Predictive performance of two types of urinary biomarkers for renal non-recovery in sepsis-associated acute kidney injury: a prospective observational study.

BACKGROUND AND PURPOSE: Renal non-recovery is known to have negative prognostic implications in patients suffering from acute kidney injury (AKI). Nevertheless, the identification of biomarkers for predicting renal non-recovery in sepsis-associated AKI (SA-AKI) within clinical settings remains unresolved. This study aims to evaluate and compare the predictive ability for renal non-recovery, use of kidney replacement therapy (KRT) in the Intensive Care Unit (ICU), and 30-day mortality after SA-AKI by two urinary biomarkers, namely C-C motif chemokine ligand 14 (CCL14) and [TIMP-2]•[IGFBP7]. METHODS: We prospectively screened adult patients who met the criteria for AKI stage 2-3 and Sepsis-3.0 in two ICUs from January 2019 to May 2022. Patients who developed new-onset SA-AKI after ICU admission were enrolled and urinary biomarkers including [TIMP-2]•[IGFBP7] and CCL14 were detected at the time of SA-AKI diagnosis. The primary endpoint was non-recovery from SA-AKI within 7 days. The secondary endpoints were the use of KRT in the ICU and 30-day mortality after SA-AKI. The individual discriminative ability of [TIMP-2]•[IGFBP7] and CCL14 to predict renal non-recovery were evaluated by the area under receiver operating characteristics curve (AUC). RESULTS: 141 patients with stage 2-3 SA-AKI were finally included, among whom 54 (38.3%) experienced renal non-recovery. Urinary CCL14 exhibited a higher predictive capability for renal non-recovery compared to [TIMP-2]•[IGFBP7], with CCL14 showing an AUC of 0.901, versus an AUC of 0.730 for [TIMP-2]•[IGFBP7] (P = 0.001). Urinary CCL14 and [TIMP-2]•[IGFBP7] demonstrated a moderate predictive value for the need for KRT in ICU, with AUC values of 0.794 and 0.725, respectively; The AUC of [TIMP-2]•[IGFBP7] combined with CCL14 reached up to 0.816. Urinary CCL14 and [TIMP-2]•[IGFBP7] exhibited poor predictive power for 30-day mortality, with respective AUC values of 0.623 and 0.593. CONCLUSION: Urinary CCL14 had excellent predictive value for renal non-recovery in SA-AKI patients. For predicting the use of KRT in the ICU, the predictive capability of urinary [TIMP-2]•[IGFBP7] or CCL14 was fair. However, a combination of [TIMP-2]•[IGFBP7] and CCL14 showed good predictive ability for the use of KRT.

Sagittal balance parameters measurement on cervical spine MR images based on superpixel segmentation.

Introduction: Magnetic Resonance Imaging (MRI) is essential in diagnosing cervical spondylosis, providing detailed visualization of osseous and soft tissue structures in the cervical spine. However, manual measurements hinder the assessment of cervical spine sagittal balance, leading to time-consuming and error-prone processes. This study presents the Pyramid DBSCAN Simple Linear Iterative Cluster (PDB-SLIC), an automated segmentation algorithm for vertebral bodies in T2-weighted MR images, aiming to streamline sagittal balance assessment for spinal surgeons. Method: PDB-SLIC combines the SLIC superpixel segmentation algorithm with DBSCAN clustering and underwent rigorous testing using an extensive dataset of T2-weighted mid-sagittal MR images from 4,258 patients across ten hospitals in China. The efficacy of PDB-SLIC was compared against other algorithms and networks in terms of superpixel segmentation quality and vertebral body segmentation accuracy. Validation included a comparative analysis of manual and automated measurements of cervical sagittal parameters and scrutiny of PDB-SLIC's measurement stability across diverse hospital settings and MR scanning machines. Result: PDB-SLIC outperforms other algorithms in vertebral body segmentation quality, with high accuracy, recall, and Jaccard index. Minimal error deviation was observed compared to manual measurements, with correlation coefficients exceeding 95%. PDB-SLIC demonstrated commendable performance in processing cervical spine T2-weighted MR images from various hospital settings, MRI machines, and patient demographics. Discussion: The PDB-SLIC algorithm emerges as an accurate, objective, and efficient tool for evaluating cervical spine sagittal balance, providing valuable assistance to spinal surgeons in preoperative assessment, surgical strategy formulation, and prognostic inference. Additionally, it facilitates comprehensive measurement of sagittal balance parameters across diverse patient cohorts, contributing to the establishment of normative standards for cervical spine MR imaging.

Attributable mortality of acute kidney injury among critically ill patients with sepsis: a multicenter, retrospective cohort study.

BACKGROUND: Sepsis and acute kidney injury (AKI) are common severe diseases in the intensive care unit (ICU). This study aimed to estimate the attributable mortality of AKI among critically ill patients with sepsis and to assess whether AKI was an independent risk factor for 30-day mortality. METHODS: The information we used was derived from a multicenter prospective cohort study conducted in 18 Chinese ICUs, focusing on septic patients post ICU admission. The patients were categorized into two groups: those who developed AKI (AKI group) within seven days following a sepsis diagnosis and those who did not develop AKI (non-AKI group). Using propensity score matching (PSM), patients were matched 1:1 as AKI and non-AKI groups. We then calculated the mortality rate attributable to AKI in septic patients. Furthermore, a survival analysis was conducted comparing the matched AKI and non-AKI septic patients. The primary outcome of interest was the 30-day mortality rate following the diagnosis of sepsis. RESULTS: Out of the 2175 eligible septic patients, 61.7% developed AKI. After the application of PSM, a total of 784 septic patients who developed AKI were matched in a 1:1 ratio with 784 septic patients who did not develop AKI. The overall 30-day attributable mortality of AKI was 6.6% (95% CI 2.3 ∼ 10.9%, p = 0.002). A subgroup analysis revealed that the 30-day attributable mortality rates for stage 1, stage 2, and stage 3 AKI were 0.6% (95% CI -5.9 ∼ 7.2%, p = 0.846), 4.7% (95% CI -3.1 ∼ 12.4%, p = 0.221) and 16.8% (95% CI 8.1 ∼ 25.2%, p < 0.001), respectively. Particularly noteworthy was that stage 3 AKI emerged as an independent risk factor for 30-day mortality, possessing an adjusted hazard ratio of 1.80 (95% CI 1.31 ∼ 2.47, p < 0.001). CONCLUSIONS: The overall 30-day attributable mortality of AKI among critically ill patients with sepsis was 6.6%. Stage 3 AKI had the most significant contribution to 30-day mortality, while stage 1 and stage 2 AKI did not increase excess mortality.

Attributable mortality of ARDS among critically ill patients with sepsis: a multicenter, retrospective cohort study.

BACKGROUND: Both sepsis and acute respiratory distress syndrome (ARDS) are common severe diseases in the intensive care unit (ICU). There is no large-scale multicenter study to clarify the attributable mortality of ARDS among septic patients. This study aimed to evaluate the excess mortality of ARDS in critically ill patients with sepsis. METHODS: The data were obtained from a multicenter, prospective cohort study in 18 Chinese ICUs between January 2014 and August 2015. The study population was septic patients after ICU admission. The patients were categorized into two groups: those who developed ARDS (ARDS group) within seven days following a sepsis diagnosis and those who did not develop ARDS (non-ARDS group). Applying propensity score matching (PSM), patients were matched 1:1 as ARDS and non-ARDS groups. Mortality attributed to ARDS was calculated. Subsequently, we conducted a survival analysis to estimate the impact of ARDS on mortality. The primary endpoint was 30-day mortality after sepsis diagnosis. RESULTS: 2323 septic patients were eligible, 67.8% developed ARDS. After PSM, 737 patients with ARDS were matched 1:1 with 737 non-ARDS patients. ARDS's overall 30-day attributable mortality was 11.9% (95% CI 7.5-16.3%, p < 0.001). Subgroup analysis showed that the 30-day attributable mortality of mild, moderate, and severe ARDS was 10.5% (95% CI 4.0-16.8%, p < 0.001), 11.6% (95% CI 4.7-18.4%, p < 0.001) and 18.1% (95% CI 4.5-30.9%, p = 0.006), respectively. ARDS was an independent risk factor for 30-day mortality, with adjusted hazard ratios of 1.30 (95% CI 1.03-1.64, p = 0.027), 1.49 (95% CI 1.20-1.85, p < 0.001), and 1.95 (95% CI 1.51-2.52, p < 0.001) for mild, moderate, and severe ARDS, respectively. CONCLUSIONS: The overall 30-day attributable mortality of ARDS among critically ill patients with sepsis was 11.9%. Compared with mild and moderate ARDS, severe ARDS contributed more to death. ARDS was significantly associated with an increase in the 30-day mortality.

Association between the levels of urinary cell cycle biomarkers and non-recovery of renal function among critically ill geriatric patients with acute kidney injury.

The lack of early renal function recovery among geriatric patients with acute kidney injury (AKI) in the intensive care unit (ICU) is a commonly observed and acknowledged poor prognostic factor, especially for older adults. However, no reliable prognostic biomarker is available for identifying individuals at risk of renal non-recovery or mortality in older adults. In this prospective observational cohort study, we enrolled critically ill older adults (aged ≥ 60 years) with AKI from the ICU and followed their disease progression. The primary endpoint was renal non-recovery within seven days of follow-up, while the secondary endpoint was the determinants of 30-day mortality after AKI. We assessed the predictive accuracy using receiver operating characteristic curves and performed between-group comparisons using the log-rank test. Among 209 older adults, 117 (56.0%) experienced renal recovery. Multiple regression analysis revealed that urine levels of tissue inhibitor of metalloproteinase-2 (TIMP-2) multiplied by insulin-like growth factor-binding protein 7 (IGFBP7) ([TIMP-2]*[IGFBP7]), AKI stages 2-3, and the Acute Physiology and Chronic Health Evaluation (APACHE II) score were independently associated with renal non-recovery. The regression model incorporating [TIMP-2]*[IGFBP7] demonstrated a fair predictive value (AUC 0.774, p < 0.001), with the optimal threshold set at 0.81 (ng/mL)2/1000. When [TIMP-2]*[IGFBP7] was combined with AKI severity and the APACHE score, the AUC increased to 0.851. In conclusion, urine [TIMP-2]*[IGFBP7] is a reliable biomarker associated with renal non-recovery in critically ill older adults, and its predictive efficacy can be further enhanced when combined with AKI severity and the APACHE score.

A shock flash breaking out of a dusty red supergiant.

Shock-breakout emission is light that arises when a shockwave, generated by the core-collapse explosion of a massive star, passes through its outer envelope. Hitherto, the earliest detection of such a signal was at several hours after the explosion1, although a few others had been reported2-7. The temporal evolution of early light curves should provide insights into the shock propagation, including explosion asymmetry and environment in the vicinity, but this has been hampered by the lack of multiwavelength observations. Here we report the instant multiband observations of a type II supernova (SN 2023ixf) in the galaxy M101 (at a distance of 6.85 ± 0.15 Mpc; ref. 8), beginning at about 1.4 h after the explosion. The exploding star was a red supergiant with a radius of about 440 solar radii. The light curves evolved rapidly, on timescales of 1-2 h, and appeared unusually fainter and redder than predicted by the models9-11 within the first few hours, which we attribute to an optically thick dust shell before it was disrupted by the shockwave. We infer that the breakout and perhaps the distribution of the surrounding dust were not spherically symmetric.

Postoperative plasma presepsin as a biomarker of postoperative infectious complications in different surgical departments: A meta-analysis and systematic review.

BACKGROUND: High rates of postoperative infection persist after different surgical procedures, encompassing surgical site infections (SSIs), remote infections, sepsis, and septic shock. Our aim was to assess presepsin's diagnostic accuracy for postoperative infections in patients across surgical procedures. METHOD: We conducted a comprehensive search in seven databases, extracting data independently. Using STATA 14.0, we calculated pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and Under the receiver operator curve and 95 â€‹% confidence interval (AUC, 95 â€‹% CI) as primary outcomes, with secondary outcomes involving sensitivity and specificity in subgroup analyses. RESULTS: This meta-analysis of 14 studies (1891 cases) evaluated presepsin's diagnostic value for postoperative infectious complications. Results include sensitivity of 77 â€‹% (70-83), specificity of 81 â€‹% (71-88), DOR of 14 (8-26), AUC of 84 (80-87), PLR of 4 (3-6), and NLR of 0.28 (0.21-0.38). Presepsin exhibits promise as a diagnostic tool for postoperative infections. CONCLUSION: In summary, compared to conventional markers like C-reactive protein (CRP) and procalcitonin (PCT), presepsin demonstrated superior sensitivity and specificity for detecting postoperative infectious complications across various surgical procedures.

Diagnostic Accuracy of Procalcitonin for Infection After Adult Liver Transplantation: A Meta-Analysis and Systematic Review.

Background: Post-operative infection remains a major cause of morbidity and mortality in adults early after liver transplantation (LT). Procalcitonin (PCT) may be a good test method for early diagnosis of post-operative infection and determining its severity. This study was performed to assess the diagnostic accuracy of PCT as a biomarker for infection after LT. Patients and Methods: A meta-analysis and systematic review was conducted for studies reporting diagnostic performance of PCT for infection in adults after LT. Observational studies were evaluated for their reporting of diagnostic accuracy, relevance, and quality. Results: Ten eligible studies assessing 730 patients were included in this meta-analysis and systematic review summarizing the diagnostic value of PCT for post-operative infection in adult liver transplantation. Pooled sensitivity and specificity with corresponding 95% confidence interval were 69% (95% confidence interval [CI], 54-81; heterogeneity I2 = 82.4%) and 88% (95% CI, 82-92; I2 = 52.7%), respectively. The diagnostic odd ratio (DOR) was 16 (95% CI, 10-25; I2 = 76.4%). The summary receiver operator characteristic (SROC) of PCT for post-operative infection was 0.88. There was a wide range of variability in the cutoff values, ranging from 0.22 to 42.80 ng/mL. Heterogeneity was reduced by excluding studies that focused on pediatric LT recipients. Conclusions: Procalcitonin is a moderately accurate diagnostic marker for post-operative infection in adult LT. Additionally, the diagnostic performance can be improved by combining it with other inflammatory biomarkers. This article provides the research direction for post-operative infection control.

Urinary cell cycle biomarkers for the prediction of renal non-recovery in patients with septic acute kidney injury: a prospective study.

BACKGROUND: Poor prognosis has been associated with the absence of renal recovery after acute kidney injury (AKI). This study aimed to investigate whether urinary biomarkers at 0 and 24 h could be used independently or in conjunction with a clinical model to predict renal non-recovery in septic AKI. METHODS: A prospective observational study was conducted to measure the urinary levels of insulin-like growth factor-binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinase-2 (TIMP-2) at the time of AKI diagnosis (0 h) and 24 h later. Renal non-recovery within 7 days was defined as the outcome. The predictive value of urinary biomarkers for renal non-recovery in septic AKI was assessed using the area under the curve (AUC). RESULTS: A total of 198 individuals with septic AKI were included in the final analysis. Among them, 38.9% (n = 77) did not experience renal recovery within 7 days. The combination of urinary IGFBP7 and TIMP-2 at the initial time point demonstrated prognostic value for non-recovery of renal function, with an AUC of 0.782. When [TIMP-2]*[IGFBP7] was measured at 0 h, the clinical prognostic model, incorporating AKI stage 2-3 and the non-renal sequential organ failure assessment score, showed an improved AUC of 0.822 (with a sensitivity of 88.3% and specificity of 59.5%). CONCLUSIONS: The combination of urinary [TIMP-2]*[IGFBP7] at 0 h exhibited moderate predictive ability for renal non-recovery in cases of septic AKI. However, there is potential to enhance the prognostic capabilities of the [TIMP-2]*[IGFBP7]-clinical prediction model.

Predictive Value of Perioperative Cardiac Troponin I in Patients Undergone Liver Transplantation: A Retrospective Cohort Study.

Objective: To examine the change rule and clinical significance of cardiac troponin I (cTnI) in the perioperative period of liver transplantation in adults, as well as its association with 28-day mortality. Methods: This was a retrospective cohort study: patients who underwent elective orthotopic liver transplantation (OLT) in Beijing Chao-Yang Hospital between June 2015 and June 2020 were selected, and plasma cTnI values were collected through the electronic medical record system within 7 days after surgery. Furthermore, the baseline clinical data of these patients were collected, and the change curve of cTnI values following liver transplantation was plotted. Using univariate and multivariate logistic regression models, the relationship between the level of postoperative cTnI and short-term mortality was investigated. The primary study endpoint was mortality within 28 days after surgery. Results: We included 414 patients who had undergone liver transplantation in this study, 48 of whom died within 28 days after surgery. cTnI, a specific marker of myocardial injury, could predict that the postoperative cardiovascular complications were higher in the death group and significantly affect the short-term prognosis of patients; however, its prognostic cut-off value was approximately 0.545 ng/mL (13×URL), indicating that a minor elevation of cTnI after liver transplantation did not significantly affect the prognosis. Moreover, a comparison of the baseline data and postoperative ICU management scores of the two groups revealed that diabetes, maximum value of cTnI >0.545 ng/mL within 7 days, and the need for postoperative renal replacement therapy (RRT) were independent prognostic factors of death within 28 days after liver transplantation. Conclusion: Within 7 days after surgery, an increase in cTnI to the maximum value of 0.545 ng/mL (13×URL) could have a significant impact on the short-term prognosis of patients. Diabetes and postoperative RRT were two independent prognostic factors for liver transplantation perioperative mortality.

Neutrophil-lymphocyte ratio as a predictive marker for postoperative infectious complications: A systematic review and meta-analysis.

Objective: Postoperative infection is a common but costly complication. The neutrophil-lymphocyte ratio is a promising marker for the identification of postsurgical infectious events. We aimed to perform this meta-analysis to assessed the accuracy of the neutrophil-lymphocyte ratio for the prediction of postsurgical infection. Methods: We searched PubMed, Embase, Web of Science, and Cochrane Library without language restriction from their inceptions to April 2022, and checked reference lists of included studies. Studies were included if they assessed predictive accuracy of neutrophil-lymphocyte ratio for postsurgical infection. We estimated its predictive value and explored the source of heterogeneity. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess methodological quality and the Deeks' test to evaluate publication bias. The bivariate model and hierarchical summary receiver operating characteristic (HSROC) curve were used for meta-analysis and generated a summary receiver operating characteristic space (ROC) curve. Results: Our search returned 379 reports, of which 12 fulfilled the inclusion criteria, accounting for 4375 cases. The bivariate analysis yielded a pooled sensitivity of 0.77 (95%C.I.: 0.65-0.85) and specificity of 0.78 (95%C.I.: 0.67-0.86). Pooled positive LR and negative LR were 3.48 (95%C.I.: 2.26-5.36) and 0.30 (95%C.I.: 0.20-0.46), respectively. A negative LR of 0.30 reduces the post-test probability to 2% for a negative test result. The area under of receiver operating characteristic curve was 0.84 (95%C.I.: 0.80-0.87). Subgroups comparisons revealed difference by study design, surgical site, presentence of implant, time of sampling, type of infection event and prevalence of infection. The Deeks' test showed no publication bias. The sensitivity analysis showed no study affected the robustness of combined results. Conclusions: Low-certainty evidence suggests that the neutrophil-lymphocyte ratio is a helpful marker for predicting postoperative infectious complication. The negative predictive value of the neutrophil-lymphocyte ratio enables for reliable exclusion of postoperative infection.Trial registrationPROSPERO registration number CRD42022321197. Registered on 27 April 2022.

Association of Mitral Regurgitation with Postoperative Atrial Fibrillation in Critically Ill Noncardiac Surgery Patients: A Prospective Cohort Study.

Purpose: Atrial fibrillation (AF) is common in critically ill patients and can have serious consequences. Postoperative AF (POAF) in critically ill patients following noncardiac surgery has been understudied, contrary to cardiac procedures. Mitral regurgitation (MR) is associated with left ventricular dysfunction, which might contribute to the occurrence of AF in postoperative critically ill patients. This study aimed to investigate the association between MR and POAF in critically ill noncardiac surgery patients and establish a new nomogram for the prediction of POAF in critically ill noncardiac surgery patients. Patients and Methods: A prospective cohort of 2474 patients who underwent thoracic and general surgery was enrolled in this study. Data on preoperative transthoracic echocardiography (TTE), electrocardiogram (ECG), and several commonly utilized scoring systems (CHA2DS2-VASc, HATCH, COM-AF, HART, and C2HEST) and baseline clinical data were collected. Independent predictors were selected by univariate and multivariable logistic regression analysis, and a nomogram was constructed for POAF within 7 days after postoperative intensive care unit (ICU) admission. The ability of the MR-nomogram and other scoring systems to predict POAF was compared by receiver operator characteristic (ROC) curve analysis and decision curve analysis (DCA). Additional contributions were evaluated by integrated discrimination improvement (IDI) and net reclassification improvement (NRI) analysis. Results: A total of 213 (8.6%) patients developed POAF within 7 days after ICU admission. Compared to CHA2DS2-VASc, HATCH, COM-AF, HART, and C2HEST scoring systems, MR-nomogram showed better predictive ability for POAF with an area under the ROC curve of 0.824 (95% confidence interval: 0.805-0.842, p < 0.001). The improvement of the MR-nomogram in predictive value was supported by NRI and IDI analysis. The net benefit of the MR nomogram was maximal in DCA. Conclusion: MR is an independent risk factor of POAF in critically ill noncardiac surgery patients. The nomogram predicted POAF better than other scoring systems.

Analysis of urinary C-C motif chemokine ligand 14 (CCL14) and first-generation urinary biomarkers for predicting renal recovery from acute kidney injury: a prospective exploratory study.

BACKGROUND: Acute kidney injury (AKI) is a frequent syndrome in the intensive care unit (ICU). AKI patients with kidney function recovery have better short-term and long-term prognoses compared with those with non-recovery. Numerous studies focus on biomarkers to distinguish them. To better understand the predictive performance of urinary biomarkers of renal recovery in patients with AKI, we evaluated C-C motif chemokine ligand 14 (CCL14) and two first-generation biomarkers (cell cycle arrest biomarkers and neutrophil gelatinase-associated lipocalin) in two ICU settings. METHODS: We performed a prospective study to analyze urinary biomarkers for predicting renal recovery from AKI. Patients who developed AKI after ICU admission were enrolled and urinary biomarkers including tissue inhibitor of metalloproteinase-2 (TIMP-2), insulin-like growth factor-binding protein 7 (IGFBP7), CCL14, and neutrophil gelatinase-associated lipocalin (NGAL) were detected on the day of AKI diagnosis. The primary endpoint was non-recovery from AKI within 7 days. The individual discriminative ability of CCL14, [TIMP-2] × [IGFBP7] and NGAL to predict renal non-recovery were evaluated by the area under receiver operating characteristics curve (AUC). RESULTS: Of 164 AKI patients, 64 (39.0%) failed to recover from AKI onset. CCL14 showed a fair prediction ability for renal non-recovery with an AUC of 0.71 (95% CI 0.63-0.77, p < 0.001). [TIMP-2] × [IGFBP7] showed the best prediction for renal non-recovery with an AUC of 0.78 (95% CI 0.71-0.84, p < 0.001). However, NGAL had no use in predicting non-recovery with an AUC of 0.53 (95% CI 0.45-0.60, p = 0.562). A two-parameter model (non-renal SOFA score and AKI stage) predicted renal non-recovery with an AUC of 0.77 (95% CI 0.77-0.83, p = 0.004). When [TIMP-2] × [IGFBP7] was combined with the clinical factors, the AUC was significantly improved to 0.82 (95% CI 0.74-0.87, p = 0.049). CONCLUSIONS: Urinary CCL14 and [TIMP-2] × [IGFBP7] were fair predictors of renal non-recovery from AKI. Combing urinary [TIMP-2] × [IGFBP7] with a clinical model consisting of non-renal SOFA score and AKI stage enhanced the predictive power for renal non-recovery. Urinary CCL14 showed no significant advantage in predicting renal non-recovery compared to [TIMP-2] × [IGFBP7].

The attributable mortality of sepsis for acute kidney injury: a propensity-matched analysis based on multicenter prospective cohort study.

BACKGROUND: Both sepsis and AKI are diseases of major concern in intensive care unit (ICU). This study aimed to evaluate the excess mortality attributable to sepsis for acute kidney injury (AKI). METHODS: A propensity score-matched analysis on a multicenter prospective cohort study in 18 Chinese ICUs was performed. Propensity score was sequentially conducted to match AKI patients with and without sepsis on day 1, day 2, and day 3-5. The primary outcome was hospital death of AKI patients. RESULTS: A total of 2008 AKI patients (40.9%) were eligible for the study. Of the 1010 AKI patients with sepsis, 619 (61.3%) were matched to 619 AKI patients in whom sepsis did not develop during the screening period of the study. The hospital mortality rate of matched AKI patients with sepsis was 205 of 619 (33.1%) compared with 150 of 619 (24.0%) for their matched AKI controls without sepsis (p = 0.001). The attributable mortality of total sepsis for AKI patients was 9.1% (95% CI: 4.8-13.3%). Of the matched patients with sepsis, 328 (53.0%) diagnosed septic shock. The attributable mortality of septic shock for AKI was 16.2% (95% CI: 11.3-20.8%, p < 0.001). Further, the attributable mortality of sepsis for AKI was 1.4% (95% CI: 4.1-5.9%, p = 0.825). CONCLUSIONS: The attributable hospital mortality of total sepsis for AKI were 9.1%. Septic shock contributes to major excess mortality rate for AKI than sepsis. REGISTRATION FOR THE MULTICENTER PROSPECTIVE COHORT STUDY: registration number ChiCTR-ECH-13003934.

Chinese experts' consensus on the application of intensive care big data.

The development of intensive care medicine is inseparable from the diversified monitoring data. Intensive care medicine has been closely integrated with data since its birth. Critical care research requires an integrative approach that embraces the complexity of critical illness and the computational technology and algorithms that can make it possible. Considering the need of standardization of application of big data in intensive care, Intensive Care Medicine Branch of China Health Information and Health Care Big Data Society, Standard Committee has convened expert group, secretary group and the external audit expert group to formulate Chinese Experts' Consensus on the Application of Intensive Care Big Data (2022). This consensus makes 29 recommendations on the following five parts: Concept of intensive care big data, Important scientific issues, Standards and principles of database, Methodology in solving big data problems, Clinical application and safety consideration of intensive care big data. The consensus group believes this consensus is the starting step of application big data in the field of intensive care. More explorations and big data based retrospective research should be carried out in order to enhance safety and reliability of big data based models of critical care field.

Calprotectin as a diagnostic marker for sepsis: A meta-analysis.

Introduction: Sepsis is a life-threatening condition, and biomarkers are needed to diagnose sepsis fast and accurately. We aimed to perform this meta-analysis to investigate the diagnostic value of calprotectin on sepsis in critically ill patients. Methods: The investigators searched MEDLINE, Embase, Web of Science and Cochrane Library. Studies were included if they assessed the diagnostic accuracy of serum calprotectin for sepsis in intensive care unit (ICU). We estimated its diagnostic value and explored the source of heterogeneity. The bivariate model and the hierarchical summary receiver operating characteristic (HSROC) curve were used in the meta-analysis. Results: Six records assessing 821 patients were included in this meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio (PLR), and diagnostic odds ratio (DOR) were separately as 0.77, 0.85, 5.20, 0.27, respectively. The Fagan's nomogram showed post-test probabilities of 91% and 35% for positive and negative outcomes, respectively. Subgroup analysis indicated that sepsis definition could be a possible source of heterogeneity, but there's no sufficient data to investigate sepsis-3 definition. Sensitivity analysis suggested that two studies could affect the stability of pooled results. Conclusion: On the basis of our meta-analysis, calprotectin is a helpful marker for early diagnosis of sepsis on ICU admission.

Bone homeostasis disorders increased the mortality of sepsis patients: A preliminary retrospective cohort study.

Introduction: Sepsis is a common clinical syndrome and nearly 20% of all deaths are related to sepsis. As an important part of the body, bone homeostasis disorders are closely related to inflammatory response, but the correlation between bone homeostasis and sepsis, sepsis shock was unknown. The objective of this study was to explore the relation of bone homeostasis on sepsis and sepsis shock. Methods: In this retrospective cohort study, patients were enrolled between April 2018 and May 2022 from Beijing Chaoyang hospital. Primary outcomes were serum indicators reflected bone homeostasis, such as cross-linked carboxy-terminal telopeptide of type I collagen (CTX-I), tartrate-resistant acid phosphatase 5b (TRACP-5b) and piezo-type mechanosensitive ion channel component 1 (PIEZO1). Results: The data were analyzed retrospectively. among 88 evaluable patients, 45 were sepsis (19 were sepsis shock) and 43 were non-sepsis. There was no significant difference in age, gender, BMI, combination diseases, operation time, intraoperative blood loss, and hospital stay. Patients with sepsis or sepsis shock had higher serum CTX-I, TRACP-5b, PIEZO1 (p < 0.05). Spearman's rank correlation test showed that CTX-I, TRACP-5b, PIEZO1 and the three together (CTX-I + TRACP-5b + PIEZO1) had strong correlation with sepsis or sepsis shock (p < 0.05). The receiver operating characteristic curve (ROC) and precision-recall curve (PRC) showed that these indicators could predict the occurrence of sepsis or sepsis shock (p < 0.05). Besides, decision curve analysis (DCA) and interventions avoided curve (IAC) displayed a high net benefit of bone homeostasis disorders indicators on sepsis or sepsis shock. Kaplan-Meier survival curves revealed that sepsis or shock patients with high value indicators (>0.47227) had a higher mortality (p < 0.05). Conclusion: Bone homeostasis disorders could increase the mortality of sepsis and sepsis shock patients.

Expert consensus on the monitoring and treatment of sepsis-induced immunosuppression.

Emerged evidence has indicated that immunosuppression is involved in the occurrence and development of sepsis. To provide clinical practice recommendations on the immune function in sepsis, an expert consensus focusing on the monitoring and treatment of sepsis-induced immunosuppression was developed. Literature related to the immune monitoring and treatment of sepsis were retrieved from PubMed, Web of Science, and Chinese National Knowledge Infrastructure to design items and expert opinions were collected through an online questionnaire. Then, the Delphi method was used to form consensus opinions, and RAND appropriateness method was developed to provide consistency evaluation and recommendation levels for consensus opinions. This consensus achieved satisfactory results through two rounds of questionnaire survey, with 2 statements rated as perfect consistency, 13 as very good consistency, and 9 as good consistency. After summarizing the results, a total of 14 strong recommended opinions, 8 weak recommended opinions and 2 non-recommended opinions were produced. Finally, a face-to-face discussion of the consensus opinions was performed through an online meeting, and all judges unanimously agreed on the content of this consensus. In summary, this expert consensus provides a preliminary guidance for the monitoring and treatment of immunosuppression in patients with sepsis.

Binimetinib ameliorates the severity of septic cardiomyopathy by downregulating inflammatory factors.

BACKGROUND: Septic cardiomyopathy (SCM) has a worse prognosis with mortality rates of up to 70%. Most existing treatment is useless and no specific drug or treatment has been found in patients with myocardial hypofunction. METHODS: We explored the efficacy of the target drugs (Binimetinib) in SCM model in vivo based on high throughput sequencing and bioinformatics analysis. Firstly, a stable SCM mice model was constructed. Secondly, the hub genes of SCM were clarified by high throughput sequencing and bioinformatics analysis. The related pathways and biological process were revealed by Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO) enrichment analysis. Thirdly, the target drugs of the hub genes were investigated by network pharmacology analysis. Fourthly, the curative effects and hub genes regulatory effects of Binimetinib were demonstrated by SCM mice model. Finally, the regulatory mechanism of the target drugs on the hub genes were analyzed by molecular docking. RESULTS: 109 CFU/ml P. aeruginosa daubed in wound could establish a stable SCM mice model. Il-6, Il-1ß and Tnf were the hub genes of SCM. Immune system process and inflammatory response were the main biological process. Binimetinib was the target drug of IL-6, IL-1ß and TNF-α. JUN and NFKB1 were the transcription factor (TFs) of hub genes and Binimetinib had the lowest binding energy with NFKB1. CONCLUSIONS: A stable SCM model was established by wound P. aeruginosa infection. Tnf, Il-1ß, Il-6 were the key genes of SCM. Binimetinib might be a drug for the treatment of SCM by downregulating the hub genes. Its active mechanism might be related to NFKB1.

Comparative Study of M(â ¡)Al (M=Co, Ni) Layered Double Hydroxides for Silicone Foam: Characterization, Flame Retardancy, and Smoke Suppression.

To compare the different actions of the two representative transition metal cations of Co2+ and Ni2+ in layered double hydroxides (LDHs), CoAl-LDH and NiAl-LDH intercalated with CO32- were synthesized, and the chemical structures, microstructures, and surface areas thereof were successfully characterized. Then, the two LDHs were utilized as flame retardants and smoke suppressants for silicone foam (SiF). The densities, flame retardancy, smoke suppression, thermal stabilities, and compressive strengths of the two SiF/LDHs nanocomposites were investigated. The introduction of LDHs slightly decreased the density of SiF due to the catalytic actions of Co and Ni during the foaming process of SiF. With respect to the flame retardancy, the addition of only 1 phr of either CoAl-LDH or NiAl-LDH could effectively improve the limiting oxygen index of SiF from 28.7 to 29.6%. Based on the results of vertical flame testing and a cone calorimeter test, the flame retardancy and fire safety of the SiF were effectively enhanced by the incorporation of LDHs. In addition, owing to the good catalytic action and large specific surface area (NiAl-LDH: 174.57 m2 g-1; CoAl-LDH: 51.47 m2 g-1), NiAl-LDH revealed higher efficiencies of flame retardancy and smoke suppression than those of CoAl-LDH. According to the results of energy-dispersive X-ray spectroscopy, Co and Ni participated in the formation of protective char layers, which inhibited the release of SiO2 into the gas phase. Finally, the influences on the thermal decomposition and compressive strength for SiF resulting from the addition of LDHs are discussed.