Effectiveness and feasibility of 5G-based remote interactive ultrasound training in critical care.

BACKGROUND: Ultrasound has widely used in various medical fields related to critical care. While online and offline ultrasound trainings are faced by certain challenges, remote ultrasound based on the 5G cloud platform has been gradually adopted in many clinics. However, no study has used the 5G remote ultrasound cloud platform operating system for standardized critical care ultrasound training. This study aimed to evaluate the feasibility and effectiveness of 5G-based remote interactive ultrasound training for standardized diagnosis and treatment in critical care settings. METHODS: A 5G-based remote interactive ultrasound training system was constructed, and the course was piloted among critical care physicians. From July 2022 to July 2023, 90 critical care physicians from multiple off-site locations were enrolled and randomly divided into experimental and control groups. The 45 physicians in the experimental group were trained using the 5G-based remote interactive ultrasound training system, while the other 45 in the control group were taught using theoretical online videos. The theoretical and practical ultrasonic capabilities of both groups were evaluated before and after the training sessions, and their levels of satisfaction with the training were assessed as well. RESULTS: The total assessment scores for all of the physicians were markedly higher following the training (80.7 ± 11.9) compared to before (42.1 ± 13.4) by a statistically significant margin (P < 0.001). Before participating in the training, the experimental group scored 42.2 ± 12.5 in the critical care ultrasound competency, and the control group scored 41.9 ± 14.3-indicating no significant differences in their assessment scores (P = 0.907). After participating in the training, the experimental group's assessment scores were 88.4 ± 6.7, which were significantly higher than those of the control group (72.9 ± 10.8; P < 0.001). The satisfaction score of the experimental group was 42.6 ± 2.3, which was also significantly higher than that of the control group (34.7 ± 3.1, P < 0.001). CONCLUSION: The 5G-based remote interactive ultrasound training system was well-received and effective for critical care. These findings warrant its further promotion and application.

Machine learning-based prediction models affecting the recovery of postoperative bowel function for patients undergoing colorectal surgeries.

PURPOSE: The debate surrounding factors influencing postoperative flatus and defecation in patients undergoing colorectal resection prompted this study. Our objective was to identify independent risk factors and develop prediction models for postoperative bowel function in patients undergoing colorectal surgeries. METHODS: A retrospective analysis of medical records was conducted for patients who undergoing colorectal surgeries at Peking University People's Hospital from January 2015 to October 2021. Machine learning algorithms were employed to identify risk factors and construct prediction models for the time of the first postoperative flatus and defecation. The prediction models were evaluated using sensitivity, specificity, the Youden index, and the area under the receiver operating characteristic curve (AUC) through logistic regression, random forest, Naïve Bayes, and extreme gradient boosting algorithms. RESULTS: The study included 1358 patients for postoperative flatus timing analysis and 1430 patients for postoperative defecation timing analysis between January 2015 and December 2020 as part of the training phase. Additionally, a validation set comprised 200 patients who undergoing colorectal surgeries from January to October 2021. The logistic regression prediction model exhibited the highest AUC (0.78) for predicting the timing of the first postoperative flatus. Identified independent risk factors influencing the time of first postoperative flatus were Age (p < 0.01), oral laxatives for bowel preparation (p = 0.01), probiotics (p = 0.02), oral antibiotics for bowel preparation (p = 0.02), duration of operation (p = 0.02), postoperative fortified antibiotics (p = 0.02), and time of first postoperative feeding (p < 0.01). Furthermore, logistic regression achieved an AUC of 0.72 for predicting the time of first postoperative defecation, with age (p < 0.01), oral antibiotics for bowel preparation (p = 0.01), probiotics (p = 0.01), and time of first postoperative feeding (p < 0.01) identified as independent risk factors. CONCLUSIONS: The study suggests that he use of probiotics and early recovery of diet may enhance the recovery of bowel function in patients undergoing colorectal surgeries. Among the various analytical methods used, logistic regression emerged as the most effective approach for predicting the timing of the first postoperative flatus and defecation in this patient population.

Identification and validation of sepsis subphenotypes using time-series data.

Purpose: The recognition of sepsis as a heterogeneous syndrome necessitates identifying distinct subphenotypes to select targeted treatment. Methods: Patients with sepsis from the MIMIC-IV database (2008-2019) were randomly divided into a development cohort (80%) and an internal validation cohort (20%). Patients with sepsis from the ICU database of Peking University People's Hospital (2008-2022) were included in the external validation cohort. Time-series k-means clustering analysis and dynamic time warping was performed to develop and validate sepsis subphenotypes by analyzing the trends of 21 vital signs and laboratory indicators within 24 h after sepsis onset. Inflammatory biomarkers were compared in the ICU database of Peking University People's Hospital, whereas treatment heterogeneity was compared in the MIMIC-IV database. Findings: Three sub-phenotypes were identified in the development cohort. Type A patients (N = 2525, 47%) exhibited stable vital signs and fair organ function, type B (N = 1552, 29%) was exhibited an obvious inflammatory response and stable organ function, and type C (N = 1251, 24%) exhibited severely impaired organ function with a deteriorating tendency. Type C demonstrated the highest mortality rate (33%) and levels of inflammatory biomarkers, followed by type B (24%), whereas type A exhibited the lowest mortality rate (11%) and levels of inflammatory biomarkers. These subphenotypes were confirmed in both the internal and external cohorts, demonstrating similar features and comparable mortality rates. In type C patients, survivors had significantly lower fluid intake within 24 h after sepsis onset (median 2891 mL, interquartile range (IQR) 1530-5470 mL) than that in non-survivors (median 4342 mL, IQR 2189-7305 mL). For types B and C, survivors showed a higher proportion of indwelling central venous catheters (p < 0.05). Conclusion: Three novel phenotypes of patients with sepsis were identified and validated using time-series data, revealing significant heterogeneity in inflammatory biomarkers, treatments, and consistency across cohorts.

Urine-derived stem cells: Promising advancements and applications in regenerative medicine and beyond.

Currently, stem cells are a prominent focus of regenerative engineering research. However, due to the limitations of commonly used stem cell sources, their application in therapy is often restricted to the experimental stage and constrained by ethical considerations. In contrast, urine-derived stem cells (USCs) offer promising advantages for clinical trials and applications. The noninvasive nature of the collection process allows for repeated retrieval within a short period, making it a more feasible option. Moreover, studies have shown that USCs have a protective effect on organs, promoting vascular regeneration, inhibiting oxidative stress, and reducing inflammation in various acute and chronic organ dysfunctions. The application of USCs has also been enhanced by advancements in biomaterials technology, enabling better targeting and controlled release capabilities. This review aims to summarize the current state of research on USCs, providing insights for future applications in basic and clinical settings.

Phenotypes and Lung Microbiota Signatures of Immunocompromised Patients with Pneumonia-Related Acute Respiratory Distress Syndrome.

Objective: We aim to identify the clinical phenotypes of immunocompromised patients with pneumonia-related ARDS, to investigate the lung microbiota signatures and the outcomes of different phenotypes, and finally, to develop a machine learning classifier for a specified phenotype. Methods: This prospective study included immunocompromised patients with pneumonia-related ARDS. We identified phenotypes using hierarchical clustering to analyze clinical variables and serum cytokine levels. We then compared outcomes and lung microbiota signatures between phenotypes. Based on lung microbiota markers, we developed a random forest classifier for a specified phenotype with worse outcomes. Results: This study included 92 patients, who were divided into three phenotypes, namely "type α" (N = 33), "type ß" (N = 12), and "type γ" (N = 47). Compared to type α or type ß, patients with type γ had no obvious inflammatory presentation and had significantly lower IL-6 levels and more severe oxygenation failure. Type γ was also related to higher 30-day mortality and lower ventilator free days. The microbiota signatures of type γ were characterized by lower alpha diversity and distinct compositions than those of other patients. We developed a lung microbiota-derived random forest model to differentiate patients with type γ from other phenotypes. Conclusion: Immunocompromised patients with pneumonia-related ARDS can be clustered into three clinical phenotypes, namely type α, type ß, and type γ. Phenotypes were distinguished from each other with different outcomes and lung microbiota signatures. Type γ, which was characterized by insufficient inflammation response and worse outcomes, can be detected with a random forest model based on lung microbiota markers.

Risk factors and predictive model for mortality in patients undergoing allogeneic hematopoietic stem cell transplantation admitted to the intensive care unit.

Hematological malignant tumors represent a group of major diseases carrying a substantial risk to the lives of affected patients. Risk factors for mortality in critically ill patients have garnered substantial attention in recent research endeavors. The present research aimed to identify factors predicting intensive care unit (ICU) mortality in patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT). Furthermore, the present study analyzed and compared the mortality rate between patients undergoing haploidentical hematopoietic stem cell transplantation (Haplo-SCT) and those undergoing identical sibling donor (ISD) transplantation. A total of 108 patients were included in the present research, 83 (76.9%) of whom underwent Haplo-SCT. ICU mortality was reported in 58 (53.7%) patients, with the values of 55.4 and 48.0% associated with Haplo-SCT and ISD, respectively (P=0.514). The mortality rate of patients undergoing Haplo-SCT was comparable to that of patients undergoing ISD transplantation. The present study found that reduced hemoglobin, elevated total bilirubin, elevated brain natriuretic peptide, elevated fibrinogen degradation products, need for vasoactive drugs at ICU admission, need for invasive mechanical ventilation and elevated APACHE II scores were independent risk factors for ICU mortality. Among patients presenting with 5-7 risk factors, the ICU mortality reached 100%, significantly exceeding that of other patients. The present research revealed that ICU mortality rates remain elevated among patients who underwent allo-HSCT, especially those presenting multiple risk factors. However, the outcome of patients undergoing Haplo-SCT were comparable to those of patients undergoing ISD transplants.

Clinical Characteristics and Nomogram for Predicting Mortality in Patients with Postoperative Bloodstream Infection in Surgical Intensive Care Unit.

Background: Bloodstream infection is amongst the leading causes of mortality for critical postoperative patients. However, data, especially from developing countries, are scary. Clinical decision-making tools for predicting postoperative bloodstream infection-related mortality are important but still lacking. Objective: To analyze the distribution of pathogens and develop a nomogram for predicting mortality in patients with postoperative bloodstream infection in the surgical intensive care unit. Methods: The clinical data, infection and pathogen-related data, and prognosis of patients with PBSI in the SICU from January 2017 to January 2022 were retrospectively collected. The distribution of pathogens and clinical characteristics of patients with PBSI were analyzed. The patients were assigned to a died group and a survived group according to their survival status. Independent predictors for mortality were identified by univariate and multivariate analyses. A nomogram for predicting PBSI-related death was developed based on these independent predictors. Calibration and decision-curve analysis were established to evaluate the nomogram. We collected postoperative patients admitted to our center from February 2022 to June 2023 as external validation sets to verify the nomogram. We also add the Brier score to further validate the model. Results: In the training set, 7128 patients admitted to the SICU after different types of surgery were collected. A total of 198 patients and 308 pathogens were finally enrolled. The mean age of patients with PBSI was 64.38 ± 16.22 (range 18-90) years, and 56.1% were male. Forty-five patients (22.7%) died in the hospital. Five independent predictors including BMI, APACHE II score, estimated glomerular filtration rate (eGFR), urine volume in the first 24 hours after surgery, and peak temperature before positive blood cultures were selected to establish the nomogram. The area under the receiver operating characteristic curve for the prediction model was 0.922. Calibration curve and decision curve analysis showed good performance of the nomogram. Seventy patients with PBSI were collected as an external validation set, and thirteen patients died in this set. The external validation set was used to validate the nomogram, and the results showed that the AUC was 0.930 which was higher than that in the training set indicating that the nomogram had a good discrimination. The brier score was 0.087 for training set and 0.050 for validation set. Conclusions: PBSI was one of the key issues that clinicians were concerned and could be assessed with a good predictive model using simple clinical factors.

[Role of coagulation dysfunction in thrombocytopenia-related death in patients with septic shock].

OBJECTIVE: To explore the effect of thrombocytopenia on the prognosis of patients with septic shock and its mechanism in leading to death. METHODS: A retrospective case-control study was conducted. Patients with septic shock admitted to emergency intensive care unit (EICU) and intensive care unit (ICU) in Peking University People's Hospital from April 1, 2015 to January 31, 2023 were enrolled. Patients were divided into the thrombocytopenia group and the non-thrombocytopenia group, according to whether the minimum platelet count was less than 100×109/L within 24 hours after admission to ICU. The outcome index was the mortality during ICU stay. The baseline data, hospitalization information and laboratory test results of the two groups were compared, and the risk factors of in-hospital death were analyzed by Logistic regression, and the mediation effect was performed by Bootstrap method. RESULTS: A total of 301 patients with septic shock were enrolled, of which 172 (57.1%) had thrombocytopenia and 129 (42.9%) did not. There were significant differences between the two groups in age, mortality, disseminated intravascular coagulation (DIC), continuous renal replacement therapy, and level of creatinine, urea nitrogen, total bilirubin, white blood cell count, lymphocyte count, prothrombin time (PT) and activated partial thromboplastin time (APTT). Univariate Logistic regression analysis showed thrombocytopenia [odds ratio (OR) = 4.478], continuous renal replacement therapy (OR = 4.601), DIC (OR = 6.248), serum creatinine (OR = 1.005), urea nitrogen (OR = 1.126), total bilirubin (OR = 1.006) and PT (OR = 1.126) were risk factors of death during hospitalization in patients with septic shock (all P < 0.05). Multivariate Logistic regression analysis showed that thrombocytopenia [OR = 3.338, 95% confidence interval (95%CI) was 1.910-5.834, P = 0.000], continuous renal replacement therapy (OR = 3.175, 95%CI was 1.576-6.395, P = 0.001) and PT (OR = 1.077, 95%CI was 1.011-1.147, P = 0.021) were independent risk factors for in-hospital mortality in patients with septic shock. Mediation analysis showed that 51% of the deaths due to thrombocytopenia in patients with septic shock were due to coagulopathy. CONCLUSIONS: Thrombocytopenia is a powerful predictor of death in septic shock patients, and half of all thrombocytopenia-related deaths may be due to abnormal coagulation function.

[Stress hyperglycemia and nutritional therapy].

Stress induced hyperglycemia is the body's protect response against strong (patho-physiological and/or psychological) stress, sometimes the blood glucose level is too high due to out of the body's adjustment. Renal glucose threshold (about 9 mmol/L) is a window of glucose leak from capillary to interstitial tissue. It is important to keep blood glucose level < 9 mmol/L, for reducing vascular sclerosis as well as organs hypoperfusion, meanwhile pay attention to preventing more dangerous hypoglycemia. Glucose, as the main energy substrate, should be daily supply and its metabolism should be monitored. We used to talk "nutritional support". Support is conform the physiological ability of host, but therapy is to coordinate and change pathophysiology. So, nutritional support is not equal to nutritional therapy. For critical ill patients, we need to emphasize "nutritional therapy", i.e, do not give nutritional treatment without metabolic monitoring, make up for deficiencies and avoid metabolites overloading, rational adjustment to protect and coordinate organs function.

Efficacy and Safety of Ciprofol Sedation in ICU Patients Undergoing Mechanical Ventilation: A Multicenter, Single-Blind, Randomized, Noninferiority Trial.

OBJECTIVES: To determine the effectiveness and safety of ciprofol for sedating patients in ICUs who required mechanical ventilation (MV). DESIGN: A multicenter, single-blind, randomized, noninferiority trial. SETTING: Twenty-one centers across China from December 2020 to June 2021. PATIENTS: A total of 135 ICU patients 18 to 80 years old with endotracheal intubation and undergoing MV, who were expected to require sedation for 6-24 hours. INTERVENTIONS: One hundred thirty-five ICU patients were randomly allocated into ciprofol ( n = 90) and propofol ( n = 45) groups in a 2:1 ratio. Ciprofol or propofol were IV infused at loading doses of 0.1 mg/kg or 0.5 mg/kg, respectively, over 4 minutes ± 30 seconds depending on the physical condition of each patient. Ciprofol or propofol were then immediately administered at an initial maintenance dose of 0.3 mg/kg/hr or 1.5 mg/kg/hr, to achieve the target sedation range of Richmond Agitation-Sedation Scale (+1 to -2). Besides, continuous IV remifentanil analgesia was administered (loading dose: 0.5-1 µg/kg, maintenance dose: 0.02-0.15 µg/kg/min). MEASUREMENTS AND MAIN RESULTS: Of the 135 patients enrolled, 129 completed the study. The primary endpoint-sedation success rates of ciprofol and propofol groups were 97.7% versus 97.8% in the full analysis set (FAS) and were both 100% in per-protocol set (PPS). The noninferiority margin was set as 8% and confirmed with a lower limit of two-sided 95% CI for the inter-group difference of -5.98% and -4.32% in the FAS and PPS groups. Patients who received ciprofol had a longer recovery time ( p = 0.003), but there were no differences in the remaining secondary endpoints (all p > 0.05). The occurrence rates of treatment-emergent adverse events (TEAEs) or drug-related TEAEs were not significantly different between the groups (all p > 0.05). CONCLUSIONS: Ciprofol was well tolerated, with a noninferior sedation profile to propofol in Chinese ICU patients undergoing MV for a period of 6-24 hours.

Risk factors and predictive model for pulmonary complications in patients transferred to ICU after hepatectomy.

OBJECTIVE: Postoperative pulmonary complications (PPCs) seriously harm the recovery and prognosis of patients undergoing surgery. However, its related risk factors in critical patients after hepatectomy have been rarely reported. This study aimed at analyzing the factors related to PPCs in critical adult patients after hepatectomy and create a nomogram for prediction of the PPCs. METHODS: 503 patients' data were collected form the Peking University People's Hospital. Multivariate logistic regression analysis was used to identify independent risk factors to derive the nomogram. Nomogram's discriminatory ability was assessed using the area under the receiver operating characteristic curve (AUC), and calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test and calibration curve. RESULTS: The independent risk factor for PPCs are advanced age (odds ratio [OR] = 1.026; P = 0.008), higher body mass index (OR = 1.139; P < 0.001), lower preoperative serum albumin level (OR = 0.961; P = 0.037), and intensive care unit first day infusion volume (OR = 1.152; P = 0.040). And based on this, we created a nomogram to predict the occurrence of PPCs. Upon assessing the nomogram's predictive ability, the AUC for the model was 0.713( 95% CI: 0.668-0.758, P<0.001). The Hosmer-Lemeshow test (P = 0.590) and calibration curve showed good calibration for the prediction of PPCs. CONCLUSIONS: The prevalence and mortality of postoperative pulmonary complications in critical adult patients after hepatectomy are high. Advanced age, higher body mass index, lower preoperative serum albumin and intensive care unit first day infusion volume were found to be significantly associated with PPCs. And we created a nomogram model which can be used to predict the occurrence of PPCs.

Atrial Fibrillation (AFIB) in the ICU: Incidence, Risk Factors, and Outcomes: The International AFIB-ICU Cohort Study.

OBJECTIVES: To assess the incidence, risk factors, and outcomes of atrial fibrillation (AF) in the ICU and to describe current practice in the management of AF. DESIGN: Multicenter, prospective, inception cohort study. SETTING: Forty-four ICUs in 12 countries in four geographical regions. SUBJECTS: Adult, acutely admitted ICU patients without a history of persistent/permanent AF or recent cardiac surgery were enrolled; inception periods were from October 2020 to June 2021. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We included 1,423 ICU patients and analyzed 1,415 (99.4%), among whom 221 patients had 539 episodes of AF. Most (59%) episodes were diagnosed with continuous electrocardiogram monitoring. The incidence of AF was 15.6% (95% CI, 13.8-17.6), of which newly developed AF was 13.3% (11.5-15.1). A history of arterial hypertension, paroxysmal AF, sepsis, or high disease severity at ICU admission was associated with AF. Used interventions to manage AF were fluid bolus 19% (95% CI 16-23), magnesium 16% (13-20), potassium 15% (12-19), amiodarone 51% (47-55), beta-1 selective blockers 34% (30-38), calcium channel blockers 4% (2-6), digoxin 16% (12-19), and direct current cardioversion in 4% (2-6). Patients with AF had more ischemic, thromboembolic (13.6% vs 7.9%), and severe bleeding events (5.9% vs 2.1%), and higher mortality (41.2% vs 25.2%) than those without AF. The adjusted cause-specific hazard ratio for 90-day mortality by AF was 1.38 (95% CI, 0.95-1.99). CONCLUSIONS: In ICU patients, AF occurred in one of six and was associated with different conditions. AF was associated with worse outcomes while not statistically significantly associated with 90-day mortality in the adjusted analyses. We observed variations in the diagnostic and management strategies for AF.

Prognostic factors for patients with hematologic malignancies admitted to the intensive care unit: is allogeneic transplantation still a risk factor?

The rate of intensive care unit (ICU) mortality in patients with hematologic malignancies is high. The risk factors for this were inconsistent across several previous studies, and there is currently no accepted consensus around risk factors for these patients. We aimed to identify which prognostic factors were associated with ICU mortality in critically ill patients with hematologic malignancies, nearly half of which were allogeneic hematopoietic stem cell transplantation (allo-HSCT) recipients. In addition, we aimed to compare the characteristics and clinical outcomes of patients with and without allogenic allo-HSCT. In total, 217 patients with hematologic malignancies were enrolled consecutive, 119 (54.8%) of whom underwent HSCT (allo-HSCT: n = 115). All survivors were followed up with until August 1, 2022. The rate of ICU mortality in this cohort was 54.4%: 55.5 and 53.1% for the patients with and without HSCT, respectively (p = 0.724). The probabilities of survival after ICU admission were also comparable between the patients who had allo-HSCT and those who did not. A multivariable analysis revealed that cerebrovascular disease, hyperlactic acidemia on the day of ICU admission, lower platelet count, use of vasoactive drugs, and absence of noninvasive ventilation on the day of ICU admission were independent risk factors for ICU mortality. For patients with three to five of these risk factors, the rate of ICU mortality was as high as 84.6%, which was significantly higher than that of other patients. In this study, the ICU mortality rate in patients with hematologic malignancies was still high, particularly for those with multiple risk factors. However, allo-HSCT was not found to be a risk factor for ICU mortality.

Predictors for adverse events during cardiac lead extraction - Experience from a large single centre.

BACKGROUND: As the use of cardiac implantable electronic devices (CIED) has increased in recent years, the need for transvenous lead extraction (TLE) has also steadily increased. However, the TLE procedure could lead to serious complications and even death. Clinical decision-making tools are necessary for predicting these adverse events, but the appropriate tools have not yet been developed. OBJECTIVE: To explore the possible predictors and develop a clinical model to predict TLE related adverse events. METHODS: All the patients who were admitted to our cardiac center for TLE from January 2014 to January 2021 were included in this study. The patient information, device baseline characteristics, procedure-related information, complications and outcomes were recorded. Independent predictors of TLE related adverse events were identified by univariate, LASSO and multivariate analysis. A nomogram for predicting these adverse events was developed based on these independent predictors. Calibration and decision curve analysis were conducted to evaluate the nomogram. RESULTS: One thousand and one hundred patients were included in this study, 778 (70.7%) were male and the median age was 68 years old. A total of 2,208 leads were extracted and 2.01±0.74 leads were extracted per procedure. Fifty-five patients (5%) developed adverse events including minor complications (2.4%), major complications (2.3%) and death (0.27%). Seven independent predictors for TLE related adverse events were identified and selected to establish the nomogram including BMI, female gender, hypoalbuminemia, number of extracted leads>3, longest dwell time of the extracted leads and manual traction. The area under the receiver operating characteristic (ROC) curve (AUC) for the prediction model was 0.774. Calibration curve and decision curve analysis showed that the nomogram had good prediction performance. CONCLUSION: TLE related adverse events are some of the key issues that concern clinicians. We have identified seven independent factors and established a predictive model that may help clinicians identify at-risk patients and create better plans for lead extraction.

Xuebijing Administration Alleviates Pulmonary Endothelial Inflammation and Coagulation Dysregulation in the Early Phase of Sepsis in Rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Xuebijing injection is a Chinese herbal-derived drug composed of radix paeoniaerubra, rhizomachuanxiong, Salvia miltiorrhiza, floscarthami, and Angelica sinensis. This study aimed to investigate the effects of Xuebijing administration on pulmonary endothelial injury and coagulation dysfunction in a cecal ligation and puncture (CLP)-induced sepsis rat model. MATERIALS AND METHODS: A CLP-induced sepsis rat model was established. The CLP rats were treated with a vehicle or Xuebijing via intravenous infusion and sacrificed at 2, 4, 6, 8, or 12 h after CLP for lung tissue and blood sample collection. The mean arterial pressure (MAP) was monitored. Transmission microscopy examination and H&E staining were performed to observe pulmonary structural alterations. Enzyme linked immunosorbent assay (ELISA) was performed to measure the plasma levels of epithelial markers, proinflammatory cytokines, and coagulation-related proteins. RESULTS: Compared with vehicle treatment, Xuebijing administration maintained the MAP in the normal range until 11 h after CLP. Transmission microscopy and H&E staining revealed that Xuebijing administration alleviated alveolar-capillary barrier impairments and lung inflammation in CLP rats. ELISA showed that Xuebijing administration effectively reversed CLP-induced elevations in the plasma levels of epithelial markers endothelin-1 and von Willebrand factor, starting 6 and 8 h after CLP, respectively. Xuebijing administration also significantly abolished CLP-induced rises in circulating proinflammatory cytokines interleukin 6 (IL-6) at 6 h after CLP, IL-1ß at 2 and 12 h after CLP, and TNF-α at 2, 4, 6, 8, and 12 h after CLP. In addition, Xuebijing administration strongly reversed CLP-induced alterations in circulating active protein C and tissue-type plasminogen activator, starting 4 h and 2 h after CLP, respectively. CONCLUSIONS: Xuebijing ameliorates pulmonary endothelial injury, systemic inflammation, and coagulation dysfunction in early sepsis.

Derivation and validation of a prediction score for postoperative delirium in geriatric patients undergoing hip fracture surgery or hip arthroplasty.

Introduction: Postoperative delirium is a common complication of patients undergoing hip fracture surgery or arthroplasty and is related to decreased survival time and physical function. In this study, we aim to build and validate a prediction score of postoperative delirium in geriatric patients undergoing hip fracture surgery or hip arthroplasty. Methods: A retrospective cohort of geriatric patients undergoing hip fracture surgery or hip arthroplasty was established. Variables of included patients were collected as candidate predictors of postoperative delirium. The least absolute shrinkage and selection operator (LASSO) regression and logistic regression were used to derive a predictive score for postoperative delirium. The accuracy of the score was evaluated by the area under the curve (AUC) of the receiver operating curve (ROC). We used bootstrapping resamples for model calibration. The prediction score was validated in an extra cohort. Results: There were 1,312 patients in the derivation cohort, and the incidence of postoperative delirium was 14.33%. Of 40 variables, 9 were identified as predictors, including preoperative delirium, cerebrovascular accident (CVA) with the modified Rankin scale, diabetes with a random glucose level, Charlson comorbidity index (CCI), age, application of benzodiazepines in surgery, surgical delay ≥2 days, creatine ≥90 µmol/L, and active smoker. The prediction score achieved a mean AUC of 0.848 in the derivation cohort. In the validation cohort, the mean AUC was 0.833. The prediction model was well-calibrated in the two cohorts. Conclusion: Based on retrospective data, a prediction score for postoperative delirium in geriatric patients undergoing hip fracture surgery or hip arthroplasty was derived and validated. The performance of the scoring system outperformed the models from previous studies. Although the generalization ability of the score needs to be tested in similar populations, the scoring system will enable delirium risk stratification for hip fracture patients and facilitate the development of strategies for delirium prevention.