ICM Partners

About: ICM Partners is a based out in . It is known for research contribution in the topics: Population & Breast cancer. The organization has 1311 authors who have published 1521 publications receiving 33745 citations. The organization is also known as: International Creative Management Partners.

Effect of a fluid challenge on the Surgical Pleth Index during stable propofol-remifentanil anaesthesia.

Abstract: Background The Surgical Pleth Index (SPI), derived from pulse amplitude and heartbeat interval, is proposed to monitor anti-nociception during anaesthesia. Its response to noxious stimulation can be affected by the intravascular volume status. This study investigated the effect of a fluid challenge (FC) on SPI during steady-state conditions. Methods After Institutional Review Board approval, 33 consenting patients undergoing neurosurgery received a 4 ml/kg starch FC over less than 5 min under stable surgical stimulation conditions and stable propofol (CePPF) and remifentanil (CeREMI) effect-site concentrations as estimated by target-controlled infusion systems. Intravascular volume status was assessed using the Delta Down (DD). We looked at the SPI response to FC according to DD, CePPF, and CeREMI. Results Following FC, SPI did not change in 16, increased in 12, and decreased in 3 patients. CeREMI poorly affected the SPI response to FC. In normovolaemic patients, the probability of an SPI change after FC was low under common CePPF (0.9 to 3.9 μg/ml). A decrease in SPI was more probable with worsening hypovolaemia and lowering CePPF, while an increase in SPI was more probable with increasing CePPF. SPI changes were only attributable to modifications in pulse wave amplitude and not in heart rate. Conclusions During stable anaesthesia and surgery, SPI may change in response to FC. The effect of FC on SPI is influenced by volaemia and CePPF through pulse wave amplitude modifications. These situations may confound the interpretation of SPI as a surrogate measure of the nociception–anti-nociception balance.

CA-125 ELIMination rate constant K (KELIM) Is A Marker Of Chemosensitivity In Patients With Ovarian Cancer: Results from the Phase II CHIVA trial

Abstract: Background: In ovarian cancer patients receiving neoadjuvant chemotherapy, the first line treatment success will depend on both the tumor primary chemosensitivity and the completeness of interval debulking surgery (IDS). The modeled CA-125 ELIMination rate constant K (KELIM), calculated with the CA-125 longitudinal kinetics during the first 100 chemotherapy days, is a validated early marker of tumor chemosensitivity. The objective was to investigate the role of the chemosensitivity relative to the success of first line medical-surgical treatment. Experimental design: The CA-125 concentrations were prospectively measured in the randomized phase II trial CHIVA (NCT01583322, carboplatin-paclitaxel regimen +/- nintedanib, and IDS, n=188 patients). The KELIM predictive value regarding the tumor response rate; likelihood of complete IDS; risk of subsequent platinum-resistant relapse (PtRR); progression-free survival (PFS); and overall survival (OS) was assessed using univariate & multivariate tests. Results:The data from 134 patients were analysed. KELIM was an independent and major predictor of subsequent PtRR risk, and of survivals. The final logistic regression model, including KELIM (odds-ratio= 0.13, 95%CI 0.03-0.49) and complete IDS (no vs yes, odds-ratio= 0.30, 95%CI 0.11-0.76) highlights the preponderant role of chemosensitivity on the success of the first line treatment. In patients with highly chemosensitive diseases, the patient prognosis was driven more by the chemotherapy-induced antitumor effects than by the surgery. Conclusions: The tumor primary chemosensitivity, assessed by the modeled CA-125 KELIM calculated during neoadjuvant chemotherapy (http://www.biomarker-kinetics.org/CA-125-neo), may be a major parameter to consider for decision-making regarding IDS attempt, and selecting patients for treatments meant to reverse the primary chemoresistance.

Evolving Evidence for the Value of Neuroimaging Methods and Biological Markers in Subjects Categorized with Subjective Cognitive Decline.

Abstract: There is evolving evidence that individuals categorized with subjective cognitive decline (SCD) are potentially at higher risk for developing objective and progressive cognitive impairment compared to cognitively healthy individuals without apparent subjective complaints. Interestingly, SCD, during advancing preclinical Alzheimer's disease (AD), may denote very early, subtle cognitive decline that cannot be identified using established standardized tests of cognitive performance. The substantial heterogeneity of existing SCD-related research data has led the Subjective Cognitive Decline Initiative (SCD-I) to accomplish an international consensus on the definition of a conceptual research framework on SCD in preclinical AD. In the area of biological markers, the cerebrospinal fluid signature of AD has been reported to be more prevalent in subjects with SCD compared to healthy controls; moreover, there is a pronounced atrophy, as demonstrated by magnetic resonance imaging, and an increased hypometabolism, as revealed by positron emission tomography, in characteristic brain regions affected by AD. In addition, SCD individuals carrying an apolipoprotein ɛ4 allele are more likely to display AD-phenotypic alterations. The urgent requirement to detect and diagnose AD as early as possible has led to the critical examination of the diagnostic power of biological markers, neurophysiology, and neuroimaging methods for AD-related risk and clinical progression in individuals defined with SCD. Observational studies on the predictive value of SCD for developing AD may potentially be of practical value, and an evidence-based, validated, qualified, and fully operationalized concept may inform clinical diagnostic practice and guide earlier designs in future therapy trials.

Recommendations for the Use of Automated Gray Matter Segmentation Tools: Evidence from Huntington's Disease.

Abstract: The selection of an appropriate segmentation tool is a challenge facing any researcher aiming to measure grey matter (GM) volume. Many tools have been compared, yet there is currently no method that can be recommended above all others; in particular, there is a lack of validation in disease cohorts. This work utilises a clinical dataset to conduct an extensive comparison of segmentation tools. Our results confirm that all tools have advantages and disadvantages, and we present a series of considerations that may be of use when selecting a grey matter segmentation method, rather than a ranking of these tools. Seven segmentation tools were compared using 3T MRI data from 20 controls, 40 premanifest Huntington’s disease (HD) and 40 early HD participants. Segmented volumes underwent detailed visual quality control. Reliability and repeatability of total, cortical and lobular grey matter was investigated in repeated baseline scans. The relationship between each tool was also examined. Longitudinal within-group change over 3 years was assessed via generalised least squares regression to determine sensitivity of each tool to disease effects. Visual quality control and raw volumes highlighted large variability between tools, especially in occipital and temporal regions. Most tools showed reliable performance and the volumes were generally correlated. Results for longitudinal within-group change varied between tools, especially within lobular regions. These differences highlight the need for careful selection of segmentation methods in clinical neuroimaging studies. This guide acts as a primer aimed at the novice or non-technical imaging scientist providing recommendations for the selection of cohort-appropriate GM segmentation software.

Dynamic programming for graphs on surfaces

Abstract: We provide a framework for the design and analysis of dynamic programming algorithms for surface-embedded graphs on n vertices and branchwidth at most k. Our technique applies to general families of problems where standard dynamic programming runs in 2O(k⋅log k) ⋅ n steps. Our approach combines tools from topological graph theory and analytic combinatorics. In particular, we introduce a new type of branch decomposition called surface cut decomposition, generalizing sphere cut decompositions of planar graphs, which has nice combinatorial properties. Namely, the number of partial solutions that can be arranged on a surface cut decomposition can be upper-bounded by the number of noncrossing partitions on surfaces with boundary. It follows that partial solutions can be represented by a single-exponential (in the branchwidth k) number of configurations. This proves that, when applied on surface cut decompositions, dynamic programming runs in 2O(k) ⋅ n steps. That way, we considerably extend the class of problems that can be solved in running times with a single-exponential dependence on branchwidth and unify/improve most previous results in this direction.