Outcomes of Hospitalizations for Cardiogenic Shock at Left Ventricular Assist Device Versus Non-Left Ventricular Assist Device Centers.

Background Cardiogenic shock (CS) is a complex syndrome associated with high morbidity and mortality. In recent years, many US hospitals have formed multidisciplinary shock teams capable of rapid diagnosis and triage. Because of preexisting collaborative systems of care, hospitals with left ventricular assist device (LVAD) programs may also represent "centers of excellence" for CS care. However, the outcomes of patients with CS at LVAD centers have not been previously evaluated. Methods and Results Patients with CS were identified in the 2012 to 2014 National Inpatient Sample. Clinical characteristics, revascularization rates, and use of mechanical circulatory support were analyzed in LVAD versus non-LVAD centers. The association between hospital type and in-hospital mortality was examined using multivariable logistic regression models. Of 272 075 hospitalizations, 26.0% were in LVAD centers. CS attributable to causes other than acute myocardial infarction represented most cases. In-hospital mortality was lower in LVAD centers (38.9% versus 43.3%; P<0.001). In multivariable analysis, the odds of mortality remained significantly lower for hospitalizations in LVAD centers (odds ratio, 0.89; P<0.001). In patients with CS secondary to acute myocardial infarction, revascularization rates were similar between LVAD and non-LVAD centers. The use of intra-aortic balloon pump (18.7% versus 18.8%) and Impella/TandemHeart (2.6% versus 1.9%) was similar between hospital types, whereas extracorporeal membrane oxygenation was used more frequently in LVAD centers (4.3% versus 0.2%; P<0.001). Conclusions Risk-adjusted mortality was lower in patients with CS who were hospitalized at LVAD centers. These centers likely represent specialized, shock team capable institutions across the country that may be best suited to manage patients with CS.

Parallel Reaction Monitoring-Mass Spectrometry (PRM-MS)-Based Targeted Proteomic Surrogates for Intrinsic Subtypes in Breast Cancer: Comparative Analysis with Immunohistochemical Phenotypes.

Advances in targeted medications have improved the survival rate of breast cancer patients with molecular marker-positive tumors. To date, immunohistochemistry (IHC) has remained as the standard method for quantifying the markers including HER2, ER, and PR. Nevertheless, IHC-based grading is subjective, because the results depend on trained individuals' eye rather than numerical quantities. Thus, alternative methods that can account for quantitative levels of markers are gaining popularity, including targeted proteomics by mass spectrometry (MS). However, technical limitations have impeded the application of MS-based protein quantification to pathological FFPE slides that contain low amounts of cross-linked proteins. To challenge this, we developed a parallel reaction monitoring-mass spectrometry (PRM-MS) method to measure the expression levels of breast cancer markers. After developing the method using cell lines, we performed PRM-MS using 51 individuals' FFPE samples. As a result, we obtained numerical measures of targets, quantifying 13 peptides of 4 markers in a single analysis per sample. The results correlated well with the IHC readings of experienced pathologists. Moreover, the results distinguished a gray zone in HER2 classification, which IHC alone failed to do. This proof-of-concept study demonstrates the application of targeted proteomics in pathologic slides, further supporting the applicability of MS-based approaches in precision medicine.

Recent advances in proteomic profiling of pancreatic ductal adenocarcinoma and the road ahead.

INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers worldwide. However, there remain many unmet clinical needs, from diagnosis to treatment strategies. The inherent complexity of the molecular characteristics of PDAC has made it difficult to meet these challenges, rendering proteomic profiling of PDAC a critical area of research. Area covered: In this review, we present recent advances in mass spectrometry (MS) and its current application in proteomic studies on PDAC. In addition, we discuss future directions for research that can efficiently incorporate current MS-based technologies that address key issues of PDAC proteomics. Expert commentary: Compared with other cancer studies, little progress has been made in PDAC proteomics, perhaps attributed to the difficulty in performing in-depth and large-scale clinical studies on PDAC. However, recent advances in mass spectrometry can advance PDAC proteomics past the fundamental research stage.

Proteome characterization of human pancreatic cyst fluid from intraductal papillary mucinous neoplasm by liquid chromatography/tandem mass spectrometry.

RATIONALE: In recent years, the molecular components of pancreatic cyst fluid have been used for diagnosis and prognosis. Because the protein markers that are currently used in clinical tests are unreliable, proteomic studies to find new protein markers are being conducted. However, such researches have been limited due to the complexity of pancreatic cyst fluid and the immaturity of proteomic techniques. METHODS: To overcome these limitations and provide a pancreatic cyst proteome dataset, we examined cyst fluid proteome with tandem mass spectrometry. The proteomic analysis was performed using a Orbitrap-based mass spectrometer (Q-Exactive) coupled with a 50-cm-long nano-liquid chromatography column. Protein mutations were identified using mutation sequence database search. RESULTS: A total of 5850 protein groups were identified from microliters of cyst fluid. Among those, 3934 protein groups were reported for the first time in pancreatic cyst fluid. Although high-abundance proteins were not depleted in the experiment, our dataset detected almost all pancreatic tumor markers such as mucin family members, S100 proteins, and CEA-related proteins. In addition, 590 protein mutation marker candidates were discovered. CONCLUSIONS: We provide a comprehensive cyst proteome dataset that includes cystic cellular proteins and mutated proteins. Our findings would serve as a rich resource for further IPMN studies and clinical applications. The MS data have been deposited in the ProteomeXchange with identifier PXD005671 (http://proteomecentral.proteomexchange.org/dataset/PXD005671).

Quantitative sensory and motor measures detect change overtime and correlate with walking speed in individuals with multiple sclerosis.

BACKGROUND: Impairments of sensation, strength, and walking are common in multiple sclerosis (MS). The relationship among these abnormalities and how they change over time remains unclear. OBJECTIVE: To determine the extent that quantitative lower extremity sensory and motor measures detect abnormalities over time, relate to global disability, and to walking speed in individuals with MS. METHODS: This prospective, longitudinal analysis evaluated 136 MS subjects. Measures included measures of leg strength, sensation, the Expanded Disability Status Scale(EDSS) and timed 25-foot walk test (T25FW). Mixed effects regression models were used. RESULTS: Our cohort׳s mean age is 44.3±10.8 years (mean±SD), EDSS score range 0­7.5, 66% were females, and follow-up time was 2.1±1.2 years. Strength significantly changed over time; the RRMS group demonstrated the greatest changes in ADF (3.3 lbs/yr) while the PPMS group showed significant HF changes (−2.1 lbs/yr). Walking speed was affected most by HF, especially in the weakest individuals (HF<20 lbs); T25FW increased by 0.20 s for each 1 lb loss (p=0.001). Likewise T25FW changed by 0.19 s for each 1 lb change in ADF (p<0.01). CONCLUSION: Quantitative measures detected changes in sensation and strength over time, despite a stable respective functional systems scores of the EDSS. Quantitative measurement tools may improve the sensitivity of disability measures in MS and further investigation of these tools as outcomes in future clinical trials of rehabilitative and neuroreparative interventions is warranted.

Strength: a relevant link to functional performance in the neurodegenerative disease of adrenomyeloneuropathy.

BACKGROUND: With progressive abnormalities in leg strength, tone, and sensation, adrenomyeloneuropathy (AMN) is a differential diagnosis for multiple sclerosis and hereditary spastic paraparesis. AMN pathology has been linked to weakness, making it a relevant model to evaluate the relationship between neurodegeneration and disability. Quantifying symptom severity in AMN is essential for treatment development in rehabilitative management. OBJECTIVE: To identify deficits in body functions, activity, and participation of people with AMN and provide a practical framework for evaluating the severity of disability. METHODS: Cohort analysis of 142 participants with AMN. MEASURES: of body functions (leg strength, vibration sensation, range of motion, and spasticity), activity (walk velocity, standing balance, Timed Up and Go, and Sit-to-Stand Time), and participation (6-Minute Walk) are evaluated. Regression analyses identify relationships between the measures. A staging framework (mild, moderate, and severe) reflects the continuum of disability. Finally, an analysis of variance/Kruskal-Wallis was used for between-stage and sex differences among the variables. RESULTS: Strength is the strongest correlate for the 5 measures of activity and participation. Staging based on weakness distinguishes 3 levels of severity along a continuum of disability. Differences between the sexes are more prevalent earlier in the continuum but show equally severe deficits in the last stage. CONCLUSIONS: In AMN, staging based on degrees of weakness provides a practical means to characterize the severity of common deficits in body functions as well as activity and participation at each stage, to direct the evaluation. Such information could help clinicians develop more effective rehabilitative techniques.

Quantitative measures detect sensory and motor impairments in multiple sclerosis.

BACKGROUND: Sensory and motor dysfunction in multiple sclerosis (MS) is often assessed with rating scales which rely heavily on clinical judgment. Quantitative devices may be more precise than rating scales. OBJECTIVE: To quantify lower extremity sensorimotor measures in individuals with MS, evaluate the extent to which they can detect functional systems impairments, and determine their relationship to global disability measures. METHODS: We tested 145 MS subjects and 58 controls. Vibration thresholds were quantified using a Vibratron-II device. Strength was quantified by a hand-held dynamometer. We also recorded Expanded Disability Status Scale (EDSS) and Timed 25-Foot Walk (T25FW). t-tests and Wilcoxon-rank sum were used to compare group data. Spearman correlations were used to assess relationships between each measure. We also used a step-wise linear regression model to determine how much the quantitative measures explain the variance in the respective functional systems scores (FSS). RESULTS: EDSS scores ranged from 0-7.5, mean disease duration was 10.4 ± 9.6 years, and 66% were female. In relapsing-remitting MS, but not progressive MS, poorer vibration sensation correlated with a worse EDSS score, whereas progressive groups' ankle/hip strength changed significantly with EDSS progression. Interestingly, not only did sensorimotor measures significantly correlate with global disability measures (i.e., EDSS), but they had improved sensitivity, as they detected impairments in up to 32% of MS subjects with normal sensory and pyramidal FSS. CONCLUSIONS: Sensory and motor deficits in MS can be quantified using clinically accessible tools and distinguish differences among MS subtypes. We show that quantitative sensorimotor measures are more sensitive than FSS from the EDSS. These tools have the potential to be used as clinical outcome measures in practice and for future MS clinical trials of neurorehabilitative and neuroreparative interventions.

Automated control of blood glucose in the OR and surgical ICU.

A device which integrates existing intravenous continuous glucose monitors and infusion pumps into a central hub for automated intravenous intensive insulin therapy, targeting non-diabetic critically-ill patients is presented. Additionally, a fuzzy logic based controller that is capable of automatically making closed-loop decisions to achieve tight glycemic control between a euglycemic range of 90 to 120 mg/dl is presented. Initial bench top testing shows a significant improvement in glycemic control with fuzzy logic control when compared to manual infusion protocols currently used in hospitals; future animal testing will be performed to verify these results in vivo.