Munkholmlunding5835
Secondary outcomes will include additional HELP- and family-based performance metrics along with various neurocognitive and clinical recovery measures. Exploratory outcomes include the incidence of positive family-based delirium assessments post-discharge, 36-item Short Form Survey, PROMIS Cognitive Function Abilities Subset 4a, and 30-day readmission rates. Ethics and dissemination This trial has received approval by the University of Michigan Medical Institutional Review Board (IRBMED). Dissemination plans include presentation at scientific conferences, publication in medical journals, and distribution via educational and news media. Registration ClinicalTrials.gov Identifier NCT04007523, registered on 7/3/2019.Background Root canal disinfection is considered critical for achieving successful regenerative endodontic procedures. Photo-activated disinfection is a novel disinfection method that can help to achieve the goal of regenerative endodontics. This article reports the clinical and radiographic results after single visit regenerative endodontics using photo-activated disinfection. Methods An 8.5-year-old girl complained of fractured upper right central incisor. Pulp necrosis was diagnosed on the basis of clinical findings. The root canal was irrigated with sodium hypochlorite solution (1.5%) followed by saline. Then, the canal was dried with paper points. A combination of a photosensitizer solution and low power laser light were applied. EDTA solution was used as a final irrigant. Bleeding was induced, followed by placement of collagen resorbable matrix and white mineral trioxide aggregate. Two days later, the tooth was sealed and restored with permanent filling. Results Clinical findings revealed no pain on percussion or palpation tests. Radiographic examination revealed an increase in root length, an increase of apical root thickness and apical closure at the 12-month follow-up period. Conclusion Regenerative endodontics using photo-activated disinfection achieved successful outcomes in the necrotic immature permanent tooth.
This study examined the risk factors associated with mortality in cirrhotic patients hospitalized with variceal bleeding, and evaluated the effects of acute-on-chronic liver failure (ACLF) on the prognosis of these patients.
This study was retrospectively conducted on patients registered in the Korean acute-on-chronic liver failure study cohort, and on 474 consecutive cirrhotic patients hospitalized with variceal bleeding from January 2013 to December 2013 at 21 university hospitals. ACLF was defined as described by the European Association for the Study of Liver-Chronic Liver Failure Consortium.
Among a total of 474 patients, 61 patients were diagnosed with ACLF. The cumulative overall survival (OS) rate was lower in the patients with ACLF than in those without (P<0.001), and patients with higher ACLF grades had a lower OS rate (P<0.001). The chronic liver failure-sequential organ failure assessment (CLIF-SOFA) score was identified as a significant prognostic factor in patients hospitalized with variceal bleeding (hazard ratio [HR], 1.40; 95% confidence interval [CI], 1.30-1.50; P<0.001), even in ACLF patients with variceal bleeding (HR, 1.32; 95% CI, 1.19-1.46, P<0.001). Concerning the prediction of the mortality risk at 28- and 90-day using CLIF-SOFA scores, c-statistics were 0.895 (95% CI, 0.829-0.962) and 0.897 (95% CI, 0.842-0.951), respectively, and the optimal cut-off values were 6.5 and 6.5, respectively.
In cirrhotic patients hospitalized with variceal bleeding, the prognosis was poor when accompanied by ACLF, especially depending upon CLIF-SOFA score. CLIF-SOFA model well predicted the 28-day or 90-day mortality for cirrhotic patients who experienced variceal bleeding.
In cirrhotic patients hospitalized with variceal bleeding, the prognosis was poor when accompanied by ACLF, especially depending upon CLIF-SOFA score. CLIF-SOFA model well predicted the 28-day or 90-day mortality for cirrhotic patients who experienced variceal bleeding.Obesity and binge drinking often coexist and work synergistically to promote steatohepatitis; however, the underlying mechanisms remain obscure. In this mini-review, we briefly summarize clinical evidence of the synergistical effect of obesity and heavy drinking on steatohepatitis and discuss the underlying mechanisms obtained from the study of several mouse models. High-fat diet (HFD) feeding and binge ethanol synergistically induced steatohepatitis and fibrosis in mice with significant intrahepatic neutrophil infiltration; such HFD-plus-ethanol treatment markedly up-regulated the hepatic expression of many chemokines with the highest fold (approximately 30-fold) induction of chemokine (C-X-C motif) ligand 1 (Cxcl1), which contributes to hepatic neutrophil infiltration and liver injury. Furthermore, HFD feeding activated peroxisome proliferator-activated receptor gamma that subsequently inhibited CXCL1 upregulation in hepatocytes, thereby forming a negative feedback loop to prevent neutrophil overaction; whereas binge ethanol blocked this loop and then exacerbated CXCL1 elevation, neutrophil infiltration, and liver injury. Interestingly, inflamed mouse hepatocytes attracted neutrophils less effectively than inflamed human hepatocytes due to the lower induction of CXCL1 and the lack of the interleukin (IL)-8 gene in the mouse genome, which may be one of the reasons for difficulty in development of mouse models of alcoholic steatohepatitis and nonalcoholic steatohepatitis (NASH). Hepatic overexpression of Cxcl1 and/or IL-8 promoted steatosis-to-NASH progression in HFD-fed mice by inducing neutrophil infiltration, oxidative stress, hepatocyte death, fibrosis, and p38 mitogen-activated protein kinase activation. Collectively, obesity and binge drinking synergistically promote steatohepatitis via the induction of CXCL1 and subsequent hepatic neutrophil infiltration.
The need for tailoring ovarian cancer treatments to individual patients is increasing. This study aimed to evaluate the prognostic value of pretreatment laboratory test data for predicting the response and survival outcomes of platinumbased chemotherapy in ovarian cancer.
We enrolled 270 patients with ovarian cancer diagnosed at the Kyoto Medical Center (n=120; group A) and Kyoto University (n=150; group B). Data on 9 blood parameters (neutrophil to lymphocyte ratio [NLR], platelet to lymphocyte rate [PLR], C-reactive protein, lactate dehydrogenase [LDH], glucose, total cholesterol, high-density lipoprotein [HDL], low-density lipoprotein, and triglyceride levels), cancer pathology, cancer stage, cytoreduction outcomes, serum cancer antigen 125 levels, platinum-free interval (PFI), disease-free survival (DFS), and overall survival were assessed retrospectively.
NLR, PLR, LDH, and HDL were significantly different in advanced stage patients (P<0.001, <0.001, 0.029, and <0.001, respectively). The Kaplan-Meier curves revealed that high LDH level (≥250 U/L) was associated with reduced PFI (P=0.037 and 0.012) and DFS (P=0.007 and 0.002) in groups A and B, respectively. High NLR (≥4) was associated with reduced DFS in both groups (P=0.036 and 0.005, respectively). LDH showed higher area under the curve (AUC) values in predicting platinum resistance with a PFI of less than 6 months and 12 months (AUC=0.606 and 0.646, respectively) than NLR. In the multivariate analysis, LDH remained significant (P=0.019) after adjusting for the 9 blood parameters.
Serum LDH level may possibly predict platinum resistance and prognosis in ovarian cancer and may be useful when developing precision medicine for individual patients.
Serum LDH level may possibly predict platinum resistance and prognosis in ovarian cancer and may be useful when developing precision medicine for individual patients.
Red cell distribution width (RDW) is a prognostic marker in vascular diseases. While increased RDW predicts mortality and outcomes after ischemic stroke, evidence regarding its prognostic significance in stroke rehabilitation is lacking. Thus, the present study investigated the relationship of RDW with stroke, orthopedic, and deconditioning rehabilitation outcomes.
This prospective comparative study included three groups (stroke, orthopedic, and deconditioning) of older adult patients hospitalized for rehabilitation. The patients in each group were divided into two subgroups according to whether they had high (>14.5%) or normal (≤14.5%) RDW levels on admission. Functional outcome was assessed by total and motor FIM (Functional Independence Measure) score changes and efficiency at admission and on discharge.
Of the 234 eligible patients, 108 (46.2%) had high RDW. Of the 50 stroke rehabilitation patients, 13 (26%) had high RDW. FIM change and efficiency scores were significantly lower in patients with high RDW only in the stroke rehabilitation group. However, multiple linear regression analysis showed that high RDW was not independently associated with total and motor FIM gain or total and motor FIM efficiency.
High RDW levels on admission to rehabilitation were associated with poor rehabilitation outcome in stroke patients but were not an independent risk factor for rehabilitation outcomes.
High RDW levels on admission to rehabilitation were associated with poor rehabilitation outcome in stroke patients but were not an independent risk factor for rehabilitation outcomes.The application of artificial intelligence and machine learning to hyperspectral mass spectrometry imaging (MSI) data has received considerable attention over recent years. Various methodologies have shown great promise in their ability to handle the complexity and size of MSI data sets. Advances in this area have been particularly appealing for MSI of biological samples, which typically produce highly complicated data with often subtle relationships between features. There are many different machine learning approaches that have been applied to MSI data over the past two decades. In this review, we focus on a subset of non-linear machine learning techniques that have mostly only been applied in the past 5 years. Specifically, we review the use of the self-organizing map (SOM), SOM with relational perspective mapping (SOM-RPM), t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). While not their only functionality, we have grouped these techniques based on their ability to produce what we refer to as similarity maps. Similarity maps are color representations of hyperspectral data, in which spectral similarity between pixels-that is, their distance in high-dimensional space-is represented by relative color similarity. In discussing these techniques, we describe, briefly, their associated algorithms and functionalities, and also outline applications in MSI research with a strong focus on biological sample types. PIM447 order The aim of this review is therefore to introduce this relatively recent paradigm for visualizing and exploring hyperspectral MSI, while also providing a comparison between each technique discussed.
Long-acting products are changing the haemophilia A treatment landscape by giving patients and caregivers treatment options with varying product attributes.
A discrete choice experiment (DCE) was used to elicit treatment attribute preferences among patients with haemophilia A and caregivers of children with haemophilia A.
A survey of sociodemographics and preferences was completed by an online panel of adult patients with haemophilia A and caregivers of children (<18years) with haemophilia A. The DCE included a series of questions in which respondents chose their preferred option from pairs of hypothetical treatment profiles with systematic variation in the levels of six attributes (safety concerns with too much clotting, bleed protection, dosing frequency, length of time the product has been approved for use, product type and joint health studies). Preference weights and relative attribute importance scores were estimated using random parameters logit models.
One hundred and thirteen patients (mean age 35.
