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Cite this article as: Zong Z, Xu J, Zhang H, Xu H, Tang X, Shi L. A small "tent" in the esophagus. Turk J Gastroenterol. 2024;35(7): 587-588.
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Esôfago , Humanos , Masculino , Doenças do Esôfago , FemininoRESUMO
BACKGROUND: Congenital anomalies of the kidneys and urinary tract (CAKUT) are the most common cause of prenatally diagnosed developmental malformation. This study aimed to assess the relationship between maternal diseases and CAKUT in offspring. METHODS: This retrospective study enrolled all pregnant women registered from January 2020 to December 2022 at one medical center. Medical information on maternal noncommunicable diseases, including obesity, hypertension, diabetes mellitus, kidney disease, hyperthyroidism, hypothyroidism, psychiatric disease, epilepsy, cancer, and autoimmune disease was collected. Based on the records of ultrasound scanning during the third trimester, the diagnosis was classified as isolated urinary tract dilation (UTD) or kidney anomalies. Multivariate logistic regression was performed to establish models to predict antenatal CAKUT. RESULTS: Among the 19,656 pregnant women, perinatal ultrasound detected suspicious CAKUT in 114 (5.8/1000) fetuses, comprising 89 cases with isolated UTD and 25 cases with kidney anomalies. The risk of antenatal CAKUT was increased in the fetuses of mothers who experienced gestational diabetes, thyroid dysfunction, neuropsychiatric disease, anemia, ovarian and uterine disorders. A prediction model for isolated UTD was developed utilizing four confounding factors, namely gestational diabetes, gestational hypertension, maternal thyroid dysfunction, and hepatic disease. Similarly, a separate prediction model for kidney anomalies was established based on four distinct confounding factors, namely maternal thyroid dysfunction, gestational diabetes, disorders of ovarian/uterine, and kidney disease. CONCLUSIONS: Isolated UTD and kidney anomalies were associated with different maternal diseases. The results may inform the clinical management of pregnancy and highlight potential differences in the genesis of various subtypes of CAKUT.
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Atrial fibrillation (AF), the most prevalent cardiac rhythm disorder, significantly increases hospitalization and health risks. Reverting from AF to sinus rhythm (SR) often requires intensive interventions. This study presents a deep-learning model capable of predicting the transition from SR to AF on average 30.8 min before the onset appears, with an accuracy of 83% and an F1 score of 85% on the test data. This performance was obtained from R-to-R interval signals, which can be accessible from wearable technology. Our model, entitled Warning of Atrial Fibrillation (WARN), consists of a deep convolutional neural network trained and validated on 24-h Holter electrocardiogram data from 280 patients, with 70 additional patients used for testing and further evaluation on 33 patients from two external centers. The low computational cost of WARN makes it ideal for integration into wearable technology, allowing for continuous heart monitoring and early AF detection, which can potentially reduce emergency interventions and improve patient outcomes.
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Identifying structures of complex networks based on time series of nodal data is of considerable interest and significance in many fields of science and engineering. This article presents a sparse Bayesian learning (SBL) method for identifying structures of community-bridge networks, where nodes are grouped to form communities connected via bridges. Using the structural information of such networks with unknown nodal dynamics and community formations, network structure identification is tackled similar to sparse signal reconstruction with mixed sparsity mode. The proposed method is theoretically proved to be convergent. Its superiority to mainstream baselines is demonstrated via extensive experiments without the need for manual adjustment of regularization parameters.
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BACKGROUND: Postoperative pneumonia (POP) is the most prevalent of all nosocomial infections in patients who underwent cardiac surgery. The aim of this study was to identify independent risk factors for pneumonia after cardiac surgery, from which we constructed a nomogram for prediction. METHODS: The clinical data of patients admitted to the Department of Cardiothoracic Surgery of Nanjing Drum Tower Hospital from October 2020 to September 2021 who underwent cardiac surgery were retrospectively analyzed, and the patients were divided into two groups according to whether they had POP: POP group (n=105) and non-POP group (n=1083). Preoperative, intraoperative, and postoperative indicators were collected and analyzed. Logistic regression was used to identify independent risk factors for POP in patients who underwent cardiac surgery. We constructed a nomogram based on these independent risk factors. Model discrimination was assessed via area under the receiver operating characteristic curve (AUC), and calibration was assessed via calibration plot. RESULTS: A total of 105 events occurred in the 1188 cases. Age (>55 years) (OR: 1.83, P=0.0225), preoperative malnutrition (OR: 3.71, P<0.0001), diabetes mellitus(OR: 2.33, P=0.0036), CPB time (Cardiopulmonary Bypass Time) > 135 min (OR: 2.80, P<0.0001), moderate to severe ARDS (Acute Respiratory Distress Syndrome )(OR: 1.79, P=0.0148), use of ECMO or IABP or CRRT (ECMO: Extra Corporeal Membrane Oxygenation; IABP: Intra-Aortic Balloon Pump; CRRT: Continuous Renal Replacement Therapy )(OR: 2.60, P=0.0057) and MV( Mechanical Ventilation )> 20 hours (OR: 3.11, P<0.0001) were independent risk factors for POP. Based on those independent risk factors, we constructed a simple nomogram with an AUC of 0.82. Calibration plots showed good agreement between predicted probabilities and actual probabilities. CONCLUSION: We constructed a facile nomogram for predicting pneumonia after cardiac surgery with good discrimination and calibration. The model has excellent clinical applicability and can be used to identify and adjust modifiable risk factors to reduce the incidence of POP as well as patient mortality.
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Procedimentos Cirúrgicos Cardíacos , Nomogramas , Pneumonia , Complicações Pós-Operatórias , Humanos , Estudos Retrospectivos , Masculino , Procedimentos Cirúrgicos Cardíacos/efeitos adversos , Feminino , Pessoa de Meia-Idade , Fatores de Risco , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/diagnóstico , Pneumonia/epidemiologia , Pneumonia/etiologia , Pneumonia/diagnóstico , Idoso , Medição de Risco/métodos , China/epidemiologiaRESUMO
Due to a rapidly aging global population, osteoporosis and the associated risk of bone fractures have become a wide-spread public health problem. However, osteoporosis is very heterogeneous, and the existing standard diagnostic measure is not sufficient to accurately identify all patients at risk of osteoporotic fractures and to guide therapy. Here, we constructed the first prospective multi-omics atlas of the largest osteoporosis cohort to date (longitudinal data from 366 participants at three time points), and also implemented an explainable data-intensive analysis framework (DLSF: Deep Latent Space Fusion) for an omnigenic model based on a multi-modal approach that can capture the multi-modal molecular signatures (M3S) as explicit functional representations of hidden genotypes. Accordingly, through DLSF, we identified two subtypes of the osteoporosis population in Chinese individuals with corresponding molecular phenotypes, i.e., clinical intervention relevant subtypes (CISs), in which bone mineral density benefits response to calcium supplements in 2-year follow-up samples. Many snpGenes associated with these molecular phenotypes reveal diverse candidate biological mechanisms underlying osteoporosis, with xQTL preferences of osteoporosis and its subtypes indicating an omnigenic effect on different biological domains. Finally, these two subtypes were found to have different relevance to prior fracture and different fracture risk according to 4-year follow-up data. Thus, in clinical application, M3S could help us further develop improved diagnostic and treatment strategies for osteoporosis and identify a new composite index for fracture prediction, which were remarkably validated in an independent cohort (166 participants).
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BACKGROUND: Postoperative hyper-inflammation is a frequent event in patients with acute Stanford type A aortic dissection (ATAAD) after surgical repair. This study's objective was to determine which inflammatory biomarkers could be used to make a better formula for identifying postoperative hyper-inflammation, and which risk factors were associated with hyper-inflammation. METHODS: A total of 405 patients were enrolled in this study from October 1, 2020 to April 1, 2023. Of these patients, 124 exhibited poor outcomes. In order to investigate the optimal cut-off values for poor outcomes, logistic and receiver operating characteristic analyses were performed on the following parameters on the first postoperative day: procalcitonin (PCT), C-reactive protein (CRP), interleukin-6 (IL-6), and systemic immune-inflammation index (SII). These cut-off points were used to separate the patients into hyper-inflammatory (n = 52) and control (n = 353) groups. Finally, the logistic were used to find the risk factors of hyper-inflammatory. RESULTS: PCT, CRP, IL-6, and SII were independent risk factors of poor outcomes in the multivariate logistic model. Cut-off points of these biomarkers were 2.18 ng/ml, 49.76 mg/L, 301.88 pg/ml, 2509.96 × 109/L respectively. These points were used to define postoperative hyper-inflammation (OR 2.97, 95% CI 1.35-6.53, P < 0.01). Cardiopulmonary bypass (CPB) > 180 min, and deep hypothermia circulatory arrest (DHCA) > 40 min were the independent risk factors for hyper-inflammation. CONCLUSIONS: PCT > 2.18, CRP > 49.76, IL-6 > 301.88, and SII < 2509.96 could be used to define postoperative hyper-inflammation which increased mortality and morbidity in patients after ATAAD surgery. Based on these findings, we found that CPB > 180 min and DHCA > 40 min were separate risk factors for postoperative hyper-inflammation.
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Dissecção Aórtica , Interleucina-6 , Humanos , Dissecção Aórtica/cirurgia , Inflamação , Biomarcadores , Fatores de Risco , Pró-Calcitonina , Proteína C-Reativa , Estudos RetrospectivosRESUMO
OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data. DESIGN: A single-centre, retrospective cohort study in China. SETTING: A Chinese central tertiary hospital. PARTICIPANTS: The cohort study consisted of 1694 LN patients who had been registered in the Nanjing Glomerulonephritis Registry at the National Clinical Research Center of Kidney Diseases, Jinling Hospital from January 1985 to December 2010. METHODS: We developed a deep learning algorithm to predict LN relapse that consists of 59 features, including demographic, clinical, immunological, pathological and therapeutic characteristics that were collected for baseline analysis. A total of 32 227 data points were collected by the sliding window method and randomly divided into training (80%), validation (10%) and testing sets (10%). We developed a deep learning algorithm-based interpretable multivariable long short-term memory model for LN relapse risk prediction considering censored time-series data based on a cohort of 1694 LN patients. A mixture attention mechanism was deployed to capture variable interactions at different time points for estimating the temporal importance of the variables. Model performance was assessed according to C-index (concordance index). RESULTS: The median follow-up time since remission was 4.1 (IQR, 1.7-6.7) years. The interpretable deep learning model based on dynamic multivariable time-series data achieved the best performance, with a C-index of 0.897, among models using only variables at the point of remission or time-variant variables. The importance of urinary protein, serum albumin and serum C3 showed time dependency in the model, that is, their contributions to the risk prediction increased over time. CONCLUSIONS: Deep learning algorithms can effectively learn through time-series data to develop a predictive model for LN relapse. The model provides accurate predictions of LN relapse for different renal disease stages, which could be used in clinical practice to guide physicians on the management of LN patients.
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Aprendizado Profundo , Nefrite Lúpica , Humanos , Nefrite Lúpica/diagnóstico , Nefrite Lúpica/tratamento farmacológico , Estudos de Coortes , Estudos Retrospectivos , RecidivaRESUMO
Background: Sivelestat, a neutrophil elastase inhibitor, is specifically developed to mitigate the occurrence of acute lung injury (ALI) in individuals who are undergoing cardiovascular surgery. However, its impact on patients who are at a heightened risk of developing ALI after scheduled cardiac surgery has yet to be determined. In order to address this knowledge gap, we undertook a study to assess the efficacy of sivelestat in protecting the lungs of these patients. Methods: We conducted a prospective cohort study involving 718 patients who were at high risk of developing postoperative acute lung injury (ALI) and underwent scheduled cardiac surgery between April 25th, 2022, and September 7th, 2023. Among them, 52 patients received sivelestat (administered at a dosage of 0.2mg/kg/h for 3 days), while 666 patients served as controls, not receiving sivelestat. The control conditions were the same for all patients, including ventilation strategy, extubating time, and fluid management. Subsequently, a propensity-score matched cohort was established, consisting of 40 patients in both the sivelestat and control groups. The primary outcome measure encompassed a composite of adverse outcomes, including 30-day mortality, ALI, acute respiratory distress syndrome (ARDS), and others. Secondary outcomes assessed included pneumonia, ventricular arrhythmias, mechanical ventilation (MV) time, and more. Results: After conducting propensity matching in our study, we observed that there were no significant differences in 30-day mortality between the sivelestat and control groups (0% vs 2.5%, P=0.32). However, the use of sivelestat exhibited a significant reduction in the incidence of acute lung injury/acute respiratory distress syndrome (ALI/ARDS) compared to the control group (0% vs 55%, P<0.01), pneumonia (0 vs 37.5%, P<0.01), MV time (median:8 hours, IQR:4-14.8 hours vs median: 15.2 hours, IQR:14-16.3 hours, P<0.01). Compared to the control group, the sivelestat could significantly decrease white cell count (P<0.01), neutrophile percentage (P<0.01) and C-reactive protein (P<0.01) in the period of postoperative 5 days. Conclusion: The prophylactic administration of sivelestat has shown promising results in reducing the occurrence of acute lung injury/acute respiratory distress syndrome (ALI/ARDS) in patients with a heightened risk of developing these conditions after elective cardiac surgery. Our study findings indicate that sivelestat may provide protective effects by suppressing inflammation triggered by neutrophil activation, thereby safeguarding pulmonary function. Registration: ChiCTR2200059102, https://www.chictr.org.cn/showproj.html?proj=166643.
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Fluoride has strong electronegativity and exposes diversely in nature. Water fluoridation is the most pervasive form of occurrence, representing a significant threat to human health. In this study, we investigate the morphometric and physiological alterations triggered by fluoride stimulation during the embryogenesis of zebrafish and reveal its putative effects of stage- and/or dose-dependent. Fluoride exhibits potent biological activity and can be extensively absorbed by the yolk sac, exerting significant effects on the development of multiple organs. This is primarily manifested as restricted nutrient utilization and elevated levels of lipid peroxidation, further leading to the accumulation of superoxide in the yolk sac, liver, and intestines. Moreover, pericardial edema exerts pressure on the brain and eye development, resulting in spinal curvature and reduced body length. Besides, acute fluoride exposure with varying concentrations has led to diverse teratogenic outcomes. A low dose of water fluoridation tends to induce abnormal development of the embryonic yolk sac, while vascular malformation is widely observed in all fluoride-treated groups. The effect of fluoride exposure on blood circulation is universally present, even in zebrafish larvae that do not exhibit obvious deformities. Their swimming behavior is also affected by water fluoridation, resulting in reduced activity and delayed reactions. In conclusion, this study provides valuable insights into the monitoring of environmental quality related to water fluoridation and disease prevention.
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Poluentes Químicos da Água , Peixe-Zebra , Animais , Humanos , Fluoretos/toxicidade , Fluoretação , Desenvolvimento Embrionário , Saco Vitelino , Embrião não Mamífero , Poluentes Químicos da Água/toxicidadeRESUMO
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Azoospermia , Testículo , Humanos , Masculino , Testículo/cirurgia , Azoospermia/diagnóstico , Azoospermia/cirurgia , Recuperação Espermática , Microdissecção , Estudos Retrospectivos , Sêmen , EspermatozoidesRESUMO
Background: For the patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI), dual antiplatelet therapy (DAPT) for at least 1 year is recommended in the guidelines to minimize the risk of stent thrombosis. Persistently uncovered stent strut means delayed neointima formation and extend the window of time in which the stent is prone to thrombosis. Previous studies showed that statins could improve post-stenting strut endothelial coverage for patients undergoing PCI. However, there are lack of evidences on whether early initiation of proprotein convertase subtilisin/Kexin type 9 monoclonal antibody (PCSK9mAb) after PCI in ACS patients can further improve the rate of stent strut coverage on the background of oral lipid-lowering therapy (LLT). Methods: This is a single-center, randomized trial to enroll 36 patients undergoing PCI with a clinical diagnosis of non-ST-segment elevation ACS. The baseline level of low-density lipoprotein cholesterol (LDL-C) of these patients are between 1.4 mmol/L and 3.4 mmol/L. Patients will be assigned to intensive lipid-lowering therapy (LLT) with PCSK9mAb group and conventional LLT without PCSK9mAb group for 12 weeks in a clinical follow-up setting according to 1: 1 randomization. the rate of stent strut endothelial coverage by optical coherence tomography (OCT) examination at 12 weeks after enrollment between the groups will be compared. Conclusion: This will be the first study to investigate changes in the rate of stent strut endothelial coverage under intensive LLT with PCSK9mAb by OCT examination in ACS patients undergoing PCI. The finding of this study will provide clinical evidence for future research about the hypothesis of a novel strategy of "intensive LLT (PCSK9mAb + statin ± ezetimibe) combined with shortened DAPT duration" for ACS patients undergoing PCI.Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: ChiCTR2200063395.
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PURPOSE: Given the beneficial effects of sacubitril/valsartan on blood pressure generally, this study investigates its antihypertension effects in diabetes mellitus (DM) patients with primary hypertension specifically, and the effect of sacubitril/valsartan on glycolipid metabolism. METHODS: We conducted a randomized, open-label, active-controlled study to compare the antihypertension effects of sacubitril/valsartan in DM individuals with primary hypertension. The primary end point was reduction in mean systolic blood pressure (SBP) from baseline with sacubitril/valsartan vs. olmesartan at week 8. The secondary endpoints included the changes in diastolic blood pressure (DBP), daytime SBP/DBP, nighttime SBP/DBP, BP achievement (office sitting BP < 130/80 mmHg), and lipid profile. The trial was registered with chictr.org.cn (ChiCTR2200066428) on Dec 22, 2022. RESULTS: A total of 124 patients were included in the final analysis. SBP decreased to a greater extent in the sacubitril/valsartan group from baseline to 8 weeks [between-treatment difference: 3.51 mm Hg, 95% confidence interval (95% CI) 0.41 to 6.62 mm Hg, P = 0.03]. Furthermore, more patients achieved the blood pressure goal with sacubitril/valasartan (74.60% vs. 54.70%, P = 0.03). Multiple logistical regression analysis showed that sacubitril/valsartan was associated with BP achievement [odds ratio (OR) 0.33, 95% CI 0.14-0.73, P = 0.007], but the difference in SBP, DBP, day time SBP/DBP, and night time SBP/DBP reduction did not approach statistical significance. HbA1C1, total cholesterol, and low-density lipoprotein-cholesterol were lower than baseline in both groups (P < 0.05); however, there was no difference in the effects on glucose and lipid metabolism from sacubitril/valsartan compared to olmesartan. CONCLUSIONS: Sacubitril/valsartan not only provided superior BP reduction compared to olmesartan, it did so without adverse effects on glycemic control and lipid parameters in DM patients with primary hypertension.
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Background: Early postoperative bacterial pneumonia and sepsis (ePOPS), which occurs within the first 48 hours after cardiovascular surgery, is a serious life-threatening complication. Diagnosis of ePOPS is extremely challenging, and the existing diagnostic tools are insufficient. The purpose of this study was to construct a novel diagnostic prediction model for ePOPS. Methods: Least Absolute Shrinkage and Selection Operator (LASSO) with logistic regression was used to construct a model to diagnose ePOPS based on patients' comorbidities, medical history, and laboratory findings. The area under the receiver operating characteristic curve (AUC) was used to evaluate the model discrimination. Results: A total of 1203 patients were recruited and randomly split into a training and validation set in a 7:3 ratio. By early morning on the 3rd postoperative day (POD3), 103 patients had experienced 133 episodes of bacterial pneumonia or sepsis (15 patients had both). LASSO logistic regression model showed that duration of mechanical ventilation (P=0.015), NYHA class ≥ III (P=0.001), diabetes (P<0.001), exudation on chest radiograph (P=0.011) and IL-6 on POD3 (P<0.001) were independent risk factors. Based on these factors, we created a nomogram named DICS-I with an AUC of 0.787 in the training set and 0.739 in the validation set. Conclusion: The DICS-I model may be used to predict the risk of ePOPS after cardiovascular surgery, and is also especially suitable for predicting the risk of IRAO. The DICS-I model could help clinicians to adjust antibiotics on the POD3.
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The concept of network resilience has gained increasing attention in the last few decades owing to its great potential in strengthening and maintaining complex systems. From network-based approaches, researchers have explored resilience of real ecological systems comprising diverse types of interactions, such as mutualism, antagonist, and predation, or mixtures of them. In this paper, we propose a dimension-reduction method for analyzing the resilience of hybrid herbivore-plant-pollinator networks. We qualitatively evaluate the contribution of species toward maintaining resilience of networked systems, as well as the distinct roles played by different categories of species. Our findings demonstrate that the strong contributors to network resilience within each category are more vulnerable to extinction. Notably, among the three types of species in consideration, plants exhibit a higher likelihood of extinction, compared to pollinators and herbivores.
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BACKGROUND: We sought to explore the relationship between dexmedetomidine as an anesthetic adjuvant in cardiac surgery and postoperative complications and length of stay (LOS) in the cardiac intensive care unit (CICU). METHODS: We conducted a retrospective study of patients aged 18 years and older who underwent heart valve surgery between October 2020 and June 2022. The primary endpoint of the study was major postoperative complications (cardiac arrest, atrial fibrillation, myocardial injury/infarction, heart failure) and the secondary endpoint was prolonged CICU LOS (defined as LOS > 90th percentile). Multivariate logistic regression analysis was performed for variables that were significant in the univariate analysis. RESULTS: A total of 856 patients entered our study. The 283 patients who experienced the primary and secondary endpoints were included in the adverse outcomes group, and the remaining 573 were included in the prognostic control group. Multivariate logistic regression analysis revealed that age > 60 years (odds ratio [OR], 1.68; 95% confidence interval [CI], 1.23-2.31; p < 0.01), cardiopulmonary bypass (CPB) > 180 min (OR, 1.62; 95% CI, 1.03-2.55; p = 0.04) and postoperative mechanical ventilation time > 10 h (OR, 1.84; 95% CI, 1.35-2.52; p < 0.01) were independent risk factors for major postoperative complications; Age > 60 years (OR, 3.20; 95% CI, 1.65-6.20; p < 0.01), preoperative NYHA class 4 (OR, 4.03; 95% CI, 1.74-9.33; p < 0.01), diabetes mellitus (OR, 2.57; 95% CI, 1.22-5.41; p = 0.01), Intraoperative red blood cell (RBC) transfusion > 650 ml (OR, 2.04; 95% CI, 1.13-3.66; p = 0.02), Intraoperative bleeding > 1200 ml (OR, 2.69; 95% CI, 1.42-5.12; p < 0.01) were independent risk factors for prolonged CICU length of stay. Intraoperative use of dexmedetomidine as an anesthetic adjunct was a protective factor for major complications (odds ratio, 0.51; 95% confidence interval, 0.35-0.74; p < 0.01) and prolonged CICU stay. (odds ratio, 0.37; 95% confidence interval, 0.19-0.73; p < 0.01). CONCLUSIONS: In patients undergoing heart valve surgery, age, duration of cardiopulmonary bypass, and duration of mechanical ventilation are associated with major postoperative complication. Age, preoperative NYHA classification 4, diabetes mellitus, intraoperative bleeding, and RBC transfusion are associated with increased CICU length of stay. Intraoperative use of dexmedetomidine may improve such clinical outcomes.
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Procedimentos Cirúrgicos Cardíacos , Dexmedetomidina , Diabetes Mellitus , Humanos , Dexmedetomidina/uso terapêutico , Tempo de Internação , Estudos Retrospectivos , Procedimentos Cirúrgicos Cardíacos/efeitos adversos , Unidades de Terapia Intensiva , Fatores de Risco , Valvas Cardíacas/cirurgia , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/etiologiaRESUMO
Organic radicals are widely used as linkers or ligands to synthesize molecular magnetic materials. However, studies regarding the molecular anisotropies of radical-based magnetic materials and their multifunctionalities are rare. Herein, a photoisomerizable diarylethene ligand was used to form {[CoIII(3,5-DTSQ·-)(3,5-DTCat2-)]2(6F-DAE-py2)}·3CH3CN·H2O (o-1·3CH3CN·H2O, 6F-DAE-py2 = 1,2-bis(2-methyl-5-(4-pyridyl)-3-thienyl)perfluorocyclopentene), a valence-tautomeric (VT) coordination polymer. We directly observed dual radicals for a single crystal using high-field/-frequency (â¼13.3 T and â¼360 GHz) electron paramagnetic resonance (EPR) spectroscopy along the c-axis, which was further confirmed by angle-dependent Q-band EPR spectroscopy. Moreover, a conductive anomaly close to the VT transition temperature was observed only when probes were attached at the ab plane of the single crystal, indicative of synergy between valence tautomerism and conductivity. Structural anisotropy studies and density functional theory (DFT) calculations revealed that this synergy is due to electron transfer associated with valence tautomerism. This study presents the first example of dual-radical-based molecular anisotropy and charge-transfer-induced conductive anisotropy in a photoswitchable coordination polymer.
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Exploring the mechanism of hysteresis dynamics may facilitate the analysis and controller design to alleviate detrimental effects. Conventional models, such as the Bouc-Wen and Preisach models consist of complicated nonlinear structures, limiting the applications of hysteresis systems for high-speed and high-precision positioning, detection, execution, and other operations. In this article, a Bayesian Koopman (B-Koopman) learning algorithm is therefore developed to characterize hysteresis dynamics. Essentially, the proposed scheme establishes a simplified linear representation with time delay for hysteresis dynamics, where the properties of the original nonlinear system are preserved. Furthermore, model parameters are optimized via sparse Bayesian learning together with an iterative strategy, which simplifies the identification procedure and reduces modeling errors. Extensive experimental results on piezoelectric positioning are elaborated to substantiate the effectiveness and superiority of the proposed B-Koopman algorithm for learning hysteresis dynamics.
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BACKGROUND: Myocardial injury-related cardiogenic shock (MICS) is significantly associated with poor outcomes in patients after cardiac surgery. Herein, we aimed to investigate the risk factor for postoperative MICS. METHODS: We performed a case-control study on 792 patients undergoing cardiac surgery from 2016 to 2019, including 172 patients with postoperative MICS and 620 age- and sex-matched controls. MICS was defined as composite criteria: a cardiac index of < 2.2 L/m2/min, arterial lactate levels of > 5 mmol/L at the end of the surgery, a vasoactive-inotropic score of > 40 at the end of the surgery, and a cardiac troponin T (cTnT) level of > 0.8 µg/L on postoperative day 1 (POD1) with an increase of > 10% on POD 2. RESULTS: A total of 4671 patients who underwent cardiac surgery in our hospital between 2016 and 2019 were included; of these, 172 (3.68%) had MICS and the remaining 4499 did not. For investigating the risk factors, we selected 620 age- and sex-matched controls. In the univariate analysis, MICS was significantly associated with death (P < 0.05), extracorporeal membrane oxygenation (P < 0.05), continuous renal replacement therapy (P < 0.01), and ventricular arrhythmias (P < 0.05). Multivariable logistic regression analysis revealed that diabetes mellitus (OR:8.11, 95% CI: 3.52-18.66, P < 0.05) and a cardiopulmonary bypass (CPB) time of > 2 h (OR: 3.16, 95% CI: 1.94-5.15, P < 0.05) were associated with postoperative MICS. Moreover, long-time administration of preoperative calcium channel blocker (CCB) was associated with a less incidence of MICS (OR: 0.11, 95% CI: 0.05-0.27, P < 0.05). CONCLUSIONS: Postoperative MICS is significantly associated with poor outcomes. Diabetes mellitus and long CPB time are associated with MICS. Preoperative CCB administration is associated with less incidence of MICS.
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Procedimentos Cirúrgicos Cardíacos , Choque Cardiogênico , Humanos , Choque Cardiogênico/etiologia , Estudos de Casos e Controles , Estudos Retrospectivos , Procedimentos Cirúrgicos Cardíacos/efeitos adversos , Fatores de RiscoRESUMO
The main manifestations of Takotsubo syndrome (TTS) are a spherical expansion of the left ventricle or near the apex and decreased systolic function. TTS is mostly thought to be induced by emotional stress, and the induction of TTS by severe infection is not often reported. A 72-year-old female patient with liver abscess reported herein was admitted due to repeated fever with a history of hypertension and impaired glucose tolerance. Her severe infection caused TTS, and her blood pressure dropped to 80/40 mmHg. IABP treatment was performed immediately and continued for 10 days, and comprehensive medication was administered. Based on her disease course and her smooth recovery, general insights and learnings may be: Adding to mental and other pathological stress reaction, serious infections from pathogenic microorganism could be of great important causation of stress reaction leading to TTS, while basic diseases such as coronary heart disease, hypertension, and diabetes were be of promoting factors; In addition to effective drug therapies for TTS, the importance of the timely using of IABP should be emphasized.