Skin mottling score assesses peripheral tissue hypoperfusion in critically ill patients following cardiac surgery.

BACKGROUND: Skin mottling is a common manifestation of peripheral tissue hypoperfusion, and its severity can be described using the skin mottling score (SMS). This study aims to evaluate the value of the SMS in detecting peripheral tissue hypoperfusion in critically ill patients following cardiac surgery. METHODS: Critically ill patients following cardiac surgery with risk factors for tissue hypoperfusion were enrolled (n = 373). Among these overall patients, we further defined a hypotension population (n = 178) and a shock population (n = 51). Hemodynamic and perfusion parameters were recorded. The primary outcome was peripheral hypoperfusion, defined as significant prolonged capillary refill time (CRT, > 3.0 s). The characteristics and hospital mortality of patients with and without skin mottling were compared. The area under receiver operating characteristic curves (AUROC) were used to assess the accuracy of SMS in detecting peripheral hypoperfusion. Besides, the relationships between SMS and conventional hemodynamic and perfusion parameters were investigated, and the factors most associated with the presence of skin mottling were identified. RESULTS: Of the 373-case overall population, 13 (3.5%) patients exhibited skin mottling, with SMS ranging from 1 to 5 (5, 1, 2, 2, and 3 cases, respectively). Patients with mottling had lower mean arterial pressure, higher vasopressor dose, less urine output (UO), higher CRT, lactate levels and hospital mortality (84.6% vs. 12.2%, p < 0.001). The occurrences of skin mottling were higher in hypotension population and shock population, reaching 5.6% and 15.7%, respectively. The AUROC for SMS to identify peripheral hypoperfusion was 0.64, 0.68, and 0.81 in the overall, hypotension, and shock populations, respectively. The optimal SMS threshold was 1, which corresponded to specificities of 98, 97 and 91 and sensitivities of 29, 38 and 67 in the three populations (overall, hypotension and shock). The correlation of UO, lactate, CRT and vasopressor dose with SMS was significant, among them, UO and CRT were identified as two major factors associated with the presence of skin mottling. CONCLUSION: In critically ill patients following cardiac surgery, SMS is a very specific yet less sensitive parameter for detecting peripheral tissue hypoperfusion.

Interpreting Infrared Thermography with Deep Learning to Assess the Mortality Risk of Critically Ill Patients at Risk of Hypoperfusion.

Background: Hypoperfusion, a common manifestation of many critical illnesses, could lead to abnormalities in body surface thermal distribution. However, the interpretation of thermal images is difficult. Our aim was to assess the mortality risk of critically ill patients at risk of hypoperfusion in a prospective cohort by infrared thermography combined with deep learning methods. Methods: This post-hoc study was based on a cohort at high-risk of hypoperfusion. Patients' legs were selected as the region of interest. Thermal images and conventional hypoperfusion parameters were collected. Six deep learning models were attempted to derive the risk of mortality (range: 0 to 100%) for each patient. The area under the receiver operating characteristic curve (AUROC) was used to evaluate predictive accuracy. Results: Fifty-five hospital deaths occurred in a cohort consisting of 373 patients. The conventional hypoperfusion (capillary refill time and diastolic blood pressure) and thermal (low temperature area rate and standard deviation) parameters demonstrated similar predictive accuracies for hospital mortality (AUROC 0.73 and 0.77). The deep learning methods, especially the ResNet (18), could further improve the accuracy. The AUROC of ResNet (18) was 0.94 with a sensitivity of 84% and a specificity of 91% when using a cutoff of 36%. ResNet (18) presented a significantly increasing trend in the risk of mortality in patients with normotension (13 [7 to 26]), hypotension (18 [8 to 32]) and shock (28 [14 to 62]). Conclusions: Interpreting infrared thermography with deep learning enables accurate and non-invasive assessment of the severity of patients at risk of hypoperfusion.

Postoperative glucocorticoids in patients with acute type A aortic dissection (GLAD): study protocol for a prospective, single-center, randomized controlled trial.

BACKGROUND: Patients receiving surgical treatment of acute type A Aortic Dissection (aTAAD) are common to suffer organ dysfunction in the intensive care unit due to overwhelming inflammation. Previous studies have revealed that glucocorticoids may reduce complications in certain patient groups, but evidence between postoperative glucocorticoids administration and improvement in organ dysfunction after aTAAD surgery are lacking. METHODS: This study will be an investigator-initiated, prospective, single-blind, randomized, single-center study. Subjects with confirmed diagnosis of aTAAD undergoing surgical treatment will be enrolled and 1:1 randomly assigned to receive either glucocorticoids or normal treatment. All patients in the glucocorticoids group will be given methylprednisolone intravenously for 3 days after enrollment. The primary endpoint will be the amplitude of variation of Sequential Organ Failure Assessment score on post-operative day 4 compared to baseline. DISCUSSION: The trial will explore the rationale for postoperative application of glucocorticoids in patients after aTAAD surgery. TRIAL REGISTRATION: This study has been registered on ClinicalTrials.gov (NCT04734418).

Effect of glucocorticoid for patients with type A aortic dissection undergoing surgical repair with deep hypothermic circulatory arrest: A single-center, retrospective study.

BACKGROUND: Postoperative patients with Type A aortic dissection (TAAD) often experience severe inflammatory responses caused by multiple factors perioperatively. However, the effect of postoperative glucocorticoid (GC) use, which is a potent anti-inflammatory agent, on complications or all-cause mortality is unclear. METHODS: Patients with TAAD who underwent surgical repair requiring deep hypothermic circulatory arrest between January 2020 and December 2021 were included in the study. Characteristics of patients treated with and without GCs were compared. The primary outcome was in-hospital mortality, and a composite secondary outcome was defined as in-hospital death or any major complications. Propensity score matching was used to balance baseline differences between groups. Kaplan-Meier curves were used to compare survival probability. RESULTS: A total of 393 postoperative patients with TAAD were included in the study. Forty of them (10.2%) received GC treatment at a median daily methylprednisolone-equivalent dose of 0.6 mg/kg (0.4-0.7) for a median period of 2 (1-3) days. Patients on GCs had more intraoperative blood transfusions, higher postoperative APACHE II (12 vs 9, p = .004) and SOFA (9 vs 6, p < .001) scores, worse perioperative hepatic, renal and cardiac function. The in-hospital mortality in the matched cohort did not differ between groups [GC n = 11/40 (27.5%) versus Non-GC n = 19/80 (23.8%); p = .661]. CONCLUSIONS: The propensity to use GCs correlated with the critical status of the patient. However, low dose and short-term postoperative GC treatment did not reduce in-hospital mortality rates among patients with TAAD. A more appropriate regimen should be further investigated.

Remifentanil versus Dexmedetomidine in Cardiac Surgery Patients with Noninvasive Ventilation Intolerance: Protocol for the REDNIVI Trial.

BACKGROUND: Respiratory failure is one of the most common complications following cardiac surgery. Although noninvasive ventilation (NIV) has been an effective treatment, it has a high rate of intolerance. Both remifentanil and dexmedetomidine are used as sedatives in cardiac surgery (CS) patients with NIV intolerance. However, no randomized controlled trials have compared the effects of these drugs in relieving the intolerance. METHODS: REDNIVI will be a multicenter, prospective, single-blind, randomized controlled trial carried out in six clinical sites in China. Subjects with NIV intolerance will be randomized to receive remifentanil or dexmedetomidine in a ratio of 1:1. Primary outcomes of intolerance remission rate at different timings (15 minutes, 1, 3, 6, 12, 24, 36, 48, 60, 72 hours after initiation of treatment) and 72 h average remission rate will be determined. In addition, secondary outcomes such as mortality, duration of intensive care unit (ICU) stay, duration of mechanical ventilation (MV), the need for endotracheal intubation, hemodynamic changes, and delirium incidence will also be determined. CONCLUSIONS: This trial will provide evidence to determine the effects of remifentanil and dexmedetomidine in patients with NIV intolerance after cardiac surgery. CLINICAL TRIAL REGISTRATION: This study has been registered on ClinicalTrials.gov (NCT04734418).

Early prediction of noninvasive ventilation failure after extubation: development and validation of a machine-learning model.

BACKGROUND: Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accurate machine-learning model to identify patients at risks of NIV failure after extubation in intensive care units (ICUs). METHODS: Patients who underwent NIV after extubation in the eICU Collaborative Research Database (eICU-CRD) were included. NIV failure was defined as need for invasive ventilatory support (reintubation or tracheotomy) or death after NIV initiation. A total of 93 clinical and laboratory variables were assessed, and the recursive feature elimination algorithm was used to select key features. Hyperparameter optimization was conducted with an automated machine-learning toolkit called Neural Network Intelligence. A machine-learning model called Categorical Boosting (CatBoost) was developed and compared with nine other models. The model was then prospectively validated among patients enrolled in the Cardiac Surgical ICU of Zhongshan Hospital, Fudan University. RESULTS: Of 929 patients included in the eICU-CRD cohort, 248 (26.7%) had NIV failure. The time from extubation to NIV, age, Glasgow Coma Scale (GCS) score, heart rate, respiratory rate, mean blood pressure (MBP), saturation of pulse oxygen (SpO2), temperature, glucose, pH, pressure of oxygen in blood (PaO2), urine output, input volume, ventilation duration, and mean airway pressure were selected. After hyperparameter optimization, our model showed the greatest accuracy in predicting NIV failure (AUROC: 0.872 [95% CI 0.82-0.92]) among all predictive methods in an internal validation. In the prospective validation cohort, our model was also superior (AUROC: 0.846 [95% CI 0.80-0.89]). The sensitivity and specificity in the prediction group is 89% and 75%, while in the validation group they are 90% and 70%. MV duration and respiratory rate were the most important features. Additionally, we developed a web-based tool to help clinicians use our model. CONCLUSIONS: This study developed and prospectively validated the CatBoost model, which can be used to identify patients who are at risk of NIV failure. Thus, those patients might benefit from early triage and more intensive monitoring. TRIAL REGISTRATION: NCT03704324. Registered 1 September 2018, https://register. CLINICALTRIALS: gov .

Development and external validation of a novel modality for rapid recognition of aortic dissection based on peripheral pulse oximetry waveforms.

BACKGROUND: Aortic dissection (AD) is a life-threatening cardiovascular emergency that is often misdiagnosed as other chest pain conditions. Physiologically, AD may cause abnormalities in peripheral blood flow, which can be detected using pulse oximetry waveforms. PURPOSE: This study aimed to assess the feasibility of identifying AD based on pulse oximetry waveforms and to highlight the key waveform features that play a crucial role in this diagnostic method. METHODS: This prospective study employed high-risk chest pain cohorts from two emergency departments. The initial cohort was enriched with AD patients (n = 258, 47% AD) for model development, while the second cohort consisted of chest pain patients awaiting angiography (n = 71, 25% AD) and was used for external validation. Pulse oximetry waveforms from the four extremities were collected for each patient. After data preprocessing, a recognition model based on the random forest algorithm was trained using patients' gender, age, and waveform difference features extracted from the pulse oximetry waveforms. The performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). The importance of features was also assessed using Shapley Value and Gini importance. RESULTS: The model demonstrated strong performance in identifying AD in both the training and external validation sets. In the training set, the model achieved an area under the ROC curve of 0.979 (95% CI: 0.961-0.990), sensitivity of 0.918 (95% CI: 0.873-0.955), specificity of 0.949 (95% CI: 0.912-0.985), and accuracy of 0.933 (95% CI: 0.904-0.959). In the external validation set, the model attained an area under the ROC curve of 0.855 (95% CI: 0.720-0.965), sensitivity of 0.889 (95% CI: 0.722-1.000), specificity of 0.698 (95% CI: 0.566-0.812), and accuracy of 0.794 (95% CI: 0.672-0.878). Decision curve analysis (DCA) further showed that the model provided a substantial net benefit for identifying AD. The median mean and median variance of the four limbs' signals were the most influential features in the recognition model. CONCLUSIONS: This study demonstrated the feasibility and strong performance of identifying AD based on peripheral pulse oximetry waveforms in high-risk chest pain populations in the emergency setting. The findings also provided valuable insights for future human fluid dynamics simulations to elucidate the impact of AD on blood flow in greater detail.

Complete mediastinal lymph node dissection in video-assisted thoracoscopic lobectomy versus lobectomy by thoracotomy.

BACKGROUND: Although video-assisted thoracic surgery (VATS) lobectomy has been used more and more frequently for the treatment of patients with early-stage lung cancer, controversies are mainly focused on whether the complete mediastinal lymph node dissection (MLND) can be achieved by VATS. This retrospective study aimed to compare the validity of MLND between VATS and open thoracotomy. METHODS: Patients with lung cancer were matched from a pool of pulmonary lobectomies performed by one surgeon. Patients undergoing VATS were matched with those undergoing thoracotomy in terms of gender, age, clinical tumor stage, tumor location, and surgical procedure. RESULTS: After matching, 31 patients in VATS group and 31 patients in open group were eligible for analysis. In the VATS and open groups, the mean total number of dissected lymph nodes was 28.2 ± 8.4 and 29.8 ± 11.6 (p = 0.517), respectively. In the VATS and open groups, the number of N1 nodes was 9.5 ± 4.1 and 8.4 ± 4.7 (p = 0.333), respectively. And the number of N2 nodes was also similar between the VATS and open group (18.6 ± 7.0 vs 21.4 ± 10.0, p = 0.211). No significant differences were observed between the two groups in the operating time, the blood loss, the length of chest tube drainage, the length of hospital stay, and the rate of specific complications. CONCLUSION: Our early experience suggests that, with regard to the number of the dissected lymph nodes, VATS lobectomy can achieve complete MLND, compared with the traditional approach. MLND by VATS is technically feasible and safe for early-stage lung cancer.

[Aerobic exercise improves renal fibrosis in spontaneously hypertensive rats].

Objective: To study the effects of aerobic exercise training on renal fibrosis in spontaneously hypertensive rats (SHR), and to explore the protective effect of exercise on renal damage in hypertensive rats. Methods: Eight-week-old male SHR and Wistar Kyoto rats of the same age (WKY) were randomly divided into 4 groups (n=6): sedentary WKY control group (WKY-S), sedentary SHR control group (SHR-S), low-intensity exercise group (SHR-L) and medium-intensity exercise group (SHR-M). SHR-L group and SHR-M group were set at a slope of 0° at 14 m/min (35% of the maximum aerobic speed) and 20 m/min (50% of the maximum aerobic speed), running on a sports treadmill for 14 weeks, 5 times a week, and 60 min each time. WKY-S and SHR-S groups were kept quietly. Blood pressure was measured 72 hours after exercise training. And the serum levels of creatinine (Scr) and BUN were detected. The morphology of renal tissue was observed by hematoxylin and eosin (HE) staining. The collagen deposition of renal tissue was observed by Masson staining, and the renal collagen volume fraction (CVF) was calculated. Results: Compared with WKY-S group, blood pressure, serum Scr and BUN, kidney CVF levels and AngⅡ, AT1R, TGF-ß, α-SMA, CTGF expressions in SHR-S group were increased significantly (P＜0.05). Compared with SHR-S group, blood pressure, serum Scr and BUN, kidney CVF level and AngⅡ, AT1R, TGF-ß, α-SMA, CTGF expressions in SHR-L and SHR-M groups were decreased significantly (P＜0.05) and the decreasing trend was more obvious in SHR-M group (P＜0.05). Conclusion: Aerobic exercise can improve renal fibrosis and renal function in spontaneously hypertensive rats by inhibiting the AngⅡ-AT1R-TGF-ß pathway.

Weaning from venous-arterial extracorporeal membrane oxygenation: The hemodynamic and clinical aspects of flow challenge test.

The cardiac function reserve is crucial for the successful weaning of V-A ECMO. During the V-A ECMO weaning phase, the gradual reduction in pump flow converts the blood flow originally driven by the pump to native cardiac output and also transforms afterload (caused by retrograde flow) into ventricular preload, thus introducing a "flow challenge" to the native heart. In this perspective, we propose to use this flow challenge as a test to simulate the preload-to-afterload conversion to assess cardiac functional reserve quantitatively. With this short article we offer the hemodynamic and clinical aspects regarding the flow challenge test.

Data science in the intensive care unit.

In this editorial, we comment on the current development and deployment of data science in intensive care units (ICUs). Data in ICUs can be classified into qualitative and quantitative data with different technologies needed to translate and interpret them. Data science, in the form of artificial intelligence (AI), should find the right interaction between physicians, data and algorithm. For individual patients and physicians, sepsis and mechanical ventilation have been two important aspects where AI has been extensively studied. However, major risks of bias, lack of generalizability and poor clinical values remain. AI deployment in the ICUs should be emphasized more to facilitate AI development. For ICU management, AI has a huge potential in transforming resource allocation. The coronavirus disease 2019 pandemic has given opportunities to establish such systems which should be investigated further. Ethical concerns must be addressed when designing such AI.

INFRARED THERMOGRAPHY-BASED BODY-SURFACE THERMAL INHOMOGENEITY MONITORING TO ASSESS THE SEVERITY OF HYPOPERFUSION IN CRITICALLY ILL PATIENTS.

ABSTRACT: Background: Uneven body-surface thermal distribution is a manifestation of hypoperfusion and can be quantified by infrared thermography. Our aim was to investigate whether body-surface thermal inhomogeneity could accurately evaluate the severity of patients at risk of hypoperfusion. Methods: This was a prospective cohort study in which infrared thermography images were taken from unilateral legs of critically ill patients at high risk of hypoperfusion in a cardiac surgical intensive care unit. For each patient, five body-surface thermal inhomogeneity parameters, including standard deviation (SD), kurtosis, skewness, entropy, and low-temperature area rate (LTAR), were calculated. Demographic, clinical, and thermal characteristics of deceased and living patients were compared. The risk of mortality and capillary refill time (CRT) were chosen as the primary outcome and benchmarking parameter for hypoperfusion, respectively. The area under the receiver operating characteristic curve (AUROC) was used to evaluate predictive accuracy. Results: Three hundred seventy-three patients were included, and 55 (14.7%) died during hospital stay. Of inhomogeneity parameters, SD (0.738) and LTAR (0.768) had similar AUROC to CRT (0.757) for assessing mortality risk. Besides, there was a tendency for LTAR (1%-3%-7%) and SD (0.81°C-0.88°C-0.94°C) to increase in normotensive, hypotensive, and shock patients. These thermal parameters are associated with CRT, lactate, and blood pressure. The AUROC of a combined prediction incorporating three thermal inhomogeneity parameters (SD, kurtosis, and entropy) was considerably higher at 0.866. Conclusions: Body-surface thermal inhomogeneity provided a noninvasive and accurate assessment of the severity of critically ill patients at high risk of hypoperfusion.

Recombinant human brain natriuretic peptide ameliorates venous return function in congestive heart failure.

AIMS: Recombinant human brain natriuretic peptide (rh-BNP) is commonly used as a decongestive therapy. This study aimed to investigate the instant effects of rh-BNP on cardiac output and venous return function in post-cardiotomy patients with congestive heart failure (CHF). METHODS AND RESULTS: Twenty-four post-cardiotomy heart failure patients were enrolled and received a standard loading dose of rh-BNP. Haemodynamic monitoring was performed via a pulmonary artery catheter before and after the administration of rh-BNP. The cardiac output and venous return functions were estimated by depicting Frank-Starling and Guyton curves. After rh-BNP infusion, variables reflecting cardiac congestion and venous return function, such as pulmonary artery wedge pressure, mean systemic filling pressure (Pmsf) and venous return resistance index (VRRI), reduced from 15 ± 3 to 13 ± 3 mmHg, from 32 ± 7 to 28 ± 7 mmHg and from 6.7 ± 2.6 to 5.7 ± 1.8 mmHg min m2 /L, respectively. Meanwhile, cardiac index, stroke volume index, and the cardiac output function curve remained unchanged per se. The decline in Pmsf [-13% (-22% to -8%)] and VRRI [-12% (-25% to -5%)] was much greater than that in the systemic vascular resistance index [-7% (-14% to 0%)]. In the subgroup analysis of reduced ejection fraction (<40%) patients, the aforementioned changes were more significant. CONCLUSIONS: rh-BNP might ameliorate venous return rather than cardiac output function in post-cardiotomy CHF patients.

Exosome-Derived From Sepsis Patients' Blood Promoted Pyroptosis of Cardiomyocytes by Regulating miR-885-5p/HMBOX1.

Background: Septic myocardial depression has been associated with increased morbidity and mortality. miR-885-5p has been shown to regulate cell growth, senescence, and/or apoptosis. Published studies demonstrated that Homeobox-containing protein 1 (HMBOX1) inhibits inflammatory response, regulates cell autophagy, and apoptosis. However, the role of miR-885-5p/HMBOX1 in sepsis and septic myocardial depression and the underlying mechanism is not fully understood. Materials and Methods: Exosomes (exos) derived from sepsis patients (sepsis-exos) were isolated using ultracentrifugation. Rats were subjected to cecal ligation and puncture surgery and treated with sepsis-exos. HMBOX1 was knocked down or overexpressed in AC16 cells using lentiviral plasmids carrying short interfering RNAs targeting human HMBOX1 or carrying HMBOX1 cDNA. Cell pyroptosis was measured by flow cytometry. The secretion of IL-1ß and IL-18 was examined by ELISA kits. Quantitative polymerase chain reaction (PCR) or western blot was used for gene expression. Results: Sepsis-exos increased the level of miR-885-5p, decreased HMBOX1, elevated IL-1ß and IL-18, and promoted pyroptosis in AC16 cells. Septic rats treated with sepsis-exos increased the serum inflammatory cytokines is associated with increased pyroptosis-related proteins of hearts. MiR-885-5p bound to the three prime untranslated regions of HMBOX1 to negatively regulate its expression. Overexpressing HMBOX1 reversed miR-885-5p-induced elevation of inflammatory cytokines and upregulation of NLRP3, caspase-1, and GSDMD-N in AC16 cells. The mechanistic study indicated that the effect of HMBOX1 was NF-κB dependent. Conclusion: Sepsis-exos promoted the pyroptosis of AC16 cells through miR-885-5p via HMBOX1. The results show the significance of the miR-885-5p/HMBOX1 axis in myocardial cell pyroptosis and provide new directions for the treatment of septic myocardial depression.

Early postoperative organ dysfunction is highly associated with the mortality risk of patients with type A aortic dissection.

OBJECTIVES: This study assessed the impact of early postoperative organ dysfunction (EPOD) on in-hospital mortality of patients with type A aortic dissection (TAAD) after surgery. METHODS: Patients with TAAD who underwent surgical repair requiring deep hypothermic circulatory arrest from January 2020 to December 2021 were included. The Sequential Organ Failure Assessment (SOFA) score was calculated for 3 days postoperatively to stratify the severity of organ dysfunction. Patients with the SOFA of 0-4, 5-8 or >8 were defined as mild, moderate or severe EPOD. The primary outcome was in-hospital mortality, and a composite secondary outcome was defined as in-hospital death or any major complications. Kaplan-Meier curves were used to compare survival probability. The area under the receiver operating characteristic curve and calibration plots were used to evaluate the predictive power and overall performance of SOFA. RESULTS: Of the 368 patients, 5 patients (3%) with moderate EPOD and 33 patients (23%) with severe EPOD died. No patient died with mild EPOD. The areas under the receiver operating characteristic curve of SOFA for predicting mortality and the composite outcome were 0.85 (0.81-0.88) and 0.81 (0.77-0.85) on postoperative day 1. Each point of postoperative day 1 SOFA score corresponded to an odds ratio of 1.65 (1.42-1.92) for mortality. Of the 6 components of the SOFA system, only coagulation (2.34 [1.32-4.13]), cardiovascular (1.47 [1.04-2.08]), central nervous system (1.96 [1.36-2.82]) and renal (1.67 [1.04-2.70]) functions were associated with the higher risk of mortality. CONCLUSIONS: EPOD stratified by the SOFA score was associated with a higher risk of death and predicted the clinical outcomes of patients with TAAD with good accuracy.

Mesenchymal Stem Cell-Derived Extracellular Vesicles: A Potential Therapeutic Strategy for Acute Kidney Injury.

Acute kidney injury (AKI) is a common and potential life-threatening disease in patients admitted to hospital, affecting 10%-15% of all hospitalizations and around 50% of patients in the intensive care unit. Severe, recurrent, and uncontrolled AKI may progress to chronic kidney disease or end-stage renal disease. AKI thus requires more efficient, specific therapies, rather than just supportive therapy. Mesenchymal stem cells (MSCs) are considered to be promising cells for cellular therapy because of their ease of harvesting, low immunogenicity, and ability to expand in vitro. Recent research indicated that the main therapeutic effects of MSCs were mediated by MSC-derived extracellular vesicles (MSC-EVs). Furthermore, compared with MSCs, MSC-EVs have lower immunogenicity, easier storage, no tumorigenesis, and the potential to be artificially modified. We reviewed the therapeutic mechanism of MSCs and MSC-EVs in AKI, and considered recent research on how to improve the efficacy of MSC-EVs in AKI. We also summarized and analyzed the potential and limitations of EVs for the treatment of AKI to provide ideas for future clinical trials and the clinical application of MSC-EVs in AKI.

Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.

Background: Extubation failure (EF) can lead to an increased chance of ventilator-associated pneumonia, longer hospital stays, and a higher mortality rate. This study aimed to develop and validate an accurate machine-learning model to predict EF in intensive care units (ICUs). Methods: Patients who underwent extubation in the Medical Information Mart for Intensive Care (MIMIC)-IV database were included. EF was defined as the need for ventilatory support (non-invasive ventilation or reintubation) or death within 48 h following extubation. A machine-learning model called Categorical Boosting (CatBoost) was developed based on 89 clinical and laboratory variables. SHapley Additive exPlanations (SHAP) values were calculated to evaluate feature importance and the recursive feature elimination (RFE) algorithm was used to select key features. Hyperparameter optimization was conducted using an automated machine-learning toolkit (Neural Network Intelligence). The final model was trained based on key features and compared with 10 other models. The model was then prospectively validated in patients enrolled in the Cardiac Surgical ICU of Zhongshan Hospital, Fudan University. In addition, a web-based tool was developed to help clinicians use our model. Results: Of 16,189 patients included in the MIMIC-IV cohort, 2,756 (17.0%) had EF. Nineteen key features were selected using the RFE algorithm, including age, body mass index, stroke, heart rate, respiratory rate, mean arterial pressure, peripheral oxygen saturation, temperature, pH, central venous pressure, tidal volume, positive end-expiratory pressure, mean airway pressure, pressure support ventilation (PSV) level, mechanical ventilation (MV) durations, spontaneous breathing trial success times, urine output, crystalloid amount, and antibiotic types. After hyperparameter optimization, our model had the greatest area under the receiver operating characteristic (AUROC: 0.835) in internal validation. Significant differences in mortality, reintubation rates, and NIV rates were shown between patients with a high predicted risk and those with a low predicted risk. In the prospective validation, the superiority of our model was also observed (AUROC: 0.803). According to the SHAP values, MV duration and PSV level were the most important features for prediction. Conclusions: In conclusion, this study developed and prospectively validated a CatBoost model, which better predicted EF in ICUs than other models.

Phosphorylation of Akt at Thr308 regulates p-eNOS Ser1177 during physiological conditions.

Endothelial nitric oxide synthase (eNOS)-derived nitric oxide (NO) plays a crucial role in maintaining vascular homeostasis. As a hallmark of eNOS activation, phosphorylation of eNOS at Ser1177 induced by activated protein kinase B (PKB/Akt) is pivotal for NO production. The complete activation of Akt requires its phosphorylation of both Thr308 and Ser473. However, which site plays the main role in regulating phosphorylation of eNOS Ser1177 is still controversial. The purpose of the present study is to explore the specific regulatory mechanism of phosphorylated Akt in eNOS activation. Inhibition of Akt Thr308 phosphorylation by a specific inhibitor or by siRNA in vitro led to a decrease in eNOS phosphorylation at Ser1177 and to lower NO concentration in the cell culture medium of HUVECs. However, inhibiting p-Akt Ser473 had no effect on eNOS phosphorylation at Ser1177. Next, we administered mice with inhibitors to downregulate p-Akt Ser473 or Thr308 activity. Along with the inhibition of p-Akt Thr308, vascular p-eNOS Ser1177 protein was simultaneously downregulated in parallel with a decrease in plasma NO concentration. Additionally, we cultured HUVECs at various temperature conditions (37, 22, and 4 °C). The results showed that p-Akt Ser473 was gradually decreased in line with the reduction in temperature, accompanied by increased levels of p-Akt Thr308 and p-eNOS Ser1177. Taken together, our study indicates that the phosphorylation of Akt at Thr308, but not at Ser473, plays a more significant role in regulating p-eNOS Ser1177 levels under physiological conditions.

Tailoring glucocorticoids in patients with severe COVID-19: a narrative review.

OBJECTIVE: To discuss the pathogenesis of severe coronavirus disease 2019 (COVID-19) infection and the pharmacological effects of glucocorticoids (GCs) toward this infection. To review randomized controlled trials (RCTs) using GCs to treat patients with severe COVID-19, and investigate whether GC timing, dosage, or duration affect clinical outcomes. Finally. to discuss the use of biological markers, respiratory parameters, and radiological evidence to select patients for improved GC therapeutic precision. BACKGROUND: COVID-19 has become an unprecedented global challenge. As GCs have been used as key immunomodulators to treat inflammation-related diseases, they may play key roles in limiting disease progression by modulating immune responses, cytokine production, and endothelial function in patients with severe COVID-19, who often experience excessive cytokine production and endothelial and renin-angiotensin system (RAS) dysfunction. Current clinical trials have partially proven this efficacy, but GC timing, dosage, and duration vary greatly, with no unifying consensus, thereby creating confusion. METHODS: Publications through March 2021 were retrieved from the Web of Science and PubMed. Results from cited references in published articles were also included. CONCLUSIONS: GCs play key roles in treating severe COVID-19 infections. Pharmacologically, GCs could modulate immune cells, reduce cytokine and chemokine, and improve endothelial functions in patients with severe COVID-19. Benefits of GCs have been observed in multiple clinical trials, but the timing, dosage and duration vary across studies. Tapering as an option is not widely accepted. However, early initiation of treatment, a tailored dosage with appropriate tapering may be of particular importance, but evidence is inconclusive and more investigations are needed. Biological markers, respiratory parameters, and radiological evidence could also help select patients for specific tailored treatments.