Day Mortality Depends on Fluid Balance in Patients With Acute Respiratory Distress Syndrome: A Retrospective Cohort Study.

Background: Recent studies have mainly focused on the association between baseline intensity of mechanical ventilation (driving pressure or mechanical power) and mortality in acute respiratory distress syndrome (ARDS). It is unclear whether the association between the time-varying intensity of mechanical ventilation and mortality is significant and varies according to the fluid balance trajectories. Methods: We conducted a secondary analysis based on the NHLBI ARDS Network's Fluid and Catheter Treatment Trial (FACTT). The primary outcome was 28-day mortality. The group-based trajectory modeling (GBTM) was employed to identify phenotypes based on fluid balance trajectories. Bayesian joint models were used to account for informative censoring due to death during follow-up. Results: A total of 1,000 patients with ARDS were included in the analysis. Our study identified two phenotypes of ARDS, and compared patients with Early Negative Fluid Balance (Early NFB) and patients with Persistent-Positive Fluid Balance (Persistent-PFB) accompanied by higher tidal volume, higher static driving pressure, higher mechanical power, and lower PaO2/FiO2, over time during mechanical ventilation. The 28-day mortality was 14.8% in Early NFB and 49.6% in Persistent-PFB (p < 0.001). In the Bayesian joint models, the hazard ratio (HR) of 28-day death for time-varying static driving pressure [HR 1.03 (95% CI 1.01-1.05; p < 0.001)] and mechanical power [HR 1.01 (95% CI 1.002-1.02; p = 0.01)] was significant in patients with Early NFB, but not in patients with Persistent-PFB. Conclusion: Time-varying intensity of mechanical ventilation was associated with a 28-day mortality of ARDS in a patient with Early NFB but not in patients with Persistent-PFB.

Diagnosis Accuracy of Lung Ultrasound for ARF in Critically Ill Patients: A Systematic Review and Meta-Analysis.

Background: Acute respiratory failure (ARF) is a commonly distressing condition in critically ill patients. Its early recognition and treatment may improve clinical outcomes. Mounting evidence suggests that lung ultrasound (LUS) could be an alternative to chest X-ray (CXR) or computed tomography (CT) for the diagnosis of ARF in critically ill patients. This meta-analysis aimed to determine whether LUS can be an alternative tool used to investigate the cause of ARF or thoracic pathologies associated with the diagnosis of ARF in critically ill patients. Method: A systematic literature search of the PubMed, Web of Science, Embase, and Cochrane Library databases was conducted from inception to March 2020. Two researchers independently screened studies investigating the accuracy of LUS with CXR or CT for adult critically ill patients with ARF. Data with baseline, true positives, false positives, false negatives, and true negatives were extracted. The study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The pooled sensitivity and specificity were obtained using a bivariate model. Results: Eleven studies, including 1,232 patients, were included in the meta-analysis. Most studies were of low quality. LUS had a pooled sensitivity of 92% (95% confidence interval [CI]: 85-96) and a pooled specificity of 98% (95% CI: 94-99). The area under the summary receiver operating characteristic curve was 98% (95% CI: 97-99). The sensitivity and specificity of LUS to identify different pathological types of ARF were investigated. For consolidation (1,040 patients), LUS had a sensitivity of 89% and a specificity of 97%. For pleural effusion (279 patients), LUS had a pooled sensitivity of 95% and a specificity of 99%. For acute interstitial syndrome (174 patients), LUS had a pooled sensitivity of 95% and a specificity of 91%. Conclusions: LUS is an adjuvant tool that has a moderate sensitivity and high specificity for the diagnosis of ARF in critically ill patients. Systematic Review Registration: The study protocol was registered with PROSPERO (CRD42020211493).

Corticosteroid Therapy Is Associated With Improved Outcome in Critically Ill Patients With COVID-19 With Hyperinflammatory Phenotype.

BACKGROUND: Corticosteroid therapy is used commonly in patients with COVID-19, although its impact on outcomes and which patients could benefit from corticosteroid therapy are uncertain. RESEARCH QUESTION: Are clinical phenotypes of COVID-19 associated with differential response to corticosteroid therapy? STUDY DESIGN AND METHODS: Critically ill patients with COVID-19 from Tongji Hospital treated between January and February 2020 were included, and the main exposure of interest was the administration of IV corticosteroids. The primary outcome was 28-day mortality. Marginal structural modeling was used to account for baseline and time-dependent confounders. An unsupervised machine learning approach was carried out to identify phenotypes of COVID-19. RESULTS: A total of 428 patients were included; 280 of 428 patients (65.4%) received corticosteroid therapy. The 28-day mortality was significantly higher in patients who received corticosteroid therapy than in those who did not (53.9% vs 19.6%; P < .0001). After marginal structural modeling, corticosteroid therapy was not associated significantly with 28-day mortality (hazard ratio [HR], 0.80; 95% CI, 0.54-1.18; P = .26). Our analysis identified two phenotypes of COVID-19, and compared with the hypoinflammatory phenotype, the hyperinflammatory phenotype was characterized by elevated levels of proinflammatory cytokines, higher Sequential Organ Failure Assessment scores, and higher rates of complications. Corticosteroid therapy was associated with a reduced 28-day mortality (HR, 0.45; 95% CI, 0.25-0.80; P = .0062) in patients with the hyperinflammatory phenotype. INTERPRETATION: For critically ill patients with COVID-19, corticosteroid therapy was not associated with 28-day mortality, but the use of corticosteroids showed significant survival benefits in patients with the hyperinflammatory phenotype.

Neuroprotective strategies for patients with acute myocardial infarction combined with hypoxic ischemic encephalopathy in the ICU.

BACKGROUND: We investigated neuroprotective treatment strategies for patients with acute myocardial infarction (AMI) complicated with hypoxic ischemic encephalopathy (HIE) in the ICU. METHODS: The 83 cases diagnosed with secondary AMI were, for the first time, divided into an observation group (n = 43) and control group (n = 40). All of the patients underwent emergency or elective PCI. Patients in the control group were treated with mannitol to reduce intracranial pressure and cinepazide maleate to improve microcirculation in the brain as well as given a comprehensive treatment with oxygen inhalation, fluid infusion, acid-base imbalance correction and electrolyte disturbance. Patients in the observation group underwent conventional treatment combined with neuroprotective therapeutic strategies. The effects of the different treatment strategies were compared. RESULTS: Consciousness recovery time, reflex recovery time, muscle tension recovery time and duration of ICU stay were significantly shorter in the observation group compared with the control group (P < 0.05). After treatment, the jugular vein oxygen saturation (SjvO2) and blood lactate (JB-LA) levels of both groups were lower than before treatment and the cerebral oxygen utilization rate (O2UC) increased, with a significantly higher increase in the observation group (P < 0.05). After treatment, the activities of daily living (ADL) score was higher for both groups and the neural function defect (NIHS) score was lower. CONCLUSION: The neuroprotective strategies of hypothermia and ganglioside administration assisted with hyperbaric oxygen was effective for treating AMI patients with HIE and may be worth clinical promotion.

Identification of the nanogold particle-induced endoplasmic reticulum stress by omic techniques and systems biology analysis.

Growth inhibition and apoptotic/necrotic phenotype was observed in nanogold particle (AuNP)-treated human chronic myelogenous leukemia cells. To elucidate the underlying cellular mechanisms, proteomic techniques including two-dimensional electrophoresis/mass spectrometry and protein microarrays were utilized to study the differentially expressed proteome and phosphoproteome, respectively. Systems biology analysis of the proteomic data revealed that unfolded protein-associated endoplasmic reticulum (ER) stress response was the predominant event. Concomitant with transcriptomic analysis using mRNA expression, microarrays show ER stress response in the AuNP-treated cells. The ER stress protein markers' expression assay unveiled AuNPs as an efficient cellular ER stress elicitor. Upon ER stress, cellular responses, including reactive oxygen species increase, mitochondrial cytochrome c release, and mitochondria damage, chronologically occurred in the AuNP-treated cells. Conclusively, this study demonstrates that AuNPs cause cell death through induction of unmanageable ER stress.