70 research outputs found

    Cerebral monitoring in surgical ICU patients

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    PURPOSE OF REVIEW: To give an overview of cerebral monitoring techniques for surgical ICU patients. RECENT FINDINGS: As the burden of postsurgical neurological and neurocognitive complications becomes increasingly recognized, cerebral monitoring in the surgical ICU might gain a relevant role in detecting and possibly preventing adverse outcomes. However, identifying neurological alterations in surgical ICU patients, who are often sedated and mechanically ventilated, can be challenging. Various noninvasive and invasive techniques are available for cerebral monitoring, providing an assessment of cortical electrical activity, cerebral oxygenation, blood flow autoregulation, intracranial pressure, and cerebral metabolism. These techniques can be used for the diagnosis of subclinical seizures, the assessment of sedation depth and delirium, the detection of an impaired cerebral blood flow, and the diagnosis of neurosurgical complications. SUMMARY: Cerebral monitoring can be a valuable tool in the early detection of adverse outcomes in surgical ICU patients, but the evidence is limited, and clear clinical indications are still lacking

    What is new in microcirculation and tissue oxygenation monitoring?

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    Ensuring and maintaining adequate tissue oxygenation at the microcirculatory level might be considered the holy grail of optimal hemodynamic patient management. However, in clinical practice we usually focus on macro-hemodynamic variables such as blood pressure, heart rate, and sometimes cardiac output. Other macro-hemodynamic variables like pulse pressure or stroke volume variation are additionally used as markers of fluid responsiveness. In recent years, an increasing number of technological devices assessing tissue oxygenation or microcirculatory blood flow have been developed and validated, and some of them have already been incorporated into clinical practice. In this review, we will summarize recent research findings on this topic as published in the last 2 years in the Journal of Clinical Monitoring and Computing (JCMC). While some techniques are already currently used as routine monitoring (e.g. cerebral oxygenation using near-infrared spectroscopy (NIRS)), others still have to find their way into clinical practice. Therefore, further research is needed, particularly regarding outcome measures and cost-effectiveness, since introducing new technology is always expensive and should be balanced by downstream savings. The JCMC is glad to provide a platform for such research

    Endoscopic Tactile Capsule for Non-Polypoid Colorectal Tumour Detection

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    An endoscopic tactile robotic capsule, embedding miniaturized MEMS force sensors, is presented. The capsule is conceived to provide automatic palpation of non-polypoid colorectal tumours during colonoscopy, since it is characterized by high degree of dysplasia, higher invasiveness and lower detection rates with respect to polyps. A first test was performed employing a silicone phantom that embedded inclusions with variable hardness and curvature. A hardness-based classification was implemented, demonstrating detection robustness to curvature variation. By comparing a set of supervised classification algorithms, a weighted 3-nearest neighbor classifier was selected. A bias force normalization model was introduced in order to make different acquisition sets consistent. Parameters of this model were chosen through a particle swarm optimization method. Additionally, an ex-vivo test was performed to assess the capsule detection performance when magnetically-driven along a colonic tissue. Lumps were identified as voltage peaks with a prominence depending on the total magnetic force applied to the capsule. Accuracy of 94 % in hardness classification was achieved, while a 100 % accuracy is obtained for the lump detection within a tolerance of 5 mm from the central path described by the capsule. In real application scenario, we foresee our device aiding physicians to detect tumorous tissues

    Mitral Valve Coaptation Reserve Index:A Model to Localize Individual Resistance to Mitral Regurgitation Caused by Annular Dilation

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    Objectives: The objective of this study was to develop a mathematical model for mitral annular dilatation simulation and determine its effects on the individualized mitral valve (MV) coaptation reserve index (CRI). Design: A retrospective analysis of intraoperative transesophageal 3-dimensionalechocardiographic MV datasets was performed. A mathematical model was created to assess the mitral CRI for each leaflet segment (A1-P1, A2-P2, A3-P3). Mitral CRI was defined as the ratio between the coaptation reserve (measured coaptation length along the closure line) and an individualized correction factor. Indexing was chosen to correct for MV sphericity and area of largest valve opening. Mathematical models were created to simulate progressive mitral annular dilatation and to predict the effect on the individual mitral CRI. Setting: At a single-center academic hospital. Participants: Twenty-five patients with normally functioning MVs undergoing cardiac surgery. Interventions: None. Measurements and Main Results: Direct measurement of leaflet coaptation along the closure line showed the lowest amount of coaptation (reserve) near the commissures (A1-P1 0.21 ± 0.05 cm and A3-P3 0.22 ± 0.06 cm), and the highest amount of coaptation (reserve) at region A2 to P2 0.25 ± 0.06 cm. After indexing, the A2-to-P2 region was the area with the lowest CRI in the majority of patients, and also the area with the least resistance to mitral regurgitation (MR) occurrence after simulation of progressive annular dilation. Conclusions: Quantification and indexing of mitral coaptation reserve along the closure line are feasible. Indexing and mathematical simulation of progressive annular dilatation consistently showed that indexed coaptation reserve was lowest in the A2-to-P2 region. These results may explain why this area is prone to lose coaptation and is often affected in MR

    Multi-Gene Next-Generation Sequencing Panel for Analysis of BRCA1/BRCA2 and Homologous Recombination Repair Genes Alterations Metastatic Castration-Resistant Prostate Cancer

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    : Despite significant therapeutic advances, metastatic CRPC (mCRPC) remains a lethal disease. Mutations in homologous recombination repair (HRR) genes are frequent in mCRPC, and tumors harboring these mutations are known to be sensitive to PARP inhibitors. The aim of this study was to verify the technical effectiveness of this panel in the analysis of mCRPC, the frequency and type of mutations in the BRCA1/BRCA2 genes, as well as in the homologous recombination repair (HRR) genes. A total of 50 mCRPC cases were analyzed using a multi-gene next-generation sequencing panel evaluating a total of 1360 amplicons in 24 HRR genes. Of the 50 cases, 23 specimens (46.0%) had an mCRPC harboring a pathogenic variant or a variant of uncertain significance (VUS), whereas in 27 mCRPCs (54.0%), no mutations were detected (wild-type tumors). BRCA2 was the most commonly mutated gene (14.0% of samples), followed by ATM (12.0%), and BRCA1 (6.0%). In conclusion, we have set up an NGS multi-gene panel that is capable of analyzing BRCA1/BRCA2 and HRR alterations in mCRPC. Moreover, our clinical algorithm is currently being used in clinical practice for the management of patients with mCRPC

    Differential Modulation of TNF-α–Induced Apoptosis by Neisseria meningitidis

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    Infections by Neisseria meningitidis show duality between frequent asymptomatic carriage and occasional life-threatening disease. Bacterial and host factors involved in this balance are not fully understood. Cytopathic effects and cell damage may prelude to pathogenesis of isolates belonging to hyper-invasive lineages. We aimed to analyze cell–bacteria interactions using both pathogenic and carriage meningococcal isolates. Several pathogenic isolates of the ST-11 clonal complex and carriage isolates were used to infect human epithelial cells. Cytopathic effect was determined and apoptosis was scored using several methods (FITC-Annexin V staining followed by FACS analysis, caspase assays and DNA fragmentation). Only pathogenic isolates were able to induce apoptosis in human epithelial cells, mainly by lipooligosaccharide (endotoxin). Bioactive TNF-α is only detected when cells were infected by pathogenic isolates. At the opposite, carriage isolates seem to provoke shedding of the TNF-α receptor I (TNF-RI) from the surface that protect cells from apoptosis by chelating TNF-α. Ability to induce apoptosis and inflammation may represent major traits in the pathogenesis of N. meningitidis. However, our data strongly suggest that carriage isolates of meningococci reduce inflammatory response and apoptosis induction, resulting in the protection of their ecological niche at the human nasopharynx

    Can Clinical and Surgical Parameters Be Combined to Predict How Long It Will Take a Tibia Fracture to Heal? A Prospective Multicentre Observational Study: The FRACTING Study

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    Background. Healing of tibia fractures occurs over a wide time range of months, with a number of risk factors contributing to prolonged healing. In this prospective, multicentre, observational study, we investigated the capability of FRACTING (tibia FRACTure prediction healING days) score, calculated soon after tibia fracture treatment, to predict healing time. Methods. The study included 363 patients. Information on patient health, fracture morphology, and surgical treatment adopted were combined to calculate the FRACTING score. Fractures were considered healed when the patient was able to fully weight-bear without pain. Results. 319 fractures (88%) healed within 12 months from treatment. Forty-four fractures healed after 12 months or underwent a second surgery. FRACTING score positively correlated with days to healing: r = 0.63 (p < 0.0001). Average score value was 7.3 \ub1 2.5; ROC analysis showed strong reliability of the score in separating patients healing before versus after 6 months: AUC = 0.823. Conclusions. This study shows that the FRACTING score can be employed both to predict months needed for fracture healing and to identify immediately after treatment patients at risk of prolonged healing. In patients with high score values, new pharmacological and nonpharmacological treatments to enhance osteogenesis could be tested selectively, which may finally result in reduced disability time and health cost savings

    Can Clinical and Surgical Parameters Be Combined to Predict How Long It Will Take a Tibia Fracture to Heal? A Prospective Multicentre Observational Study: The FRACTING Study

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    Healing of tibia fractures occurs over a wide time range of months, with a number of risk factors contributing to prolonged healing. In this prospective, multicentre, observational study, we investigated the capability of FRACTING (tibia FRACTure prediction healING days) score, calculated soon after tibia fracture treatment, to predict healing time. Methods: The study included 363 patients. Information on patient health, fracture morphology, and surgical treatment adopted were combined to calculate the FRACTING score. Fractures were considered healed when the patient was able to fully weight-bear without pain. Results: 319 fractures (88%) healed within 12 months from treatment. Forty-four fractures healed after 12 months or underwent a second surgery. FRACTING score positively correlated with days to healing: r = 0.63 (p < 0.0001). Average score value was 7.3 ± 2.5; ROC analysis showed strong reliability of the score in separating patients healing before versus after 6 months: AUC = 0.823. Conclusions: This study shows that the FRACTING score can be employed both to predict months needed for fracture healing and to identify immediately after treatment patients at risk of prolonged healing. In patients with high score values, new pharmacological and nonpharmacological treatments to enhance osteogenesis could be tested selectively, which may finally result in reduced disability time and health cost savings
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