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.

Remifentanil vs. dexmedetomidine for cardiac surgery patients with noninvasive ventilation intolerance: a multicenter randomized controlled trial.

BACKGROUND: The optimal sedative regime for noninvasive ventilation (NIV) intolerance remains uncertain. The present study aimed to assess the efficacy and safety of remifentanil (REM) compared to dexmedetomidine (DEX) in cardiac surgery patients with moderate-to-severe intolerance to NIV. METHODS: In this multicenter, prospective, single-blind, randomized controlled study, adult cardiac surgery patients with moderate-to-severe intolerance to NIV were enrolled and randomly assigned to be treated with either REM or DEX for sedation. The status of NIV intolerance was evaluated using a four-point NIV intolerance score at different timepoints within a 72-h period. The primary outcome was the mitigation rate of NIV intolerance following sedation. RESULTS: A total of 179 patients were enrolled, with 89 assigned to the REM group and 90 to the DEX group. Baseline characteristics were comparable between the two groups, including NIV intolerance score [3, interquartile range (IQR) 3-3 vs. 3, IQR 3-4, p = 0.180]. The chi-squared test showed that mitigation rate, defined as the proportion of patients who were relieved from their initial intolerance status, was not significant at most timepoints, except for the 15-min timepoint (42% vs. 20%, p = 0.002). However, after considering the time factor, generalized estimating equations showed that the difference was statistically significant, and REM outperformed DEX (odds ratio = 3.31, 95% confidence interval: 1.35-8.12, p = 0.009). Adverse effects, which were not reported in the REM group, were encountered by nine patients in the DEX group, with three instances of bradycardia and six cases of severe hypotension. Secondary outcomes, including NIV failure (5.6% vs. 7.8%, p = 0.564), tracheostomy (1.12% vs. 0%, p = 0.313), ICU LOS (7.7 days, IQR 5.8-12 days vs. 7.0 days, IQR 5-10.6 days, p = 0.219), and in-hospital mortality (1.12% vs. 2.22%, p = 0.567), demonstrated comparability between the two groups. CONCLUSIONS: In summary, our study demonstrated no significant difference between REM and DEX in the percentage of patients who achieved mitigation among cardiac surgery patients with moderate-to-severe NIV intolerance. However, after considering the time factor, REM was significantly superior to DEX. Trial registration ClinicalTrials.gov (NCT04734418), registered on January 22, 2021. URL of the trial registry record: https://register. CLINICALTRIALS: gov/prs/app/action/SelectProtocol?sid=S000AM4S&selectaction=Edit&uid=U00038YX&ts=3&cx=eqn1z0 .

AKI-Pro score for predicting progression to severe acute kidney injury or death in patients with early acute kidney injury after cardiac surgery.

BACKGROUND: No reliable clinical tools exist to predict acute kidney injury (AKI) progression. We aim to explore a scoring system for predicting the composite outcome of progression to severe AKI or death within seven days among early AKI patients after cardiac surgery. METHODS: In this study, we used two independent cohorts, and patients who experienced mild/moderate AKI within 48 h after cardiac surgery were enrolled. Eventually, 3188 patients from the MIMIC-IV database were used as the derivation cohort, while 499 patients from the Zhongshan cohort were used as external validation. The primary outcome was defined by the composite outcome of progression to severe AKI or death within seven days after enrollment. The variables identified by LASSO regression analysis were entered into logistic regression models and were used to construct the risk score. RESULTS: The composite outcome accounted for 3.7% (n = 119) and 7.6% (n = 38) of the derivation and validation cohorts, respectively. Six predictors were assembled into a risk score (AKI-Pro score), including female, baseline eGFR, aortic surgery, modified furosemide responsiveness index (mFRI), SOFA, and AKI stage. And we stratified the risk score into four groups: low, moderate, high, and very high risk. The risk score displayed satisfied predictive discrimination and calibration in the derivation and validation cohort. The AKI-Pro score discriminated the composite outcome better than CRATE score, Cleveland score, AKICS score, Simplified renal index, and SRI risk score (all P < 0.05). CONCLUSIONS: The AKI-Pro score is a new clinical tool that could assist clinicians to identify early AKI patients at high risk for AKI progression or death.

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.

Furosemide Responsiveness Predicts Acute Kidney Injury Progression After Cardiac Surgery.

BACKGROUND: As patients with acute kidney injury (AKI) progress to a higher stage, the risk for poor outcomes dramatically rises. Early identification of patients at high risk for AKI progression remains a major challenge. This study aimed to evaluate the value of furosemide responsiveness (FR) for predicting AKI progression in patients with initial mild and moderate AKI after cardiac surgery. METHODS: We performed 2 separate exploratory analyses. The Zhongshan cohort was a single-center, prospective, observational cohort, whereas the Beth Israel Deaconess Medical Center cohort was a single-center, retrospective cohort. We calculated 2 FR parameters for each patient, namely the FR index and modified FR index, defined as 2-hour urine output divided by furosemide dose (FR index, mL/mg/2 h) and by furosemide dose and body weight (modified FR index, mL/[mg·kg]/2 h), respectively. The primary outcome was AKI progression within 7 days. RESULTS: AKI progression occurred in 80 (16.0%) and 359 (11.3%) patients in the Zhongshan and Beth Israel Deaconess Medical Center cohorts, respectively. All FR parameters (considered continuously or in quartiles) were inversely associated with risk of AKI progression in both cohorts (all adjusted P < .01). The addition of FR parameters significantly improved prediction for AKI progression based on baseline clinical models involving C-index, net reclassification improvement, and integrated discrimination improvement index in both cohorts (all P < .01). CONCLUSIONS: FR parameters were inversely associated with risk of AKI progression in patients with mild and moderate AKI after cardiac surgery. The addition of FR parameters significantly improved prediction for AKI progression based on baseline clinical models.

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.

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).

Extracellular vesicles derived from CD4+ T cells carry DGKK to promote sepsis-induced lung injury by regulating oxidative stress and inflammation.

BACKGROUND: Sepsis is an abnormal immune response after infection, wherein the lung is the most susceptible organ to fail, leading to acute lung injury. To overcome the limitations of current therapeutic strategies and develop more specific treatment, the inflammatory process, in which T cell-derived extracellular vesicles (EVs) play a central role, should be explored deeply. METHODS: Liquid chromatography-tandem mass spectrometry was performed for serum EV protein profiling. The serum diacylglycerol kinase kappa (DGKK) and endotoxin contents of patients with sepsis-induced lung injury were measured. Apoptosis, oxidative stress, and inflammation in A549 cells, bronchoalveolar lavage fluid, and lung tissues of mice were measured by flow cytometry, biochemical analysis, enzyme-linked immunosorbent assay, quantitative real-time polymerase chain reaction, and western blot. RESULTS: DGKK, the key regulator of the diacylglycerol (DAG)/protein kinase C (PKC) pathway, exhibited elevated expression in serum EVs of patients with sepsis-induced lung injury and showed strong correlation with sepsis severity and disease progression. DGKK was expressed in CD4+ T cells under regulation of the NF-κB pathway and delivered by EVs to target cells, including alveolar epithelial cells. EVs produced by CD4+ T lymphocytes exerted toxic effects on A549 cells to induce apoptotic cell death, oxidative cell damage, and inflammation. In mice with sepsis induced by cecal ligation and puncture, EVs derived from CD4+ T cells also promoted tissue damage, oxidative stress, and inflammation in the lungs. These toxic effects of T cell-derived EVs were attenuated by the inhibition of PKC and NOX4, the downstream effectors of DGKK and DAG. CONCLUSIONS: This approach established the mechanism that T-cell-derived EVs carrying DGKK triggered alveolar epithelial cell apoptosis, oxidative stress, inflammation, and tissue damage in sepsis-induced lung injury through the DAG/PKC/NOX4 pathway. Thus, T-cell-derived EVs and the elevated distribution of DGKK should be further investigated to develop therapeutic strategies for sepsis-induced lung injury.

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.

A cross-sectional survey on the lung ultrasound training and practice of respiratory therapists in mainland China.

PURPOSE: This national study aimed to investigate the lung ultrasound (LUS) training and practice of respiratory therapists (RTs) in mainland China. METHODS: A cross-sectional multicenter survey was conducted from May 22, 2021 to August 12, 2021, through online platforms. This survey included RTs in mainland China. The survey was divided into four sections: (1) demographic characteristics and basic information; (2) basic information about LUS training and practice; (3) LUS practice details; and (4) Other ultrasound training and practice. RESULTS: A total of 514 responses were received, and 494 valid responses were included in the analysis. 81.2% (401/494) participants' highest degree of education was a bachelor's degree, and 43.1% (213/494) participants were at level II in terms of job ranking. 99.2%(490/494) participants agreed that the RTs needed to learn lung ultrasound, but only 12.3% (61/494) participants had received a LUS training course. Further, 66.2% (327/494) experienced participants responded to Sect. 3. Most of RTs used LUS when the patient had hypoxia (265/327, 81%) or dyspnea (260/317, 79.5%); they also used it during spontaneous breathing trial(SBT) (191/327, 58.4%) or in prone position (177/327, 54.1%). The A-line (302/327, 92.4%), B-line (299/327, 91.4%), lung slide (263/327, 80.4%), and bat sign (259/327, 79.2%) were well known as LUS signs. Also, 30.6% (100/327) participants did not use the LUS protocol in their clinical practice, and only 25.4%(83/327) participants said they had used LUS scores. Moreover, 55.7% (182/327) participants frequently changed the respiratory therapy strategy according to LUS results. CONCLUSIONS: We should improve the number and workplace of RTs in mainland China in the future. We should also standardize the application of LUS practice and training for RTs in mainland China and establish corresponding certification pathways.

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.

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.

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.

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 .

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.