Citations

Lower body negative pressure (LBNP) is often used to simulate blood loss in humans. It is unknown if cerebral blood flow responses to actual blood loss are analogous to simulated blood loss during LBNP. Nine healthy men were studied at baseline, during three levels of LBNP (5 min at −15, −30, and −45 mmHg), and during three levels of blood loss (333, 667, and 1,000 ml). LBNP and blood loss conditions were randomized. Intra-arterial mean arterial pressure (MAP) during LBNP was similar to that during blood loss ( P ≥ 0.42). Central venous pressure (2.8 ± 0.7 vs. 4.0 ± 0.8, 1.2 ± 0.6 vs. 3.5 ± 0.8, and 0.2 ± 0.9 vs. 2.1 ± 0.9 mmHg for levels 1, 2, and 3, respectively, P ≤ 0.003) and stroke volume (71 ± 4 vs. 80 ± 3, 60 ± 3 vs. 74 ± 3, and 51 ± 2 vs. 68 ± 4 ml for levels 1, 2, and 3, respectively, P ≤ 0.002) were lower during LBNP than blood loss. Despite differences in central venous pressure, middle cerebral artery velocity (MCAv) and cerebrovascular conductance were similar between LBNP and blood loss at each level (MCAv at level 3: 62 ± 6 vs. 66 ± 5 cm/s, P = 0.37; cerebrovascular conductance at level 3: 0.72 ± 0.05 vs. 0.73 ± 0.05 cm·s−1·mmHg−1, P = 0.53). While the slope of the MAP-MCAv relationship was slightly different between LBNP and blood loss (0.41 ± 0.03 and 0.66 ± 0.04 cm·s−1·mmHg−1, respectively, P = 0.05), time domain gain between MAP and MCAv at maximal LBNP/blood loss ( P = 0.23) and low-frequency MAP-mean MCAv transfer function coherence, gain, and phase were similar ( P ≥ 0.10). Our results suggest that cerebral hemodynamic responses to LBNP to −45 mmHg and blood loss up to 1,000 ml follow a similar trajectory, and the arterial pressure-cerebral blood velocity relationship is not altered from baseline under these conditions.

ABSTRACTBackgroundThe panelists of the Joint National Committee recently published new recommendations for the management of hypertension. Our study aims to evaluate how current practice compares.HypothesisCurrent practice likely deviates from the recent JNC 8 panelists' recommendations.MethodsA survey was sent to cardiology providers at 3 academic medical centers: Mayo Clinic, Jacksonville, Florida; Mayo Clinic, Scottsdale, Arizona; and Mayo Clinic, Rochester, Minnesota. Providers were asked to select which blood‐pressure goal would be deemed appropriate in various cases based on individual practice in both the maintenance of patients already on therapy as well as threshold of when to initiate therapy. Comparisons with current recommendations were made, as well as geographic location and level of experience.ResultsA total of 251 survey requests were sent (May 2014), and 77 responses (30.7%) were received. Cardiologists tended not to practice according to the new guidelines, with most variation seen in patients age >60 years without comorbidities on active treatment. Providers' selection of initial pharmacologic agents in non–African American patients, African American patients, and patients with diabetes mellitus reflected congruency with guidelines.ConclusionsOur study found that clinical practice does not correlate well with the new blood‐pressure goal recommendations published by the Joint National Committee 8 panelists, particularly in patients age >60 years. Practitioners are likely to follow the recommendations in regard to pharmacologic management.

A mouse model for ALS A G4C2 repeat expansion in C9ORF72 is known to be the major genetic cause of frontotemporal dementia and amyotrophic lateral sclerosis (c9FTD/ALS). However, a lack of animal models recapitulating key disease features has hindered efforts to understand and prevent c9FTD/ALS-related neurodegeneration. Until now. Chew et al. describe a mouse model that mimics both neuropathological and clinical phenotypes of c9FTD/ALS. Science , this issue p. 1151

Abstract Background: Previous data on the relationship between PD-L1 expression and activity of anti-PD-1 and anti-PD-L1 antibodies have been conflicting. MK-3475, a humanized monoclonal IgG4 antibody against PD-1, has demonstrated durable antitumor activity in MEL and NSCLC. We evaluated tumor PD-L1 expression and its relationship with outcomes in a phase I clinical trial of MK-3475. We also evaluated T cell activation as a pharmacodynamic marker of MK-3475 activity. Methods: 135 MEL pts received MK-3475 10 mg/kg Q2W, 10 mg/kg Q3W, or 2 mg/kg Q3W. Tumor response was assessed by RECIST 1.1 per independent central review, including requirement for a confirmatory CT scan. Pretreatment biopsy was required. Serial blood samples were collected before infusion at the start of cycles 1-5 (Q2W dosing) or 1-4 (Q3W dosing). Tumor PD-L1 expression was assessed by IHC. A preliminary cutoff of 1% of stained cells was used to define PD-L1 positivity. Absolute CD4+ and CD8+ T cell counts and the percentage of activated (HLA-DR as marker) CD4+ and CD8+ T cells in peripheral blood were assessed by multiplex flow cytometry (n = 101). Results: Median PFS was 36 weeks, 6-month overall survival (OS) rate was 89%, and 12-month OS rate was 81%. Median duration of response and OS were not reached. In the 116 pts with measurable disease, ORR was 41%. PFS and response rate were significantly associated with tumor PD-L1 expression (Table). At week 6, a statistically significant percent increase from baseline in the percentage of activated (HLA-DR+) CD4+ and CD8+ T cells was observed at all doses (pooled mean percent change [SE], +24.0% [4.7%] for HLA-DR+/CD8+, +17.5% [2.7%] for HLA-DR+/CD4+). Conclusions: Tumor PD-L1 expression levels were associated with tumor response and PFS in MEL pts treated with MK-3475; activity was also observed in pts with low PD-L1 expression. As assessed by HLA-DR expression, post-treatment T cell activation in the circulating pool was increased at all doses tested. Patients WithMeasurable Disease and Interpretable PD-L1 IHC ResultsPatients With InterpretablePD-L1 IHC Results and PFS and OS Data PD-L1 TumorExpressionNORR, n (%)NPFS at 6 months, % (95% CI)Median PFSOS at 6 months, % (95% CI)Median OSPositive (membrane staining in ≥1% of cells)5529 (53)6058 (47-72)10.6 mo93(87-100)Not reachedNegative (membrane staining in <1% of cells)161* (6)2232 (16-64)2.9 mo75(58-97)Not reachedHR (95% CI) for PD-L1-positive vs negative____0.54(0.28-1.05)_0.67(0.25-1.83)One-sidedP value(PD-L1 association test)_<0.004 (logistic regression)__0.034(Cox regression)_0.220(Cox regression)*IPI-pretreated patient who received MK-3475 10 mg/kg Q2W. Citation Format: Adil I. Daud, Omid Hamid, Antoni Ribas, F. Stephen Hodi, Wen-Jen Hwu, Richard Kefford, Jedd Wolchok, Peter Hersey, Jeffrey S. Weber, Richard Joseph, Tara C. Gangadhar, Roxana S. Dronca, Amita Patnaik, Hassane Zarour, Anthony M. Joshua, Kevin Gergich, Dianna Wu, Jared K. Lunceford, Kenneth Emancipator, Marisa Dolled-Filhart, Nicole Li, Scot Ebbinghaus, S. Peter Kang, Caroline Robert. Antitumor activity of the anti-PD-1 monoclonal antibody MK-3475 in melanoma(MEL): Correlation of tumor PD-L1 expression with outcome. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr CT104. doi:10.1158/1538-7445.AM2014-CT104

BACKGROUNDFailures in communication at the time of patient handoff have been implicated as contributing factors to preventable adverse events.OBJECTIVEExamine the relationship between face‐to‐face handoffs and the rate of patient outcomes, including adverse events.DESIGNRetrospective cohort.SETTINGA 1157‐bed academic tertiary referral hospital.PATIENTSThere were 805 adult patients admitted to general internal medicine services.INTERVENTIONRetrospective comparison of clinical outcomes, including the rate of adverse events, of patients whose care was transitioned with and without face‐to‐face handoffs.MEASUREMENTSRapid response team calls, code team calls, transfers to a higher level of care, death in hospital, 30‐day readmission rate, length of stay, and adverse events (as identified using the Global Trigger Tool).RESULTSThere was no significant difference with respect to the frequency of rapid response team calls, code team calls, transfers to a higher level of care, deaths in hospital, length of stay, 30‐day readmission rate, or adverse events between patients whose care was transitioned with or without a face‐to‐face handoff.CONCLUSIONSFace‐to‐face handoff of patients admitted to general medical services at a large academic tertiary referral hospital was not associated with a significant difference in measured patient outcomes, including the rate of adverse events, compared to a non–face‐to‐face handoff. Additional study is needed to determine the qualities of patient handoff that optimize efficiency and safety. Journal of Hospital Medicine 2015;10:137–141. © 2015 Society of Hospital Medicine

AbstractBackgroundLate‐onset Alzheimer's disease (AD) is heritable with 20 genes showing genome‐wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis.MethodsThe ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain.ResultsALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 × 10−12 after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 × 10−11), cholesterol transport (P = 2.96 × 10−9), and proteasome‐ubiquitin activity (P = 1.34 × 10−6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002–.05).ConclusionsThe immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics.