Acute ischemic stroke (IS) is one of the leading causes of morbidity, functional disability and mortality worldwide. The objective was to evaluate IS risk factors and imaging variables as predictors ...of short-term disability and mortality in IS. Consecutive 106 IS patients were enrolled. We examined the accuracy of IS severity using the National Institutes of Health Stroke Scale (NIHSS), carotid intima-media thickness (cIMT) and carotid stenosis (both assessed using ultrasonography with doppler) predicting IS outcome assessed with the modified Rankin scale (mRS) three months after hospital admission. Poor prognosis (mRS ≥ 3) at three months was predicted by carotid stenosis (≥ 50%), type 2 diabetes mellitus and NIHSS with an accuracy of 85.2% (sensitivity: 90.2%; specificity: 81.8%). The mRS score at three months was strongly predicted by NIHSS (β = 0.709, p < 0.001). Short-term mortality was strongly predicted using a neural network model with cIMT (≥ 1.0 mm
versus
< 1.0 mm), NIHSS and age, yielding an area under the receiving operator characteristic curve of 0.977 and an accuracy of 94.7% (sensitivity: 100.0%; specificity: 90.9%). High NIHSS (≥ 15) and cIMT (≥ 1.0 mm) increased the probability of dying with hazard ratios of 7.62 and 3.23, respectively. Baseline NIHSS was significantly predicted by the combined effects of age, large artery atherosclerosis stroke, sex, cIMT, body mass index, and smoking. In conclusion, high values of cIMT and NIHSS at admission strongly predict short-term functional impairment as well as mortality three months after IS, underscoring the importance of those measurements to predict clinical IS outcome.
The aim was to investigate the association between plasma levels of cellular adhesion molecules (CAMs) and risk factors, subtypes, severity and short-term mortality of acute ischemic stroke (IS), and ...to identify a panel of biomarkers to predict short-term mortality after IS. The prospective study evaluated 132 IS patients within 24 h of their hospital admission. The baseline IS severity was assessed using the National Institutes Health Stroke Scale (NIHSS) and categorized as mild (NIHSS < 5), moderate (NIHSS 5–14) and severe (NIHSS ≥ 15). After three-month follow-up, the disability was assessed using the modified Rankin Scale (mRS); moreover, the patients were classified as survivors and non-survivors. Baseline inflammatory and anti-inflammatory cytokines and soluble CAMs were evaluated. Twenty-nine (21.9%) IS patients were non-survivors and showed higher NIHSS and soluble vascular cellular adhesion molecule 1 (sVCAM-1) than the survivors. The sVCAM-1 levels positively correlated with age, homocysteine, severity, and disability. The model #3 combining sVCAM-1 and NIHSS showed better results to predict short-term mortality with an area under the curve receiving operating characteristics (AUC/ROC) of 0.8841 95% confidence interval (CI): 0.795–0.941 than the models with sVCAM-1 and NIHSS alone, with positive predictive value of 68.0%, negative predictive value of 91.3%, and accuracy of 86.5%. In conclusion, the combined model with baseline severity of IS and sVCAM-1 levels can early predict the prognosis of IS patients who may benefit with therapeutic measures of personalized therapy that taken into account these biomarkers. Moreover, this result suggests that VCAM-1 might be a potential target for the therapeutic strategies in IS.
Some clinical, imaging, and laboratory biomarkers have been identified as predictors of prognosis of acute ischemic stroke (IS). The aim of this study was to evaluate the prognostic validity of a ...combination of clinical, imaging, and laboratory biomarkers in predicting 1-year mortality of IS. We evaluated 103 patients with IS within 24 h of their hospital admission and assessed demographic data, IS severity using the National Institutes of Health Stroke Scale (NIHSS), carotid intima-media thickness (cIMT), and degree of stenosis, as well as laboratory variables including immune-inflammatory, coagulation, and endothelial dysfunction biomarkers. The IS patients were categorized as survivors and non-survivors 1 year after admission. Non-survivors showed higher NIHSS and cIMT values, lower antithrombin, Protein C, platelet counts, and albumin, and higher Factor VIII, von Willebrand Factor (vWF), white blood cells, tumor necrosis factor (TNF)-α, interleukin (IL)-10, high-sensitivity C-reactive protein (hsCRP), and vascular cellular adhesion molecule 1 (VCAM-1) than survivors. Neural network models separated non-survivors from survivors using NIHSS, cIMT, age, IL-6, TNF-α, hsCRP, Protein C, Protein S, vWF, and platelet endothelial cell adhesion molecule 1 (PECAM-1) with an area under the receiving operating characteristics curve (AUC/ROC) of 0.975, cross-validated accuracy of 93.3%, sensitivity of 100% and specificity of 85.7%. In conclusion, imaging, immune-inflammatory, and coagulation biomarkers add predictive information to the NIHSS clinical score and these biomarkers in combination may act as predictors of 1-year mortality after IS. An early prediction of IS outcome is important for personalized therapeutic strategies that may improve the outcome of IS.
Gingival recession is an oral health problem that affects a large part of the population. Several treatments are suggested in the current literature; among them is the use of buccal fat pad grafting. ...The objective of this case report is to describe the treatment of a Miller Class I gingival recession using a nonpedicled buccal fat pad graft immediately after performing the surgery for buccal fat pad removal (bichectomy technique). First, bilateral surgical removal of the buccal fat pad was performed with the main objective of eliminating oral mucosa biting. The recipient site was prepared to receive a portion of the fat pad that was cut and macerated in a size that was sufficient to cover the recession. The patient was followed up at 15, 30, 60, and 365 days postsurgery, and the results showed an elimination of the oral mucosa biting and complete coverage of the gingival recession. It was concluded that the nonpedicled buccal fat pad graft is another option for the treatment of Miller Class I recessions.
Summary
Background
In HCV‐infected cirrhotic patients with successfully treated early hepatocellular carcinoma (HCC), the time to HCC recurrence and the effects of sustained viral eradication (SVR) ...by interferon (IFN)‐based or IFN‐free regimens on HCC recurrence remain unclear.
Aim
To perform an indirect comparison of time to recurrence (TTR) in patients with successfully treated early HCC and active HCV infection with those of patients with SVR by IFN‐based and by IFN‐free regimens.
Methods
We evaluated 443 patients with HCV‐related cirrhosis and Barcelona Clinic Liver Cancer Stage A/0 HCC who had a complete radiological response after curative resection or ablation. Active HCV infection was present in 328, selected from the Italian Liver Cancer group cohort; 58 patients had SVR achieved by IFN‐free regimens after HCC cure, and 57 patients had SVR achieved by IFN‐based regimens after HCC cure. Individual data of patients in the last two groups were extracted from available publications.
Results
TTR by Kaplan–Meier curve was significantly lower in patients with active HCV infection compared with those with SVR both by IFN‐free (P = 0.02) and by IFN‐based (P < 0.001) treatments. TTR was similar in patients with SVR by IFN‐free or by IFN‐based (P = 0.49) strategies.
Conclusion
In HCV‐infected, successfully treated patients with early HCC, SVR obtained by IFN‐based or IFN‐free regimens significantly reduce tumour recurrence without differences related to the anti‐viral strategy used.
Background
Dichotomous models like Milan Criteria represent the routinely used tools for predicting the outcome of patients with hepatocellular carcinoma (HCC). However, a paradigm shift from a ...dichotomous to continuous prognostic stratification should represent a good strategy for improving the prediction process. Recently, the tumor burden score (TBS) has been proposed for selecting patients with colorectal liver metastases. To date, TBS has not been validated in a large HCC population. The main objective of this study was to evaluate the prognostic power of TBS in an HCC population treated with different curative and palliative modalities.
Methods
Prospectively collected data from consecutive HCC patients managed in 24 institutions participating in the ITA.LI.CA group between Jan 2002 and Mar 2015 were analyzed (
n
= 4759). A sub-analysis focused on 3909 patients with the radiological evidence of vascular invasion or metastatic disease was also performed.
Results
TBS demonstrated the best discriminative ability when compared to MC and other tumor-specific scores. At multivariable Cox regression analysis, TBS was an independent risk factor of overall survival, with a 6% increased risk for patient death for each point increase in TBS. At survival analysis, when TBS ≥ 8 was connected with MELD ≥ 15 and alpha-fetoprotein ≥ 1000 ng/mL, patients presenting all these three risk factors presented the worst results (
p
value < 0.0001).
Conclusions
Survival prediction of HCC patients was very well done using TBS model, even stratifying the population in relation to the presence of metastases and/or vascular invasion. TBS model was the best in terms of discriminatory ability and goodness of fit when compared with other continuous or binary variables. Its incorporation in a model composed by tumor- and liver function-related variables further increases its survival prediction.
Background
The Italian Liver Cancer (ITA.LI.CA) prognostic system for patients with hepatocellular carcinoma (HCC) has recently been proposed and validated. We sought to explore the relationship ...among the ITA.LI.CA prognostic variables (ie tumour stage, functional score based on performance status and Child‐Pugh score, and alpha‐fetoprotein), treatment selection and survival outcome in HCC patients.
Patients and Methods
We analysed 4,867 consecutive HCC patients undergoing six main treatment strategies (liver transplantation, LT; liver resection, LR; ablation, ABL; intra‐arterial therapy, IAT; Sorafenib, SOR; and best supportive care, BSC) and enrolled during 2002‐2015 in a multicenter Italian database. In order to control pretreatment imbalances in observed variables, a machine learning methodology was used and inverse probability of treatment weights (IPTW) was calculated. An IPTW‐adjusted multivariate survival model that included ITA.LI.CA prognostic variables, treatment period and treatment strategy was then developed. The survival benefit of HCC treatments was described as a hazard ratio (95% confidence interval), using BSC as a reference value and as predicted median survival.
Results
After the IPTW, the six treatment groups became well balanced for most baseline characteristics. In the IPTW‐adjusted multivariate survival model, treatment strategy was found to be the strongest survival predictor, irrespective of ITA.LI.CA prognostic variables and treatment period. The survival benefit of different therapies over BSC was: LT = 0.19 (0.18‐0.20); RES = 0.40 (0.37‐0.42); ABL 0.42 (0.40‐0.44); IAT = 0.58 (0.55‐0.61); SOR = 0.92 (0.87‐0.97). This multivariate model was then used to predict median survival for each therapy within each ITA.LI.CA stage.
Conclusion
The concept of therapeutic hierarchy was established within each ITA.LI.CA stage.
Nosocomial acute-on-chronic liver failure (nACLF) develops in at least 10% of patients with cirrhosis hospitalized for acute decompensation (AD), greatly worsening their prognosis. In this ...prospective observational study, we aimed to identify rapidly obtainable predictors at admission, which allow for the early recognition and stratification of patients at risk of nACLF.
A total of 516 consecutive patients hospitalized for AD of cirrhosis were screened: those who did not present ACLF at admission (410) were enrolled and surveilled for the development of nACLF.
Fifty-nine (14%) patients developed nALCF after a median of 7 (IQR 4-18) days. At admission, they presented a more severe disease and higher degrees of systemic inflammation and anemia than those (351; 86%) who remained free from nACLF. Competing risk multivariable regression analysis showed that baseline MELD score (sub-distribution hazard ratio sHR 1.15; 95% CI 1.10-1.21;
0.001), hemoglobin level (sHR 0.81; 95% CI 0.68-0.96;
0.018), and leukocyte count (sHR 1.11; 95% CI 1.06-1.16;
0.001) independently predicted nACLF. Their optimal cut-off points, determined by receiver-operating characteristic curve analysis, were: 13 points for MELD score, 9.8 g/dl for hemoglobin, and 5.6x10
/L for leukocyte count. These thresholds were used to stratify patients according to the cumulative incidence of nACLF, being 0, 6, 21 and 59% in the presence of 0, 1, 2 or 3 risk factors (
0.001). Nosocomial bacterial infections only increased the probability of developing nACLF in patients with at least 1 risk factor, rising from 3% to 29%, 16% to 50% and 52% to 83% in patients with 1, 2 or 3 risk factors, respectively.
Easily available laboratory parameters, related to disease severity, systemic inflammation, and anemia, can be used to identify, at admission, hospitalized patients with AD at increased risk of developing nACLF.
More than 10% of patients with cirrhosis hospitalized because of an acute decompensation develop acute-on-chronic liver failure, which is associated with high short-term mortality, during their hospital stay. We found that the combination of 3 easily obtainable variables (model for end-stage liver disease score, leukocyte count and hemoglobin level) help to identify and stratify patients according to their risk of developing nosocomial acute-on-chronic liver failure, from nil to 59%. Moreover, if a nosocomial bacterial infection occurs, such an incidence proportionally increases from nil to 83%. This simple approach helps to identify patients at risk of developing nosocomial acute-on-chronic liver failure at admission to hospital, enabling clinicians to put in place preventive measures.
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